Tutorial:RNA+ATAC (no label)

In this tutorial, we will show how to cluster RNA+ATAC(no labeled) data using scMAGCA. As an example, we use a human peripheral blood mononuclear sample dataset ‘GSM4949911’ containing 8213 cells with two omics. Among them, ATAC has 66828 features and RNA containis 36601 features.

Loading package

import numpy as np
import pandas as pd
import torch
import scanpy as sc
import random
import warnings
warnings.filterwarnings("ignore")

from scMAGCA.preprocess import read_dataset, preprocess_dataset
from scMAGCA.utils import *
from scMAGCA.scMAGCA import scMultiCluster

# set seed
random.seed(3407)
np.random.seed(3407)
torch.manual_seed(3407)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.enabled = False
torch.backends.cudnn.benchmark = False

Reading dataset

The required input files include:

1. x1: Chromatin accessibility matrix (data format is h5ad file) : GSM4949911_tea_atac.h5ad;

2. x2: Gene expression matrix (data format is h5ad file) : GSM4949911_tea_rna.h5ad.

To ensure reproducibility of the results, please read the above data as follows:

x1 = np.array(sc.read_h5ad('../datasets/GSM4949911/GSM4949911_atac.h5ad').to_df()).astype('float32')
x2 = np.array(sc.read_h5ad('../datasets/GSM4949911/GSM4949911_rna.h5ad').to_df()).astype('float32')
y = None

x1,x2

(array([[0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.],
        ...,
        [0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.]], dtype=float32),
 array([[0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.],
        ...,
        [0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.],
        [0., 0., 0., ..., 0., 0., 0.]], dtype=float32))

We select the two omics data for high expression, and the number of chosen features are both set to 2000.

importantGenes = geneSelection(x1, n=2000)
x1 = x1[:, importantGenes]
importantGenes = geneSelection(x2, n=2000)
x2 = x2[:, importantGenes]

Chosen offset: 1.24
Chosen offset: 0.33

adata1 = sc.AnnData(x1)
adata1 = read_dataset(adata1, copy=True)
adata1 = preprocess_dataset(adata1, normalize_input=True, logtrans_input=True)

### Autoencoder: Successfully preprocessed 2000 features and 8213 cells.

adata1

AnnData object with n_obs × n_vars = 8213 × 2000
    obs: 'DCA_split', 'size_factors'
    var: 'mean', 'std'
    uns: 'log1p'

adata2 = sc.AnnData(x2)
adata2 = read_dataset(adata2, copy=True)
adata2 = preprocess_dataset(adata2, normalize_input=True, logtrans_input=True)

### Autoencoder: Successfully preprocessed 2000 features and 8213 cells.

adata2

AnnData object with n_obs × n_vars = 8213 × 2000
    obs: 'DCA_split', 'size_factors'
    var: 'mean', 'std'
    uns: 'log1p'

Training the model

model = scMultiCluster(input_dim1=adata1.n_vars,input_dim2=adata2.n_vars,
                       alpha=0.2,beta=0.8,gama=0.01,device='cuda').to('cuda')

model

scMultiCluster(
  (encoder): Encoder(
    (stacked_gnn): ModuleList(
      (0): GCNConv(4000, 1024)
      (1): GCNConv(1024, 256)
      (2): GCNConv(256, 64)
      (3): GCNConv(64, 32)
    )
    (stacked_bns): ModuleList(
      (0): BatchNorm1d(1024, eps=1e-05, momentum=0.01, affine=True, track_running_stats=True)
      (1): BatchNorm1d(256, eps=1e-05, momentum=0.01, affine=True, track_running_stats=True)
      (2): BatchNorm1d(64, eps=1e-05, momentum=0.01, affine=True, track_running_stats=True)
      (3): BatchNorm1d(32, eps=1e-05, momentum=0.01, affine=True, track_running_stats=True)
    )
    (stacked_prelus): ModuleList(
      (0-3): 4 x PReLU(num_parameters=1)
    )
  )
  (decoder): Sequential(
    (0): Linear(in_features=32, out_features=512, bias=True)
    (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (2): PReLU(num_parameters=1)
    (3): Linear(in_features=512, out_features=1024, bias=True)
    (4): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (5): PReLU(num_parameters=1)
    (6): Linear(in_features=1024, out_features=4000, bias=True)
  )
  (dec_mean): Sequential(
    (0): Linear(in_features=32, out_features=256, bias=True)
    (1): Linear(in_features=256, out_features=512, bias=True)
    (2): Linear(in_features=512, out_features=4000, bias=True)
    (3): MeanAct()
  )
  (dec_disp): Sequential(
    (0): Linear(in_features=32, out_features=256, bias=True)
    (1): Linear(in_features=256, out_features=512, bias=True)
    (2): Linear(in_features=512, out_features=4000, bias=True)
    (3): DispAct()
  )
  (dec_pi): Sequential(
    (0): Linear(in_features=32, out_features=256, bias=True)
    (1): Linear(in_features=256, out_features=512, bias=True)
    (2): Linear(in_features=512, out_features=4000, bias=True)
    (3): Sigmoid()
  )
  (zinb_loss): ZINBLoss()
)

The ad_out parameter is set to 32 in the RNA+ATAC dataset.

pretrain_latent = model.pretrain_autoencoder(
                        X1=adata1.X, X2=adata2.X, X1_raw=adata1.raw.X, X2_raw=adata2.raw.X,
                        epochs=400, file='GSM4949911',ad_out=32)

Pretraining stage
Pretrain epoch 1, recon_loss:1.177419, zinb_loss:0.945166, adversial_loss:1.372231
Pretrain epoch 2, recon_loss:1.087229, zinb_loss:0.921236, adversial_loss:1.373194
Pretrain epoch 3, recon_loss:0.948224, zinb_loss:0.890657, adversial_loss:1.373617
Pretrain epoch 4, recon_loss:0.885800, zinb_loss:0.858559, adversial_loss:1.358683
Pretrain epoch 5, recon_loss:0.866452, zinb_loss:0.824501, adversial_loss:1.359133
Pretrain epoch 6, recon_loss:0.856318, zinb_loss:0.789515, adversial_loss:1.355022
Pretrain epoch 7, recon_loss:0.850889, zinb_loss:0.759701, adversial_loss:1.351529
Pretrain epoch 8, recon_loss:0.842909, zinb_loss:0.738662, adversial_loss:1.351824
Pretrain epoch 9, recon_loss:0.836522, zinb_loss:0.726100, adversial_loss:1.351907
Pretrain epoch 10, recon_loss:0.829639, zinb_loss:0.718908, adversial_loss:1.350247
Pretrain epoch 11, recon_loss:0.824786, zinb_loss:0.713263, adversial_loss:1.348227
Pretrain epoch 12, recon_loss:0.821581, zinb_loss:0.707017, adversial_loss:1.347948
Pretrain epoch 13, recon_loss:0.818954, zinb_loss:0.699969, adversial_loss:1.349329
Pretrain epoch 14, recon_loss:0.816677, zinb_loss:0.693693, adversial_loss:1.350878
Pretrain epoch 15, recon_loss:0.813920, zinb_loss:0.688917, adversial_loss:1.350498
Pretrain epoch 16, recon_loss:0.811877, zinb_loss:0.685424, adversial_loss:1.349127
Pretrain epoch 17, recon_loss:0.809966, zinb_loss:0.682478, adversial_loss:1.348064
Pretrain epoch 18, recon_loss:0.808354, zinb_loss:0.679629, adversial_loss:1.347751
Pretrain epoch 19, recon_loss:0.807258, zinb_loss:0.676862, adversial_loss:1.347479
Pretrain epoch 20, recon_loss:0.806017, zinb_loss:0.674137, adversial_loss:1.346404
Pretrain epoch 21, recon_loss:0.804428, zinb_loss:0.671521, adversial_loss:1.344638
Pretrain epoch 22, recon_loss:0.802824, zinb_loss:0.668903, adversial_loss:1.343253
Pretrain epoch 23, recon_loss:0.801624, zinb_loss:0.666379, adversial_loss:1.341949
Pretrain epoch 24, recon_loss:0.800622, zinb_loss:0.663973, adversial_loss:1.340480
Pretrain epoch 25, recon_loss:0.799793, zinb_loss:0.661805, adversial_loss:1.340241
Pretrain epoch 26, recon_loss:0.799017, zinb_loss:0.659948, adversial_loss:1.340883
Pretrain epoch 27, recon_loss:0.798392, zinb_loss:0.658303, adversial_loss:1.340143
Pretrain epoch 28, recon_loss:0.797557, zinb_loss:0.656784, adversial_loss:1.339819
Pretrain epoch 29, recon_loss:0.796525, zinb_loss:0.655244, adversial_loss:1.339375
Pretrain epoch 30, recon_loss:0.795610, zinb_loss:0.653714, adversial_loss:1.339210
Pretrain epoch 31, recon_loss:0.794745, zinb_loss:0.652404, adversial_loss:1.337723
Pretrain epoch 32, recon_loss:0.794299, zinb_loss:0.651255, adversial_loss:1.338467
Pretrain epoch 33, recon_loss:0.793691, zinb_loss:0.650216, adversial_loss:1.335549
Pretrain epoch 34, recon_loss:0.792576, zinb_loss:0.648704, adversial_loss:1.335775
Pretrain epoch 35, recon_loss:0.792066, zinb_loss:0.647766, adversial_loss:1.335634
Pretrain epoch 36, recon_loss:0.791833, zinb_loss:0.647147, adversial_loss:1.333670
Pretrain epoch 37, recon_loss:0.790898, zinb_loss:0.646018, adversial_loss:1.333558
Pretrain epoch 38, recon_loss:0.790367, zinb_loss:0.645174, adversial_loss:1.333227
Pretrain epoch 39, recon_loss:0.789837, zinb_loss:0.644639, adversial_loss:1.331793
Pretrain epoch 40, recon_loss:0.789169, zinb_loss:0.643823, adversial_loss:1.332080
Pretrain epoch 41, recon_loss:0.788582, zinb_loss:0.643115, adversial_loss:1.331233
Pretrain epoch 42, recon_loss:0.788083, zinb_loss:0.642528, adversial_loss:1.329755
Pretrain epoch 43, recon_loss:0.787743, zinb_loss:0.642012, adversial_loss:1.330270
Pretrain epoch 44, recon_loss:0.787233, zinb_loss:0.641469, adversial_loss:1.329388
Pretrain epoch 45, recon_loss:0.786937, zinb_loss:0.641088, adversial_loss:1.328254
Pretrain epoch 46, recon_loss:0.786540, zinb_loss:0.640810, adversial_loss:1.328790
Pretrain epoch 47, recon_loss:0.786258, zinb_loss:0.640202, adversial_loss:1.327587
Pretrain epoch 48, recon_loss:0.785733, zinb_loss:0.639601, adversial_loss:1.327571
Pretrain epoch 49, recon_loss:0.785445, zinb_loss:0.639265, adversial_loss:1.327048
Pretrain epoch 50, recon_loss:0.785088, zinb_loss:0.638992, adversial_loss:1.325881
Pretrain epoch 51, recon_loss:0.784727, zinb_loss:0.638529, adversial_loss:1.326414
Pretrain epoch 52, recon_loss:0.784363, zinb_loss:0.638133, adversial_loss:1.325543
Pretrain epoch 53, recon_loss:0.784103, zinb_loss:0.637940, adversial_loss:1.324549
Pretrain epoch 54, recon_loss:0.783760, zinb_loss:0.637597, adversial_loss:1.325459
Pretrain epoch 55, recon_loss:0.783446, zinb_loss:0.637262, adversial_loss:1.324351
Pretrain epoch 56, recon_loss:0.783150, zinb_loss:0.637093, adversial_loss:1.324194
Pretrain epoch 57, recon_loss:0.782939, zinb_loss:0.636965, adversial_loss:1.323673
Pretrain epoch 58, recon_loss:0.782717, zinb_loss:0.636879, adversial_loss:1.324108
Pretrain epoch 59, recon_loss:0.782628, zinb_loss:0.637086, adversial_loss:1.321680
Pretrain epoch 60, recon_loss:0.782271, zinb_loss:0.636703, adversial_loss:1.323040
Pretrain epoch 61, recon_loss:0.781838, zinb_loss:0.636147, adversial_loss:1.320967
Pretrain epoch 62, recon_loss:0.781431, zinb_loss:0.635768, adversial_loss:1.320497
Pretrain epoch 63, recon_loss:0.781378, zinb_loss:0.635902, adversial_loss:1.320936
Pretrain epoch 64, recon_loss:0.781003, zinb_loss:0.635670, adversial_loss:1.319416
Pretrain epoch 65, recon_loss:0.780600, zinb_loss:0.635297, adversial_loss:1.319215
Pretrain epoch 66, recon_loss:0.780387, zinb_loss:0.635358, adversial_loss:1.319530
Pretrain epoch 67, recon_loss:0.780119, zinb_loss:0.635134, adversial_loss:1.317977
Pretrain epoch 68, recon_loss:0.779724, zinb_loss:0.634855, adversial_loss:1.317650
Pretrain epoch 69, recon_loss:0.779647, zinb_loss:0.634964, adversial_loss:1.318024
Pretrain epoch 70, recon_loss:0.779239, zinb_loss:0.634626, adversial_loss:1.316499
Pretrain epoch 71, recon_loss:0.778984, zinb_loss:0.634477, adversial_loss:1.316283
Pretrain epoch 72, recon_loss:0.778745, zinb_loss:0.634437, adversial_loss:1.316512
Pretrain epoch 73, recon_loss:0.778422, zinb_loss:0.634171, adversial_loss:1.315362
Pretrain epoch 74, recon_loss:0.778190, zinb_loss:0.634086, adversial_loss:1.314840
Pretrain epoch 75, recon_loss:0.777988, zinb_loss:0.634006, adversial_loss:1.314906
Pretrain epoch 76, recon_loss:0.777692, zinb_loss:0.633817, adversial_loss:1.314137
Pretrain epoch 77, recon_loss:0.777451, zinb_loss:0.633776, adversial_loss:1.313697
Pretrain epoch 78, recon_loss:0.777205, zinb_loss:0.633718, adversial_loss:1.313863
Pretrain epoch 79, recon_loss:0.776992, zinb_loss:0.633652, adversial_loss:1.312968
Pretrain epoch 80, recon_loss:0.776972, zinb_loss:0.633797, adversial_loss:1.312713
Pretrain epoch 81, recon_loss:0.776964, zinb_loss:0.634136, adversial_loss:1.312556
Pretrain epoch 82, recon_loss:0.777046, zinb_loss:0.634610, adversial_loss:1.311600
Pretrain epoch 83, recon_loss:0.776634, zinb_loss:0.634098, adversial_loss:1.311629
Pretrain epoch 84, recon_loss:0.775969, zinb_loss:0.633054, adversial_loss:1.311265
Pretrain epoch 85, recon_loss:0.776029, zinb_loss:0.633389, adversial_loss:1.310533
Pretrain epoch 86, recon_loss:0.775819, zinb_loss:0.633396, adversial_loss:1.310469
Pretrain epoch 87, recon_loss:0.775534, zinb_loss:0.632921, adversial_loss:1.309945
Pretrain epoch 88, recon_loss:0.775337, zinb_loss:0.632915, adversial_loss:1.309785
Pretrain epoch 89, recon_loss:0.775196, zinb_loss:0.632826, adversial_loss:1.309403
Pretrain epoch 90, recon_loss:0.775106, zinb_loss:0.632720, adversial_loss:1.308682
Pretrain epoch 91, recon_loss:0.774817, zinb_loss:0.632539, adversial_loss:1.308952
Pretrain epoch 92, recon_loss:0.774637, zinb_loss:0.632432, adversial_loss:1.308161
Pretrain epoch 93, recon_loss:0.774580, zinb_loss:0.632434, adversial_loss:1.307136
Pretrain epoch 94, recon_loss:0.774255, zinb_loss:0.632254, adversial_loss:1.307646
Pretrain epoch 95, recon_loss:0.774129, zinb_loss:0.632149, adversial_loss:1.306916
Pretrain epoch 96, recon_loss:0.773953, zinb_loss:0.632100, adversial_loss:1.306219
Pretrain epoch 97, recon_loss:0.773769, zinb_loss:0.631987, adversial_loss:1.306318
Pretrain epoch 98, recon_loss:0.773663, zinb_loss:0.631933, adversial_loss:1.305686
Pretrain epoch 99, recon_loss:0.773468, zinb_loss:0.631802, adversial_loss:1.305677
Pretrain epoch 100, recon_loss:0.773266, zinb_loss:0.631716, adversial_loss:1.305090
Pretrain epoch 101, recon_loss:0.773141, zinb_loss:0.631620, adversial_loss:1.305019
Pretrain epoch 102, recon_loss:0.772991, zinb_loss:0.631532, adversial_loss:1.304864
Pretrain epoch 103, recon_loss:0.772879, zinb_loss:0.631514, adversial_loss:1.303902
Pretrain epoch 104, recon_loss:0.772725, zinb_loss:0.631433, adversial_loss:1.304510
Pretrain epoch 105, recon_loss:0.772648, zinb_loss:0.631401, adversial_loss:1.303271
Pretrain epoch 106, recon_loss:0.772535, zinb_loss:0.631453, adversial_loss:1.303749
Pretrain epoch 107, recon_loss:0.772562, zinb_loss:0.631585, adversial_loss:1.302562
Pretrain epoch 108, recon_loss:0.772743, zinb_loss:0.631804, adversial_loss:1.303632
Pretrain epoch 109, recon_loss:0.773139, zinb_loss:0.632166, adversial_loss:1.301710
Pretrain epoch 110, recon_loss:0.772615, zinb_loss:0.631620, adversial_loss:1.302210
Pretrain epoch 111, recon_loss:0.772099, zinb_loss:0.631244, adversial_loss:1.302199
Pretrain epoch 112, recon_loss:0.772691, zinb_loss:0.631441, adversial_loss:1.300339
Pretrain epoch 113, recon_loss:0.771753, zinb_loss:0.630972, adversial_loss:1.301244
Pretrain epoch 114, recon_loss:0.771948, zinb_loss:0.631223, adversial_loss:1.301844
Pretrain epoch 115, recon_loss:0.771766, zinb_loss:0.630892, adversial_loss:1.300058
Pretrain epoch 116, recon_loss:0.771387, zinb_loss:0.630823, adversial_loss:1.300245
Pretrain epoch 117, recon_loss:0.771327, zinb_loss:0.630725, adversial_loss:1.300648
Pretrain epoch 118, recon_loss:0.770896, zinb_loss:0.630538, adversial_loss:1.299725
Pretrain epoch 119, recon_loss:0.771083, zinb_loss:0.630620, adversial_loss:1.299314
Pretrain epoch 120, recon_loss:0.770678, zinb_loss:0.630338, adversial_loss:1.298796
Pretrain epoch 121, recon_loss:0.770595, zinb_loss:0.630327, adversial_loss:1.299041
Pretrain epoch 122, recon_loss:0.770426, zinb_loss:0.630228, adversial_loss:1.298796
Pretrain epoch 123, recon_loss:0.770400, zinb_loss:0.630227, adversial_loss:1.297851
Pretrain epoch 124, recon_loss:0.769996, zinb_loss:0.630014, adversial_loss:1.297896
Pretrain epoch 125, recon_loss:0.770002, zinb_loss:0.630018, adversial_loss:1.297887
Pretrain epoch 126, recon_loss:0.769764, zinb_loss:0.629883, adversial_loss:1.297321
Pretrain epoch 127, recon_loss:0.769703, zinb_loss:0.629920, adversial_loss:1.297207
Pretrain epoch 128, recon_loss:0.769471, zinb_loss:0.629776, adversial_loss:1.296510
Pretrain epoch 129, recon_loss:0.769474, zinb_loss:0.629844, adversial_loss:1.296746
Pretrain epoch 130, recon_loss:0.769316, zinb_loss:0.629907, adversial_loss:1.296185
Pretrain epoch 131, recon_loss:0.769345, zinb_loss:0.630119, adversial_loss:1.296040
Pretrain epoch 132, recon_loss:0.769921, zinb_loss:0.630883, adversial_loss:1.295672
Pretrain epoch 133, recon_loss:0.769987, zinb_loss:0.631382, adversial_loss:1.295606
Pretrain epoch 134, recon_loss:0.770319, zinb_loss:0.630958, adversial_loss:1.295570
Pretrain epoch 135, recon_loss:0.769544, zinb_loss:0.630117, adversial_loss:1.293905
Pretrain epoch 136, recon_loss:0.769243, zinb_loss:0.630311, adversial_loss:1.294124
Pretrain epoch 137, recon_loss:0.769668, zinb_loss:0.630274, adversial_loss:1.294208
Pretrain epoch 138, recon_loss:0.768874, zinb_loss:0.629551, adversial_loss:1.293011
Pretrain epoch 139, recon_loss:0.769396, zinb_loss:0.630022, adversial_loss:1.292869
Pretrain epoch 140, recon_loss:0.768710, zinb_loss:0.629450, adversial_loss:1.292766
Pretrain epoch 141, recon_loss:0.768588, zinb_loss:0.629526, adversial_loss:1.292793
Pretrain epoch 142, recon_loss:0.768435, zinb_loss:0.629493, adversial_loss:1.291975
Pretrain epoch 143, recon_loss:0.768048, zinb_loss:0.629232, adversial_loss:1.291733
Pretrain epoch 144, recon_loss:0.767937, zinb_loss:0.629348, adversial_loss:1.292000
Pretrain epoch 145, recon_loss:0.767733, zinb_loss:0.629056, adversial_loss:1.291455
Pretrain epoch 146, recon_loss:0.767740, zinb_loss:0.629110, adversial_loss:1.290631
Pretrain epoch 147, recon_loss:0.767510, zinb_loss:0.628934, adversial_loss:1.290836
Pretrain epoch 148, recon_loss:0.767375, zinb_loss:0.628849, adversial_loss:1.291117
Pretrain epoch 149, recon_loss:0.767231, zinb_loss:0.628824, adversial_loss:1.290537
Pretrain epoch 150, recon_loss:0.767011, zinb_loss:0.628681, adversial_loss:1.289755
Pretrain epoch 151, recon_loss:0.766930, zinb_loss:0.628695, adversial_loss:1.289879
Pretrain epoch 152, recon_loss:0.766698, zinb_loss:0.628563, adversial_loss:1.289621
Pretrain epoch 153, recon_loss:0.766584, zinb_loss:0.628529, adversial_loss:1.289369
Pretrain epoch 154, recon_loss:0.766406, zinb_loss:0.628483, adversial_loss:1.288932
Pretrain epoch 155, recon_loss:0.766286, zinb_loss:0.628409, adversial_loss:1.288240
Pretrain epoch 156, recon_loss:0.766156, zinb_loss:0.628336, adversial_loss:1.287966
Pretrain epoch 157, recon_loss:0.765973, zinb_loss:0.628333, adversial_loss:1.288143
Pretrain epoch 158, recon_loss:0.765870, zinb_loss:0.628206, adversial_loss:1.287627
Pretrain epoch 159, recon_loss:0.765755, zinb_loss:0.628209, adversial_loss:1.287160
Pretrain epoch 160, recon_loss:0.765601, zinb_loss:0.628156, adversial_loss:1.286916
Pretrain epoch 161, recon_loss:0.765482, zinb_loss:0.628089, adversial_loss:1.286921
Pretrain epoch 162, recon_loss:0.765553, zinb_loss:0.628178, adversial_loss:1.285903
Pretrain epoch 163, recon_loss:0.765706, zinb_loss:0.628333, adversial_loss:1.286662
Pretrain epoch 164, recon_loss:0.766546, zinb_loss:0.629138, adversial_loss:1.285251
Pretrain epoch 165, recon_loss:0.767097, zinb_loss:0.629627, adversial_loss:1.285976
Pretrain epoch 166, recon_loss:0.766208, zinb_loss:0.628702, adversial_loss:1.284390
Pretrain epoch 167, recon_loss:0.765260, zinb_loss:0.628191, adversial_loss:1.283949
Pretrain epoch 168, recon_loss:0.766244, zinb_loss:0.628701, adversial_loss:1.284614
Pretrain epoch 169, recon_loss:0.765279, zinb_loss:0.628139, adversial_loss:1.283516
Pretrain epoch 170, recon_loss:0.765658, zinb_loss:0.628244, adversial_loss:1.283159
Pretrain epoch 171, recon_loss:0.765288, zinb_loss:0.628052, adversial_loss:1.283587
Pretrain epoch 172, recon_loss:0.764857, zinb_loss:0.627844, adversial_loss:1.283251
Pretrain epoch 173, recon_loss:0.765260, zinb_loss:0.628118, adversial_loss:1.282436
Pretrain epoch 174, recon_loss:0.764392, zinb_loss:0.627717, adversial_loss:1.282285
Pretrain epoch 175, recon_loss:0.764773, zinb_loss:0.627935, adversial_loss:1.282586
Pretrain epoch 176, recon_loss:0.764257, zinb_loss:0.627658, adversial_loss:1.281763
Pretrain epoch 177, recon_loss:0.764276, zinb_loss:0.627682, adversial_loss:1.281396
Pretrain epoch 178, recon_loss:0.764062, zinb_loss:0.627596, adversial_loss:1.281657
Pretrain epoch 179, recon_loss:0.763986, zinb_loss:0.627492, adversial_loss:1.281358
Pretrain epoch 180, recon_loss:0.763848, zinb_loss:0.627575, adversial_loss:1.280781
Pretrain epoch 181, recon_loss:0.763658, zinb_loss:0.627387, adversial_loss:1.280916
Pretrain epoch 182, recon_loss:0.763669, zinb_loss:0.627456, adversial_loss:1.280822
Pretrain epoch 183, recon_loss:0.763358, zinb_loss:0.627285, adversial_loss:1.280413
Pretrain epoch 184, recon_loss:0.763430, zinb_loss:0.627338, adversial_loss:1.279923
Pretrain epoch 185, recon_loss:0.763196, zinb_loss:0.627269, adversial_loss:1.279783
Pretrain epoch 186, recon_loss:0.763281, zinb_loss:0.627313, adversial_loss:1.280205
Pretrain epoch 187, recon_loss:0.763191, zinb_loss:0.627381, adversial_loss:1.279038
Pretrain epoch 188, recon_loss:0.763060, zinb_loss:0.627429, adversial_loss:1.278970
Pretrain epoch 189, recon_loss:0.763346, zinb_loss:0.627577, adversial_loss:1.279608
Pretrain epoch 190, recon_loss:0.762973, zinb_loss:0.627280, adversial_loss:1.278903
Pretrain epoch 191, recon_loss:0.763026, zinb_loss:0.627135, adversial_loss:1.278417
Pretrain epoch 192, recon_loss:0.762511, zinb_loss:0.626993, adversial_loss:1.278164
Pretrain epoch 193, recon_loss:0.762645, zinb_loss:0.627139, adversial_loss:1.278583
Pretrain epoch 194, recon_loss:0.762589, zinb_loss:0.627038, adversial_loss:1.277658
Pretrain epoch 195, recon_loss:0.762198, zinb_loss:0.626901, adversial_loss:1.277149
Pretrain epoch 196, recon_loss:0.762336, zinb_loss:0.626877, adversial_loss:1.277972
Pretrain epoch 197, recon_loss:0.762059, zinb_loss:0.626925, adversial_loss:1.276962
Pretrain epoch 198, recon_loss:0.761929, zinb_loss:0.626830, adversial_loss:1.276672
Pretrain epoch 199, recon_loss:0.761676, zinb_loss:0.626703, adversial_loss:1.276777
Pretrain epoch 200, recon_loss:0.761598, zinb_loss:0.626732, adversial_loss:1.276787
Pretrain epoch 201, recon_loss:0.761551, zinb_loss:0.626729, adversial_loss:1.276282
Pretrain epoch 202, recon_loss:0.761438, zinb_loss:0.626608, adversial_loss:1.275815
Pretrain epoch 203, recon_loss:0.761329, zinb_loss:0.626583, adversial_loss:1.276529
Pretrain epoch 204, recon_loss:0.761202, zinb_loss:0.626573, adversial_loss:1.275519
Pretrain epoch 205, recon_loss:0.761257, zinb_loss:0.626585, adversial_loss:1.275652
Pretrain epoch 206, recon_loss:0.761152, zinb_loss:0.626577, adversial_loss:1.275099
Pretrain epoch 207, recon_loss:0.761234, zinb_loss:0.626690, adversial_loss:1.275626
Pretrain epoch 208, recon_loss:0.761665, zinb_loss:0.627107, adversial_loss:1.273614
Pretrain epoch 209, recon_loss:0.761999, zinb_loss:0.627263, adversial_loss:1.275154
Pretrain epoch 210, recon_loss:0.761713, zinb_loss:0.627031, adversial_loss:1.273631
Pretrain epoch 211, recon_loss:0.760860, zinb_loss:0.626554, adversial_loss:1.273066
Pretrain epoch 212, recon_loss:0.761342, zinb_loss:0.626922, adversial_loss:1.274019
Pretrain epoch 213, recon_loss:0.762381, zinb_loss:0.627192, adversial_loss:1.272925
Pretrain epoch 214, recon_loss:0.761405, zinb_loss:0.626692, adversial_loss:1.273736
Pretrain epoch 215, recon_loss:0.761456, zinb_loss:0.626911, adversial_loss:1.272705
Pretrain epoch 216, recon_loss:0.760689, zinb_loss:0.626513, adversial_loss:1.272339
Pretrain epoch 217, recon_loss:0.760589, zinb_loss:0.626463, adversial_loss:1.273166
Pretrain epoch 218, recon_loss:0.760831, zinb_loss:0.626679, adversial_loss:1.272440
Pretrain epoch 219, recon_loss:0.760364, zinb_loss:0.626378, adversial_loss:1.271747
Pretrain epoch 220, recon_loss:0.760391, zinb_loss:0.626402, adversial_loss:1.272083
Pretrain epoch 221, recon_loss:0.759937, zinb_loss:0.626285, adversial_loss:1.272450
Pretrain epoch 222, recon_loss:0.760152, zinb_loss:0.626306, adversial_loss:1.271766
Pretrain epoch 223, recon_loss:0.759920, zinb_loss:0.626314, adversial_loss:1.271065
Pretrain epoch 224, recon_loss:0.759479, zinb_loss:0.626046, adversial_loss:1.271957
Pretrain epoch 225, recon_loss:0.759670, zinb_loss:0.626167, adversial_loss:1.271603
Pretrain epoch 226, recon_loss:0.759341, zinb_loss:0.626084, adversial_loss:1.270462
Pretrain epoch 227, recon_loss:0.759355, zinb_loss:0.626023, adversial_loss:1.271136
Pretrain epoch 228, recon_loss:0.758976, zinb_loss:0.625971, adversial_loss:1.271234
Pretrain epoch 229, recon_loss:0.759075, zinb_loss:0.625943, adversial_loss:1.270373
Pretrain epoch 230, recon_loss:0.758902, zinb_loss:0.625946, adversial_loss:1.270608
Pretrain epoch 231, recon_loss:0.758847, zinb_loss:0.625828, adversial_loss:1.270542
Pretrain epoch 232, recon_loss:0.758621, zinb_loss:0.625816, adversial_loss:1.270036
Pretrain epoch 233, recon_loss:0.758484, zinb_loss:0.625754, adversial_loss:1.269886
Pretrain epoch 234, recon_loss:0.758580, zinb_loss:0.625754, adversial_loss:1.269803
Pretrain epoch 235, recon_loss:0.758282, zinb_loss:0.625766, adversial_loss:1.269494
Pretrain epoch 236, recon_loss:0.758247, zinb_loss:0.625758, adversial_loss:1.269161
Pretrain epoch 237, recon_loss:0.758274, zinb_loss:0.625919, adversial_loss:1.269464
Pretrain epoch 238, recon_loss:0.758416, zinb_loss:0.626123, adversial_loss:1.269094
Pretrain epoch 239, recon_loss:0.759425, zinb_loss:0.627000, adversial_loss:1.268666
Pretrain epoch 240, recon_loss:0.759433, zinb_loss:0.627312, adversial_loss:1.269424
Pretrain epoch 241, recon_loss:0.758946, zinb_loss:0.626515, adversial_loss:1.268044
Pretrain epoch 242, recon_loss:0.758398, zinb_loss:0.625859, adversial_loss:1.267596
Pretrain epoch 243, recon_loss:0.758400, zinb_loss:0.626189, adversial_loss:1.267879
Pretrain epoch 244, recon_loss:0.758251, zinb_loss:0.625972, adversial_loss:1.267945
Pretrain epoch 245, recon_loss:0.757926, zinb_loss:0.625754, adversial_loss:1.267376
Pretrain epoch 246, recon_loss:0.758450, zinb_loss:0.625991, adversial_loss:1.267111
Pretrain epoch 247, recon_loss:0.757817, zinb_loss:0.625638, adversial_loss:1.267705
Pretrain epoch 248, recon_loss:0.757740, zinb_loss:0.625709, adversial_loss:1.267026
Pretrain epoch 249, recon_loss:0.757581, zinb_loss:0.625628, adversial_loss:1.266837
Pretrain epoch 250, recon_loss:0.757324, zinb_loss:0.625543, adversial_loss:1.267304
Pretrain epoch 251, recon_loss:0.757314, zinb_loss:0.625634, adversial_loss:1.266793
Pretrain epoch 252, recon_loss:0.756889, zinb_loss:0.625389, adversial_loss:1.266628
Pretrain epoch 253, recon_loss:0.756935, zinb_loss:0.625487, adversial_loss:1.266536
Pretrain epoch 254, recon_loss:0.756694, zinb_loss:0.625405, adversial_loss:1.266254
Pretrain epoch 255, recon_loss:0.756546, zinb_loss:0.625338, adversial_loss:1.265859
Pretrain epoch 256, recon_loss:0.756459, zinb_loss:0.625372, adversial_loss:1.265898
Pretrain epoch 257, recon_loss:0.756208, zinb_loss:0.625240, adversial_loss:1.265420
Pretrain epoch 258, recon_loss:0.756110, zinb_loss:0.625279, adversial_loss:1.265282
Pretrain epoch 259, recon_loss:0.755972, zinb_loss:0.625202, adversial_loss:1.264920
Pretrain epoch 260, recon_loss:0.755845, zinb_loss:0.625181, adversial_loss:1.264856
Pretrain epoch 261, recon_loss:0.755776, zinb_loss:0.625212, adversial_loss:1.264385
Pretrain epoch 262, recon_loss:0.755658, zinb_loss:0.625171, adversial_loss:1.264643
Pretrain epoch 263, recon_loss:0.755740, zinb_loss:0.625268, adversial_loss:1.263762
Pretrain epoch 264, recon_loss:0.755793, zinb_loss:0.625322, adversial_loss:1.264693
Pretrain epoch 265, recon_loss:0.756047, zinb_loss:0.625576, adversial_loss:1.263003
Pretrain epoch 266, recon_loss:0.756053, zinb_loss:0.625506, adversial_loss:1.264240
Pretrain epoch 267, recon_loss:0.755714, zinb_loss:0.625297, adversial_loss:1.262850
Pretrain epoch 268, recon_loss:0.755153, zinb_loss:0.625064, adversial_loss:1.263153
Pretrain epoch 269, recon_loss:0.755243, zinb_loss:0.625092, adversial_loss:1.263150
Pretrain epoch 270, recon_loss:0.755230, zinb_loss:0.625185, adversial_loss:1.262389
Pretrain epoch 271, recon_loss:0.755256, zinb_loss:0.625203, adversial_loss:1.262950
Pretrain epoch 272, recon_loss:0.755542, zinb_loss:0.625343, adversial_loss:1.262252
Pretrain epoch 273, recon_loss:0.756221, zinb_loss:0.625609, adversial_loss:1.262175
Pretrain epoch 274, recon_loss:0.757112, zinb_loss:0.625953, adversial_loss:1.262888
Pretrain epoch 275, recon_loss:0.757585, zinb_loss:0.626125, adversial_loss:1.261826
Pretrain epoch 276, recon_loss:0.755297, zinb_loss:0.625102, adversial_loss:1.261289
Pretrain epoch 277, recon_loss:0.755384, zinb_loss:0.625368, adversial_loss:1.261689
Pretrain epoch 278, recon_loss:0.756129, zinb_loss:0.625459, adversial_loss:1.260738
Pretrain epoch 279, recon_loss:0.754724, zinb_loss:0.625007, adversial_loss:1.260598
Pretrain epoch 280, recon_loss:0.755369, zinb_loss:0.625379, adversial_loss:1.261417
Pretrain epoch 281, recon_loss:0.754782, zinb_loss:0.624991, adversial_loss:1.260518
Pretrain epoch 282, recon_loss:0.754534, zinb_loss:0.625051, adversial_loss:1.259917
Pretrain epoch 283, recon_loss:0.754491, zinb_loss:0.625008, adversial_loss:1.260628
Pretrain epoch 284, recon_loss:0.754288, zinb_loss:0.624848, adversial_loss:1.260599
Pretrain epoch 285, recon_loss:0.754080, zinb_loss:0.624923, adversial_loss:1.259742
Pretrain epoch 286, recon_loss:0.753993, zinb_loss:0.624777, adversial_loss:1.259850
Pretrain epoch 287, recon_loss:0.753858, zinb_loss:0.624777, adversial_loss:1.260215
Pretrain epoch 288, recon_loss:0.753481, zinb_loss:0.624721, adversial_loss:1.259990
Pretrain epoch 289, recon_loss:0.753600, zinb_loss:0.624683, adversial_loss:1.259371
Pretrain epoch 290, recon_loss:0.753198, zinb_loss:0.624659, adversial_loss:1.259436
Pretrain epoch 291, recon_loss:0.753150, zinb_loss:0.624620, adversial_loss:1.259738
Pretrain epoch 292, recon_loss:0.753045, zinb_loss:0.624606, adversial_loss:1.259176
Pretrain epoch 293, recon_loss:0.752695, zinb_loss:0.624578, adversial_loss:1.258881
Pretrain epoch 294, recon_loss:0.752711, zinb_loss:0.624557, adversial_loss:1.259076
Pretrain epoch 295, recon_loss:0.752386, zinb_loss:0.624516, adversial_loss:1.258735
Pretrain epoch 296, recon_loss:0.752381, zinb_loss:0.624503, adversial_loss:1.258430
Pretrain epoch 297, recon_loss:0.752095, zinb_loss:0.624473, adversial_loss:1.258393
Pretrain epoch 298, recon_loss:0.752020, zinb_loss:0.624451, adversial_loss:1.258269
Pretrain epoch 299, recon_loss:0.751884, zinb_loss:0.624454, adversial_loss:1.257985
Pretrain epoch 300, recon_loss:0.751720, zinb_loss:0.624407, adversial_loss:1.257759
Pretrain epoch 301, recon_loss:0.751619, zinb_loss:0.624393, adversial_loss:1.257720
Pretrain epoch 302, recon_loss:0.751603, zinb_loss:0.624389, adversial_loss:1.257465
Pretrain epoch 303, recon_loss:0.751616, zinb_loss:0.624417, adversial_loss:1.257201
Pretrain epoch 304, recon_loss:0.751976, zinb_loss:0.624573, adversial_loss:1.257134
Pretrain epoch 305, recon_loss:0.753156, zinb_loss:0.625050, adversial_loss:1.257288
Pretrain epoch 306, recon_loss:0.754855, zinb_loss:0.625786, adversial_loss:1.256867
Pretrain epoch 307, recon_loss:0.754816, zinb_loss:0.626012, adversial_loss:1.256853
Pretrain epoch 308, recon_loss:0.751676, zinb_loss:0.624669, adversial_loss:1.256409
Pretrain epoch 309, recon_loss:0.752470, zinb_loss:0.624667, adversial_loss:1.256081
Pretrain epoch 310, recon_loss:0.753001, zinb_loss:0.625094, adversial_loss:1.256042
Pretrain epoch 311, recon_loss:0.751207, zinb_loss:0.624419, adversial_loss:1.255652
Pretrain epoch 312, recon_loss:0.752243, zinb_loss:0.624646, adversial_loss:1.255806
Pretrain epoch 313, recon_loss:0.751611, zinb_loss:0.624558, adversial_loss:1.255658
Pretrain epoch 314, recon_loss:0.751132, zinb_loss:0.624370, adversial_loss:1.255069
Pretrain epoch 315, recon_loss:0.751409, zinb_loss:0.624456, adversial_loss:1.255266
Pretrain epoch 316, recon_loss:0.750799, zinb_loss:0.624303, adversial_loss:1.255428
Pretrain epoch 317, recon_loss:0.750899, zinb_loss:0.624351, adversial_loss:1.254581
Pretrain epoch 318, recon_loss:0.750526, zinb_loss:0.624260, adversial_loss:1.254706
Pretrain epoch 319, recon_loss:0.750601, zinb_loss:0.624306, adversial_loss:1.255149
Pretrain epoch 320, recon_loss:0.750154, zinb_loss:0.624208, adversial_loss:1.254608
Pretrain epoch 321, recon_loss:0.750454, zinb_loss:0.624261, adversial_loss:1.253649
Pretrain epoch 322, recon_loss:0.750311, zinb_loss:0.624279, adversial_loss:1.255018
Pretrain epoch 323, recon_loss:0.750246, zinb_loss:0.624426, adversial_loss:1.253833
Pretrain epoch 324, recon_loss:0.750702, zinb_loss:0.624627, adversial_loss:1.253942
Pretrain epoch 325, recon_loss:0.750848, zinb_loss:0.624686, adversial_loss:1.253212
Pretrain epoch 326, recon_loss:0.750545, zinb_loss:0.624489, adversial_loss:1.254483
Pretrain epoch 327, recon_loss:0.749625, zinb_loss:0.624184, adversial_loss:1.252910
Pretrain epoch 328, recon_loss:0.749357, zinb_loss:0.624110, adversial_loss:1.252911
Pretrain epoch 329, recon_loss:0.749682, zinb_loss:0.624217, adversial_loss:1.253526
Pretrain epoch 330, recon_loss:0.749361, zinb_loss:0.624243, adversial_loss:1.252541
Pretrain epoch 331, recon_loss:0.749046, zinb_loss:0.624085, adversial_loss:1.252763
Pretrain epoch 332, recon_loss:0.748671, zinb_loss:0.623996, adversial_loss:1.252374
Pretrain epoch 333, recon_loss:0.748825, zinb_loss:0.624106, adversial_loss:1.252345
Pretrain epoch 334, recon_loss:0.748693, zinb_loss:0.624035, adversial_loss:1.252432
Pretrain epoch 335, recon_loss:0.748310, zinb_loss:0.623969, adversial_loss:1.251544
Pretrain epoch 336, recon_loss:0.748171, zinb_loss:0.623935, adversial_loss:1.252011
Pretrain epoch 337, recon_loss:0.748107, zinb_loss:0.623957, adversial_loss:1.252016
Pretrain epoch 338, recon_loss:0.748038, zinb_loss:0.623936, adversial_loss:1.250951
Pretrain epoch 339, recon_loss:0.747790, zinb_loss:0.623863, adversial_loss:1.251737
Pretrain epoch 340, recon_loss:0.747788, zinb_loss:0.623857, adversial_loss:1.251112
Pretrain epoch 341, recon_loss:0.747594, zinb_loss:0.623835, adversial_loss:1.250883
Pretrain epoch 342, recon_loss:0.747351, zinb_loss:0.623804, adversial_loss:1.250976
Pretrain epoch 343, recon_loss:0.747299, zinb_loss:0.623808, adversial_loss:1.250553
Pretrain epoch 344, recon_loss:0.747291, zinb_loss:0.623843, adversial_loss:1.250751
Pretrain epoch 345, recon_loss:0.747353, zinb_loss:0.623880, adversial_loss:1.250244
Pretrain epoch 346, recon_loss:0.747712, zinb_loss:0.623967, adversial_loss:1.250278
Pretrain epoch 347, recon_loss:0.748533, zinb_loss:0.624176, adversial_loss:1.250290
Pretrain epoch 348, recon_loss:0.749864, zinb_loss:0.624498, adversial_loss:1.249875
Pretrain epoch 349, recon_loss:0.749792, zinb_loss:0.624604, adversial_loss:1.249688
Pretrain epoch 350, recon_loss:0.747748, zinb_loss:0.624104, adversial_loss:1.249543
Pretrain epoch 351, recon_loss:0.747056, zinb_loss:0.623864, adversial_loss:1.248984
Pretrain epoch 352, recon_loss:0.748128, zinb_loss:0.624133, adversial_loss:1.249011
Pretrain epoch 353, recon_loss:0.747624, zinb_loss:0.624018, adversial_loss:1.249153
Pretrain epoch 354, recon_loss:0.746567, zinb_loss:0.623769, adversial_loss:1.248775
Pretrain epoch 355, recon_loss:0.746866, zinb_loss:0.623964, adversial_loss:1.248478
Pretrain epoch 356, recon_loss:0.746527, zinb_loss:0.623889, adversial_loss:1.248987
Pretrain epoch 357, recon_loss:0.746377, zinb_loss:0.623701, adversial_loss:1.248239
Pretrain epoch 358, recon_loss:0.746282, zinb_loss:0.623742, adversial_loss:1.248244
Pretrain epoch 359, recon_loss:0.746046, zinb_loss:0.623740, adversial_loss:1.248407
Pretrain epoch 360, recon_loss:0.745941, zinb_loss:0.623657, adversial_loss:1.248133
Pretrain epoch 361, recon_loss:0.745735, zinb_loss:0.623707, adversial_loss:1.247800
Pretrain epoch 362, recon_loss:0.745730, zinb_loss:0.623680, adversial_loss:1.248000
Pretrain epoch 363, recon_loss:0.745833, zinb_loss:0.623627, adversial_loss:1.247833
Pretrain epoch 364, recon_loss:0.745583, zinb_loss:0.623639, adversial_loss:1.247455
Pretrain epoch 365, recon_loss:0.745557, zinb_loss:0.623658, adversial_loss:1.247508
Pretrain epoch 366, recon_loss:0.745358, zinb_loss:0.623622, adversial_loss:1.247385
Pretrain epoch 367, recon_loss:0.745166, zinb_loss:0.623627, adversial_loss:1.247007
Pretrain epoch 368, recon_loss:0.745114, zinb_loss:0.623602, adversial_loss:1.247067
Pretrain epoch 369, recon_loss:0.745092, zinb_loss:0.623547, adversial_loss:1.246902
Pretrain epoch 370, recon_loss:0.744758, zinb_loss:0.623542, adversial_loss:1.246693
Pretrain epoch 371, recon_loss:0.745036, zinb_loss:0.623572, adversial_loss:1.246650
Pretrain epoch 372, recon_loss:0.744833, zinb_loss:0.623528, adversial_loss:1.246337
Pretrain epoch 373, recon_loss:0.744253, zinb_loss:0.623511, adversial_loss:1.246203
Pretrain epoch 374, recon_loss:0.744213, zinb_loss:0.623551, adversial_loss:1.246197
Pretrain epoch 375, recon_loss:0.744185, zinb_loss:0.623590, adversial_loss:1.245750
Pretrain epoch 376, recon_loss:0.744927, zinb_loss:0.623700, adversial_loss:1.245964
Pretrain epoch 377, recon_loss:0.745542, zinb_loss:0.623854, adversial_loss:1.245949
Pretrain epoch 378, recon_loss:0.746172, zinb_loss:0.624132, adversial_loss:1.245143
Pretrain epoch 379, recon_loss:0.745374, zinb_loss:0.624021, adversial_loss:1.246134
Pretrain epoch 380, recon_loss:0.744613, zinb_loss:0.623714, adversial_loss:1.244378
Pretrain epoch 381, recon_loss:0.745395, zinb_loss:0.623964, adversial_loss:1.245559
Pretrain epoch 382, recon_loss:0.745601, zinb_loss:0.624205, adversial_loss:1.244211
Pretrain epoch 383, recon_loss:0.744020, zinb_loss:0.623674, adversial_loss:1.245310
Pretrain epoch 384, recon_loss:0.744484, zinb_loss:0.623604, adversial_loss:1.244278
Pretrain epoch 385, recon_loss:0.744280, zinb_loss:0.623744, adversial_loss:1.244271
Pretrain epoch 386, recon_loss:0.744052, zinb_loss:0.623587, adversial_loss:1.244613
Pretrain epoch 387, recon_loss:0.743644, zinb_loss:0.623512, adversial_loss:1.244011
Pretrain epoch 388, recon_loss:0.743463, zinb_loss:0.623467, adversial_loss:1.243936
Pretrain epoch 389, recon_loss:0.743408, zinb_loss:0.623382, adversial_loss:1.244285
Pretrain epoch 390, recon_loss:0.742802, zinb_loss:0.623369, adversial_loss:1.243493
Pretrain epoch 391, recon_loss:0.742870, zinb_loss:0.623338, adversial_loss:1.243549
Pretrain epoch 392, recon_loss:0.742498, zinb_loss:0.623299, adversial_loss:1.243875
Pretrain epoch 393, recon_loss:0.742168, zinb_loss:0.623262, adversial_loss:1.243256
Pretrain epoch 394, recon_loss:0.742424, zinb_loss:0.623246, adversial_loss:1.243256
Pretrain epoch 395, recon_loss:0.741983, zinb_loss:0.623228, adversial_loss:1.243176
Pretrain epoch 396, recon_loss:0.741756, zinb_loss:0.623253, adversial_loss:1.243132
Pretrain epoch 397, recon_loss:0.742005, zinb_loss:0.623249, adversial_loss:1.242527
Pretrain epoch 398, recon_loss:0.742020, zinb_loss:0.623239, adversial_loss:1.243070
Pretrain epoch 399, recon_loss:0.742514, zinb_loss:0.623436, adversial_loss:1.241964
Pretrain epoch 400, recon_loss:0.743174, zinb_loss:0.623717, adversial_loss:1.243144

When the parameter n_cluster is set to -1, scMAGCA will use GetCluster to estimate the number of clusters according to the resolution parameter and the potential representation obtained by pre-training, and use ASW, DB index and CH value to evaluate the clustering results.

y_pred, final_latent = model.fit(y=y, n_clusters=-1, num_epochs=2000, file='GSM4949911',
                                 pretrain_latent=pretrain_latent, resolution=0.1)

Clustering stage
Estimated n_clusters is:  6
Initializing cluster centers with kmeans.
Initializing k-means: ASW= 0.4081, DB= 0.9771, CH= 4057.4425
Training epoch 1, recon_loss:0.744567, zinb_loss:0.624116, cluster_loss:0.184134
Clustering   1: ASW= 0.4081, DB= 0.9771, CH= 4057.4425
Training epoch 2, recon_loss:0.781684, zinb_loss:0.635306, cluster_loss:0.192307
Clustering   2: ASW= 0.5035, DB= 0.7872, CH= 7048.4868
Training epoch 3, recon_loss:0.781879, zinb_loss:0.638056, cluster_loss:0.199501
Clustering   3: ASW= 0.5203, DB= 0.7576, CH= 7181.4846
Training epoch 4, recon_loss:0.802478, zinb_loss:0.644835, cluster_loss:0.204655
Clustering   4: ASW= 0.5511, DB= 0.7052, CH= 9237.8673
Training epoch 5, recon_loss:0.788960, zinb_loss:0.637543, cluster_loss:0.195610
Clustering   5: ASW= 0.5629, DB= 0.6762, CH= 9559.8021
Training epoch 6, recon_loss:0.791756, zinb_loss:0.640890, cluster_loss:0.195503
Clustering   6: ASW= 0.5875, DB= 0.6388, CH= 10485.6587
Training epoch 7, recon_loss:0.788115, zinb_loss:0.639390, cluster_loss:0.190574
Clustering   7: ASW= 0.5878, DB= 0.6310, CH= 10706.3957
Training epoch 8, recon_loss:0.795532, zinb_loss:0.643657, cluster_loss:0.196299
Clustering   8: ASW= 0.6004, DB= 0.6067, CH= 11318.9830
Training epoch 9, recon_loss:0.793502, zinb_loss:0.644986, cluster_loss:0.191464
Clustering   9: ASW= 0.6066, DB= 0.5921, CH= 12165.7921
Training epoch 10, recon_loss:0.795640, zinb_loss:0.645226, cluster_loss:0.193899
Clustering   10: ASW= 0.6189, DB= 0.5795, CH= 12337.0980
Training epoch 11, recon_loss:0.794627, zinb_loss:0.646246, cluster_loss:0.190530
Clustering   11: ASW= 0.6209, DB= 0.5646, CH= 13181.4561
Training epoch 12, recon_loss:0.793503, zinb_loss:0.643653, cluster_loss:0.191122
Clustering   12: ASW= 0.6333, DB= 0.5539, CH= 13114.1243
Training epoch 13, recon_loss:0.790501, zinb_loss:0.643247, cluster_loss:0.185939
Clustering   13: ASW= 0.6322, DB= 0.5480, CH= 13909.9101
Training epoch 14, recon_loss:0.791912, zinb_loss:0.644665, cluster_loss:0.186220
Clustering   14: ASW= 0.6435, DB= 0.5346, CH= 13930.9664
Training epoch 15, recon_loss:0.789298, zinb_loss:0.644028, cluster_loss:0.182875
Clustering   15: ASW= 0.6452, DB= 0.5299, CH= 14541.9165
Training epoch 16, recon_loss:0.790982, zinb_loss:0.644929, cluster_loss:0.183325
Clustering   16: ASW= 0.6533, DB= 0.5175, CH= 14713.5949
Training epoch 17, recon_loss:0.789246, zinb_loss:0.643808, cluster_loss:0.181418
Clustering   17: ASW= 0.6554, DB= 0.5132, CH= 15224.9930
Training epoch 18, recon_loss:0.791492, zinb_loss:0.645494, cluster_loss:0.181958
Clustering   18: ASW= 0.6629, DB= 0.5014, CH= 15485.4823
Training epoch 19, recon_loss:0.789743, zinb_loss:0.644231, cluster_loss:0.180452
Clustering   19: ASW= 0.6651, DB= 0.4963, CH= 15993.7179
Training epoch 20, recon_loss:0.791554, zinb_loss:0.645630, cluster_loss:0.180706
Clustering   20: ASW= 0.6718, DB= 0.4855, CH= 16238.4130
Training epoch 21, recon_loss:0.789927, zinb_loss:0.644363, cluster_loss:0.179470
Clustering   21: ASW= 0.6741, DB= 0.4805, CH= 16741.5947
Training epoch 22, recon_loss:0.791409, zinb_loss:0.645626, cluster_loss:0.179546
Clustering   22: ASW= 0.6800, DB= 0.4708, CH= 16957.5644
Training epoch 23, recon_loss:0.790026, zinb_loss:0.644476, cluster_loss:0.178504
Clustering   23: ASW= 0.6824, DB= 0.4654, CH= 17467.1475
Training epoch 24, recon_loss:0.791160, zinb_loss:0.645633, cluster_loss:0.178435
Clustering   24: ASW= 0.6876, DB= 0.4572, CH= 17651.8670
Training epoch 25, recon_loss:0.790033, zinb_loss:0.644636, cluster_loss:0.177479
Clustering   25: ASW= 0.6899, DB= 0.4520, CH= 18159.1258
Training epoch 26, recon_loss:0.790941, zinb_loss:0.645726, cluster_loss:0.177350
Clustering   26: ASW= 0.6945, DB= 0.4448, CH= 18320.8315
Training epoch 27, recon_loss:0.790051, zinb_loss:0.644885, cluster_loss:0.176457
Clustering   27: ASW= 0.6965, DB= 0.4400, CH= 18799.5358
Training epoch 28, recon_loss:0.790884, zinb_loss:0.645942, cluster_loss:0.176336
Clustering   28: ASW= 0.7009, DB= 0.4337, CH= 18973.0495
Training epoch 29, recon_loss:0.790154, zinb_loss:0.645214, cluster_loss:0.175504
Clustering   29: ASW= 0.7021, DB= 0.4284, CH= 19374.2514
Training epoch 30, recon_loss:0.790992, zinb_loss:0.646239, cluster_loss:0.175394
Clustering   30: ASW= 0.7066, DB= 0.4239, CH= 19596.3244
Training epoch 31, recon_loss:0.790411, zinb_loss:0.645577, cluster_loss:0.174676
Clustering   31: ASW= 0.7069, DB= 0.4194, CH= 19914.3225
Training epoch 32, recon_loss:0.791320, zinb_loss:0.646544, cluster_loss:0.174585
Clustering   32: ASW= 0.7119, DB= 0.4148, CH= 20200.7676
Training epoch 33, recon_loss:0.790896, zinb_loss:0.645896, cluster_loss:0.174084
Clustering   33: ASW= 0.7108, DB= 0.4114, CH= 20389.9855
Training epoch 34, recon_loss:0.791883, zinb_loss:0.646757, cluster_loss:0.173998
Clustering   34: ASW= 0.7167, DB= 0.4066, CH= 20784.2287
Training epoch 35, recon_loss:0.791580, zinb_loss:0.646077, cluster_loss:0.173861
Clustering   35: ASW= 0.7142, DB= 0.4048, CH= 20818.7748
Training epoch 36, recon_loss:0.792708, zinb_loss:0.646908, cluster_loss:0.173661
Clustering   36: ASW= 0.7209, DB= 0.3997, CH= 21376.5842
Training epoch 37, recon_loss:0.792308, zinb_loss:0.646198, cluster_loss:0.173958
Clustering   37: ASW= 0.7178, DB= 0.3997, CH= 21227.3954
Training epoch 38, recon_loss:0.793536, zinb_loss:0.647071, cluster_loss:0.173452
Clustering   38: ASW= 0.7243, DB= 0.3938, CH= 21940.6146
Training epoch 39, recon_loss:0.792650, zinb_loss:0.646334, cluster_loss:0.173853
Clustering   39: ASW= 0.7216, DB= 0.3933, CH= 21605.7713
Training epoch 40, recon_loss:0.793561, zinb_loss:0.647123, cluster_loss:0.172832
Clustering   40: ASW= 0.7270, DB= 0.3889, CH= 22434.8069
Training epoch 41, recon_loss:0.792455, zinb_loss:0.646422, cluster_loss:0.173081
Clustering   41: ASW= 0.7253, DB= 0.3880, CH= 22016.1240
Training epoch 42, recon_loss:0.793121, zinb_loss:0.647158, cluster_loss:0.171864
Clustering   42: ASW= 0.7296, DB= 0.3841, CH= 22880.1381
Training epoch 43, recon_loss:0.792161, zinb_loss:0.646511, cluster_loss:0.172056
Clustering   43: ASW= 0.7285, DB= 0.3832, CH= 22441.1165
Training epoch 44, recon_loss:0.792669, zinb_loss:0.647224, cluster_loss:0.170923
Clustering   44: ASW= 0.7323, DB= 0.3801, CH= 23308.4009
Training epoch 45, recon_loss:0.791936, zinb_loss:0.646629, cluster_loss:0.171171
Clustering   45: ASW= 0.7311, DB= 0.3794, CH= 22830.8324
Training epoch 46, recon_loss:0.792408, zinb_loss:0.647386, cluster_loss:0.170139
Clustering   46: ASW= 0.7350, DB= 0.3758, CH= 23720.7644
Training epoch 47, recon_loss:0.791735, zinb_loss:0.646757, cluster_loss:0.170424
Clustering   47: ASW= 0.7334, DB= 0.3752, CH= 23184.3867
Training epoch 48, recon_loss:0.792224, zinb_loss:0.647568, cluster_loss:0.169477
Clustering   48: ASW= 0.7376, DB= 0.3716, CH= 24119.5970
Training epoch 49, recon_loss:0.791572, zinb_loss:0.646885, cluster_loss:0.169838
Clustering   49: ASW= 0.7355, DB= 0.3721, CH= 23523.7886
Training epoch 50, recon_loss:0.792151, zinb_loss:0.647766, cluster_loss:0.168988
Clustering   50: ASW= 0.7399, DB= 0.3682, CH= 24495.2883
Training epoch 51, recon_loss:0.791514, zinb_loss:0.647032, cluster_loss:0.169469
Clustering   51: ASW= 0.7374, DB= 0.3690, CH= 23838.4278
Training epoch 52, recon_loss:0.792260, zinb_loss:0.647990, cluster_loss:0.168765
Clustering   52: ASW= 0.7418, DB= 0.3664, CH= 24852.9703
Training epoch 53, recon_loss:0.791620, zinb_loss:0.647189, cluster_loss:0.169355
Clustering   53: ASW= 0.7392, DB= 0.3669, CH= 24137.3850
Training epoch 54, recon_loss:0.792565, zinb_loss:0.648117, cluster_loss:0.168693
Clustering   54: ASW= 0.7431, DB= 0.3626, CH= 25153.7847
Training epoch 55, recon_loss:0.791842, zinb_loss:0.647240, cluster_loss:0.169230
Clustering   55: ASW= 0.7412, DB= 0.3646, CH= 24445.4218
Training epoch 56, recon_loss:0.792959, zinb_loss:0.648107, cluster_loss:0.168525
Clustering   56: ASW= 0.7445, DB= 0.3594, CH= 25456.0063
Training epoch 57, recon_loss:0.791962, zinb_loss:0.647209, cluster_loss:0.168900
Clustering   57: ASW= 0.7435, DB= 0.3615, CH= 24805.0179
Training epoch 58, recon_loss:0.793046, zinb_loss:0.647981, cluster_loss:0.168251
Clustering   58: ASW= 0.7461, DB= 0.3563, CH= 25740.0570
Training epoch 59, recon_loss:0.792017, zinb_loss:0.647157, cluster_loss:0.168451
Clustering   59: ASW= 0.7455, DB= 0.3588, CH= 25160.9770
Training epoch 60, recon_loss:0.793047, zinb_loss:0.647811, cluster_loss:0.168048
Clustering   60: ASW= 0.7478, DB= 0.3540, CH= 26001.7672
Training epoch 61, recon_loss:0.792132, zinb_loss:0.647105, cluster_loss:0.168134
Clustering   61: ASW= 0.7472, DB= 0.3569, CH= 25502.1591
Training epoch 62, recon_loss:0.793054, zinb_loss:0.647648, cluster_loss:0.167881
Clustering   62: ASW= 0.7493, DB= 0.3515, CH= 26258.3489
Training epoch 63, recon_loss:0.792143, zinb_loss:0.647033, cluster_loss:0.167827
Clustering   63: ASW= 0.7487, DB= 0.3546, CH= 25811.4141
Training epoch 64, recon_loss:0.792888, zinb_loss:0.647470, cluster_loss:0.167610
Clustering   64: ASW= 0.7508, DB= 0.3495, CH= 26516.5546
Training epoch 65, recon_loss:0.791956, zinb_loss:0.646935, cluster_loss:0.167434
Clustering   65: ASW= 0.7502, DB= 0.3524, CH= 26101.7202
Training epoch 66, recon_loss:0.792565, zinb_loss:0.647317, cluster_loss:0.167206
Clustering   66: ASW= 0.7521, DB= 0.3474, CH= 26784.6218
Training epoch 67, recon_loss:0.791658, zinb_loss:0.646850, cluster_loss:0.166972
Clustering   67: ASW= 0.7517, DB= 0.3500, CH= 26380.8573
Training epoch 68, recon_loss:0.792175, zinb_loss:0.647203, cluster_loss:0.166745
Clustering   68: ASW= 0.7534, DB= 0.3456, CH= 27058.3477
Training epoch 69, recon_loss:0.791458, zinb_loss:0.646813, cluster_loss:0.166587
Clustering   69: ASW= 0.7532, DB= 0.3479, CH= 26629.1185
Training epoch 70, recon_loss:0.791937, zinb_loss:0.647191, cluster_loss:0.166368
Clustering   70: ASW= 0.7546, DB= 0.3439, CH= 27347.3599
Training epoch 71, recon_loss:0.791464, zinb_loss:0.646864, cluster_loss:0.166331
Clustering   71: ASW= 0.7546, DB= 0.3453, CH= 26882.8002
Training epoch 72, recon_loss:0.791901, zinb_loss:0.647289, cluster_loss:0.166123
Clustering   72: ASW= 0.7558, DB= 0.3417, CH= 27621.0542
Training epoch 73, recon_loss:0.791706, zinb_loss:0.647042, cluster_loss:0.166227
Clustering   73: ASW= 0.7559, DB= 0.3442, CH= 27139.2965
Training epoch 74, recon_loss:0.792051, zinb_loss:0.647543, cluster_loss:0.166005
Clustering   74: ASW= 0.7569, DB= 0.3395, CH= 27884.7212
Training epoch 75, recon_loss:0.791942, zinb_loss:0.647306, cluster_loss:0.166171
Clustering   75: ASW= 0.7572, DB= 0.3421, CH= 27372.6464
Training epoch 76, recon_loss:0.792110, zinb_loss:0.647812, cluster_loss:0.165873
Clustering   76: ASW= 0.7579, DB= 0.3380, CH= 28129.3803
Training epoch 77, recon_loss:0.791903, zinb_loss:0.647530, cluster_loss:0.166023
Clustering   77: ASW= 0.7583, DB= 0.3402, CH= 27610.8474
Training epoch 78, recon_loss:0.791952, zinb_loss:0.647974, cluster_loss:0.165621
Clustering   78: ASW= 0.7589, DB= 0.3367, CH= 28350.4636
Training epoch 79, recon_loss:0.791602, zinb_loss:0.647666, cluster_loss:0.165760
Clustering   79: ASW= 0.7593, DB= 0.3382, CH= 27862.7363
Training epoch 80, recon_loss:0.791686, zinb_loss:0.648010, cluster_loss:0.165302
Clustering   80: ASW= 0.7600, DB= 0.3357, CH= 28551.4303
Training epoch 81, recon_loss:0.791312, zinb_loss:0.647766, cluster_loss:0.165492
Clustering   81: ASW= 0.7602, DB= 0.3365, CH= 28115.4741
Training epoch 82, recon_loss:0.791460, zinb_loss:0.647985, cluster_loss:0.165009
Clustering   82: ASW= 0.7611, DB= 0.3345, CH= 28734.5324
Training epoch 83, recon_loss:0.791164, zinb_loss:0.647894, cluster_loss:0.165249
Clustering   83: ASW= 0.7610, DB= 0.3356, CH= 28402.8143
Training epoch 84, recon_loss:0.791352, zinb_loss:0.647991, cluster_loss:0.164766
Clustering   84: ASW= 0.7622, DB= 0.3332, CH= 28892.9929
Training epoch 85, recon_loss:0.791217, zinb_loss:0.648101, cluster_loss:0.165010
Clustering   85: ASW= 0.7617, DB= 0.3346, CH= 28710.5160
Training epoch 86, recon_loss:0.791365, zinb_loss:0.648078, cluster_loss:0.164574
Clustering   86: ASW= 0.7633, DB= 0.3321, CH= 29017.3921
Training epoch 87, recon_loss:0.791659, zinb_loss:0.648519, cluster_loss:0.164832
Clustering   87: ASW= 0.7624, DB= 0.3331, CH= 29044.2741
Training epoch 88, recon_loss:0.791725, zinb_loss:0.648356, cluster_loss:0.164560
Clustering   88: ASW= 0.7644, DB= 0.3316, CH= 29099.2268
Training epoch 89, recon_loss:0.792552, zinb_loss:0.649082, cluster_loss:0.164823
Clustering   89: ASW= 0.7631, DB= 0.3314, CH= 29388.3728
Training epoch 90, recon_loss:0.792114, zinb_loss:0.648588, cluster_loss:0.164634
Clustering   90: ASW= 0.7654, DB= 0.3309, CH= 29217.1969
Training epoch 91, recon_loss:0.793110, zinb_loss:0.649289, cluster_loss:0.164880
Clustering   91: ASW= 0.7637, DB= 0.3298, CH= 29646.5459
Training epoch 92, recon_loss:0.792037, zinb_loss:0.648463, cluster_loss:0.164504
Clustering   92: ASW= 0.7662, DB= 0.3299, CH= 29425.2856
Training epoch 93, recon_loss:0.793016, zinb_loss:0.649034, cluster_loss:0.164729
Clustering   93: ASW= 0.7647, DB= 0.3290, CH= 29855.6239
Training epoch 94, recon_loss:0.791845, zinb_loss:0.648197, cluster_loss:0.164285
Clustering   94: ASW= 0.7668, DB= 0.3292, CH= 29613.7612
Training epoch 95, recon_loss:0.792960, zinb_loss:0.648805, cluster_loss:0.164481
Clustering   95: ASW= 0.7659, DB= 0.3274, CH= 30072.6021
Training epoch 96, recon_loss:0.791553, zinb_loss:0.647937, cluster_loss:0.163971
Clustering   96: ASW= 0.7674, DB= 0.3287, CH= 29820.9324
Training epoch 97, recon_loss:0.792576, zinb_loss:0.648543, cluster_loss:0.164059
Clustering   97: ASW= 0.7671, DB= 0.3262, CH= 30270.7187
Training epoch 98, recon_loss:0.791022, zinb_loss:0.647711, cluster_loss:0.163519
Clustering   98: ASW= 0.7682, DB= 0.3276, CH= 30035.1755
Training epoch 99, recon_loss:0.791844, zinb_loss:0.648285, cluster_loss:0.163517
Clustering   99: ASW= 0.7680, DB= 0.3250, CH= 30463.0335
Training epoch 100, recon_loss:0.790507, zinb_loss:0.647555, cluster_loss:0.163100
Clustering   100: ASW= 0.7688, DB= 0.3264, CH= 30233.9740
Training epoch 101, recon_loss:0.791299, zinb_loss:0.648140, cluster_loss:0.163104
Clustering   101: ASW= 0.7689, DB= 0.3246, CH= 30648.5508
Training epoch 102, recon_loss:0.790149, zinb_loss:0.647484, cluster_loss:0.162793
Clustering   102: ASW= 0.7694, DB= 0.3248, CH= 30430.7393
Training epoch 103, recon_loss:0.790937, zinb_loss:0.648067, cluster_loss:0.162810
Clustering   103: ASW= 0.7697, DB= 0.3239, CH= 30831.6858
Training epoch 104, recon_loss:0.789932, zinb_loss:0.647466, cluster_loss:0.162593
Clustering   104: ASW= 0.7700, DB= 0.3237, CH= 30619.4572
Training epoch 105, recon_loss:0.790782, zinb_loss:0.648062, cluster_loss:0.162627
Clustering   105: ASW= 0.7705, DB= 0.3226, CH= 31014.7771
Training epoch 106, recon_loss:0.789860, zinb_loss:0.647489, cluster_loss:0.162502
Clustering   106: ASW= 0.7705, DB= 0.3236, CH= 30815.1758
Training epoch 107, recon_loss:0.790819, zinb_loss:0.648092, cluster_loss:0.162557
Clustering   107: ASW= 0.7713, DB= 0.3220, CH= 31183.3700
Training epoch 108, recon_loss:0.789977, zinb_loss:0.647529, cluster_loss:0.162542
Clustering   108: ASW= 0.7710, DB= 0.3228, CH= 30992.0955
Training epoch 109, recon_loss:0.791109, zinb_loss:0.648135, cluster_loss:0.162631
Clustering   109: ASW= 0.7719, DB= 0.3209, CH= 31325.5398
Training epoch 110, recon_loss:0.790383, zinb_loss:0.647578, cluster_loss:0.162762
Clustering   110: ASW= 0.7713, DB= 0.3228, CH= 31167.5080
Training epoch 111, recon_loss:0.791713, zinb_loss:0.648188, cluster_loss:0.162856
Clustering   111: ASW= 0.7726, DB= 0.3200, CH= 31440.4167
Training epoch 112, recon_loss:0.790986, zinb_loss:0.647628, cluster_loss:0.163121
Clustering   112: ASW= 0.7714, DB= 0.3222, CH= 31310.5559
Training epoch 113, recon_loss:0.792351, zinb_loss:0.648193, cluster_loss:0.163090
Clustering   113: ASW= 0.7733, DB= 0.3195, CH= 31541.7789
Training epoch 114, recon_loss:0.791462, zinb_loss:0.647629, cluster_loss:0.163362
Clustering   114: ASW= 0.7715, DB= 0.3215, CH= 31451.7911
Training epoch 115, recon_loss:0.792591, zinb_loss:0.648087, cluster_loss:0.163118
Clustering   115: ASW= 0.7739, DB= 0.3181, CH= 31619.3713
Training epoch 116, recon_loss:0.791608, zinb_loss:0.647552, cluster_loss:0.163241
Clustering   116: ASW= 0.7718, DB= 0.3206, CH= 31640.3609
Training epoch 117, recon_loss:0.792424, zinb_loss:0.647879, cluster_loss:0.162888
Clustering   117: ASW= 0.7744, DB= 0.3172, CH= 31687.6710
Training epoch 118, recon_loss:0.791625, zinb_loss:0.647466, cluster_loss:0.162862
Clustering   118: ASW= 0.7725, DB= 0.3195, CH= 31868.0086
Training epoch 119, recon_loss:0.792284, zinb_loss:0.647676, cluster_loss:0.162608
Clustering   119: ASW= 0.7748, DB= 0.3152, CH= 31723.7642
Training epoch 120, recon_loss:0.791855, zinb_loss:0.647488, cluster_loss:0.162505
Clustering   120: ASW= 0.7733, DB= 0.3188, CH= 32136.3572
Training epoch 121, recon_loss:0.792293, zinb_loss:0.647569, cluster_loss:0.162416
Clustering   121: ASW= 0.7750, DB= 0.3149, CH= 31745.1165
Training epoch 122, recon_loss:0.792150, zinb_loss:0.647669, cluster_loss:0.162275
Clustering   122: ASW= 0.7742, DB= 0.3166, CH= 32380.2880
Training epoch 123, recon_loss:0.792139, zinb_loss:0.647593, cluster_loss:0.162282
Clustering   123: ASW= 0.7750, DB= 0.3147, CH= 31769.1720
Training epoch 124, recon_loss:0.792110, zinb_loss:0.647936, cluster_loss:0.162088
Clustering   124: ASW= 0.7750, DB= 0.3154, CH= 32595.3393
Training epoch 125, recon_loss:0.791530, zinb_loss:0.647629, cluster_loss:0.162002
Clustering   125: ASW= 0.7752, DB= 0.3141, CH= 31880.2922
Training epoch 126, recon_loss:0.791491, zinb_loss:0.648025, cluster_loss:0.161784
Clustering   126: ASW= 0.7756, DB= 0.3147, CH= 32750.3761
Training epoch 127, recon_loss:0.790674, zinb_loss:0.647611, cluster_loss:0.161643
Clustering   127: ASW= 0.7757, DB= 0.3137, CH= 32057.4534
Training epoch 128, recon_loss:0.790538, zinb_loss:0.647938, cluster_loss:0.161414
Clustering   128: ASW= 0.7761, DB= 0.3131, CH= 32891.1686
Training epoch 129, recon_loss:0.789994, zinb_loss:0.647598, cluster_loss:0.161360
Clustering   129: ASW= 0.7763, DB= 0.3128, CH= 32224.6116
Training epoch 130, recon_loss:0.789937, zinb_loss:0.647914, cluster_loss:0.161178
Clustering   130: ASW= 0.7765, DB= 0.3134, CH= 33048.1193
Training epoch 131, recon_loss:0.789634, zinb_loss:0.647636, cluster_loss:0.161213
Clustering   131: ASW= 0.7768, DB= 0.3121, CH= 32376.5297
Training epoch 132, recon_loss:0.789717, zinb_loss:0.647963, cluster_loss:0.161099
Clustering   132: ASW= 0.7769, DB= 0.3128, CH= 33208.1892
Training epoch 133, recon_loss:0.789611, zinb_loss:0.647707, cluster_loss:0.161209
Clustering   133: ASW= 0.7774, DB= 0.3114, CH= 32509.1537
Training epoch 134, recon_loss:0.789891, zinb_loss:0.648032, cluster_loss:0.161167
Clustering   134: ASW= 0.7774, DB= 0.3121, CH= 33367.2963
Training epoch 135, recon_loss:0.789930, zinb_loss:0.647751, cluster_loss:0.161295
Clustering   135: ASW= 0.7779, DB= 0.3107, CH= 32634.3532
Training epoch 136, recon_loss:0.790256, zinb_loss:0.648018, cluster_loss:0.161264
Clustering   136: ASW= 0.7778, DB= 0.3106, CH= 33513.3374
Training epoch 137, recon_loss:0.790208, zinb_loss:0.647672, cluster_loss:0.161322
Clustering   137: ASW= 0.7784, DB= 0.3105, CH= 32745.6510
Training epoch 138, recon_loss:0.790391, zinb_loss:0.647878, cluster_loss:0.161230
Clustering   138: ASW= 0.7783, DB= 0.3100, CH= 33635.9323
Training epoch 139, recon_loss:0.790088, zinb_loss:0.647482, cluster_loss:0.161231
Clustering   139: ASW= 0.7788, DB= 0.3100, CH= 32859.0466
Training epoch 140, recon_loss:0.790142, zinb_loss:0.647671, cluster_loss:0.161069
Clustering   140: ASW= 0.7787, DB= 0.3103, CH= 33752.5650
Training epoch 141, recon_loss:0.789717, zinb_loss:0.647284, cluster_loss:0.161141
Clustering   141: ASW= 0.7790, DB= 0.3097, CH= 32956.8777
Training epoch 142, recon_loss:0.789876, zinb_loss:0.647508, cluster_loss:0.160954
Clustering   142: ASW= 0.7792, DB= 0.3089, CH= 33848.8049
Training epoch 143, recon_loss:0.789464, zinb_loss:0.647152, cluster_loss:0.161189
Clustering   143: ASW= 0.7792, DB= 0.3103, CH= 33052.8102
Training epoch 144, recon_loss:0.789789, zinb_loss:0.647434, cluster_loss:0.160990
Clustering   144: ASW= 0.7797, DB= 0.3078, CH= 33939.1097
Training epoch 145, recon_loss:0.789447, zinb_loss:0.647129, cluster_loss:0.161428
Clustering   145: ASW= 0.7793, DB= 0.3102, CH= 33124.0345
Training epoch 146, recon_loss:0.789799, zinb_loss:0.647474, cluster_loss:0.161149
Clustering   146: ASW= 0.7801, DB= 0.3071, CH= 34014.0696
Training epoch 147, recon_loss:0.789473, zinb_loss:0.647211, cluster_loss:0.161685
Clustering   147: ASW= 0.7793, DB= 0.3095, CH= 33217.4109
Training epoch 148, recon_loss:0.789732, zinb_loss:0.647540, cluster_loss:0.161194
Clustering   148: ASW= 0.7805, DB= 0.3067, CH= 34059.2656
Training epoch 149, recon_loss:0.789302, zinb_loss:0.647296, cluster_loss:0.161626
Clustering   149: ASW= 0.7795, DB= 0.3091, CH= 33365.1027
Training epoch 150, recon_loss:0.789441, zinb_loss:0.647519, cluster_loss:0.161005
Clustering   150: ASW= 0.7809, DB= 0.3061, CH= 34072.2818
Training epoch 151, recon_loss:0.789131, zinb_loss:0.647338, cluster_loss:0.161321
Clustering   151: ASW= 0.7797, DB= 0.3085, CH= 33545.2856
Training epoch 152, recon_loss:0.789247, zinb_loss:0.647456, cluster_loss:0.160789
Clustering   152: ASW= 0.7814, DB= 0.3055, CH= 34118.0969
Training epoch 153, recon_loss:0.789350, zinb_loss:0.647390, cluster_loss:0.161075
Clustering   153: ASW= 0.7799, DB= 0.3079, CH= 33737.9179
Training epoch 154, recon_loss:0.789473, zinb_loss:0.647395, cluster_loss:0.160680
Clustering   154: ASW= 0.7819, DB= 0.3049, CH= 34205.6265
Training epoch 155, recon_loss:0.789800, zinb_loss:0.647415, cluster_loss:0.160970
Clustering   155: ASW= 0.7801, DB= 0.3070, CH= 33895.7064
Training epoch 156, recon_loss:0.789937, zinb_loss:0.647308, cluster_loss:0.160674
Clustering   156: ASW= 0.7824, DB= 0.3045, CH= 34303.7215
Training epoch 157, recon_loss:0.790202, zinb_loss:0.647368, cluster_loss:0.160925
Clustering   157: ASW= 0.7802, DB= 0.3069, CH= 34041.6637
Training epoch 158, recon_loss:0.790305, zinb_loss:0.647213, cluster_loss:0.160733
Clustering   158: ASW= 0.7828, DB= 0.3043, CH= 34377.2423
Training epoch 159, recon_loss:0.790305, zinb_loss:0.647324, cluster_loss:0.160886
Clustering   159: ASW= 0.7803, DB= 0.3065, CH= 34148.2796
Training epoch 160, recon_loss:0.790137, zinb_loss:0.647136, cluster_loss:0.160722
Clustering   160: ASW= 0.7831, DB= 0.3042, CH= 34433.4541
Training epoch 161, recon_loss:0.789960, zinb_loss:0.647286, cluster_loss:0.160749
Clustering   161: ASW= 0.7806, DB= 0.3059, CH= 34264.2217
Training epoch 162, recon_loss:0.789572, zinb_loss:0.647085, cluster_loss:0.160563
Clustering   162: ASW= 0.7833, DB= 0.3049, CH= 34495.2659
Training epoch 163, recon_loss:0.789475, zinb_loss:0.647276, cluster_loss:0.160534
Clustering   163: ASW= 0.7811, DB= 0.3051, CH= 34416.2714
Training epoch 164, recon_loss:0.789002, zinb_loss:0.647072, cluster_loss:0.160331
Clustering   164: ASW= 0.7835, DB= 0.3048, CH= 34554.4926
Training epoch 165, recon_loss:0.789022, zinb_loss:0.647278, cluster_loss:0.160316
Clustering   165: ASW= 0.7817, DB= 0.3050, CH= 34582.6276
Training epoch 166, recon_loss:0.788554, zinb_loss:0.647097, cluster_loss:0.160096
Clustering   166: ASW= 0.7837, DB= 0.3050, CH= 34625.7116
Training epoch 167, recon_loss:0.788675, zinb_loss:0.647311, cluster_loss:0.160132
Clustering   167: ASW= 0.7822, DB= 0.3042, CH= 34739.4302
Training epoch 168, recon_loss:0.788257, zinb_loss:0.647164, cluster_loss:0.159888
Clustering   168: ASW= 0.7839, DB= 0.3046, CH= 34704.9376
Training epoch 169, recon_loss:0.788426, zinb_loss:0.647373, cluster_loss:0.159976
Clustering   169: ASW= 0.7828, DB= 0.3030, CH= 34898.1016
Training epoch 170, recon_loss:0.788167, zinb_loss:0.647290, cluster_loss:0.159731
Clustering   170: ASW= 0.7840, DB= 0.3030, CH= 34765.7245
Training epoch 171, recon_loss:0.788394, zinb_loss:0.647511, cluster_loss:0.159876
Clustering   171: ASW= 0.7832, DB= 0.3018, CH= 35037.9415
Training epoch 172, recon_loss:0.788393, zinb_loss:0.647513, cluster_loss:0.159655
Clustering   172: ASW= 0.7842, DB= 0.3026, CH= 34835.7089
Training epoch 173, recon_loss:0.788721, zinb_loss:0.647767, cluster_loss:0.159879
Clustering   173: ASW= 0.7835, DB= 0.3022, CH= 35174.6043
Training epoch 174, recon_loss:0.789079, zinb_loss:0.647865, cluster_loss:0.159703
Clustering   174: ASW= 0.7843, DB= 0.3020, CH= 34887.7394
Training epoch 175, recon_loss:0.789534, zinb_loss:0.648131, cluster_loss:0.160043
Clustering   175: ASW= 0.7837, DB= 0.3014, CH= 35251.4131
Training epoch 176, recon_loss:0.790042, zinb_loss:0.648247, cluster_loss:0.159865
Clustering   176: ASW= 0.7843, DB= 0.3019, CH= 34915.0024
Training epoch 177, recon_loss:0.790381, zinb_loss:0.648361, cluster_loss:0.160277
Clustering   177: ASW= 0.7839, DB= 0.3007, CH= 35289.9667
Training epoch 178, recon_loss:0.790610, zinb_loss:0.648408, cluster_loss:0.159975
Clustering   178: ASW= 0.7844, DB= 0.3010, CH= 34942.9135
Training epoch 179, recon_loss:0.790428, zinb_loss:0.648308, cluster_loss:0.160384
Clustering   179: ASW= 0.7840, DB= 0.3003, CH= 35323.6997
Training epoch 180, recon_loss:0.790463, zinb_loss:0.648340, cluster_loss:0.160018
Clustering   180: ASW= 0.7846, DB= 0.3009, CH= 35017.0617
Training epoch 181, recon_loss:0.789932, zinb_loss:0.648164, cluster_loss:0.160367
Clustering   181: ASW= 0.7842, DB= 0.3002, CH= 35387.8759
Training epoch 182, recon_loss:0.789944, zinb_loss:0.648180, cluster_loss:0.160067
Clustering   182: ASW= 0.7849, DB= 0.3004, CH= 35101.0235
Training epoch 183, recon_loss:0.789397, zinb_loss:0.648016, cluster_loss:0.160332
Clustering   183: ASW= 0.7844, DB= 0.3004, CH= 35452.8007
Training epoch 184, recon_loss:0.789369, zinb_loss:0.648022, cluster_loss:0.160072
Clustering   184: ASW= 0.7852, DB= 0.2998, CH= 35199.1717
Training epoch 185, recon_loss:0.788864, zinb_loss:0.647886, cluster_loss:0.160190
Clustering   185: ASW= 0.7846, DB= 0.3006, CH= 35537.0317
Training epoch 186, recon_loss:0.788791, zinb_loss:0.647859, cluster_loss:0.159958
Clustering   186: ASW= 0.7855, DB= 0.2992, CH= 35305.9777
Training epoch 187, recon_loss:0.788381, zinb_loss:0.647764, cluster_loss:0.159952
Clustering   187: ASW= 0.7849, DB= 0.3005, CH= 35640.0452
Training epoch 188, recon_loss:0.788266, zinb_loss:0.647711, cluster_loss:0.159772
Clustering   188: ASW= 0.7858, DB= 0.2988, CH= 35424.6203
Training epoch 189, recon_loss:0.787956, zinb_loss:0.647653, cluster_loss:0.159684
Clustering   189: ASW= 0.7851, DB= 0.3004, CH= 35743.0840
Training epoch 190, recon_loss:0.787825, zinb_loss:0.647595, cluster_loss:0.159570
Clustering   190: ASW= 0.7862, DB= 0.2982, CH= 35539.2503
Training epoch 191, recon_loss:0.787674, zinb_loss:0.647595, cluster_loss:0.159453
Clustering   191: ASW= 0.7855, DB= 0.3002, CH= 35852.2894
Training epoch 192, recon_loss:0.787610, zinb_loss:0.647543, cluster_loss:0.159421
Clustering   192: ASW= 0.7864, DB= 0.2994, CH= 35674.4264
Training epoch 193, recon_loss:0.787740, zinb_loss:0.647604, cluster_loss:0.159327
Clustering   193: ASW= 0.7858, DB= 0.3002, CH= 35961.0214
Training epoch 194, recon_loss:0.787893, zinb_loss:0.647555, cluster_loss:0.159423
Clustering   194: ASW= 0.7867, DB= 0.2989, CH= 35770.2504
Training epoch 195, recon_loss:0.788319, zinb_loss:0.647650, cluster_loss:0.159362
Clustering   195: ASW= 0.7862, DB= 0.2991, CH= 36035.4665
Training epoch 196, recon_loss:0.788633, zinb_loss:0.647557, cluster_loss:0.159580
Clustering   196: ASW= 0.7869, DB= 0.2986, CH= 35848.0341
Training epoch 197, recon_loss:0.788916, zinb_loss:0.647615, cluster_loss:0.159423
Clustering   197: ASW= 0.7865, DB= 0.2998, CH= 36116.0539
Training epoch 198, recon_loss:0.788901, zinb_loss:0.647423, cluster_loss:0.159595
Clustering   198: ASW= 0.7870, DB= 0.2984, CH= 35923.0315
Training epoch 199, recon_loss:0.788959, zinb_loss:0.647498, cluster_loss:0.159343
Clustering   199: ASW= 0.7869, DB= 0.2989, CH= 36158.5533
Training epoch 200, recon_loss:0.788627, zinb_loss:0.647291, cluster_loss:0.159448
Clustering   200: ASW= 0.7872, DB= 0.2981, CH= 36022.3588
Training epoch 201, recon_loss:0.788765, zinb_loss:0.647442, cluster_loss:0.159228
Clustering   201: ASW= 0.7872, DB= 0.2979, CH= 36191.0196
Training epoch 202, recon_loss:0.788382, zinb_loss:0.647327, cluster_loss:0.159301
Clustering   202: ASW= 0.7874, DB= 0.2974, CH= 36161.7040
Training epoch 203, recon_loss:0.788552, zinb_loss:0.647442, cluster_loss:0.159153
Clustering   203: ASW= 0.7875, DB= 0.2971, CH= 36218.5402
Training epoch 204, recon_loss:0.788152, zinb_loss:0.647406, cluster_loss:0.159190
Clustering   204: ASW= 0.7875, DB= 0.2978, CH= 36271.4412
Training epoch 205, recon_loss:0.788121, zinb_loss:0.647354, cluster_loss:0.159051
Clustering   205: ASW= 0.7878, DB= 0.2965, CH= 36263.0611
Training epoch 206, recon_loss:0.787602, zinb_loss:0.647322, cluster_loss:0.159021
Clustering   206: ASW= 0.7875, DB= 0.2978, CH= 36338.8404
Training epoch 207, recon_loss:0.787642, zinb_loss:0.647239, cluster_loss:0.158942
Clustering   207: ASW= 0.7880, DB= 0.2964, CH= 36324.8044
Training epoch 208, recon_loss:0.787179, zinb_loss:0.647245, cluster_loss:0.158869
Clustering   208: ASW= 0.7876, DB= 0.2979, CH= 36391.1172
Training epoch 209, recon_loss:0.787342, zinb_loss:0.647176, cluster_loss:0.158860
Clustering   209: ASW= 0.7883, DB= 0.2958, CH= 36403.2179
Training epoch 210, recon_loss:0.786963, zinb_loss:0.647211, cluster_loss:0.158753
Clustering   210: ASW= 0.7877, DB= 0.2975, CH= 36436.7100
Training epoch 211, recon_loss:0.787193, zinb_loss:0.647157, cluster_loss:0.158781
Clustering   211: ASW= 0.7886, DB= 0.2954, CH= 36500.2965
Training epoch 212, recon_loss:0.786908, zinb_loss:0.647200, cluster_loss:0.158673
Clustering   212: ASW= 0.7879, DB= 0.2967, CH= 36485.3514
Training epoch 213, recon_loss:0.787201, zinb_loss:0.647175, cluster_loss:0.158714
Clustering   213: ASW= 0.7889, DB= 0.2947, CH= 36611.0354
Training epoch 214, recon_loss:0.787015, zinb_loss:0.647202, cluster_loss:0.158642
Clustering   214: ASW= 0.7881, DB= 0.2964, CH= 36506.4855
Training epoch 215, recon_loss:0.787364, zinb_loss:0.647219, cluster_loss:0.158673
Clustering   215: ASW= 0.7891, DB= 0.2941, CH= 36734.6814
Training epoch 216, recon_loss:0.787332, zinb_loss:0.647222, cluster_loss:0.158700
Clustering   216: ASW= 0.7882, DB= 0.2958, CH= 36499.5096
Training epoch 217, recon_loss:0.787727, zinb_loss:0.647284, cluster_loss:0.158714
Clustering   217: ASW= 0.7894, DB= 0.2938, CH= 36848.7984
Training epoch 218, recon_loss:0.787858, zinb_loss:0.647252, cluster_loss:0.158845
Clustering   218: ASW= 0.7882, DB= 0.2950, CH= 36471.9399
Training epoch 219, recon_loss:0.788038, zinb_loss:0.647318, cluster_loss:0.158831
Clustering   219: ASW= 0.7896, DB= 0.2932, CH= 36922.4594
Training epoch 220, recon_loss:0.787745, zinb_loss:0.647208, cluster_loss:0.158859
Clustering   220: ASW= 0.7882, DB= 0.2958, CH= 36516.8361
Training epoch 221, recon_loss:0.787484, zinb_loss:0.647207, cluster_loss:0.158799
Clustering   221: ASW= 0.7898, DB= 0.2926, CH= 36977.5866
Training epoch 222, recon_loss:0.787212, zinb_loss:0.647100, cluster_loss:0.158749
Clustering   222: ASW= 0.7883, DB= 0.2952, CH= 36576.9621
Training epoch 223, recon_loss:0.786801, zinb_loss:0.647046, cluster_loss:0.158685
Clustering   223: ASW= 0.7900, DB= 0.2922, CH= 37038.2019
Training epoch 224, recon_loss:0.786777, zinb_loss:0.647009, cluster_loss:0.158652
Clustering   224: ASW= 0.7884, DB= 0.2944, CH= 36631.9032
Training epoch 225, recon_loss:0.786375, zinb_loss:0.646925, cluster_loss:0.158598
Clustering   225: ASW= 0.7902, DB= 0.2921, CH= 37113.1379
Training epoch 226, recon_loss:0.786578, zinb_loss:0.646966, cluster_loss:0.158660
Clustering   226: ASW= 0.7886, DB= 0.2934, CH= 36695.3175
Training epoch 227, recon_loss:0.786220, zinb_loss:0.646852, cluster_loss:0.158616
Clustering   227: ASW= 0.7903, DB= 0.2918, CH= 37180.3474
Training epoch 228, recon_loss:0.786608, zinb_loss:0.646981, cluster_loss:0.158775
Clustering   228: ASW= 0.7887, DB= 0.2930, CH= 36737.8528
Training epoch 229, recon_loss:0.786241, zinb_loss:0.646830, cluster_loss:0.158712
Clustering   229: ASW= 0.7904, DB= 0.2909, CH= 37238.2187
Training epoch 230, recon_loss:0.786718, zinb_loss:0.647037, cluster_loss:0.158915
Clustering   230: ASW= 0.7888, DB= 0.2927, CH= 36764.7003
Training epoch 231, recon_loss:0.786432, zinb_loss:0.646858, cluster_loss:0.158820
Clustering   231: ASW= 0.7905, DB= 0.2905, CH= 37291.1512
Training epoch 232, recon_loss:0.787145, zinb_loss:0.647165, cluster_loss:0.159045
Clustering   232: ASW= 0.7889, DB= 0.2923, CH= 36787.9435
Training epoch 233, recon_loss:0.787190, zinb_loss:0.647023, cluster_loss:0.158948
Clustering   233: ASW= 0.7906, DB= 0.2904, CH= 37338.3803
Training epoch 234, recon_loss:0.788264, zinb_loss:0.647473, cluster_loss:0.159215
Clustering   234: ASW= 0.7892, DB= 0.2917, CH= 36818.7903
Training epoch 235, recon_loss:0.788489, zinb_loss:0.647391, cluster_loss:0.159046
Clustering   235: ASW= 0.7908, DB= 0.2904, CH= 37401.5963
Training epoch 236, recon_loss:0.789089, zinb_loss:0.647701, cluster_loss:0.159242
Clustering   236: ASW= 0.7896, DB= 0.2911, CH= 36908.4564
Training epoch 237, recon_loss:0.788512, zinb_loss:0.647421, cluster_loss:0.158794
Clustering   237: ASW= 0.7910, DB= 0.2885, CH= 37468.2002
Training epoch 238, recon_loss:0.788288, zinb_loss:0.647432, cluster_loss:0.158921
Clustering   238: ASW= 0.7900, DB= 0.2906, CH= 37013.7336
Training epoch 239, recon_loss:0.787527, zinb_loss:0.647129, cluster_loss:0.158382
Clustering   239: ASW= 0.7910, DB= 0.2882, CH= 37499.3674
Training epoch 240, recon_loss:0.787364, zinb_loss:0.647135, cluster_loss:0.158593
Clustering   240: ASW= 0.7904, DB= 0.2899, CH= 37140.7009
Training epoch 241, recon_loss:0.786973, zinb_loss:0.646926, cluster_loss:0.158108
Clustering   241: ASW= 0.7911, DB= 0.2887, CH= 37554.2132
Training epoch 242, recon_loss:0.786919, zinb_loss:0.646965, cluster_loss:0.158426
Clustering   242: ASW= 0.7909, DB= 0.2894, CH= 37275.9489
Training epoch 243, recon_loss:0.786982, zinb_loss:0.646846, cluster_loss:0.158012
Clustering   243: ASW= 0.7910, DB= 0.2889, CH= 37611.8044
Training epoch 244, recon_loss:0.786894, zinb_loss:0.646879, cluster_loss:0.158428
Clustering   244: ASW= 0.7914, DB= 0.2889, CH= 37402.4978
Training epoch 245, recon_loss:0.787138, zinb_loss:0.646849, cluster_loss:0.158086
Clustering   245: ASW= 0.7909, DB= 0.2891, CH= 37655.5011
Training epoch 246, recon_loss:0.786808, zinb_loss:0.646853, cluster_loss:0.158535
Clustering   246: ASW= 0.7919, DB= 0.2883, CH= 37516.8700
Training epoch 247, recon_loss:0.786954, zinb_loss:0.646879, cluster_loss:0.158256
Clustering   247: ASW= 0.7908, DB= 0.2892, CH= 37681.2233
Training epoch 248, recon_loss:0.786418, zinb_loss:0.646841, cluster_loss:0.158598
Clustering   248: ASW= 0.7924, DB= 0.2879, CH= 37637.0881
Training epoch 249, recon_loss:0.786700, zinb_loss:0.646874, cluster_loss:0.158397
Clustering   249: ASW= 0.7907, DB= 0.2897, CH= 37701.8988
Training epoch 250, recon_loss:0.786047, zinb_loss:0.646830, cluster_loss:0.158618
Clustering   250: ASW= 0.7928, DB= 0.2873, CH= 37753.0344
Training epoch 251, recon_loss:0.786658, zinb_loss:0.646857, cluster_loss:0.158539
Clustering   251: ASW= 0.7907, DB= 0.2899, CH= 37706.5189
Training epoch 252, recon_loss:0.785958, zinb_loss:0.646834, cluster_loss:0.158678
Clustering   252: ASW= 0.7932, DB= 0.2870, CH= 37865.8206
Training epoch 253, recon_loss:0.786892, zinb_loss:0.646847, cluster_loss:0.158700
Clustering   253: ASW= 0.7907, DB= 0.2902, CH= 37693.9245
Training epoch 254, recon_loss:0.786172, zinb_loss:0.646860, cluster_loss:0.158787
Clustering   254: ASW= 0.7934, DB= 0.2866, CH= 37961.4993
Training epoch 255, recon_loss:0.787088, zinb_loss:0.646855, cluster_loss:0.158807
Clustering   255: ASW= 0.7908, DB= 0.2899, CH= 37687.3160
Training epoch 256, recon_loss:0.786275, zinb_loss:0.646892, cluster_loss:0.158833
Clustering   256: ASW= 0.7936, DB= 0.2860, CH= 38040.6100
Training epoch 257, recon_loss:0.787086, zinb_loss:0.646881, cluster_loss:0.158807
Clustering   257: ASW= 0.7911, DB= 0.2897, CH= 37697.1560
Training epoch 258, recon_loss:0.786307, zinb_loss:0.646957, cluster_loss:0.158836
Clustering   258: ASW= 0.7936, DB= 0.2858, CH= 38114.2956
Training epoch 259, recon_loss:0.787124, zinb_loss:0.646951, cluster_loss:0.158853
Clustering   259: ASW= 0.7915, DB= 0.2893, CH= 37732.2314
Training epoch 260, recon_loss:0.786496, zinb_loss:0.647079, cluster_loss:0.158938
Clustering   260: ASW= 0.7934, DB= 0.2857, CH= 38163.7264
Training epoch 261, recon_loss:0.787307, zinb_loss:0.647069, cluster_loss:0.159027
Clustering   261: ASW= 0.7920, DB= 0.2884, CH= 37771.1374
Training epoch 262, recon_loss:0.786772, zinb_loss:0.647206, cluster_loss:0.159157
Clustering   262: ASW= 0.7932, DB= 0.2856, CH= 38196.7233
Training epoch 263, recon_loss:0.787382, zinb_loss:0.647124, cluster_loss:0.159247
Clustering   263: ASW= 0.7924, DB= 0.2883, CH= 37814.1218
Training epoch 264, recon_loss:0.786832, zinb_loss:0.647251, cluster_loss:0.159289
Clustering   264: ASW= 0.7930, DB= 0.2863, CH= 38259.8555
Training epoch 265, recon_loss:0.787051, zinb_loss:0.647068, cluster_loss:0.159267
Clustering   265: ASW= 0.7928, DB= 0.2876, CH= 37874.0528
Training epoch 266, recon_loss:0.786587, zinb_loss:0.647170, cluster_loss:0.159177
Clustering   266: ASW= 0.7930, DB= 0.2863, CH= 38342.9050
Training epoch 267, recon_loss:0.786597, zinb_loss:0.646949, cluster_loss:0.159081
Clustering   267: ASW= 0.7933, DB= 0.2867, CH= 37964.8956
Training epoch 268, recon_loss:0.786359, zinb_loss:0.647032, cluster_loss:0.158946
Clustering   268: ASW= 0.7931, DB= 0.2860, CH= 38431.3046
Training epoch 269, recon_loss:0.786446, zinb_loss:0.646833, cluster_loss:0.158870
Clustering   269: ASW= 0.7937, DB= 0.2860, CH= 38059.9492
Training epoch 270, recon_loss:0.786403, zinb_loss:0.646913, cluster_loss:0.158752
Clustering   270: ASW= 0.7932, DB= 0.2856, CH= 38525.2092
Training epoch 271, recon_loss:0.786725, zinb_loss:0.646734, cluster_loss:0.158752
Clustering   271: ASW= 0.7940, DB= 0.2856, CH= 38133.0860
Training epoch 272, recon_loss:0.786713, zinb_loss:0.646807, cluster_loss:0.158641
Clustering   272: ASW= 0.7935, DB= 0.2858, CH= 38609.2539
Training epoch 273, recon_loss:0.787074, zinb_loss:0.646615, cluster_loss:0.158680
Clustering   273: ASW= 0.7942, DB= 0.2850, CH= 38191.5029
Training epoch 274, recon_loss:0.786879, zinb_loss:0.646687, cluster_loss:0.158559
Clustering   274: ASW= 0.7937, DB= 0.2849, CH= 38650.2062
Training epoch 275, recon_loss:0.787080, zinb_loss:0.646483, cluster_loss:0.158592
Clustering   275: ASW= 0.7943, DB= 0.2846, CH= 38265.2667
Training epoch 276, recon_loss:0.786802, zinb_loss:0.646569, cluster_loss:0.158478
Clustering   276: ASW= 0.7940, DB= 0.2844, CH= 38676.9603
Training epoch 277, recon_loss:0.786903, zinb_loss:0.646390, cluster_loss:0.158524
Clustering   277: ASW= 0.7944, DB= 0.2845, CH= 38340.0552
Training epoch 278, recon_loss:0.786682, zinb_loss:0.646510, cluster_loss:0.158427
Clustering   278: ASW= 0.7942, DB= 0.2841, CH= 38692.6829
Training epoch 279, recon_loss:0.786608, zinb_loss:0.646394, cluster_loss:0.158468
Clustering   279: ASW= 0.7945, DB= 0.2841, CH= 38425.6102
Training epoch 280, recon_loss:0.786587, zinb_loss:0.646562, cluster_loss:0.158385
Clustering   280: ASW= 0.7944, DB= 0.2838, CH= 38691.1363
Training epoch 281, recon_loss:0.786411, zinb_loss:0.646533, cluster_loss:0.158444
Clustering   281: ASW= 0.7946, DB= 0.2837, CH= 38528.6757
Training epoch 282, recon_loss:0.786670, zinb_loss:0.646774, cluster_loss:0.158411
Clustering   282: ASW= 0.7946, DB= 0.2836, CH= 38678.7303
Training epoch 283, recon_loss:0.786470, zinb_loss:0.646825, cluster_loss:0.158500
Clustering   283: ASW= 0.7947, DB= 0.2836, CH= 38648.4502
Training epoch 284, recon_loss:0.786706, zinb_loss:0.647098, cluster_loss:0.158449
Clustering   284: ASW= 0.7948, DB= 0.2832, CH= 38672.7606
Training epoch 285, recon_loss:0.786450, zinb_loss:0.647113, cluster_loss:0.158513
Clustering   285: ASW= 0.7949, DB= 0.2836, CH= 38754.3535
Training epoch 286, recon_loss:0.786486, zinb_loss:0.647346, cluster_loss:0.158366
Clustering   286: ASW= 0.7950, DB= 0.2837, CH= 38703.0693
Training epoch 287, recon_loss:0.786154, zinb_loss:0.647228, cluster_loss:0.158382
Clustering   287: ASW= 0.7951, DB= 0.2830, CH= 38846.0095
Training epoch 288, recon_loss:0.786063, zinb_loss:0.647402, cluster_loss:0.158175
Clustering   288: ASW= 0.7952, DB= 0.2835, CH= 38762.8936
Training epoch 289, recon_loss:0.785666, zinb_loss:0.647175, cluster_loss:0.158158
Clustering   289: ASW= 0.7954, DB= 0.2828, CH= 38958.1805
Training epoch 290, recon_loss:0.785566, zinb_loss:0.647319, cluster_loss:0.157980
Clustering   290: ASW= 0.7954, DB= 0.2827, CH= 38841.4063
Training epoch 291, recon_loss:0.785194, zinb_loss:0.647073, cluster_loss:0.157953
Clustering   291: ASW= 0.7958, DB= 0.2826, CH= 39073.1084
Training epoch 292, recon_loss:0.785157, zinb_loss:0.647207, cluster_loss:0.157845
Clustering   292: ASW= 0.7956, DB= 0.2823, CH= 38907.0059
Training epoch 293, recon_loss:0.784849, zinb_loss:0.646977, cluster_loss:0.157809
Clustering   293: ASW= 0.7961, DB= 0.2822, CH= 39176.9252
Training epoch 294, recon_loss:0.784885, zinb_loss:0.647112, cluster_loss:0.157785
Clustering   294: ASW= 0.7957, DB= 0.2820, CH= 38971.1153
Training epoch 295, recon_loss:0.784659, zinb_loss:0.646913, cluster_loss:0.157729
Clustering   295: ASW= 0.7965, DB= 0.2813, CH= 39267.3010
Training epoch 296, recon_loss:0.784774, zinb_loss:0.647065, cluster_loss:0.157790
Clustering   296: ASW= 0.7958, DB= 0.2818, CH= 39031.8003
Training epoch 297, recon_loss:0.784628, zinb_loss:0.646877, cluster_loss:0.157712
Clustering   297: ASW= 0.7968, DB= 0.2810, CH= 39346.3105
Training epoch 298, recon_loss:0.784813, zinb_loss:0.647039, cluster_loss:0.157856
Clustering   298: ASW= 0.7958, DB= 0.2814, CH= 39075.4216
Training epoch 299, recon_loss:0.784744, zinb_loss:0.646857, cluster_loss:0.157740
Clustering   299: ASW= 0.7971, DB= 0.2805, CH= 39409.4129
Training epoch 300, recon_loss:0.784963, zinb_loss:0.647021, cluster_loss:0.157959
Clustering   300: ASW= 0.7958, DB= 0.2809, CH= 39105.4821
Training epoch 301, recon_loss:0.784951, zinb_loss:0.646833, cluster_loss:0.157789
Clustering   301: ASW= 0.7973, DB= 0.2801, CH= 39453.4958
Training epoch 302, recon_loss:0.785138, zinb_loss:0.646986, cluster_loss:0.158054
Clustering   302: ASW= 0.7957, DB= 0.2801, CH= 39148.1492
Training epoch 303, recon_loss:0.785166, zinb_loss:0.646791, cluster_loss:0.157838
Clustering   303: ASW= 0.7976, DB= 0.2799, CH= 39481.3289
Training epoch 304, recon_loss:0.785283, zinb_loss:0.646926, cluster_loss:0.158131
Clustering   304: ASW= 0.7956, DB= 0.2797, CH= 39185.3458
Training epoch 305, recon_loss:0.785348, zinb_loss:0.646732, cluster_loss:0.157872
Clustering   305: ASW= 0.7978, DB= 0.2795, CH= 39500.4129
Training epoch 306, recon_loss:0.785432, zinb_loss:0.646834, cluster_loss:0.158187
Clustering   306: ASW= 0.7955, DB= 0.2799, CH= 39262.2548
Training epoch 307, recon_loss:0.785535, zinb_loss:0.646657, cluster_loss:0.157918
Clustering   307: ASW= 0.7981, DB= 0.2793, CH= 39515.7214
Training epoch 308, recon_loss:0.785671, zinb_loss:0.646717, cluster_loss:0.158265
Clustering   308: ASW= 0.7954, DB= 0.2799, CH= 39334.8905
Training epoch 309, recon_loss:0.785794, zinb_loss:0.646585, cluster_loss:0.158013
Clustering   309: ASW= 0.7983, DB= 0.2791, CH= 39528.2604
Training epoch 310, recon_loss:0.786066, zinb_loss:0.646601, cluster_loss:0.158389
Clustering   310: ASW= 0.7953, DB= 0.2801, CH= 39408.4300
Training epoch 311, recon_loss:0.785987, zinb_loss:0.646495, cluster_loss:0.158117
Clustering   311: ASW= 0.7986, DB= 0.2789, CH= 39538.2086
Training epoch 312, recon_loss:0.786186, zinb_loss:0.646461, cluster_loss:0.158411
Clustering   312: ASW= 0.7954, DB= 0.2803, CH= 39498.6042
Training epoch 313, recon_loss:0.785747, zinb_loss:0.646367, cluster_loss:0.158097
Clustering   313: ASW= 0.7986, DB= 0.2789, CH= 39550.1381
Training epoch 314, recon_loss:0.785798, zinb_loss:0.646298, cluster_loss:0.158266
Clustering   314: ASW= 0.7956, DB= 0.2804, CH= 39624.6997
Training epoch 315, recon_loss:0.785159, zinb_loss:0.646244, cluster_loss:0.157953
Clustering   315: ASW= 0.7986, DB= 0.2792, CH= 39563.3367
Training epoch 316, recon_loss:0.785254, zinb_loss:0.646180, cluster_loss:0.158050
Clustering   316: ASW= 0.7962, DB= 0.2800, CH= 39775.2930
Training epoch 317, recon_loss:0.784736, zinb_loss:0.646198, cluster_loss:0.157841
Clustering   317: ASW= 0.7984, DB= 0.2793, CH= 39561.8870
Training epoch 318, recon_loss:0.785061, zinb_loss:0.646195, cluster_loss:0.157938
Clustering   318: ASW= 0.7969, DB= 0.2793, CH= 39948.4093
Training epoch 319, recon_loss:0.784805, zinb_loss:0.646258, cluster_loss:0.157859
Clustering   319: ASW= 0.7982, DB= 0.2791, CH= 39533.0317
Training epoch 320, recon_loss:0.785335, zinb_loss:0.646327, cluster_loss:0.157975
Clustering   320: ASW= 0.7975, DB= 0.2784, CH= 40100.7149
Training epoch 321, recon_loss:0.785166, zinb_loss:0.646330, cluster_loss:0.157830
Clustering   321: ASW= 0.7981, DB= 0.2800, CH= 39540.4951
Training epoch 322, recon_loss:0.785838, zinb_loss:0.646426, cluster_loss:0.157942
Clustering   322: ASW= 0.7980, DB= 0.2784, CH= 40207.6920
Training epoch 323, recon_loss:0.786024, zinb_loss:0.646382, cluster_loss:0.157724
Clustering   323: ASW= 0.7980, DB= 0.2803, CH= 39585.8443
Training epoch 324, recon_loss:0.787200, zinb_loss:0.646475, cluster_loss:0.157926
Clustering   324: ASW= 0.7982, DB= 0.2784, CH= 40239.6111
Training epoch 325, recon_loss:0.787723, zinb_loss:0.646466, cluster_loss:0.157706
Clustering   325: ASW= 0.7982, DB= 0.2803, CH= 39649.3508
Training epoch 326, recon_loss:0.788941, zinb_loss:0.646481, cluster_loss:0.158034
Clustering   326: ASW= 0.7982, DB= 0.2782, CH= 40175.1510
Training epoch 327, recon_loss:0.788127, zinb_loss:0.646453, cluster_loss:0.157632
Clustering   327: ASW= 0.7985, DB= 0.2799, CH= 39732.8075
Training epoch 328, recon_loss:0.788174, zinb_loss:0.646293, cluster_loss:0.157867
Clustering   328: ASW= 0.7980, DB= 0.2780, CH= 40093.6703
Training epoch 329, recon_loss:0.787187, zinb_loss:0.646260, cluster_loss:0.157376
Clustering   329: ASW= 0.7989, DB= 0.2792, CH= 39842.3204
Training epoch 330, recon_loss:0.787006, zinb_loss:0.646065, cluster_loss:0.157621
Clustering   330: ASW= 0.7978, DB= 0.2787, CH= 40089.6482
Training epoch 331, recon_loss:0.786532, zinb_loss:0.646061, cluster_loss:0.157240
Clustering   331: ASW= 0.7994, DB= 0.2783, CH= 39963.9266
Training epoch 332, recon_loss:0.786244, zinb_loss:0.645890, cluster_loss:0.157563
Clustering   332: ASW= 0.7976, DB= 0.2783, CH= 40074.4025
Training epoch 333, recon_loss:0.786043, zinb_loss:0.645923, cluster_loss:0.157236
Clustering   333: ASW= 0.7997, DB= 0.2775, CH= 40057.8489
Training epoch 334, recon_loss:0.785571, zinb_loss:0.645771, cluster_loss:0.157590
Clustering   334: ASW= 0.7974, DB= 0.2780, CH= 40065.8502
Training epoch 335, recon_loss:0.785604, zinb_loss:0.645851, cluster_loss:0.157250
Clustering   335: ASW= 0.8001, DB= 0.2771, CH= 40163.3839
Training epoch 336, recon_loss:0.785193, zinb_loss:0.645705, cluster_loss:0.157648
Clustering   336: ASW= 0.7974, DB= 0.2782, CH= 40081.0488
Training epoch 337, recon_loss:0.785358, zinb_loss:0.645820, cluster_loss:0.157300
Clustering   337: ASW= 0.8003, DB= 0.2771, CH= 40284.0330
Training epoch 338, recon_loss:0.785027, zinb_loss:0.645683, cluster_loss:0.157771
Clustering   338: ASW= 0.7973, DB= 0.2774, CH= 40072.7514
Training epoch 339, recon_loss:0.785255, zinb_loss:0.645821, cluster_loss:0.157430
Clustering   339: ASW= 0.8006, DB= 0.2767, CH= 40381.5408
Training epoch 340, recon_loss:0.784987, zinb_loss:0.645698, cluster_loss:0.157981
Clustering   340: ASW= 0.7973, DB= 0.2775, CH= 40062.0131
Training epoch 341, recon_loss:0.785221, zinb_loss:0.645849, cluster_loss:0.157647
Clustering   341: ASW= 0.8008, DB= 0.2761, CH= 40453.8745
Training epoch 342, recon_loss:0.784933, zinb_loss:0.645746, cluster_loss:0.158185
Clustering   342: ASW= 0.7974, DB= 0.2773, CH= 40033.8847
Training epoch 343, recon_loss:0.785092, zinb_loss:0.645890, cluster_loss:0.157806
Clustering   343: ASW= 0.8009, DB= 0.2760, CH= 40508.9414
Training epoch 344, recon_loss:0.784587, zinb_loss:0.645782, cluster_loss:0.158124
Clustering   344: ASW= 0.7976, DB= 0.2772, CH= 40052.8884
Training epoch 345, recon_loss:0.784670, zinb_loss:0.645877, cluster_loss:0.157720
Clustering   345: ASW= 0.8009, DB= 0.2759, CH= 40546.2951
Training epoch 346, recon_loss:0.784024, zinb_loss:0.645771, cluster_loss:0.157836
Clustering   346: ASW= 0.7980, DB= 0.2769, CH= 40128.2500
Training epoch 347, recon_loss:0.784118, zinb_loss:0.645820, cluster_loss:0.157466
Clustering   347: ASW= 0.8009, DB= 0.2762, CH= 40603.3594
Training epoch 348, recon_loss:0.783497, zinb_loss:0.645740, cluster_loss:0.157521
Clustering   348: ASW= 0.7984, DB= 0.2768, CH= 40243.0112
Training epoch 349, recon_loss:0.783688, zinb_loss:0.645762, cluster_loss:0.157234
Clustering   349: ASW= 0.8009, DB= 0.2757, CH= 40664.2492
Training epoch 350, recon_loss:0.783155, zinb_loss:0.645719, cluster_loss:0.157285
Clustering   350: ASW= 0.7988, DB= 0.2762, CH= 40344.5852
Training epoch 351, recon_loss:0.783432, zinb_loss:0.645727, cluster_loss:0.157060
Clustering   351: ASW= 0.8011, DB= 0.2757, CH= 40735.4760
Training epoch 352, recon_loss:0.782982, zinb_loss:0.645710, cluster_loss:0.157115
Clustering   352: ASW= 0.7991, DB= 0.2758, CH= 40446.2223
Training epoch 353, recon_loss:0.783337, zinb_loss:0.645714, cluster_loss:0.156937
Clustering   353: ASW= 0.8012, DB= 0.2753, CH= 40803.3542
Training epoch 354, recon_loss:0.782993, zinb_loss:0.645717, cluster_loss:0.156994
Clustering   354: ASW= 0.7994, DB= 0.2753, CH= 40537.9631
Training epoch 355, recon_loss:0.783435, zinb_loss:0.645735, cluster_loss:0.156861
Clustering   355: ASW= 0.8013, DB= 0.2754, CH= 40868.4653
Training epoch 356, recon_loss:0.783249, zinb_loss:0.645768, cluster_loss:0.156935
Clustering   356: ASW= 0.7996, DB= 0.2753, CH= 40612.2424
Training epoch 357, recon_loss:0.783817, zinb_loss:0.645836, cluster_loss:0.156846
Clustering   357: ASW= 0.8015, DB= 0.2749, CH= 40919.6528
Training epoch 358, recon_loss:0.783946, zinb_loss:0.645938, cluster_loss:0.156968
Clustering   358: ASW= 0.7997, DB= 0.2752, CH= 40670.7753
Training epoch 359, recon_loss:0.784643, zinb_loss:0.646123, cluster_loss:0.156934
Clustering   359: ASW= 0.8016, DB= 0.2745, CH= 40952.6551
Training epoch 360, recon_loss:0.785131, zinb_loss:0.646333, cluster_loss:0.157133
Clustering   360: ASW= 0.7997, DB= 0.2753, CH= 40709.6457
Training epoch 361, recon_loss:0.785187, zinb_loss:0.646537, cluster_loss:0.157089
Clustering   361: ASW= 0.8017, DB= 0.2741, CH= 40957.8316
Training epoch 362, recon_loss:0.785484, zinb_loss:0.646701, cluster_loss:0.157191
Clustering   362: ASW= 0.7997, DB= 0.2756, CH= 40744.2463
Training epoch 363, recon_loss:0.784484, zinb_loss:0.646685, cluster_loss:0.157090
Clustering   363: ASW= 0.8018, DB= 0.2738, CH= 40976.7268
Training epoch 364, recon_loss:0.784661, zinb_loss:0.646711, cluster_loss:0.157001
Clustering   364: ASW= 0.7999, DB= 0.2756, CH= 40819.1409
Training epoch 365, recon_loss:0.783616, zinb_loss:0.646592, cluster_loss:0.156990
Clustering   365: ASW= 0.8019, DB= 0.2735, CH= 41000.1584
Training epoch 366, recon_loss:0.783898, zinb_loss:0.646617, cluster_loss:0.156852
Clustering   366: ASW= 0.8001, DB= 0.2755, CH= 40914.5288
Training epoch 367, recon_loss:0.783135, zinb_loss:0.646513, cluster_loss:0.156948
Clustering   367: ASW= 0.8019, DB= 0.2733, CH= 41027.9324
Training epoch 368, recon_loss:0.783522, zinb_loss:0.646562, cluster_loss:0.156804
Clustering   368: ASW= 0.8003, DB= 0.2753, CH= 41011.6800
Training epoch 369, recon_loss:0.782932, zinb_loss:0.646469, cluster_loss:0.156962
Clustering   369: ASW= 0.8020, DB= 0.2732, CH= 41067.3155
Training epoch 370, recon_loss:0.783347, zinb_loss:0.646534, cluster_loss:0.156801
Clustering   370: ASW= 0.8005, DB= 0.2751, CH= 41097.3987
Training epoch 371, recon_loss:0.782807, zinb_loss:0.646430, cluster_loss:0.156972
Clustering   371: ASW= 0.8020, DB= 0.2729, CH= 41109.3090
Training epoch 372, recon_loss:0.783209, zinb_loss:0.646492, cluster_loss:0.156778
Clustering   372: ASW= 0.8008, DB= 0.2744, CH= 41171.1664
Training epoch 373, recon_loss:0.782648, zinb_loss:0.646365, cluster_loss:0.156949
Clustering   373: ASW= 0.8021, DB= 0.2729, CH= 41160.4034
Training epoch 374, recon_loss:0.783032, zinb_loss:0.646417, cluster_loss:0.156736
Clustering   374: ASW= 0.8010, DB= 0.2740, CH= 41250.9416
Training epoch 375, recon_loss:0.782515, zinb_loss:0.646286, cluster_loss:0.156919
Clustering   375: ASW= 0.8022, DB= 0.2728, CH= 41216.0965
Training epoch 376, recon_loss:0.782903, zinb_loss:0.646333, cluster_loss:0.156712
Clustering   376: ASW= 0.8013, DB= 0.2736, CH= 41324.4518
Training epoch 377, recon_loss:0.782488, zinb_loss:0.646203, cluster_loss:0.156925
Clustering   377: ASW= 0.8022, DB= 0.2725, CH= 41264.1971
Training epoch 378, recon_loss:0.782908, zinb_loss:0.646238, cluster_loss:0.156751
Clustering   378: ASW= 0.8016, DB= 0.2731, CH= 41389.2264
Training epoch 379, recon_loss:0.782692, zinb_loss:0.646116, cluster_loss:0.157020
Clustering   379: ASW= 0.8022, DB= 0.2727, CH= 41290.6948
Training epoch 380, recon_loss:0.783153, zinb_loss:0.646126, cluster_loss:0.156918
Clustering   380: ASW= 0.8018, DB= 0.2726, CH= 41435.4682
Training epoch 381, recon_loss:0.783252, zinb_loss:0.646026, cluster_loss:0.157251
Clustering   381: ASW= 0.8020, DB= 0.2726, CH= 41275.4083
Training epoch 382, recon_loss:0.783548, zinb_loss:0.645969, cluster_loss:0.157223
Clustering   382: ASW= 0.8019, DB= 0.2727, CH= 41434.1137
Training epoch 383, recon_loss:0.783832, zinb_loss:0.645914, cluster_loss:0.157466
Clustering   383: ASW= 0.8020, DB= 0.2727, CH= 41281.0251
Training epoch 384, recon_loss:0.783618, zinb_loss:0.645785, cluster_loss:0.157459
Clustering   384: ASW= 0.8021, DB= 0.2723, CH= 41414.9984
Training epoch 385, recon_loss:0.784032, zinb_loss:0.645786, cluster_loss:0.157538
Clustering   385: ASW= 0.8019, DB= 0.2727, CH= 41290.4623
Training epoch 386, recon_loss:0.783367, zinb_loss:0.645607, cluster_loss:0.157531
Clustering   386: ASW= 0.8021, DB= 0.2723, CH= 41392.3360
Training epoch 387, recon_loss:0.783855, zinb_loss:0.645688, cluster_loss:0.157443
Clustering   387: ASW= 0.8020, DB= 0.2727, CH= 41327.3356
Training epoch 388, recon_loss:0.782986, zinb_loss:0.645506, cluster_loss:0.157428
Clustering   388: ASW= 0.8023, DB= 0.2721, CH= 41412.7919
Training epoch 389, recon_loss:0.783655, zinb_loss:0.645650, cluster_loss:0.157300
Clustering   389: ASW= 0.8021, DB= 0.2723, CH= 41349.7366
Training epoch 390, recon_loss:0.782935, zinb_loss:0.645518, cluster_loss:0.157319
Clustering   390: ASW= 0.8024, DB= 0.2721, CH= 41447.6609
Training epoch 391, recon_loss:0.783760, zinb_loss:0.645714, cluster_loss:0.157195
Clustering   391: ASW= 0.8023, DB= 0.2721, CH= 41368.2446
Training epoch 392, recon_loss:0.783295, zinb_loss:0.645631, cluster_loss:0.157276
Clustering   392: ASW= 0.8025, DB= 0.2721, CH= 41467.0872
Training epoch 393, recon_loss:0.783961, zinb_loss:0.645831, cluster_loss:0.157075
Clustering   393: ASW= 0.8026, DB= 0.2714, CH= 41391.1979
Training epoch 394, recon_loss:0.783588, zinb_loss:0.645717, cluster_loss:0.157175
Clustering   394: ASW= 0.8026, DB= 0.2716, CH= 41504.7855
Training epoch 395, recon_loss:0.783971, zinb_loss:0.645875, cluster_loss:0.156943
Clustering   395: ASW= 0.8027, DB= 0.2711, CH= 41413.4835
Training epoch 396, recon_loss:0.783731, zinb_loss:0.645721, cluster_loss:0.157071
Clustering   396: ASW= 0.8026, DB= 0.2714, CH= 41567.0369
Training epoch 397, recon_loss:0.783928, zinb_loss:0.645854, cluster_loss:0.156864
Clustering   397: ASW= 0.8028, DB= 0.2709, CH= 41421.8283
Training epoch 398, recon_loss:0.783817, zinb_loss:0.645672, cluster_loss:0.157010
Clustering   398: ASW= 0.8029, DB= 0.2710, CH= 41623.6251
Training epoch 399, recon_loss:0.783943, zinb_loss:0.645799, cluster_loss:0.156887
Clustering   399: ASW= 0.8028, DB= 0.2708, CH= 41409.6842
Training epoch 400, recon_loss:0.783811, zinb_loss:0.645585, cluster_loss:0.156979
Clustering   400: ASW= 0.8031, DB= 0.2707, CH= 41701.9741
Training epoch 401, recon_loss:0.783887, zinb_loss:0.645714, cluster_loss:0.156941
Clustering   401: ASW= 0.8029, DB= 0.2702, CH= 41391.6178
Training epoch 402, recon_loss:0.783523, zinb_loss:0.645475, cluster_loss:0.156873
Clustering   402: ASW= 0.8032, DB= 0.2705, CH= 41779.6771
Training epoch 403, recon_loss:0.783517, zinb_loss:0.645600, cluster_loss:0.156855
Clustering   403: ASW= 0.8031, DB= 0.2699, CH= 41439.2827
Training epoch 404, recon_loss:0.782992, zinb_loss:0.645342, cluster_loss:0.156709
Clustering   404: ASW= 0.8032, DB= 0.2705, CH= 41849.7804
Training epoch 405, recon_loss:0.783020, zinb_loss:0.645486, cluster_loss:0.156713
Clustering   405: ASW= 0.8033, DB= 0.2696, CH= 41521.0471
Training epoch 406, recon_loss:0.782500, zinb_loss:0.645229, cluster_loss:0.156569
Clustering   406: ASW= 0.8033, DB= 0.2706, CH= 41913.7505
Training epoch 407, recon_loss:0.782619, zinb_loss:0.645398, cluster_loss:0.156615
Clustering   407: ASW= 0.8035, DB= 0.2692, CH= 41600.9177
Training epoch 408, recon_loss:0.782161, zinb_loss:0.645145, cluster_loss:0.156476
Clustering   408: ASW= 0.8033, DB= 0.2708, CH= 41979.3412
Training epoch 409, recon_loss:0.782339, zinb_loss:0.645332, cluster_loss:0.156558
Clustering   409: ASW= 0.8037, DB= 0.2689, CH= 41673.6319
Training epoch 410, recon_loss:0.781991, zinb_loss:0.645082, cluster_loss:0.156423
Clustering   410: ASW= 0.8034, DB= 0.2708, CH= 42039.2813
Training epoch 411, recon_loss:0.782239, zinb_loss:0.645280, cluster_loss:0.156537
Clustering   411: ASW= 0.8039, DB= 0.2689, CH= 41743.5516
Training epoch 412, recon_loss:0.782046, zinb_loss:0.645029, cluster_loss:0.156411
Clustering   412: ASW= 0.8034, DB= 0.2708, CH= 42094.1068
Training epoch 413, recon_loss:0.782291, zinb_loss:0.645225, cluster_loss:0.156547
Clustering   413: ASW= 0.8040, DB= 0.2688, CH= 41804.2023
Training epoch 414, recon_loss:0.782210, zinb_loss:0.644979, cluster_loss:0.156436
Clustering   414: ASW= 0.8035, DB= 0.2709, CH= 42138.9944
Training epoch 415, recon_loss:0.782168, zinb_loss:0.645153, cluster_loss:0.156560
Clustering   415: ASW= 0.8041, DB= 0.2686, CH= 41862.9103
Training epoch 416, recon_loss:0.782156, zinb_loss:0.644922, cluster_loss:0.156448
Clustering   416: ASW= 0.8035, DB= 0.2707, CH= 42174.9479
Training epoch 417, recon_loss:0.782045, zinb_loss:0.645084, cluster_loss:0.156555
Clustering   417: ASW= 0.8041, DB= 0.2684, CH= 41912.7899
Training epoch 418, recon_loss:0.782157, zinb_loss:0.644887, cluster_loss:0.156476
Clustering   418: ASW= 0.8036, DB= 0.2706, CH= 42212.3904
Training epoch 419, recon_loss:0.782355, zinb_loss:0.645083, cluster_loss:0.156609
Clustering   419: ASW= 0.8041, DB= 0.2681, CH= 41932.8975
Training epoch 420, recon_loss:0.782541, zinb_loss:0.644936, cluster_loss:0.156559
Clustering   420: ASW= 0.8037, DB= 0.2705, CH= 42242.9432
Training epoch 421, recon_loss:0.783104, zinb_loss:0.645197, cluster_loss:0.156689
Clustering   421: ASW= 0.8041, DB= 0.2681, CH= 41947.9524
Training epoch 422, recon_loss:0.782922, zinb_loss:0.645078, cluster_loss:0.156609
Clustering   422: ASW= 0.8038, DB= 0.2701, CH= 42261.6981
Training epoch 423, recon_loss:0.783453, zinb_loss:0.645352, cluster_loss:0.156645
Clustering   423: ASW= 0.8041, DB= 0.2681, CH= 41964.3545
Training epoch 424, recon_loss:0.782791, zinb_loss:0.645249, cluster_loss:0.156517
Clustering   424: ASW= 0.8041, DB= 0.2697, CH= 42304.6991
Training epoch 425, recon_loss:0.783186, zinb_loss:0.645497, cluster_loss:0.156497
Clustering   425: ASW= 0.8040, DB= 0.2682, CH= 41990.7505
Training epoch 426, recon_loss:0.782374, zinb_loss:0.645421, cluster_loss:0.156370
Clustering   426: ASW= 0.8044, DB= 0.2693, CH= 42360.4523
Training epoch 427, recon_loss:0.782788, zinb_loss:0.645659, cluster_loss:0.156373
Clustering   427: ASW= 0.8040, DB= 0.2682, CH= 42025.9546
Training epoch 428, recon_loss:0.781998, zinb_loss:0.645603, cluster_loss:0.156259
Clustering   428: ASW= 0.8046, DB= 0.2689, CH= 42428.8099
Training epoch 429, recon_loss:0.782397, zinb_loss:0.645810, cluster_loss:0.156301
Clustering   429: ASW= 0.8039, DB= 0.2686, CH= 42063.8559
Training epoch 430, recon_loss:0.781668, zinb_loss:0.645776, cluster_loss:0.156176
Clustering   430: ASW= 0.8050, DB= 0.2683, CH= 42502.7234
Training epoch 431, recon_loss:0.782070, zinb_loss:0.645920, cluster_loss:0.156266
Clustering   431: ASW= 0.8039, DB= 0.2686, CH= 42095.0676
Training epoch 432, recon_loss:0.781397, zinb_loss:0.645904, cluster_loss:0.156120
Clustering   432: ASW= 0.8053, DB= 0.2678, CH= 42573.0110
Training epoch 433, recon_loss:0.781764, zinb_loss:0.645975, cluster_loss:0.156248
Clustering   433: ASW= 0.8039, DB= 0.2686, CH= 42122.1112
Training epoch 434, recon_loss:0.781163, zinb_loss:0.645964, cluster_loss:0.156066
Clustering   434: ASW= 0.8056, DB= 0.2672, CH= 42643.4703
Training epoch 435, recon_loss:0.781488, zinb_loss:0.645980, cluster_loss:0.156224
Clustering   435: ASW= 0.8040, DB= 0.2686, CH= 42157.9828
Training epoch 436, recon_loss:0.781028, zinb_loss:0.645971, cluster_loss:0.156016
Clustering   436: ASW= 0.8059, DB= 0.2669, CH= 42706.4407
Training epoch 437, recon_loss:0.781396, zinb_loss:0.646009, cluster_loss:0.156229
Clustering   437: ASW= 0.8040, DB= 0.2685, CH= 42189.7299
Training epoch 438, recon_loss:0.781202, zinb_loss:0.646021, cluster_loss:0.156027
Clustering   438: ASW= 0.8061, DB= 0.2669, CH= 42757.8668
Training epoch 439, recon_loss:0.781787, zinb_loss:0.646141, cluster_loss:0.156332
Clustering   439: ASW= 0.8041, DB= 0.2683, CH= 42213.2693
Training epoch 440, recon_loss:0.781872, zinb_loss:0.646158, cluster_loss:0.156149
Clustering   440: ASW= 0.8063, DB= 0.2667, CH= 42792.5731
Training epoch 441, recon_loss:0.782709, zinb_loss:0.646264, cluster_loss:0.156557
Clustering   441: ASW= 0.8041, DB= 0.2680, CH= 42226.4646
Training epoch 442, recon_loss:0.782786, zinb_loss:0.646134, cluster_loss:0.156328
Clustering   442: ASW= 0.8064, DB= 0.2671, CH= 42785.2483
Training epoch 443, recon_loss:0.783539, zinb_loss:0.646057, cluster_loss:0.156781
Clustering   443: ASW= 0.8040, DB= 0.2681, CH= 42225.7401
Training epoch 444, recon_loss:0.783658, zinb_loss:0.645823, cluster_loss:0.156513
Clustering   444: ASW= 0.8063, DB= 0.2669, CH= 42714.9748
Training epoch 445, recon_loss:0.784057, zinb_loss:0.645686, cluster_loss:0.156963
Clustering   445: ASW= 0.8039, DB= 0.2681, CH= 42212.4398
Training epoch 446, recon_loss:0.784271, zinb_loss:0.645471, cluster_loss:0.156662
Clustering   446: ASW= 0.8063, DB= 0.2670, CH= 42647.6379
Training epoch 447, recon_loss:0.784022, zinb_loss:0.645337, cluster_loss:0.157054
Clustering   447: ASW= 0.8039, DB= 0.2679, CH= 42207.8667
Training epoch 448, recon_loss:0.784171, zinb_loss:0.645173, cluster_loss:0.156692
Clustering   448: ASW= 0.8062, DB= 0.2677, CH= 42635.0963
Training epoch 449, recon_loss:0.783479, zinb_loss:0.645044, cluster_loss:0.156997
Clustering   449: ASW= 0.8041, DB= 0.2681, CH= 42247.4413
Training epoch 450, recon_loss:0.783575, zinb_loss:0.644946, cluster_loss:0.156609
Clustering   450: ASW= 0.8062, DB= 0.2675, CH= 42667.0624
Training epoch 451, recon_loss:0.782723, zinb_loss:0.644834, cluster_loss:0.156819
Clustering   451: ASW= 0.8043, DB= 0.2678, CH= 42296.4157
Training epoch 452, recon_loss:0.782901, zinb_loss:0.644782, cluster_loss:0.156461
Clustering   452: ASW= 0.8062, DB= 0.2674, CH= 42713.3822
Training epoch 453, recon_loss:0.782083, zinb_loss:0.644685, cluster_loss:0.156610
Clustering   453: ASW= 0.8046, DB= 0.2674, CH= 42357.9854
Training epoch 454, recon_loss:0.782394, zinb_loss:0.644658, cluster_loss:0.156294
Clustering   454: ASW= 0.8062, DB= 0.2674, CH= 42766.5342
Training epoch 455, recon_loss:0.781705, zinb_loss:0.644589, cluster_loss:0.156417
Clustering   455: ASW= 0.8049, DB= 0.2668, CH= 42433.6958
Training epoch 456, recon_loss:0.782064, zinb_loss:0.644581, cluster_loss:0.156152
Clustering   456: ASW= 0.8062, DB= 0.2675, CH= 42826.2027
Training epoch 457, recon_loss:0.781430, zinb_loss:0.644544, cluster_loss:0.156243
Clustering   457: ASW= 0.8052, DB= 0.2666, CH= 42521.7148
Training epoch 458, recon_loss:0.781874, zinb_loss:0.644533, cluster_loss:0.156021
Clustering   458: ASW= 0.8062, DB= 0.2669, CH= 42869.8353
Training epoch 459, recon_loss:0.781307, zinb_loss:0.644540, cluster_loss:0.156071
Clustering   459: ASW= 0.8056, DB= 0.2665, CH= 42632.2811
Training epoch 460, recon_loss:0.781876, zinb_loss:0.644515, cluster_loss:0.155935
Clustering   460: ASW= 0.8062, DB= 0.2664, CH= 42906.1827
Training epoch 461, recon_loss:0.781477, zinb_loss:0.644597, cluster_loss:0.155954
Clustering   461: ASW= 0.8059, DB= 0.2662, CH= 42738.7006
Training epoch 462, recon_loss:0.782171, zinb_loss:0.644557, cluster_loss:0.155950
Clustering   462: ASW= 0.8063, DB= 0.2657, CH= 42927.0080
Training epoch 463, recon_loss:0.781933, zinb_loss:0.644721, cluster_loss:0.155947
Clustering   463: ASW= 0.8061, DB= 0.2660, CH= 42803.4954
Training epoch 464, recon_loss:0.782661, zinb_loss:0.644673, cluster_loss:0.156098
Clustering   464: ASW= 0.8063, DB= 0.2657, CH= 42963.6026
Training epoch 465, recon_loss:0.782513, zinb_loss:0.644900, cluster_loss:0.156089
Clustering   465: ASW= 0.8062, DB= 0.2656, CH= 42832.2117
Training epoch 466, recon_loss:0.783129, zinb_loss:0.644843, cluster_loss:0.156380
Clustering   466: ASW= 0.8064, DB= 0.2656, CH= 42975.8083
Training epoch 467, recon_loss:0.782888, zinb_loss:0.645055, cluster_loss:0.156330
Clustering   467: ASW= 0.8062, DB= 0.2656, CH= 42820.7894
Training epoch 468, recon_loss:0.783332, zinb_loss:0.644984, cluster_loss:0.156721
Clustering   468: ASW= 0.8065, DB= 0.2657, CH= 42953.0430
Training epoch 469, recon_loss:0.782964, zinb_loss:0.645104, cluster_loss:0.156572
Clustering   469: ASW= 0.8060, DB= 0.2657, CH= 42802.0896
Training epoch 470, recon_loss:0.783184, zinb_loss:0.645021, cluster_loss:0.157003
Clustering   470: ASW= 0.8065, DB= 0.2661, CH= 42880.7125
Training epoch 471, recon_loss:0.782867, zinb_loss:0.645058, cluster_loss:0.156684
Clustering   471: ASW= 0.8059, DB= 0.2660, CH= 42818.4602
Training epoch 472, recon_loss:0.782944, zinb_loss:0.644980, cluster_loss:0.157168
Clustering   472: ASW= 0.8064, DB= 0.2656, CH= 42774.3863
Training epoch 473, recon_loss:0.782769, zinb_loss:0.645017, cluster_loss:0.156714
Clustering   473: ASW= 0.8058, DB= 0.2670, CH= 42854.1509
Training epoch 474, recon_loss:0.782834, zinb_loss:0.644981, cluster_loss:0.157267
Clustering   474: ASW= 0.8062, DB= 0.2654, CH= 42676.7876
Training epoch 475, recon_loss:0.782649, zinb_loss:0.645059, cluster_loss:0.156579
Clustering   475: ASW= 0.8058, DB= 0.2667, CH= 42905.8273
Training epoch 476, recon_loss:0.782543, zinb_loss:0.645011, cluster_loss:0.157114
Clustering   476: ASW= 0.8062, DB= 0.2645, CH= 42656.7664
Training epoch 477, recon_loss:0.782328, zinb_loss:0.645115, cluster_loss:0.156375
Clustering   477: ASW= 0.8059, DB= 0.2669, CH= 42958.6983
Training epoch 478, recon_loss:0.782134, zinb_loss:0.645056, cluster_loss:0.156864
Clustering   478: ASW= 0.8065, DB= 0.2643, CH= 42694.5783
Training epoch 479, recon_loss:0.781886, zinb_loss:0.645164, cluster_loss:0.156161
Clustering   479: ASW= 0.8060, DB= 0.2670, CH= 43047.9461
Training epoch 480, recon_loss:0.781694, zinb_loss:0.645106, cluster_loss:0.156595
Clustering   480: ASW= 0.8067, DB= 0.2641, CH= 42773.1816
Training epoch 481, recon_loss:0.781385, zinb_loss:0.645189, cluster_loss:0.155970
Clustering   481: ASW= 0.8063, DB= 0.2663, CH= 43161.7936
Training epoch 482, recon_loss:0.781314, zinb_loss:0.645156, cluster_loss:0.156376
Clustering   482: ASW= 0.8069, DB= 0.2636, CH= 42849.7210
Training epoch 483, recon_loss:0.780963, zinb_loss:0.645234, cluster_loss:0.155834
Clustering   483: ASW= 0.8066, DB= 0.2658, CH= 43280.6560
Training epoch 484, recon_loss:0.781117, zinb_loss:0.645257, cluster_loss:0.156239
Clustering   484: ASW= 0.8071, DB= 0.2635, CH= 42892.1872
Training epoch 485, recon_loss:0.780792, zinb_loss:0.645387, cluster_loss:0.155761
Clustering   485: ASW= 0.8069, DB= 0.2653, CH= 43410.5354
Training epoch 486, recon_loss:0.781168, zinb_loss:0.645461, cluster_loss:0.156198
Clustering   486: ASW= 0.8071, DB= 0.2635, CH= 42908.3689
Training epoch 487, recon_loss:0.780824, zinb_loss:0.645700, cluster_loss:0.155735
Clustering   487: ASW= 0.8072, DB= 0.2649, CH= 43553.9411
Training epoch 488, recon_loss:0.781349, zinb_loss:0.645780, cluster_loss:0.156197
Clustering   488: ASW= 0.8070, DB= 0.2637, CH= 42891.1891
Training epoch 489, recon_loss:0.781043, zinb_loss:0.646115, cluster_loss:0.155759
Clustering   489: ASW= 0.8076, DB= 0.2643, CH= 43661.8192
Training epoch 490, recon_loss:0.781533, zinb_loss:0.646003, cluster_loss:0.156187
Clustering   490: ASW= 0.8071, DB= 0.2643, CH= 42930.4356
Training epoch 491, recon_loss:0.781008, zinb_loss:0.646146, cluster_loss:0.155823
Clustering   491: ASW= 0.8077, DB= 0.2639, CH= 43670.5296
Training epoch 492, recon_loss:0.781421, zinb_loss:0.645903, cluster_loss:0.156165
Clustering   492: ASW= 0.8071, DB= 0.2643, CH= 42999.8136
Training epoch 493, recon_loss:0.780909, zinb_loss:0.646012, cluster_loss:0.155929
Clustering   493: ASW= 0.8078, DB= 0.2637, CH= 43674.0917
Training epoch 494, recon_loss:0.781362, zinb_loss:0.645672, cluster_loss:0.156194
Clustering   494: ASW= 0.8072, DB= 0.2647, CH= 43064.4736
Training epoch 495, recon_loss:0.780889, zinb_loss:0.645789, cluster_loss:0.156084
Clustering   495: ASW= 0.8078, DB= 0.2635, CH= 43654.7972
Training epoch 496, recon_loss:0.781393, zinb_loss:0.645433, cluster_loss:0.156236
Clustering   496: ASW= 0.8074, DB= 0.2647, CH= 43135.9342
Training epoch 497, recon_loss:0.780949, zinb_loss:0.645567, cluster_loss:0.156249
Clustering   497: ASW= 0.8077, DB= 0.2633, CH= 43636.3722
Training epoch 498, recon_loss:0.781443, zinb_loss:0.645212, cluster_loss:0.156266
Clustering   498: ASW= 0.8077, DB= 0.2647, CH= 43218.7986
Training epoch 499, recon_loss:0.780995, zinb_loss:0.645362, cluster_loss:0.156389
Clustering   499: ASW= 0.8075, DB= 0.2627, CH= 43614.6982
Training epoch 500, recon_loss:0.781478, zinb_loss:0.645033, cluster_loss:0.156240
Clustering   500: ASW= 0.8079, DB= 0.2645, CH= 43295.4937
Training epoch 501, recon_loss:0.781003, zinb_loss:0.645158, cluster_loss:0.156424
Clustering   501: ASW= 0.8075, DB= 0.2620, CH= 43604.4781
Training epoch 502, recon_loss:0.781499, zinb_loss:0.644866, cluster_loss:0.156133
Clustering   502: ASW= 0.8080, DB= 0.2645, CH= 43366.2404
Training epoch 503, recon_loss:0.780951, zinb_loss:0.644941, cluster_loss:0.156316
Clustering   503: ASW= 0.8076, DB= 0.2619, CH= 43646.0121
Training epoch 504, recon_loss:0.781585, zinb_loss:0.644680, cluster_loss:0.156014
Clustering   504: ASW= 0.8082, DB= 0.2643, CH= 43432.1042
Training epoch 505, recon_loss:0.781119, zinb_loss:0.644731, cluster_loss:0.156250
Clustering   505: ASW= 0.8077, DB= 0.2618, CH= 43690.5528
Training epoch 506, recon_loss:0.781912, zinb_loss:0.644498, cluster_loss:0.155966
Clustering   506: ASW= 0.8083, DB= 0.2642, CH= 43462.9658
Training epoch 507, recon_loss:0.781417, zinb_loss:0.644560, cluster_loss:0.156240
Clustering   507: ASW= 0.8077, DB= 0.2620, CH= 43714.3784
Training epoch 508, recon_loss:0.781772, zinb_loss:0.644329, cluster_loss:0.155905
Clustering   508: ASW= 0.8084, DB= 0.2639, CH= 43493.2263
Training epoch 509, recon_loss:0.781109, zinb_loss:0.644385, cluster_loss:0.156155
Clustering   509: ASW= 0.8077, DB= 0.2619, CH= 43725.5124
Training epoch 510, recon_loss:0.781332, zinb_loss:0.644181, cluster_loss:0.155804
Clustering   510: ASW= 0.8087, DB= 0.2638, CH= 43564.7812
Training epoch 511, recon_loss:0.780725, zinb_loss:0.644224, cluster_loss:0.156108
Clustering   511: ASW= 0.8076, DB= 0.2620, CH= 43714.6881
Training epoch 512, recon_loss:0.781039, zinb_loss:0.644077, cluster_loss:0.155776
Clustering   512: ASW= 0.8088, DB= 0.2638, CH= 43618.2890
Training epoch 513, recon_loss:0.780609, zinb_loss:0.644134, cluster_loss:0.156076
Clustering   513: ASW= 0.8075, DB= 0.2618, CH= 43715.4106
Training epoch 514, recon_loss:0.780862, zinb_loss:0.644052, cluster_loss:0.155765
Clustering   514: ASW= 0.8090, DB= 0.2631, CH= 43722.3490
Training epoch 515, recon_loss:0.780496, zinb_loss:0.644112, cluster_loss:0.156101
Clustering   515: ASW= 0.8074, DB= 0.2621, CH= 43716.2648
Training epoch 516, recon_loss:0.780753, zinb_loss:0.644062, cluster_loss:0.155805
Clustering   516: ASW= 0.8090, DB= 0.2631, CH= 43748.7848
Training epoch 517, recon_loss:0.780328, zinb_loss:0.644140, cluster_loss:0.156029
Clustering   517: ASW= 0.8074, DB= 0.2615, CH= 43733.7683
Training epoch 518, recon_loss:0.780543, zinb_loss:0.644125, cluster_loss:0.155714
Clustering   518: ASW= 0.8092, DB= 0.2628, CH= 43848.0465
Training epoch 519, recon_loss:0.780233, zinb_loss:0.644224, cluster_loss:0.155912
Clustering   519: ASW= 0.8076, DB= 0.2615, CH= 43790.9650
Training epoch 520, recon_loss:0.780553, zinb_loss:0.644206, cluster_loss:0.155683
Clustering   520: ASW= 0.8092, DB= 0.2626, CH= 43908.3510
Training epoch 521, recon_loss:0.780473, zinb_loss:0.644381, cluster_loss:0.155870
Clustering   521: ASW= 0.8078, DB= 0.2617, CH= 43872.0880
Training epoch 522, recon_loss:0.780958, zinb_loss:0.644316, cluster_loss:0.155730
Clustering   522: ASW= 0.8091, DB= 0.2622, CH= 43907.3297
Training epoch 523, recon_loss:0.780957, zinb_loss:0.644573, cluster_loss:0.155873
Clustering   523: ASW= 0.8082, DB= 0.2612, CH= 43958.4974
Training epoch 524, recon_loss:0.781487, zinb_loss:0.644431, cluster_loss:0.155802
Clustering   524: ASW= 0.8089, DB= 0.2622, CH= 43921.3709
Training epoch 525, recon_loss:0.781397, zinb_loss:0.644716, cluster_loss:0.155900
Clustering   525: ASW= 0.8086, DB= 0.2605, CH= 44028.3166
Training epoch 526, recon_loss:0.781711, zinb_loss:0.644469, cluster_loss:0.155880
Clustering   526: ASW= 0.8086, DB= 0.2627, CH= 43887.2726
Training epoch 527, recon_loss:0.781568, zinb_loss:0.644754, cluster_loss:0.155896
Clustering   527: ASW= 0.8091, DB= 0.2604, CH= 44131.1273
Training epoch 528, recon_loss:0.781582, zinb_loss:0.644455, cluster_loss:0.155926
Clustering   528: ASW= 0.8082, DB= 0.2629, CH= 43867.1461
Training epoch 529, recon_loss:0.781701, zinb_loss:0.644750, cluster_loss:0.155894
Clustering   529: ASW= 0.8096, DB= 0.2601, CH= 44193.9407
Training epoch 530, recon_loss:0.781560, zinb_loss:0.644439, cluster_loss:0.156010
Clustering   530: ASW= 0.8079, DB= 0.2637, CH= 43846.5786
Training epoch 531, recon_loss:0.782124, zinb_loss:0.644764, cluster_loss:0.155918
Clustering   531: ASW= 0.8099, DB= 0.2598, CH= 44233.6913
Training epoch 532, recon_loss:0.781639, zinb_loss:0.644465, cluster_loss:0.156129
Clustering   532: ASW= 0.8074, DB= 0.2639, CH= 43786.8876
Training epoch 533, recon_loss:0.782126, zinb_loss:0.644795, cluster_loss:0.155941
Clustering   533: ASW= 0.8102, DB= 0.2606, CH= 44258.9145
Training epoch 534, recon_loss:0.781268, zinb_loss:0.644469, cluster_loss:0.156163
Clustering   534: ASW= 0.8072, DB= 0.2644, CH= 43786.2120
Training epoch 535, recon_loss:0.781620, zinb_loss:0.644782, cluster_loss:0.155873
Clustering   535: ASW= 0.8103, DB= 0.2605, CH= 44253.5166
Training epoch 536, recon_loss:0.780965, zinb_loss:0.644442, cluster_loss:0.156071
Clustering   536: ASW= 0.8072, DB= 0.2641, CH= 43828.0405
Training epoch 537, recon_loss:0.781209, zinb_loss:0.644735, cluster_loss:0.155799
Clustering   537: ASW= 0.8102, DB= 0.2605, CH= 44236.6775
Training epoch 538, recon_loss:0.780710, zinb_loss:0.644404, cluster_loss:0.155909
Clustering   538: ASW= 0.8074, DB= 0.2638, CH= 43926.4304
Training epoch 539, recon_loss:0.780764, zinb_loss:0.644591, cluster_loss:0.155703
Clustering   539: ASW= 0.8102, DB= 0.2610, CH= 44236.4976
Training epoch 540, recon_loss:0.780322, zinb_loss:0.644306, cluster_loss:0.155708
Clustering   540: ASW= 0.8078, DB= 0.2633, CH= 44051.4582
Training epoch 541, recon_loss:0.780304, zinb_loss:0.644400, cluster_loss:0.155580
Clustering   541: ASW= 0.8101, DB= 0.2608, CH= 44259.5912
Training epoch 542, recon_loss:0.779960, zinb_loss:0.644208, cluster_loss:0.155538
Clustering   542: ASW= 0.8081, DB= 0.2628, CH= 44157.6921
Training epoch 543, recon_loss:0.779965, zinb_loss:0.644250, cluster_loss:0.155475
Clustering   543: ASW= 0.8101, DB= 0.2604, CH= 44293.5226
Training epoch 544, recon_loss:0.779716, zinb_loss:0.644152, cluster_loss:0.155395
Clustering   544: ASW= 0.8085, DB= 0.2622, CH= 44268.6185
Training epoch 545, recon_loss:0.779738, zinb_loss:0.644150, cluster_loss:0.155389
Clustering   545: ASW= 0.8101, DB= 0.2603, CH= 44337.2439
Training epoch 546, recon_loss:0.779611, zinb_loss:0.644139, cluster_loss:0.155293
Clustering   546: ASW= 0.8088, DB= 0.2618, CH= 44360.3563
Training epoch 547, recon_loss:0.779602, zinb_loss:0.644111, cluster_loss:0.155321
Clustering   547: ASW= 0.8102, DB= 0.2604, CH= 44387.6416
Training epoch 548, recon_loss:0.779616, zinb_loss:0.644168, cluster_loss:0.155215
Clustering   548: ASW= 0.8091, DB= 0.2615, CH= 44444.3837
Training epoch 549, recon_loss:0.779568, zinb_loss:0.644131, cluster_loss:0.155278
Clustering   549: ASW= 0.8102, DB= 0.2603, CH= 44442.0928
Training epoch 550, recon_loss:0.779770, zinb_loss:0.644243, cluster_loss:0.155183
Clustering   550: ASW= 0.8094, DB= 0.2612, CH= 44510.0034
Training epoch 551, recon_loss:0.779762, zinb_loss:0.644250, cluster_loss:0.155291
Clustering   551: ASW= 0.8103, DB= 0.2599, CH= 44493.5821
Training epoch 552, recon_loss:0.780256, zinb_loss:0.644387, cluster_loss:0.155213
Clustering   552: ASW= 0.8096, DB= 0.2604, CH= 44546.4168
Training epoch 553, recon_loss:0.780334, zinb_loss:0.644457, cluster_loss:0.155398
Clustering   553: ASW= 0.8104, DB= 0.2601, CH= 44542.7050
Training epoch 554, recon_loss:0.781065, zinb_loss:0.644579, cluster_loss:0.155348
Clustering   554: ASW= 0.8097, DB= 0.2603, CH= 44572.9343
Training epoch 555, recon_loss:0.780900, zinb_loss:0.644676, cluster_loss:0.155614
Clustering   555: ASW= 0.8104, DB= 0.2606, CH= 44570.2040
Training epoch 556, recon_loss:0.781378, zinb_loss:0.644686, cluster_loss:0.155497
Clustering   556: ASW= 0.8098, DB= 0.2602, CH= 44588.7587
Training epoch 557, recon_loss:0.781050, zinb_loss:0.644688, cluster_loss:0.155802
Clustering   557: ASW= 0.8105, DB= 0.2606, CH= 44575.7605
Training epoch 558, recon_loss:0.781319, zinb_loss:0.644619, cluster_loss:0.155588
Clustering   558: ASW= 0.8097, DB= 0.2601, CH= 44599.4676
Training epoch 559, recon_loss:0.780849, zinb_loss:0.644492, cluster_loss:0.155919
Clustering   559: ASW= 0.8105, DB= 0.2605, CH= 44566.4428
Training epoch 560, recon_loss:0.781081, zinb_loss:0.644398, cluster_loss:0.155652
Clustering   560: ASW= 0.8096, DB= 0.2597, CH= 44555.8493
Training epoch 561, recon_loss:0.780511, zinb_loss:0.644249, cluster_loss:0.155969
Clustering   561: ASW= 0.8105, DB= 0.2603, CH= 44574.0596
Training epoch 562, recon_loss:0.780675, zinb_loss:0.644134, cluster_loss:0.155664
Clustering   562: ASW= 0.8095, DB= 0.2596, CH= 44530.2719
Training epoch 563, recon_loss:0.780114, zinb_loss:0.644012, cluster_loss:0.155955
Clustering   563: ASW= 0.8106, DB= 0.2596, CH= 44570.6584
Training epoch 564, recon_loss:0.780267, zinb_loss:0.643910, cluster_loss:0.155615
Clustering   564: ASW= 0.8096, DB= 0.2596, CH= 44578.2046
Training epoch 565, recon_loss:0.779836, zinb_loss:0.643820, cluster_loss:0.155943
Clustering   565: ASW= 0.8106, DB= 0.2600, CH= 44535.6738
Training epoch 566, recon_loss:0.780137, zinb_loss:0.643812, cluster_loss:0.155584
Clustering   566: ASW= 0.8099, DB= 0.2589, CH= 44644.5828
Training epoch 567, recon_loss:0.779757, zinb_loss:0.643773, cluster_loss:0.155926
Clustering   567: ASW= 0.8106, DB= 0.2600, CH= 44492.0582
Training epoch 568, recon_loss:0.779920, zinb_loss:0.643830, cluster_loss:0.155548
Clustering   568: ASW= 0.8101, DB= 0.2587, CH= 44747.4730
Training epoch 569, recon_loss:0.779741, zinb_loss:0.643841, cluster_loss:0.155910
Clustering   569: ASW= 0.8104, DB= 0.2604, CH= 44434.5430
Training epoch 570, recon_loss:0.779863, zinb_loss:0.643956, cluster_loss:0.155537
Clustering   570: ASW= 0.8105, DB= 0.2588, CH= 44861.7968
Training epoch 571, recon_loss:0.779666, zinb_loss:0.643933, cluster_loss:0.155828
Clustering   571: ASW= 0.8103, DB= 0.2604, CH= 44412.1202
Training epoch 572, recon_loss:0.779611, zinb_loss:0.644006, cluster_loss:0.155444
Clustering   572: ASW= 0.8107, DB= 0.2586, CH= 44960.0115
Training epoch 573, recon_loss:0.779459, zinb_loss:0.643924, cluster_loss:0.155664
Clustering   573: ASW= 0.8104, DB= 0.2605, CH= 44457.4602
Training epoch 574, recon_loss:0.779400, zinb_loss:0.643964, cluster_loss:0.155354
Clustering   574: ASW= 0.8110, DB= 0.2583, CH= 45074.2866
Training epoch 575, recon_loss:0.779589, zinb_loss:0.643899, cluster_loss:0.155644
Clustering   575: ASW= 0.8104, DB= 0.2602, CH= 44477.7655
Training epoch 576, recon_loss:0.779616, zinb_loss:0.643937, cluster_loss:0.155405
Clustering   576: ASW= 0.8111, DB= 0.2584, CH= 45163.3471
Training epoch 577, recon_loss:0.779986, zinb_loss:0.643890, cluster_loss:0.155754
Clustering   577: ASW= 0.8104, DB= 0.2599, CH= 44473.0167
Training epoch 578, recon_loss:0.779858, zinb_loss:0.643922, cluster_loss:0.155492
Clustering   578: ASW= 0.8112, DB= 0.2583, CH= 45208.1166
Training epoch 579, recon_loss:0.780190, zinb_loss:0.643871, cluster_loss:0.155848
Clustering   579: ASW= 0.8104, DB= 0.2598, CH= 44460.5708
Training epoch 580, recon_loss:0.779888, zinb_loss:0.643903, cluster_loss:0.155502
Clustering   580: ASW= 0.8113, DB= 0.2581, CH= 45227.9453
Training epoch 581, recon_loss:0.780053, zinb_loss:0.643794, cluster_loss:0.155811
Clustering   581: ASW= 0.8104, DB= 0.2594, CH= 44473.9500
Training epoch 582, recon_loss:0.779590, zinb_loss:0.643846, cluster_loss:0.155399
Clustering   582: ASW= 0.8114, DB= 0.2583, CH= 45254.8656
Training epoch 583, recon_loss:0.779654, zinb_loss:0.643672, cluster_loss:0.155681
Clustering   583: ASW= 0.8104, DB= 0.2593, CH= 44516.5553
Training epoch 584, recon_loss:0.779198, zinb_loss:0.643770, cluster_loss:0.155252
Clustering   584: ASW= 0.8116, DB= 0.2580, CH= 45286.3452
Training epoch 585, recon_loss:0.779274, zinb_loss:0.643570, cluster_loss:0.155553
Clustering   585: ASW= 0.8104, DB= 0.2592, CH= 44573.8160
Training epoch 586, recon_loss:0.779026, zinb_loss:0.643756, cluster_loss:0.155140
Clustering   586: ASW= 0.8118, DB= 0.2579, CH= 45337.5574
Training epoch 587, recon_loss:0.779299, zinb_loss:0.643565, cluster_loss:0.155518
Clustering   587: ASW= 0.8103, DB= 0.2592, CH= 44617.2740
Training epoch 588, recon_loss:0.779417, zinb_loss:0.643859, cluster_loss:0.155128
Clustering   588: ASW= 0.8122, DB= 0.2576, CH= 45384.2594
Training epoch 589, recon_loss:0.779754, zinb_loss:0.643700, cluster_loss:0.155634
Clustering   589: ASW= 0.8101, DB= 0.2595, CH= 44638.3082
Training epoch 590, recon_loss:0.780169, zinb_loss:0.644096, cluster_loss:0.155266
Clustering   590: ASW= 0.8126, DB= 0.2574, CH= 45404.3221
Training epoch 591, recon_loss:0.780172, zinb_loss:0.643955, cluster_loss:0.155839
Clustering   591: ASW= 0.8099, DB= 0.2585, CH= 44691.1306
Training epoch 592, recon_loss:0.780529, zinb_loss:0.644264, cluster_loss:0.155436
Clustering   592: ASW= 0.8127, DB= 0.2574, CH= 45350.0267
Training epoch 593, recon_loss:0.780281, zinb_loss:0.644100, cluster_loss:0.155915
Clustering   593: ASW= 0.8100, DB= 0.2579, CH= 44779.0745
Training epoch 594, recon_loss:0.780412, zinb_loss:0.644187, cluster_loss:0.155406
Clustering   594: ASW= 0.8124, DB= 0.2575, CH= 45275.9918
Training epoch 595, recon_loss:0.780148, zinb_loss:0.644089, cluster_loss:0.155744
Clustering   595: ASW= 0.8102, DB= 0.2576, CH= 44839.5361
Training epoch 596, recon_loss:0.780226, zinb_loss:0.644087, cluster_loss:0.155358
Clustering   596: ASW= 0.8122, DB= 0.2582, CH= 45228.0594
Training epoch 597, recon_loss:0.780186, zinb_loss:0.644096, cluster_loss:0.155618
Clustering   597: ASW= 0.8105, DB= 0.2573, CH= 44903.7156
Training epoch 598, recon_loss:0.780114, zinb_loss:0.644071, cluster_loss:0.155342
Clustering   598: ASW= 0.8120, DB= 0.2583, CH= 45227.3790
Training epoch 599, recon_loss:0.780177, zinb_loss:0.644115, cluster_loss:0.155575
Clustering   599: ASW= 0.8106, DB= 0.2574, CH= 44917.6847
Training epoch 600, recon_loss:0.779871, zinb_loss:0.644093, cluster_loss:0.155316
Clustering   600: ASW= 0.8120, DB= 0.2582, CH= 45278.4881
Training epoch 601, recon_loss:0.780074, zinb_loss:0.644150, cluster_loss:0.155532
Clustering   601: ASW= 0.8109, DB= 0.2570, CH= 44968.4103
Training epoch 602, recon_loss:0.779644, zinb_loss:0.644147, cluster_loss:0.155275
Clustering   602: ASW= 0.8119, DB= 0.2580, CH= 45325.4166
Training epoch 603, recon_loss:0.779885, zinb_loss:0.644182, cluster_loss:0.155513
Clustering   603: ASW= 0.8109, DB= 0.2569, CH= 44963.3408
Training epoch 604, recon_loss:0.779539, zinb_loss:0.644206, cluster_loss:0.155252
Clustering   604: ASW= 0.8120, DB= 0.2578, CH= 45389.3617
Training epoch 605, recon_loss:0.779861, zinb_loss:0.644250, cluster_loss:0.155534
Clustering   605: ASW= 0.8110, DB= 0.2570, CH= 44987.3507
Training epoch 606, recon_loss:0.779782, zinb_loss:0.644377, cluster_loss:0.155290
Clustering   606: ASW= 0.8120, DB= 0.2578, CH= 45449.1004
Training epoch 607, recon_loss:0.780254, zinb_loss:0.644470, cluster_loss:0.155681
Clustering   607: ASW= 0.8110, DB= 0.2569, CH= 44970.5108
Training epoch 608, recon_loss:0.780501, zinb_loss:0.644767, cluster_loss:0.155456
Clustering   608: ASW= 0.8121, DB= 0.2576, CH= 45496.2287
Training epoch 609, recon_loss:0.781070, zinb_loss:0.644817, cluster_loss:0.155961
Clustering   609: ASW= 0.8109, DB= 0.2572, CH= 44881.7386
Training epoch 610, recon_loss:0.781091, zinb_loss:0.645018, cluster_loss:0.155601
Clustering   610: ASW= 0.8121, DB= 0.2577, CH= 45534.6271
Training epoch 611, recon_loss:0.781349, zinb_loss:0.644752, cluster_loss:0.156029
Clustering   611: ASW= 0.8110, DB= 0.2574, CH= 44885.5987
Training epoch 612, recon_loss:0.780716, zinb_loss:0.644738, cluster_loss:0.155497
Clustering   612: ASW= 0.8120, DB= 0.2577, CH= 45539.3884
Training epoch 613, recon_loss:0.780712, zinb_loss:0.644317, cluster_loss:0.155810
Clustering   613: ASW= 0.8113, DB= 0.2571, CH= 44953.3667
Training epoch 614, recon_loss:0.779934, zinb_loss:0.644289, cluster_loss:0.155257
Clustering   614: ASW= 0.8120, DB= 0.2577, CH= 45555.5730
Training epoch 615, recon_loss:0.779892, zinb_loss:0.643909, cluster_loss:0.155541
Clustering   615: ASW= 0.8115, DB= 0.2570, CH= 45032.9228
Training epoch 616, recon_loss:0.779302, zinb_loss:0.643939, cluster_loss:0.155064
Clustering   616: ASW= 0.8122, DB= 0.2573, CH= 45593.9422
Training epoch 617, recon_loss:0.779354, zinb_loss:0.643635, cluster_loss:0.155360
Clustering   617: ASW= 0.8117, DB= 0.2571, CH= 45118.8111
Training epoch 618, recon_loss:0.778943, zinb_loss:0.643714, cluster_loss:0.154949
Clustering   618: ASW= 0.8123, DB= 0.2572, CH= 45658.5656
Training epoch 619, recon_loss:0.779048, zinb_loss:0.643465, cluster_loss:0.155241
Clustering   619: ASW= 0.8119, DB= 0.2569, CH= 45192.1463
Training epoch 620, recon_loss:0.778766, zinb_loss:0.643574, cluster_loss:0.154897
Clustering   620: ASW= 0.8124, DB= 0.2574, CH= 45727.7503
Training epoch 621, recon_loss:0.778904, zinb_loss:0.643371, cluster_loss:0.155152
Clustering   621: ASW= 0.8121, DB= 0.2567, CH= 45275.0496
Training epoch 622, recon_loss:0.778715, zinb_loss:0.643481, cluster_loss:0.154887
Clustering   622: ASW= 0.8125, DB= 0.2575, CH= 45781.0486
Training epoch 623, recon_loss:0.778906, zinb_loss:0.643325, cluster_loss:0.155087
Clustering   623: ASW= 0.8123, DB= 0.2564, CH= 45345.1516
Training epoch 624, recon_loss:0.778799, zinb_loss:0.643415, cluster_loss:0.154909
Clustering   624: ASW= 0.8125, DB= 0.2574, CH= 45828.8004
Training epoch 625, recon_loss:0.778948, zinb_loss:0.643295, cluster_loss:0.155038
Clustering   625: ASW= 0.8125, DB= 0.2566, CH= 45414.2683
Training epoch 626, recon_loss:0.778839, zinb_loss:0.643373, cluster_loss:0.154931
Clustering   626: ASW= 0.8126, DB= 0.2577, CH= 45889.1364
Training epoch 627, recon_loss:0.778906, zinb_loss:0.643268, cluster_loss:0.155004
Clustering   627: ASW= 0.8127, DB= 0.2567, CH= 45448.2311
Training epoch 628, recon_loss:0.778695, zinb_loss:0.643359, cluster_loss:0.154924
Clustering   628: ASW= 0.8127, DB= 0.2576, CH= 45969.5222
Training epoch 629, recon_loss:0.778753, zinb_loss:0.643264, cluster_loss:0.154970
Clustering   629: ASW= 0.8128, DB= 0.2570, CH= 45486.5367
Training epoch 630, recon_loss:0.778469, zinb_loss:0.643391, cluster_loss:0.154932
Clustering   630: ASW= 0.8128, DB= 0.2577, CH= 46042.2409
Training epoch 631, recon_loss:0.778628, zinb_loss:0.643313, cluster_loss:0.154984
Clustering   631: ASW= 0.8129, DB= 0.2571, CH= 45490.5853
Training epoch 632, recon_loss:0.778464, zinb_loss:0.643528, cluster_loss:0.155019
Clustering   632: ASW= 0.8128, DB= 0.2575, CH= 46073.0330
Training epoch 633, recon_loss:0.778854, zinb_loss:0.643483, cluster_loss:0.155110
Clustering   633: ASW= 0.8130, DB= 0.2569, CH= 45466.2708
Training epoch 634, recon_loss:0.778808, zinb_loss:0.643761, cluster_loss:0.155187
Clustering   634: ASW= 0.8128, DB= 0.2576, CH= 46074.6084
Training epoch 635, recon_loss:0.779661, zinb_loss:0.643759, cluster_loss:0.155224
Clustering   635: ASW= 0.8129, DB= 0.2573, CH= 45420.8440
Training epoch 636, recon_loss:0.779147, zinb_loss:0.643916, cluster_loss:0.155295
Clustering   636: ASW= 0.8126, DB= 0.2576, CH= 46045.3832
Training epoch 637, recon_loss:0.780143, zinb_loss:0.643879, cluster_loss:0.155275
Clustering   637: ASW= 0.8132, DB= 0.2572, CH= 45468.4731
Training epoch 638, recon_loss:0.779234, zinb_loss:0.643869, cluster_loss:0.155395
Clustering   638: ASW= 0.8124, DB= 0.2579, CH= 45930.5185
Training epoch 639, recon_loss:0.780603, zinb_loss:0.643804, cluster_loss:0.155244
Clustering   639: ASW= 0.8135, DB= 0.2562, CH= 45527.8077
Training epoch 640, recon_loss:0.779197, zinb_loss:0.643699, cluster_loss:0.155385
Clustering   640: ASW= 0.8123, DB= 0.2572, CH= 45925.8813
Training epoch 641, recon_loss:0.780247, zinb_loss:0.643587, cluster_loss:0.155176
Clustering   641: ASW= 0.8140, DB= 0.2559, CH= 45687.7344
Training epoch 642, recon_loss:0.778833, zinb_loss:0.643461, cluster_loss:0.155491
Clustering   642: ASW= 0.8119, DB= 0.2569, CH= 45827.4094
Training epoch 643, recon_loss:0.779603, zinb_loss:0.643329, cluster_loss:0.155149
Clustering   643: ASW= 0.8140, DB= 0.2562, CH= 45735.2778
Training epoch 644, recon_loss:0.778496, zinb_loss:0.643321, cluster_loss:0.155468
Clustering   644: ASW= 0.8119, DB= 0.2560, CH= 45823.4928
Training epoch 645, recon_loss:0.779218, zinb_loss:0.643208, cluster_loss:0.155015
Clustering   645: ASW= 0.8140, DB= 0.2558, CH= 45819.4702
Training epoch 646, recon_loss:0.778248, zinb_loss:0.643196, cluster_loss:0.155308
Clustering   646: ASW= 0.8120, DB= 0.2559, CH= 45863.8867
Training epoch 647, recon_loss:0.778884, zinb_loss:0.643091, cluster_loss:0.154901
Clustering   647: ASW= 0.8140, DB= 0.2558, CH= 45884.1937
Training epoch 648, recon_loss:0.778124, zinb_loss:0.643097, cluster_loss:0.155182
Clustering   648: ASW= 0.8122, DB= 0.2557, CH= 45897.9540
Training epoch 649, recon_loss:0.778705, zinb_loss:0.643025, cluster_loss:0.154817
Clustering   649: ASW= 0.8141, DB= 0.2557, CH= 45963.7538
Training epoch 650, recon_loss:0.778107, zinb_loss:0.643033, cluster_loss:0.155092
Clustering   650: ASW= 0.8122, DB= 0.2554, CH= 45924.6186
Training epoch 651, recon_loss:0.778690, zinb_loss:0.643006, cluster_loss:0.154796
Clustering   651: ASW= 0.8142, DB= 0.2552, CH= 46018.5789
Training epoch 652, recon_loss:0.778243, zinb_loss:0.643031, cluster_loss:0.155043
Clustering   652: ASW= 0.8124, DB= 0.2553, CH= 45964.8776
Training epoch 653, recon_loss:0.778872, zinb_loss:0.643057, cluster_loss:0.154833
Clustering   653: ASW= 0.8142, DB= 0.2555, CH= 46079.7586
Training epoch 654, recon_loss:0.778560, zinb_loss:0.643091, cluster_loss:0.155050
Clustering   654: ASW= 0.8125, DB= 0.2552, CH= 45989.8558
Training epoch 655, recon_loss:0.779242, zinb_loss:0.643167, cluster_loss:0.155024
Clustering   655: ASW= 0.8142, DB= 0.2551, CH= 46103.8140
Training epoch 656, recon_loss:0.779103, zinb_loss:0.643213, cluster_loss:0.155182
Clustering   656: ASW= 0.8125, DB= 0.2551, CH= 45961.2954
Training epoch 657, recon_loss:0.779602, zinb_loss:0.643325, cluster_loss:0.155302
Clustering   657: ASW= 0.8141, DB= 0.2560, CH= 46109.7265
Training epoch 658, recon_loss:0.779604, zinb_loss:0.643361, cluster_loss:0.155346
Clustering   658: ASW= 0.8125, DB= 0.2549, CH= 45954.9612
Training epoch 659, recon_loss:0.779723, zinb_loss:0.643470, cluster_loss:0.155545
Clustering   659: ASW= 0.8141, DB= 0.2561, CH= 46158.1466
Training epoch 660, recon_loss:0.779932, zinb_loss:0.643498, cluster_loss:0.155542
Clustering   660: ASW= 0.8124, DB= 0.2548, CH= 45891.4763
Training epoch 661, recon_loss:0.779578, zinb_loss:0.643465, cluster_loss:0.155658
Clustering   661: ASW= 0.8139, DB= 0.2559, CH= 46129.4767
Training epoch 662, recon_loss:0.779792, zinb_loss:0.643494, cluster_loss:0.155491
Clustering   662: ASW= 0.8127, DB= 0.2544, CH= 45972.8724
Training epoch 663, recon_loss:0.779059, zinb_loss:0.643351, cluster_loss:0.155534
Clustering   663: ASW= 0.8140, DB= 0.2559, CH= 46168.9750
Training epoch 664, recon_loss:0.779199, zinb_loss:0.643385, cluster_loss:0.155254
Clustering   664: ASW= 0.8130, DB= 0.2544, CH= 46095.6254
Training epoch 665, recon_loss:0.778309, zinb_loss:0.643074, cluster_loss:0.155305
Clustering   665: ASW= 0.8139, DB= 0.2563, CH= 46148.6770
Training epoch 666, recon_loss:0.778481, zinb_loss:0.643155, cluster_loss:0.154932
Clustering   666: ASW= 0.8134, DB= 0.2545, CH= 46252.4600
Training epoch 667, recon_loss:0.777918, zinb_loss:0.642933, cluster_loss:0.155062
Clustering   667: ASW= 0.8141, DB= 0.2559, CH= 46260.1339
Training epoch 668, recon_loss:0.778191, zinb_loss:0.643055, cluster_loss:0.154723
Clustering   668: ASW= 0.8136, DB= 0.2541, CH= 46334.1467
Training epoch 669, recon_loss:0.777863, zinb_loss:0.642852, cluster_loss:0.154928
Clustering   669: ASW= 0.8141, DB= 0.2559, CH= 46338.1977
Training epoch 670, recon_loss:0.778222, zinb_loss:0.643019, cluster_loss:0.154581
Clustering   670: ASW= 0.8139, DB= 0.2537, CH= 46419.8440
Training epoch 671, recon_loss:0.778079, zinb_loss:0.642846, cluster_loss:0.154857
Clustering   671: ASW= 0.8142, DB= 0.2560, CH= 46407.3440
Training epoch 672, recon_loss:0.778468, zinb_loss:0.643025, cluster_loss:0.154485
Clustering   672: ASW= 0.8141, DB= 0.2542, CH= 46490.7059
Training epoch 673, recon_loss:0.778338, zinb_loss:0.642851, cluster_loss:0.154799
Clustering   673: ASW= 0.8142, DB= 0.2555, CH= 46440.3844
Training epoch 674, recon_loss:0.778714, zinb_loss:0.643021, cluster_loss:0.154398
Clustering   674: ASW= 0.8142, DB= 0.2541, CH= 46530.2675
Training epoch 675, recon_loss:0.778520, zinb_loss:0.642832, cluster_loss:0.154742
Clustering   675: ASW= 0.8141, DB= 0.2556, CH= 46463.8192
Training epoch 676, recon_loss:0.778898, zinb_loss:0.642989, cluster_loss:0.154327
Clustering   676: ASW= 0.8142, DB= 0.2541, CH= 46551.0367
Training epoch 677, recon_loss:0.778592, zinb_loss:0.642767, cluster_loss:0.154707
Clustering   677: ASW= 0.8140, DB= 0.2556, CH= 46449.3458
Training epoch 678, recon_loss:0.778952, zinb_loss:0.642918, cluster_loss:0.154287
Clustering   678: ASW= 0.8142, DB= 0.2539, CH= 46559.4259
Training epoch 679, recon_loss:0.778521, zinb_loss:0.642660, cluster_loss:0.154701
Clustering   679: ASW= 0.8138, DB= 0.2559, CH= 46413.8801
Training epoch 680, recon_loss:0.778830, zinb_loss:0.642816, cluster_loss:0.154281
Clustering   680: ASW= 0.8142, DB= 0.2539, CH= 46582.0812
Training epoch 681, recon_loss:0.778301, zinb_loss:0.642551, cluster_loss:0.154719
Clustering   681: ASW= 0.8135, DB= 0.2561, CH= 46363.5061
Training epoch 682, recon_loss:0.778553, zinb_loss:0.642714, cluster_loss:0.154291
Clustering   682: ASW= 0.8144, DB= 0.2539, CH= 46621.6832
Training epoch 683, recon_loss:0.778053, zinb_loss:0.642472, cluster_loss:0.154773
Clustering   683: ASW= 0.8132, DB= 0.2560, CH= 46290.9516
Training epoch 684, recon_loss:0.778334, zinb_loss:0.642665, cluster_loss:0.154350
Clustering   684: ASW= 0.8146, DB= 0.2541, CH= 46680.9755
Training epoch 685, recon_loss:0.778035, zinb_loss:0.642466, cluster_loss:0.154950
Clustering   685: ASW= 0.8128, DB= 0.2559, CH= 46159.7453
Training epoch 686, recon_loss:0.778376, zinb_loss:0.642728, cluster_loss:0.154539
Clustering   686: ASW= 0.8147, DB= 0.2542, CH= 46705.1483
Training epoch 687, recon_loss:0.778331, zinb_loss:0.642698, cluster_loss:0.155236
Clustering   687: ASW= 0.8123, DB= 0.2554, CH= 46010.4483
Training epoch 688, recon_loss:0.778654, zinb_loss:0.643076, cluster_loss:0.154769
Clustering   688: ASW= 0.8146, DB= 0.2537, CH= 46667.7891
Training epoch 689, recon_loss:0.778960, zinb_loss:0.643261, cluster_loss:0.155450
Clustering   689: ASW= 0.8121, DB= 0.2550, CH= 45859.9627
Training epoch 690, recon_loss:0.779204, zinb_loss:0.643671, cluster_loss:0.154960
Clustering   690: ASW= 0.8143, DB= 0.2548, CH= 46637.5341
Training epoch 691, recon_loss:0.779466, zinb_loss:0.643745, cluster_loss:0.155420
Clustering   691: ASW= 0.8128, DB= 0.2543, CH= 45939.9380
Training epoch 692, recon_loss:0.779247, zinb_loss:0.643721, cluster_loss:0.154902
Clustering   692: ASW= 0.8145, DB= 0.2547, CH= 46684.2038
Training epoch 693, recon_loss:0.779477, zinb_loss:0.643743, cluster_loss:0.155122
Clustering   693: ASW= 0.8138, DB= 0.2528, CH= 46308.1874
Training epoch 694, recon_loss:0.778943, zinb_loss:0.643501, cluster_loss:0.154745
Clustering   694: ASW= 0.8146, DB= 0.2553, CH= 46758.6592
Training epoch 695, recon_loss:0.779277, zinb_loss:0.643511, cluster_loss:0.155040
Clustering   695: ASW= 0.8141, DB= 0.2531, CH= 46291.7327
Training epoch 696, recon_loss:0.779168, zinb_loss:0.643279, cluster_loss:0.154750
Clustering   696: ASW= 0.8146, DB= 0.2552, CH= 46754.3705
Training epoch 697, recon_loss:0.779291, zinb_loss:0.643358, cluster_loss:0.154886
Clustering   697: ASW= 0.8149, DB= 0.2524, CH= 46554.2697
Training epoch 698, recon_loss:0.778885, zinb_loss:0.643145, cluster_loss:0.154585
Clustering   698: ASW= 0.8149, DB= 0.2550, CH= 46884.2579
Training epoch 699, recon_loss:0.779008, zinb_loss:0.643128, cluster_loss:0.154762
Clustering   699: ASW= 0.8151, DB= 0.2521, CH= 46651.5204
Training epoch 700, recon_loss:0.778591, zinb_loss:0.642866, cluster_loss:0.154573
Clustering   700: ASW= 0.8147, DB= 0.2549, CH= 46854.4308
Training epoch 701, recon_loss:0.778886, zinb_loss:0.642988, cluster_loss:0.154722
Clustering   701: ASW= 0.8155, DB= 0.2524, CH= 46714.4321
Training epoch 702, recon_loss:0.778507, zinb_loss:0.642817, cluster_loss:0.154476
Clustering   702: ASW= 0.8148, DB= 0.2543, CH= 46985.8439
Training epoch 703, recon_loss:0.778516, zinb_loss:0.642859, cluster_loss:0.154665
Clustering   703: ASW= 0.8157, DB= 0.2525, CH= 46747.6141
Training epoch 704, recon_loss:0.778098, zinb_loss:0.642716, cluster_loss:0.154412
Clustering   704: ASW= 0.8148, DB= 0.2542, CH= 47041.9454
Training epoch 705, recon_loss:0.778243, zinb_loss:0.642762, cluster_loss:0.154617
Clustering   705: ASW= 0.8158, DB= 0.2527, CH= 46798.1154
Training epoch 706, recon_loss:0.777888, zinb_loss:0.642665, cluster_loss:0.154378
Clustering   706: ASW= 0.8148, DB= 0.2539, CH= 47120.0528
Training epoch 707, recon_loss:0.778087, zinb_loss:0.642735, cluster_loss:0.154629
Clustering   707: ASW= 0.8159, DB= 0.2528, CH= 46818.5047
Training epoch 708, recon_loss:0.777859, zinb_loss:0.642722, cluster_loss:0.154401
Clustering   708: ASW= 0.8149, DB= 0.2539, CH= 47221.0879
Training epoch 709, recon_loss:0.778074, zinb_loss:0.642790, cluster_loss:0.154725
Clustering   709: ASW= 0.8158, DB= 0.2530, CH= 46777.9486
Training epoch 710, recon_loss:0.777951, zinb_loss:0.642915, cluster_loss:0.154469
Clustering   710: ASW= 0.8150, DB= 0.2536, CH= 47345.5181
Training epoch 711, recon_loss:0.778174, zinb_loss:0.643005, cluster_loss:0.154892
Clustering   711: ASW= 0.8157, DB= 0.2529, CH= 46715.3361
Training epoch 712, recon_loss:0.778256, zinb_loss:0.643272, cluster_loss:0.154632
Clustering   712: ASW= 0.8152, DB= 0.2536, CH= 47443.6459
Training epoch 713, recon_loss:0.778531, zinb_loss:0.643366, cluster_loss:0.155186
Clustering   713: ASW= 0.8154, DB= 0.2533, CH= 46578.3952
Training epoch 714, recon_loss:0.778820, zinb_loss:0.643772, cluster_loss:0.154919
Clustering   714: ASW= 0.8152, DB= 0.2538, CH= 47489.9950
Training epoch 715, recon_loss:0.779109, zinb_loss:0.643819, cluster_loss:0.155592
Clustering   715: ASW= 0.8152, DB= 0.2524, CH= 46404.5132
Training epoch 716, recon_loss:0.779317, zinb_loss:0.644271, cluster_loss:0.155242
Clustering   716: ASW= 0.8152, DB= 0.2538, CH= 47404.3629
Training epoch 717, recon_loss:0.779436, zinb_loss:0.644071, cluster_loss:0.155811
Clustering   717: ASW= 0.8148, DB= 0.2524, CH= 46274.4754
Training epoch 718, recon_loss:0.778766, zinb_loss:0.644258, cluster_loss:0.155210
Clustering   718: ASW= 0.8153, DB= 0.2540, CH= 47273.7566
Training epoch 719, recon_loss:0.778815, zinb_loss:0.643840, cluster_loss:0.155524
Clustering   719: ASW= 0.8145, DB= 0.2524, CH= 46314.4062
Training epoch 720, recon_loss:0.778028, zinb_loss:0.643948, cluster_loss:0.154941
Clustering   720: ASW= 0.8152, DB= 0.2540, CH= 47183.4404
Training epoch 721, recon_loss:0.778078, zinb_loss:0.643497, cluster_loss:0.155191
Clustering   721: ASW= 0.8145, DB= 0.2532, CH= 46429.2643
Training epoch 722, recon_loss:0.777466, zinb_loss:0.643652, cluster_loss:0.154664
Clustering   722: ASW= 0.8154, DB= 0.2537, CH= 47163.5072
Training epoch 723, recon_loss:0.777766, zinb_loss:0.643245, cluster_loss:0.154889
Clustering   723: ASW= 0.8145, DB= 0.2527, CH= 46547.4448
Training epoch 724, recon_loss:0.777325, zinb_loss:0.643434, cluster_loss:0.154423
Clustering   724: ASW= 0.8157, DB= 0.2538, CH= 47274.7167
Training epoch 725, recon_loss:0.777768, zinb_loss:0.643120, cluster_loss:0.154753
Clustering   725: ASW= 0.8146, DB= 0.2530, CH= 46646.5248
Training epoch 726, recon_loss:0.777500, zinb_loss:0.643337, cluster_loss:0.154298
Clustering   726: ASW= 0.8158, DB= 0.2537, CH= 47291.3223
Training epoch 727, recon_loss:0.778230, zinb_loss:0.643104, cluster_loss:0.154717
Clustering   727: ASW= 0.8145, DB= 0.2533, CH= 46688.4826
Training epoch 728, recon_loss:0.777669, zinb_loss:0.643242, cluster_loss:0.154247
Clustering   728: ASW= 0.8158, DB= 0.2538, CH= 47312.7544
Training epoch 729, recon_loss:0.778311, zinb_loss:0.643057, cluster_loss:0.154645
Clustering   729: ASW= 0.8146, DB= 0.2534, CH= 46782.4242
Training epoch 730, recon_loss:0.777685, zinb_loss:0.643163, cluster_loss:0.154194
Clustering   730: ASW= 0.8158, DB= 0.2537, CH= 47302.4639
Training epoch 731, recon_loss:0.778329, zinb_loss:0.643000, cluster_loss:0.154654
Clustering   731: ASW= 0.8145, DB= 0.2534, CH= 46777.8121
Training epoch 732, recon_loss:0.777722, zinb_loss:0.643079, cluster_loss:0.154186
Clustering   732: ASW= 0.8157, DB= 0.2539, CH= 47282.2563
Training epoch 733, recon_loss:0.778195, zinb_loss:0.642983, cluster_loss:0.154594
Clustering   733: ASW= 0.8148, DB= 0.2529, CH= 46894.3607
Training epoch 734, recon_loss:0.777556, zinb_loss:0.643051, cluster_loss:0.154137
Clustering   734: ASW= 0.8158, DB= 0.2528, CH= 47289.6340
Training epoch 735, recon_loss:0.778127, zinb_loss:0.642976, cluster_loss:0.154633
Clustering   735: ASW= 0.8147, DB= 0.2528, CH= 46873.6539
Training epoch 736, recon_loss:0.777626, zinb_loss:0.643013, cluster_loss:0.154179
Clustering   736: ASW= 0.8158, DB= 0.2534, CH= 47272.0766
Training epoch 737, recon_loss:0.778224, zinb_loss:0.643000, cluster_loss:0.154608
Clustering   737: ASW= 0.8149, DB= 0.2525, CH= 46986.4518
Training epoch 738, recon_loss:0.777667, zinb_loss:0.642999, cluster_loss:0.154204
Clustering   738: ASW= 0.8160, DB= 0.2525, CH= 47320.4043
Training epoch 739, recon_loss:0.778128, zinb_loss:0.642991, cluster_loss:0.154619
Clustering   739: ASW= 0.8150, DB= 0.2525, CH= 47063.7451
Training epoch 740, recon_loss:0.777665, zinb_loss:0.642931, cluster_loss:0.154264
Clustering   740: ASW= 0.8162, DB= 0.2524, CH= 47371.2833
Training epoch 741, recon_loss:0.778091, zinb_loss:0.642901, cluster_loss:0.154643
Clustering   741: ASW= 0.8152, DB= 0.2522, CH= 47139.6468
Training epoch 742, recon_loss:0.777611, zinb_loss:0.642796, cluster_loss:0.154310
Clustering   742: ASW= 0.8163, DB= 0.2526, CH= 47401.2335
Training epoch 743, recon_loss:0.778017, zinb_loss:0.642759, cluster_loss:0.154595
Clustering   743: ASW= 0.8156, DB= 0.2522, CH= 47266.1735
Training epoch 744, recon_loss:0.777525, zinb_loss:0.642649, cluster_loss:0.154324
Clustering   744: ASW= 0.8163, DB= 0.2529, CH= 47411.0784
Training epoch 745, recon_loss:0.778003, zinb_loss:0.642626, cluster_loss:0.154541
Clustering   745: ASW= 0.8160, DB= 0.2523, CH= 47403.1263
Training epoch 746, recon_loss:0.777745, zinb_loss:0.642576, cluster_loss:0.154450
Clustering   746: ASW= 0.8160, DB= 0.2527, CH= 47327.2942
Training epoch 747, recon_loss:0.778618, zinb_loss:0.642709, cluster_loss:0.154583
Clustering   747: ASW= 0.8165, DB= 0.2523, CH= 47529.0536
Training epoch 748, recon_loss:0.778444, zinb_loss:0.642643, cluster_loss:0.154656
Clustering   748: ASW= 0.8158, DB= 0.2532, CH= 47145.3374
Training epoch 749, recon_loss:0.778834, zinb_loss:0.642681, cluster_loss:0.154616
Clustering   749: ASW= 0.8166, DB= 0.2518, CH= 47480.6571
Training epoch 750, recon_loss:0.778071, zinb_loss:0.642586, cluster_loss:0.154525
Clustering   750: ASW= 0.8162, DB= 0.2519, CH= 47376.8111
Training epoch 751, recon_loss:0.778302, zinb_loss:0.642574, cluster_loss:0.154495
Clustering   751: ASW= 0.8173, DB= 0.2515, CH= 47628.3939
Training epoch 752, recon_loss:0.777697, zinb_loss:0.642467, cluster_loss:0.154564
Clustering   752: ASW= 0.8159, DB= 0.2515, CH= 47291.5846
Training epoch 753, recon_loss:0.777785, zinb_loss:0.642463, cluster_loss:0.154371
Clustering   753: ASW= 0.8174, DB= 0.2506, CH= 47658.2725
Training epoch 754, recon_loss:0.777374, zinb_loss:0.642398, cluster_loss:0.154467
Clustering   754: ASW= 0.8161, DB= 0.2514, CH= 47404.3883
Training epoch 755, recon_loss:0.777439, zinb_loss:0.642371, cluster_loss:0.154306
Clustering   755: ASW= 0.8175, DB= 0.2505, CH= 47725.8554
Training epoch 756, recon_loss:0.777338, zinb_loss:0.642399, cluster_loss:0.154446
Clustering   756: ASW= 0.8160, DB= 0.2512, CH= 47434.3642
Training epoch 757, recon_loss:0.777346, zinb_loss:0.642335, cluster_loss:0.154306
Clustering   757: ASW= 0.8176, DB= 0.2506, CH= 47756.8651
Training epoch 758, recon_loss:0.777390, zinb_loss:0.642441, cluster_loss:0.154453
Clustering   758: ASW= 0.8160, DB= 0.2512, CH= 47490.4779
Training epoch 759, recon_loss:0.777287, zinb_loss:0.642327, cluster_loss:0.154353
Clustering   759: ASW= 0.8176, DB= 0.2505, CH= 47780.7299
Training epoch 760, recon_loss:0.777355, zinb_loss:0.642479, cluster_loss:0.154476
Clustering   760: ASW= 0.8159, DB= 0.2511, CH= 47512.1207
Training epoch 761, recon_loss:0.777063, zinb_loss:0.642295, cluster_loss:0.154399
Clustering   761: ASW= 0.8177, DB= 0.2504, CH= 47804.9705
Training epoch 762, recon_loss:0.777165, zinb_loss:0.642490, cluster_loss:0.154481
Clustering   762: ASW= 0.8159, DB= 0.2509, CH= 47541.0533
Training epoch 763, recon_loss:0.776744, zinb_loss:0.642252, cluster_loss:0.154441
Clustering   763: ASW= 0.8177, DB= 0.2505, CH= 47860.1241
Training epoch 764, recon_loss:0.776937, zinb_loss:0.642473, cluster_loss:0.154499
Clustering   764: ASW= 0.8159, DB= 0.2506, CH= 47546.3944
Training epoch 765, recon_loss:0.776554, zinb_loss:0.642238, cluster_loss:0.154515
Clustering   765: ASW= 0.8177, DB= 0.2508, CH= 47919.2878
Training epoch 766, recon_loss:0.776914, zinb_loss:0.642466, cluster_loss:0.154557
Clustering   766: ASW= 0.8159, DB= 0.2506, CH= 47535.5444
Training epoch 767, recon_loss:0.776619, zinb_loss:0.642280, cluster_loss:0.154659
Clustering   767: ASW= 0.8177, DB= 0.2513, CH= 47962.3543
Training epoch 768, recon_loss:0.777070, zinb_loss:0.642494, cluster_loss:0.154678
Clustering   768: ASW= 0.8160, DB= 0.2504, CH= 47496.6849
Training epoch 769, recon_loss:0.776925, zinb_loss:0.642351, cluster_loss:0.154852
Clustering   769: ASW= 0.8175, DB= 0.2519, CH= 47951.3571
Training epoch 770, recon_loss:0.777375, zinb_loss:0.642543, cluster_loss:0.154771
Clustering   770: ASW= 0.8162, DB= 0.2503, CH= 47494.7784
Training epoch 771, recon_loss:0.777223, zinb_loss:0.642378, cluster_loss:0.154939
Clustering   771: ASW= 0.8175, DB= 0.2517, CH= 47902.5939
Training epoch 772, recon_loss:0.777657, zinb_loss:0.642523, cluster_loss:0.154726
Clustering   772: ASW= 0.8163, DB= 0.2498, CH= 47455.9876
Training epoch 773, recon_loss:0.777357, zinb_loss:0.642314, cluster_loss:0.154855
Clustering   773: ASW= 0.8174, DB= 0.2517, CH= 47929.0949
Training epoch 774, recon_loss:0.777748, zinb_loss:0.642456, cluster_loss:0.154608
Clustering   774: ASW= 0.8167, DB= 0.2500, CH= 47466.7829
Training epoch 775, recon_loss:0.777261, zinb_loss:0.642362, cluster_loss:0.154642
Clustering   775: ASW= 0.8175, DB= 0.2517, CH= 48040.5220
Training epoch 776, recon_loss:0.777675, zinb_loss:0.642417, cluster_loss:0.154412
Clustering   776: ASW= 0.8167, DB= 0.2502, CH= 47520.0338
Training epoch 777, recon_loss:0.777097, zinb_loss:0.642360, cluster_loss:0.154397
Clustering   777: ASW= 0.8177, DB= 0.2512, CH= 48195.8718
Training epoch 778, recon_loss:0.777402, zinb_loss:0.642360, cluster_loss:0.154232
Clustering   778: ASW= 0.8170, DB= 0.2500, CH= 47569.5095
Training epoch 779, recon_loss:0.777089, zinb_loss:0.642446, cluster_loss:0.154225
Clustering   779: ASW= 0.8177, DB= 0.2509, CH= 48318.4659
Training epoch 780, recon_loss:0.777348, zinb_loss:0.642391, cluster_loss:0.154156
Clustering   780: ASW= 0.8171, DB= 0.2500, CH= 47600.6326
Training epoch 781, recon_loss:0.777106, zinb_loss:0.642578, cluster_loss:0.154125
Clustering   781: ASW= 0.8178, DB= 0.2504, CH= 48402.8916
Training epoch 782, recon_loss:0.777366, zinb_loss:0.642482, cluster_loss:0.154117
Clustering   782: ASW= 0.8172, DB= 0.2501, CH= 47661.2916
Training epoch 783, recon_loss:0.777195, zinb_loss:0.642721, cluster_loss:0.154126
Clustering   783: ASW= 0.8177, DB= 0.2500, CH= 48385.4478
Training epoch 784, recon_loss:0.777570, zinb_loss:0.642617, cluster_loss:0.154152
Clustering   784: ASW= 0.8173, DB= 0.2500, CH= 47741.7082
Training epoch 785, recon_loss:0.777457, zinb_loss:0.642872, cluster_loss:0.154243
Clustering   785: ASW= 0.8176, DB= 0.2498, CH= 48351.9413
Training epoch 786, recon_loss:0.777874, zinb_loss:0.642687, cluster_loss:0.154366
Clustering   786: ASW= 0.8172, DB= 0.2504, CH= 47727.0965
Training epoch 787, recon_loss:0.777787, zinb_loss:0.643018, cluster_loss:0.154381
Clustering   787: ASW= 0.8178, DB= 0.2493, CH= 48381.5106
Training epoch 788, recon_loss:0.778060, zinb_loss:0.642752, cluster_loss:0.154558
Clustering   788: ASW= 0.8170, DB= 0.2506, CH= 47712.5417
Training epoch 789, recon_loss:0.777937, zinb_loss:0.643020, cluster_loss:0.154499
Clustering   789: ASW= 0.8178, DB= 0.2491, CH= 48367.9728
Training epoch 790, recon_loss:0.777849, zinb_loss:0.642692, cluster_loss:0.154598
Clustering   790: ASW= 0.8170, DB= 0.2508, CH= 47727.6427
Training epoch 791, recon_loss:0.777770, zinb_loss:0.642872, cluster_loss:0.154431
Clustering   791: ASW= 0.8181, DB= 0.2493, CH= 48373.9331
Training epoch 792, recon_loss:0.777454, zinb_loss:0.642546, cluster_loss:0.154465
Clustering   792: ASW= 0.8172, DB= 0.2506, CH= 47795.4850
Training epoch 793, recon_loss:0.777261, zinb_loss:0.642619, cluster_loss:0.154237
Clustering   793: ASW= 0.8181, DB= 0.2492, CH= 48399.6225
Training epoch 794, recon_loss:0.777027, zinb_loss:0.642347, cluster_loss:0.154358
Clustering   794: ASW= 0.8172, DB= 0.2508, CH= 47901.9421
Training epoch 795, recon_loss:0.776922, zinb_loss:0.642503, cluster_loss:0.154068
Clustering   795: ASW= 0.8186, DB= 0.2489, CH= 48454.2996
Training epoch 796, recon_loss:0.776757, zinb_loss:0.642251, cluster_loss:0.154356
Clustering   796: ASW= 0.8169, DB= 0.2507, CH= 47818.2988
Training epoch 797, recon_loss:0.776722, zinb_loss:0.642344, cluster_loss:0.154045
Clustering   797: ASW= 0.8187, DB= 0.2486, CH= 48441.2521
Training epoch 798, recon_loss:0.776676, zinb_loss:0.642167, cluster_loss:0.154342
Clustering   798: ASW= 0.8170, DB= 0.2504, CH= 47976.0835
Training epoch 799, recon_loss:0.776579, zinb_loss:0.642202, cluster_loss:0.154067
Clustering   799: ASW= 0.8190, DB= 0.2488, CH= 48440.0572
Training epoch 800, recon_loss:0.776459, zinb_loss:0.642036, cluster_loss:0.154354
Clustering   800: ASW= 0.8169, DB= 0.2502, CH= 48030.9443
Training epoch 801, recon_loss:0.776354, zinb_loss:0.642006, cluster_loss:0.154069
Clustering   801: ASW= 0.8190, DB= 0.2491, CH= 48375.9419
Training epoch 802, recon_loss:0.776317, zinb_loss:0.641914, cluster_loss:0.154342
Clustering   802: ASW= 0.8168, DB= 0.2502, CH= 48102.7502
Training epoch 803, recon_loss:0.776293, zinb_loss:0.641914, cluster_loss:0.154051
Clustering   803: ASW= 0.8191, DB= 0.2494, CH= 48320.9716
Training epoch 804, recon_loss:0.776182, zinb_loss:0.641863, cluster_loss:0.154286
Clustering   804: ASW= 0.8166, DB= 0.2503, CH= 48104.1027
Training epoch 805, recon_loss:0.776241, zinb_loss:0.641802, cluster_loss:0.153981
Clustering   805: ASW= 0.8187, DB= 0.2487, CH= 48238.8003
Training epoch 806, recon_loss:0.776287, zinb_loss:0.641803, cluster_loss:0.154259
Clustering   806: ASW= 0.8162, DB= 0.2501, CH= 48069.5493
Training epoch 807, recon_loss:0.776543, zinb_loss:0.641743, cluster_loss:0.154024
Clustering   807: ASW= 0.8186, DB= 0.2488, CH= 48205.3504
Training epoch 808, recon_loss:0.776842, zinb_loss:0.641853, cluster_loss:0.154445
Clustering   808: ASW= 0.8159, DB= 0.2499, CH= 47990.6884
Training epoch 809, recon_loss:0.777597, zinb_loss:0.641726, cluster_loss:0.154176
Clustering   809: ASW= 0.8180, DB= 0.2495, CH= 48075.4070
Training epoch 810, recon_loss:0.778103, zinb_loss:0.641896, cluster_loss:0.154592
Clustering   810: ASW= 0.8158, DB= 0.2492, CH= 47977.0058
Training epoch 811, recon_loss:0.778300, zinb_loss:0.641769, cluster_loss:0.154309
Clustering   811: ASW= 0.8181, DB= 0.2492, CH= 48138.0054
Training epoch 812, recon_loss:0.778090, zinb_loss:0.641837, cluster_loss:0.154685
Clustering   812: ASW= 0.8160, DB= 0.2492, CH= 47929.4855
Training epoch 813, recon_loss:0.778098, zinb_loss:0.641629, cluster_loss:0.154289
Clustering   813: ASW= 0.8177, DB= 0.2498, CH= 48024.8445
Training epoch 814, recon_loss:0.777516, zinb_loss:0.641690, cluster_loss:0.154535
Clustering   814: ASW= 0.8165, DB= 0.2485, CH= 48183.1802
Training epoch 815, recon_loss:0.777463, zinb_loss:0.641537, cluster_loss:0.154098
Clustering   815: ASW= 0.8182, DB= 0.2489, CH= 48281.9729
Training epoch 816, recon_loss:0.776912, zinb_loss:0.641548, cluster_loss:0.154250
Clustering   816: ASW= 0.8172, DB= 0.2483, CH= 48368.4019
Training epoch 817, recon_loss:0.776816, zinb_loss:0.641339, cluster_loss:0.154047
Clustering   817: ASW= 0.8183, DB= 0.2493, CH= 48405.7639
Training epoch 818, recon_loss:0.776597, zinb_loss:0.641512, cluster_loss:0.154149
Clustering   818: ASW= 0.8179, DB= 0.2478, CH= 48606.5199
Training epoch 819, recon_loss:0.776546, zinb_loss:0.641218, cluster_loss:0.154173
Clustering   819: ASW= 0.8182, DB= 0.2495, CH= 48396.1961
Training epoch 820, recon_loss:0.776774, zinb_loss:0.641644, cluster_loss:0.154259
Clustering   820: ASW= 0.8182, DB= 0.2475, CH= 48763.4320
Training epoch 821, recon_loss:0.776839, zinb_loss:0.641285, cluster_loss:0.154583
Clustering   821: ASW= 0.8178, DB= 0.2503, CH= 48176.7142
Training epoch 822, recon_loss:0.777665, zinb_loss:0.642235, cluster_loss:0.154503
Clustering   822: ASW= 0.8187, DB= 0.2472, CH= 48936.6512
Training epoch 823, recon_loss:0.777820, zinb_loss:0.641901, cluster_loss:0.154954
Clustering   823: ASW= 0.8176, DB= 0.2507, CH= 47989.3517
Training epoch 824, recon_loss:0.778772, zinb_loss:0.642889, cluster_loss:0.154606
Clustering   824: ASW= 0.8190, DB= 0.2472, CH= 49019.9698
Training epoch 825, recon_loss:0.778876, zinb_loss:0.642552, cluster_loss:0.155118
Clustering   825: ASW= 0.8175, DB= 0.2504, CH= 47861.7666
Training epoch 826, recon_loss:0.778771, zinb_loss:0.643058, cluster_loss:0.154575
Clustering   826: ASW= 0.8189, DB= 0.2470, CH= 48913.4511
Training epoch 827, recon_loss:0.777959, zinb_loss:0.642427, cluster_loss:0.154883
Clustering   827: ASW= 0.8177, DB= 0.2507, CH= 47915.0480
Training epoch 828, recon_loss:0.777856, zinb_loss:0.642755, cluster_loss:0.154371
Clustering   828: ASW= 0.8188, DB= 0.2477, CH= 48821.8021
Training epoch 829, recon_loss:0.777135, zinb_loss:0.642103, cluster_loss:0.154636
Clustering   829: ASW= 0.8178, DB= 0.2504, CH= 48037.2285
Training epoch 830, recon_loss:0.777458, zinb_loss:0.642535, cluster_loss:0.154187
Clustering   830: ASW= 0.8189, DB= 0.2474, CH= 48886.5609
Training epoch 831, recon_loss:0.776849, zinb_loss:0.641941, cluster_loss:0.154521
Clustering   831: ASW= 0.8181, DB= 0.2506, CH= 48239.6799
Training epoch 832, recon_loss:0.777565, zinb_loss:0.642464, cluster_loss:0.154255
Clustering   832: ASW= 0.8187, DB= 0.2479, CH= 48836.7624
Training epoch 833, recon_loss:0.776898, zinb_loss:0.641913, cluster_loss:0.154519
Clustering   833: ASW= 0.8183, DB= 0.2507, CH= 48351.9679
Training epoch 834, recon_loss:0.777486, zinb_loss:0.642343, cluster_loss:0.154225
Clustering   834: ASW= 0.8189, DB= 0.2474, CH= 48877.4241
Training epoch 835, recon_loss:0.776627, zinb_loss:0.641858, cluster_loss:0.154377
Clustering   835: ASW= 0.8186, DB= 0.2503, CH= 48513.1028
Training epoch 836, recon_loss:0.777136, zinb_loss:0.642107, cluster_loss:0.154150
Clustering   836: ASW= 0.8187, DB= 0.2477, CH= 48818.0219
Training epoch 837, recon_loss:0.776188, zinb_loss:0.641703, cluster_loss:0.154169
Clustering   837: ASW= 0.8188, DB= 0.2500, CH= 48629.4057
Training epoch 838, recon_loss:0.776659, zinb_loss:0.641880, cluster_loss:0.153944
Clustering   838: ASW= 0.8188, DB= 0.2479, CH= 48890.2256
Training epoch 839, recon_loss:0.775945, zinb_loss:0.641649, cluster_loss:0.153953
Clustering   839: ASW= 0.8192, DB= 0.2493, CH= 48838.2534
Training epoch 840, recon_loss:0.776527, zinb_loss:0.641753, cluster_loss:0.153930
Clustering   840: ASW= 0.8186, DB= 0.2479, CH= 48808.6493
Training epoch 841, recon_loss:0.776093, zinb_loss:0.641703, cluster_loss:0.153929
Clustering   841: ASW= 0.8193, DB= 0.2488, CH= 48952.4310
Training epoch 842, recon_loss:0.776862, zinb_loss:0.641785, cluster_loss:0.154051
Clustering   842: ASW= 0.8184, DB= 0.2480, CH= 48691.5546
Training epoch 843, recon_loss:0.776577, zinb_loss:0.641929, cluster_loss:0.153992
Clustering   843: ASW= 0.8194, DB= 0.2483, CH= 49078.8101
Training epoch 844, recon_loss:0.777104, zinb_loss:0.641928, cluster_loss:0.154271
Clustering   844: ASW= 0.8179, DB= 0.2485, CH= 48428.4199
Training epoch 845, recon_loss:0.776686, zinb_loss:0.642224, cluster_loss:0.153975
Clustering   845: ASW= 0.8194, DB= 0.2481, CH= 49182.5850
Training epoch 846, recon_loss:0.776856, zinb_loss:0.642071, cluster_loss:0.154360
Clustering   846: ASW= 0.8174, DB= 0.2488, CH= 48188.5857
Training epoch 847, recon_loss:0.776391, zinb_loss:0.642389, cluster_loss:0.153843
Clustering   847: ASW= 0.8193, DB= 0.2476, CH= 49199.4540
Training epoch 848, recon_loss:0.776544, zinb_loss:0.642187, cluster_loss:0.154341
Clustering   848: ASW= 0.8172, DB= 0.2497, CH= 48098.5152
Training epoch 849, recon_loss:0.776126, zinb_loss:0.642438, cluster_loss:0.153665
Clustering   849: ASW= 0.8194, DB= 0.2473, CH= 49257.7995
Training epoch 850, recon_loss:0.776290, zinb_loss:0.642164, cluster_loss:0.154293
Clustering   850: ASW= 0.8172, DB= 0.2500, CH= 48094.6433
Training epoch 851, recon_loss:0.776050, zinb_loss:0.642405, cluster_loss:0.153577
Clustering   851: ASW= 0.8195, DB= 0.2470, CH= 49271.4837
Training epoch 852, recon_loss:0.776298, zinb_loss:0.642146, cluster_loss:0.154313
Clustering   852: ASW= 0.8173, DB= 0.2500, CH= 48112.5844
Training epoch 853, recon_loss:0.776291, zinb_loss:0.642317, cluster_loss:0.153604
Clustering   853: ASW= 0.8195, DB= 0.2470, CH= 49225.9738
Training epoch 854, recon_loss:0.776489, zinb_loss:0.642110, cluster_loss:0.154367
Clustering   854: ASW= 0.8176, DB= 0.2497, CH= 48214.9162
Training epoch 855, recon_loss:0.776680, zinb_loss:0.642224, cluster_loss:0.153711
Clustering   855: ASW= 0.8194, DB= 0.2468, CH= 49177.6360
Training epoch 856, recon_loss:0.776897, zinb_loss:0.642057, cluster_loss:0.154503
Clustering   856: ASW= 0.8178, DB= 0.2490, CH= 48223.4335
Training epoch 857, recon_loss:0.777168, zinb_loss:0.642093, cluster_loss:0.153857
Clustering   857: ASW= 0.8193, DB= 0.2470, CH= 49111.9809
Training epoch 858, recon_loss:0.777337, zinb_loss:0.641986, cluster_loss:0.154566
Clustering   858: ASW= 0.8183, DB= 0.2485, CH= 48402.0899
Training epoch 859, recon_loss:0.777555, zinb_loss:0.641897, cluster_loss:0.153988
Clustering   859: ASW= 0.8191, DB= 0.2473, CH= 49053.1113
Training epoch 860, recon_loss:0.777549, zinb_loss:0.641824, cluster_loss:0.154606
Clustering   860: ASW= 0.8186, DB= 0.2482, CH= 48452.2812
Training epoch 861, recon_loss:0.777591, zinb_loss:0.641687, cluster_loss:0.154002
Clustering   861: ASW= 0.8190, DB= 0.2476, CH= 49075.9767
Training epoch 862, recon_loss:0.777537, zinb_loss:0.641681, cluster_loss:0.154504
Clustering   862: ASW= 0.8192, DB= 0.2474, CH= 48710.5364
Training epoch 863, recon_loss:0.777382, zinb_loss:0.641459, cluster_loss:0.153977
Clustering   863: ASW= 0.8190, DB= 0.2476, CH= 49083.5528
Training epoch 864, recon_loss:0.777363, zinb_loss:0.641582, cluster_loss:0.154385
Clustering   864: ASW= 0.8195, DB= 0.2470, CH= 48804.1760
Training epoch 865, recon_loss:0.777330, zinb_loss:0.641377, cluster_loss:0.153967
Clustering   865: ASW= 0.8189, DB= 0.2481, CH= 49119.5843
Training epoch 866, recon_loss:0.777327, zinb_loss:0.641616, cluster_loss:0.154273
Clustering   866: ASW= 0.8198, DB= 0.2466, CH= 48910.9381
Training epoch 867, recon_loss:0.777462, zinb_loss:0.641447, cluster_loss:0.154025
Clustering   867: ASW= 0.8189, DB= 0.2484, CH= 49139.2860
Training epoch 868, recon_loss:0.777375, zinb_loss:0.641889, cluster_loss:0.154189
Clustering   868: ASW= 0.8201, DB= 0.2462, CH= 49053.0416
Training epoch 869, recon_loss:0.777481, zinb_loss:0.641662, cluster_loss:0.154128
Clustering   869: ASW= 0.8186, DB= 0.2485, CH= 49001.0625
Training epoch 870, recon_loss:0.777012, zinb_loss:0.642208, cluster_loss:0.154050
Clustering   870: ASW= 0.8204, DB= 0.2454, CH= 49177.6975
Training epoch 871, recon_loss:0.776890, zinb_loss:0.641845, cluster_loss:0.154109
Clustering   871: ASW= 0.8187, DB= 0.2491, CH= 48911.9288
Training epoch 872, recon_loss:0.776434, zinb_loss:0.642285, cluster_loss:0.153890
Clustering   872: ASW= 0.8204, DB= 0.2458, CH= 49266.3066
Training epoch 873, recon_loss:0.776381, zinb_loss:0.641928, cluster_loss:0.153984
Clustering   873: ASW= 0.8187, DB= 0.2490, CH= 48958.6766
Training epoch 874, recon_loss:0.776054, zinb_loss:0.642358, cluster_loss:0.153766
Clustering   874: ASW= 0.8204, DB= 0.2453, CH= 49322.4070
Training epoch 875, recon_loss:0.776039, zinb_loss:0.641927, cluster_loss:0.153966
Clustering   875: ASW= 0.8188, DB= 0.2494, CH= 48940.5879
Training epoch 876, recon_loss:0.775909, zinb_loss:0.642292, cluster_loss:0.153727
Clustering   876: ASW= 0.8203, DB= 0.2457, CH= 49378.6881
Training epoch 877, recon_loss:0.775911, zinb_loss:0.641876, cluster_loss:0.153920
Clustering   877: ASW= 0.8189, DB= 0.2492, CH= 49021.6875
Training epoch 878, recon_loss:0.775879, zinb_loss:0.642224, cluster_loss:0.153697
Clustering   878: ASW= 0.8204, DB= 0.2455, CH= 49424.6005
Training epoch 879, recon_loss:0.775882, zinb_loss:0.641790, cluster_loss:0.153885
Clustering   879: ASW= 0.8192, DB= 0.2491, CH= 49060.6757
Training epoch 880, recon_loss:0.775906, zinb_loss:0.642080, cluster_loss:0.153682
Clustering   880: ASW= 0.8203, DB= 0.2462, CH= 49474.9811
Training epoch 881, recon_loss:0.775888, zinb_loss:0.641684, cluster_loss:0.153857
Clustering   881: ASW= 0.8194, DB= 0.2490, CH= 49091.7465
Training epoch 882, recon_loss:0.776044, zinb_loss:0.641960, cluster_loss:0.153683
Clustering   882: ASW= 0.8202, DB= 0.2460, CH= 49515.3348
Training epoch 883, recon_loss:0.776074, zinb_loss:0.641578, cluster_loss:0.153841
Clustering   883: ASW= 0.8195, DB= 0.2490, CH= 49137.5406
Training epoch 884, recon_loss:0.776212, zinb_loss:0.641790, cluster_loss:0.153684
Clustering   884: ASW= 0.8201, DB= 0.2460, CH= 49532.8735
Training epoch 885, recon_loss:0.776194, zinb_loss:0.641456, cluster_loss:0.153851
Clustering   885: ASW= 0.8194, DB= 0.2487, CH= 49141.0682
Training epoch 886, recon_loss:0.776248, zinb_loss:0.641718, cluster_loss:0.153637
Clustering   886: ASW= 0.8203, DB= 0.2461, CH= 49586.6471
Training epoch 887, recon_loss:0.776062, zinb_loss:0.641394, cluster_loss:0.153757
Clustering   887: ASW= 0.8197, DB= 0.2482, CH= 49189.4583
Training epoch 888, recon_loss:0.776075, zinb_loss:0.641554, cluster_loss:0.153617
Clustering   888: ASW= 0.8201, DB= 0.2461, CH= 49618.5872
Training epoch 889, recon_loss:0.775857, zinb_loss:0.641287, cluster_loss:0.153741
Clustering   889: ASW= 0.8197, DB= 0.2483, CH= 49236.0970
Training epoch 890, recon_loss:0.775937, zinb_loss:0.641456, cluster_loss:0.153599
Clustering   890: ASW= 0.8202, DB= 0.2461, CH= 49685.8725
Training epoch 891, recon_loss:0.775771, zinb_loss:0.641211, cluster_loss:0.153749
Clustering   891: ASW= 0.8198, DB= 0.2477, CH= 49256.8575
Training epoch 892, recon_loss:0.776006, zinb_loss:0.641408, cluster_loss:0.153616
Clustering   892: ASW= 0.8203, DB= 0.2460, CH= 49729.4514
Training epoch 893, recon_loss:0.776000, zinb_loss:0.641221, cluster_loss:0.153811
Clustering   893: ASW= 0.8198, DB= 0.2476, CH= 49261.4920
Training epoch 894, recon_loss:0.776626, zinb_loss:0.641509, cluster_loss:0.153740
Clustering   894: ASW= 0.8205, DB= 0.2456, CH= 49730.7893
Training epoch 895, recon_loss:0.776918, zinb_loss:0.641520, cluster_loss:0.153961
Clustering   895: ASW= 0.8198, DB= 0.2476, CH= 49312.8215
Training epoch 896, recon_loss:0.777924, zinb_loss:0.641974, cluster_loss:0.154006
Clustering   896: ASW= 0.8206, DB= 0.2454, CH= 49635.2764
Training epoch 897, recon_loss:0.778024, zinb_loss:0.642160, cluster_loss:0.154118
Clustering   897: ASW= 0.8199, DB= 0.2477, CH= 49419.9058
Training epoch 898, recon_loss:0.778888, zinb_loss:0.642606, cluster_loss:0.154226
Clustering   898: ASW= 0.8208, DB= 0.2453, CH= 49470.1499
Training epoch 899, recon_loss:0.777643, zinb_loss:0.642440, cluster_loss:0.154074
Clustering   899: ASW= 0.8201, DB= 0.2476, CH= 49560.5846
Training epoch 900, recon_loss:0.778005, zinb_loss:0.642648, cluster_loss:0.154119
Clustering   900: ASW= 0.8209, DB= 0.2450, CH= 49384.7983
Training epoch 901, recon_loss:0.776661, zinb_loss:0.642404, cluster_loss:0.153874
Clustering   901: ASW= 0.8200, DB= 0.2474, CH= 49649.3758
Training epoch 902, recon_loss:0.777056, zinb_loss:0.642510, cluster_loss:0.154074
Clustering   902: ASW= 0.8208, DB= 0.2450, CH= 49246.1665
Training epoch 903, recon_loss:0.776133, zinb_loss:0.642395, cluster_loss:0.153687
Clustering   903: ASW= 0.8202, DB= 0.2473, CH= 49827.8885
Training epoch 904, recon_loss:0.776688, zinb_loss:0.642479, cluster_loss:0.154041
Clustering   904: ASW= 0.8209, DB= 0.2449, CH= 49214.7281
Training epoch 905, recon_loss:0.776016, zinb_loss:0.642453, cluster_loss:0.153575
Clustering   905: ASW= 0.8202, DB= 0.2473, CH= 49962.7548
Training epoch 906, recon_loss:0.776620, zinb_loss:0.642479, cluster_loss:0.154053
Clustering   906: ASW= 0.8208, DB= 0.2448, CH= 49136.2638
Training epoch 907, recon_loss:0.775994, zinb_loss:0.642473, cluster_loss:0.153460
Clustering   907: ASW= 0.8203, DB= 0.2471, CH= 50121.1496
Training epoch 908, recon_loss:0.776681, zinb_loss:0.642443, cluster_loss:0.154127
Clustering   908: ASW= 0.8206, DB= 0.2447, CH= 48995.7732
Training epoch 909, recon_loss:0.776141, zinb_loss:0.642524, cluster_loss:0.153410
Clustering   909: ASW= 0.8204, DB= 0.2471, CH= 50248.5051
Training epoch 910, recon_loss:0.776631, zinb_loss:0.642364, cluster_loss:0.154162
Clustering   910: ASW= 0.8208, DB= 0.2447, CH= 49014.4653
Training epoch 911, recon_loss:0.775948, zinb_loss:0.642436, cluster_loss:0.153302
Clustering   911: ASW= 0.8204, DB= 0.2470, CH= 50340.6364
Training epoch 912, recon_loss:0.776161, zinb_loss:0.642151, cluster_loss:0.154118
Clustering   912: ASW= 0.8210, DB= 0.2447, CH= 49106.5318
Training epoch 913, recon_loss:0.775764, zinb_loss:0.642362, cluster_loss:0.153293
Clustering   913: ASW= 0.8203, DB= 0.2465, CH= 50341.7872
Training epoch 914, recon_loss:0.776203, zinb_loss:0.641954, cluster_loss:0.154253
Clustering   914: ASW= 0.8210, DB= 0.2453, CH= 49148.2019
Training epoch 915, recon_loss:0.776044, zinb_loss:0.642134, cluster_loss:0.153481
Clustering   915: ASW= 0.8202, DB= 0.2461, CH= 50242.1804
Training epoch 916, recon_loss:0.776715, zinb_loss:0.641684, cluster_loss:0.154564
Clustering   916: ASW= 0.8207, DB= 0.2460, CH= 49102.8026
Training epoch 917, recon_loss:0.776289, zinb_loss:0.641765, cluster_loss:0.153764
Clustering   917: ASW= 0.8199, DB= 0.2461, CH= 50081.1733
Training epoch 918, recon_loss:0.776485, zinb_loss:0.641361, cluster_loss:0.154756
Clustering   918: ASW= 0.8206, DB= 0.2460, CH= 49043.0344
Training epoch 919, recon_loss:0.776031, zinb_loss:0.641425, cluster_loss:0.153844
Clustering   919: ASW= 0.8200, DB= 0.2456, CH= 49940.2353
Training epoch 920, recon_loss:0.776033, zinb_loss:0.641055, cluster_loss:0.154786
Clustering   920: ASW= 0.8205, DB= 0.2466, CH= 49015.7086
Training epoch 921, recon_loss:0.776022, zinb_loss:0.641189, cluster_loss:0.153862
Clustering   921: ASW= 0.8202, DB= 0.2454, CH= 49871.7022
Training epoch 922, recon_loss:0.775995, zinb_loss:0.640775, cluster_loss:0.154793
Clustering   922: ASW= 0.8204, DB= 0.2470, CH= 49013.4202
Training epoch 923, recon_loss:0.776050, zinb_loss:0.640999, cluster_loss:0.153827
Clustering   923: ASW= 0.8203, DB= 0.2452, CH= 49775.1593
Training epoch 924, recon_loss:0.775631, zinb_loss:0.640561, cluster_loss:0.154574
Clustering   924: ASW= 0.8206, DB= 0.2469, CH= 49208.0691
Training epoch 925, recon_loss:0.775892, zinb_loss:0.640883, cluster_loss:0.153674
Clustering   925: ASW= 0.8206, DB= 0.2445, CH= 49792.9730
Training epoch 926, recon_loss:0.775377, zinb_loss:0.640449, cluster_loss:0.154408
Clustering   926: ASW= 0.8206, DB= 0.2471, CH= 49378.4618
Training epoch 927, recon_loss:0.775965, zinb_loss:0.640841, cluster_loss:0.153659
Clustering   927: ASW= 0.8206, DB= 0.2441, CH= 49754.3804
Training epoch 928, recon_loss:0.775498, zinb_loss:0.640606, cluster_loss:0.154298
Clustering   928: ASW= 0.8210, DB= 0.2469, CH= 49661.6168
Training epoch 929, recon_loss:0.776103, zinb_loss:0.640991, cluster_loss:0.153740
Clustering   929: ASW= 0.8206, DB= 0.2443, CH= 49637.9140
Training epoch 930, recon_loss:0.775426, zinb_loss:0.640912, cluster_loss:0.154189
Clustering   930: ASW= 0.8212, DB= 0.2463, CH= 49907.6346
Training epoch 931, recon_loss:0.775953, zinb_loss:0.641246, cluster_loss:0.153845
Clustering   931: ASW= 0.8204, DB= 0.2444, CH= 49528.2611
Training epoch 932, recon_loss:0.775294, zinb_loss:0.641312, cluster_loss:0.154089
Clustering   932: ASW= 0.8214, DB= 0.2455, CH= 50078.0948
Training epoch 933, recon_loss:0.775774, zinb_loss:0.641584, cluster_loss:0.153893
Clustering   933: ASW= 0.8204, DB= 0.2447, CH= 49575.5879
Training epoch 934, recon_loss:0.775276, zinb_loss:0.641691, cluster_loss:0.154007
Clustering   934: ASW= 0.8217, DB= 0.2447, CH= 50171.4320
Training epoch 935, recon_loss:0.775643, zinb_loss:0.641841, cluster_loss:0.153967
Clustering   935: ASW= 0.8203, DB= 0.2449, CH= 49606.7985
Training epoch 936, recon_loss:0.775418, zinb_loss:0.641946, cluster_loss:0.153999
Clustering   936: ASW= 0.8219, DB= 0.2448, CH= 50261.8751
Training epoch 937, recon_loss:0.775770, zinb_loss:0.641974, cluster_loss:0.154115
Clustering   937: ASW= 0.8203, DB= 0.2453, CH= 49602.3933
Training epoch 938, recon_loss:0.775727, zinb_loss:0.642072, cluster_loss:0.154040
Clustering   938: ASW= 0.8219, DB= 0.2440, CH= 50241.8509
Training epoch 939, recon_loss:0.776015, zinb_loss:0.641972, cluster_loss:0.154267
Clustering   939: ASW= 0.8202, DB= 0.2454, CH= 49552.2925
Training epoch 940, recon_loss:0.776008, zinb_loss:0.642108, cluster_loss:0.154051
Clustering   940: ASW= 0.8220, DB= 0.2439, CH= 50264.3502
Training epoch 941, recon_loss:0.776126, zinb_loss:0.641864, cluster_loss:0.154313
Clustering   941: ASW= 0.8202, DB= 0.2459, CH= 49507.5603
Training epoch 942, recon_loss:0.776039, zinb_loss:0.642041, cluster_loss:0.153949
Clustering   942: ASW= 0.8221, DB= 0.2437, CH= 50320.6255
Training epoch 943, recon_loss:0.775981, zinb_loss:0.641658, cluster_loss:0.154253
Clustering   943: ASW= 0.8203, DB= 0.2459, CH= 49477.8211
Training epoch 944, recon_loss:0.775839, zinb_loss:0.641838, cluster_loss:0.153782
Clustering   944: ASW= 0.8222, DB= 0.2435, CH= 50390.3066
Training epoch 945, recon_loss:0.775697, zinb_loss:0.641373, cluster_loss:0.154116
Clustering   945: ASW= 0.8204, DB= 0.2462, CH= 49517.5703
Training epoch 946, recon_loss:0.775706, zinb_loss:0.641617, cluster_loss:0.153643
Clustering   946: ASW= 0.8223, DB= 0.2434, CH= 50452.5558
Training epoch 947, recon_loss:0.775548, zinb_loss:0.641124, cluster_loss:0.153979
Clustering   947: ASW= 0.8206, DB= 0.2460, CH= 49581.5547
Training epoch 948, recon_loss:0.775715, zinb_loss:0.641411, cluster_loss:0.153572
Clustering   948: ASW= 0.8223, DB= 0.2436, CH= 50440.3620
Training epoch 949, recon_loss:0.775554, zinb_loss:0.640954, cluster_loss:0.153866
Clustering   949: ASW= 0.8208, DB= 0.2456, CH= 49667.0371
Training epoch 950, recon_loss:0.775860, zinb_loss:0.641265, cluster_loss:0.153520
Clustering   950: ASW= 0.8222, DB= 0.2437, CH= 50460.8942
Training epoch 951, recon_loss:0.775514, zinb_loss:0.640827, cluster_loss:0.153793
Clustering   951: ASW= 0.8209, DB= 0.2460, CH= 49678.3158
Training epoch 952, recon_loss:0.776003, zinb_loss:0.641251, cluster_loss:0.153448
Clustering   952: ASW= 0.8223, DB= 0.2439, CH= 50473.1184
Training epoch 953, recon_loss:0.775709, zinb_loss:0.640835, cluster_loss:0.153730
Clustering   953: ASW= 0.8212, DB= 0.2455, CH= 49782.0559
Training epoch 954, recon_loss:0.776081, zinb_loss:0.641191, cluster_loss:0.153390
Clustering   954: ASW= 0.8223, DB= 0.2437, CH= 50508.5557
Training epoch 955, recon_loss:0.775705, zinb_loss:0.640885, cluster_loss:0.153591
Clustering   955: ASW= 0.8216, DB= 0.2455, CH= 49942.8353
Training epoch 956, recon_loss:0.775884, zinb_loss:0.641126, cluster_loss:0.153374
Clustering   956: ASW= 0.8220, DB= 0.2438, CH= 50456.2604
Training epoch 957, recon_loss:0.775367, zinb_loss:0.640870, cluster_loss:0.153429
Clustering   957: ASW= 0.8218, DB= 0.2453, CH= 50021.5257
Training epoch 958, recon_loss:0.775568, zinb_loss:0.641136, cluster_loss:0.153301
Clustering   958: ASW= 0.8220, DB= 0.2435, CH= 50543.7448
Training epoch 959, recon_loss:0.775313, zinb_loss:0.641017, cluster_loss:0.153332
Clustering   959: ASW= 0.8220, DB= 0.2445, CH= 50103.0253
Training epoch 960, recon_loss:0.775505, zinb_loss:0.641212, cluster_loss:0.153419
Clustering   960: ASW= 0.8216, DB= 0.2441, CH= 50358.6860
Training epoch 961, recon_loss:0.775427, zinb_loss:0.641155, cluster_loss:0.153333
Clustering   961: ASW= 0.8218, DB= 0.2440, CH= 50036.3343
Training epoch 962, recon_loss:0.775604, zinb_loss:0.641232, cluster_loss:0.153506
Clustering   962: ASW= 0.8214, DB= 0.2443, CH= 50348.6532
Training epoch 963, recon_loss:0.776001, zinb_loss:0.641393, cluster_loss:0.153394
Clustering   963: ASW= 0.8218, DB= 0.2436, CH= 50133.4659
Training epoch 964, recon_loss:0.775528, zinb_loss:0.641249, cluster_loss:0.153777
Clustering   964: ASW= 0.8203, DB= 0.2454, CH= 49707.4270
Training epoch 965, recon_loss:0.775644, zinb_loss:0.641277, cluster_loss:0.153624
Clustering   965: ASW= 0.8206, DB= 0.2450, CH= 49505.6651
Training epoch 966, recon_loss:0.775920, zinb_loss:0.641359, cluster_loss:0.154351
Clustering   966: ASW= 0.8197, DB= 0.2457, CH= 49611.9980
Training epoch 967, recon_loss:0.775865, zinb_loss:0.641455, cluster_loss:0.153637
Clustering   967: ASW= 0.8209, DB= 0.2441, CH= 49806.9834
Training epoch 968, recon_loss:0.775242, zinb_loss:0.641323, cluster_loss:0.154025
Clustering   968: ASW= 0.8200, DB= 0.2452, CH= 49682.6118
Training epoch 969, recon_loss:0.775132, zinb_loss:0.641191, cluster_loss:0.153353
Clustering   969: ASW= 0.8210, DB= 0.2440, CH= 49892.1741
Training epoch 970, recon_loss:0.774995, zinb_loss:0.641213, cluster_loss:0.153712
Clustering   970: ASW= 0.8202, DB= 0.2448, CH= 49904.3556
Training epoch 971, recon_loss:0.774953, zinb_loss:0.640983, cluster_loss:0.153206
Clustering   971: ASW= 0.8211, DB= 0.2442, CH= 49945.0347
Training epoch 972, recon_loss:0.775123, zinb_loss:0.641131, cluster_loss:0.153545
Clustering   972: ASW= 0.8204, DB= 0.2439, CH= 50083.6425
Training epoch 973, recon_loss:0.775388, zinb_loss:0.640825, cluster_loss:0.153212
Clustering   973: ASW= 0.8211, DB= 0.2446, CH= 50003.1611
Training epoch 974, recon_loss:0.775489, zinb_loss:0.641091, cluster_loss:0.153475
Clustering   974: ASW= 0.8207, DB= 0.2439, CH= 50221.4849
Training epoch 975, recon_loss:0.775899, zinb_loss:0.640686, cluster_loss:0.153341
Clustering   975: ASW= 0.8210, DB= 0.2448, CH= 49975.2323
Training epoch 976, recon_loss:0.775533, zinb_loss:0.641061, cluster_loss:0.153438
Clustering   976: ASW= 0.8210, DB= 0.2435, CH= 50348.5970
Training epoch 977, recon_loss:0.775812, zinb_loss:0.640572, cluster_loss:0.153414
Clustering   977: ASW= 0.8210, DB= 0.2450, CH= 50029.6433
Training epoch 978, recon_loss:0.775255, zinb_loss:0.641029, cluster_loss:0.153381
Clustering   978: ASW= 0.8215, DB= 0.2435, CH= 50457.8365
Training epoch 979, recon_loss:0.775421, zinb_loss:0.640511, cluster_loss:0.153397
Clustering   979: ASW= 0.8214, DB= 0.2450, CH= 50177.2513
Training epoch 980, recon_loss:0.774964, zinb_loss:0.641081, cluster_loss:0.153307
Clustering   980: ASW= 0.8220, DB= 0.2429, CH= 50649.4802
Training epoch 981, recon_loss:0.775087, zinb_loss:0.640552, cluster_loss:0.153419
Clustering   981: ASW= 0.8215, DB= 0.2454, CH= 50247.2643
Training epoch 982, recon_loss:0.774816, zinb_loss:0.641254, cluster_loss:0.153259
Clustering   982: ASW= 0.8225, DB= 0.2425, CH= 50773.6733
Training epoch 983, recon_loss:0.774959, zinb_loss:0.640777, cluster_loss:0.153436
Clustering   983: ASW= 0.8216, DB= 0.2455, CH= 50279.7720
Training epoch 984, recon_loss:0.774858, zinb_loss:0.641565, cluster_loss:0.153215
Clustering   984: ASW= 0.8228, DB= 0.2420, CH= 50878.0192
Training epoch 985, recon_loss:0.774992, zinb_loss:0.641189, cluster_loss:0.153491
Clustering   985: ASW= 0.8216, DB= 0.2453, CH= 50272.7620
Training epoch 986, recon_loss:0.775061, zinb_loss:0.641959, cluster_loss:0.153230
Clustering   986: ASW= 0.8231, DB= 0.2419, CH= 50939.6393
Training epoch 987, recon_loss:0.774991, zinb_loss:0.641593, cluster_loss:0.153502
Clustering   987: ASW= 0.8216, DB= 0.2457, CH= 50311.2786
Training epoch 988, recon_loss:0.774966, zinb_loss:0.642084, cluster_loss:0.153216
Clustering   988: ASW= 0.8232, DB= 0.2416, CH= 50958.2240
Training epoch 989, recon_loss:0.774881, zinb_loss:0.641655, cluster_loss:0.153486
Clustering   989: ASW= 0.8214, DB= 0.2454, CH= 50347.6130
Training epoch 990, recon_loss:0.774816, zinb_loss:0.641966, cluster_loss:0.153200
Clustering   990: ASW= 0.8233, DB= 0.2416, CH= 50920.7321
Training epoch 991, recon_loss:0.774580, zinb_loss:0.641527, cluster_loss:0.153281
Clustering   991: ASW= 0.8217, DB= 0.2451, CH= 50522.3623
Training epoch 992, recon_loss:0.774458, zinb_loss:0.641629, cluster_loss:0.153183
Clustering   992: ASW= 0.8231, DB= 0.2417, CH= 50901.0535
Training epoch 993, recon_loss:0.774289, zinb_loss:0.641304, cluster_loss:0.153184
Clustering   993: ASW= 0.8218, DB= 0.2446, CH= 50638.3711
Training epoch 994, recon_loss:0.774186, zinb_loss:0.641344, cluster_loss:0.153230
Clustering   994: ASW= 0.8231, DB= 0.2416, CH= 50873.8986
Training epoch 995, recon_loss:0.774071, zinb_loss:0.641112, cluster_loss:0.153066
Clustering   995: ASW= 0.8220, DB= 0.2438, CH= 50775.4149
Training epoch 996, recon_loss:0.773959, zinb_loss:0.641106, cluster_loss:0.153265
Clustering   996: ASW= 0.8232, DB= 0.2424, CH= 50900.3564
Training epoch 997, recon_loss:0.774089, zinb_loss:0.641002, cluster_loss:0.153042
Clustering   997: ASW= 0.8221, DB= 0.2431, CH= 50854.4477
Training epoch 998, recon_loss:0.774073, zinb_loss:0.640900, cluster_loss:0.153453
Clustering   998: ASW= 0.8231, DB= 0.2430, CH= 50836.5761
Training epoch 999, recon_loss:0.774590, zinb_loss:0.640967, cluster_loss:0.153166
Clustering   999: ASW= 0.8222, DB= 0.2429, CH= 50888.1350
Training epoch 1000, recon_loss:0.774464, zinb_loss:0.640694, cluster_loss:0.153752
Clustering   1000: ASW= 0.8229, DB= 0.2437, CH= 50672.6236
Training epoch 1001, recon_loss:0.775363, zinb_loss:0.640935, cluster_loss:0.153360
Clustering   1001: ASW= 0.8221, DB= 0.2433, CH= 50857.1890
Training epoch 1002, recon_loss:0.774808, zinb_loss:0.640473, cluster_loss:0.153986
Clustering   1002: ASW= 0.8227, DB= 0.2444, CH= 50474.1399
Training epoch 1003, recon_loss:0.775801, zinb_loss:0.640854, cluster_loss:0.153354
Clustering   1003: ASW= 0.8223, DB= 0.2428, CH= 50842.6361
Training epoch 1004, recon_loss:0.774872, zinb_loss:0.640223, cluster_loss:0.154007
Clustering   1004: ASW= 0.8225, DB= 0.2448, CH= 50373.5489
Training epoch 1005, recon_loss:0.775838, zinb_loss:0.640723, cluster_loss:0.153199
Clustering   1005: ASW= 0.8225, DB= 0.2425, CH= 50910.2397
Training epoch 1006, recon_loss:0.774710, zinb_loss:0.640018, cluster_loss:0.153908
Clustering   1006: ASW= 0.8223, DB= 0.2450, CH= 50386.1029
Training epoch 1007, recon_loss:0.775670, zinb_loss:0.640588, cluster_loss:0.153072
Clustering   1007: ASW= 0.8228, DB= 0.2423, CH= 50950.2659
Training epoch 1008, recon_loss:0.774410, zinb_loss:0.639877, cluster_loss:0.153721
Clustering   1008: ASW= 0.8224, DB= 0.2454, CH= 50523.0174
Training epoch 1009, recon_loss:0.775360, zinb_loss:0.640477, cluster_loss:0.152959
Clustering   1009: ASW= 0.8232, DB= 0.2420, CH= 51011.8464
Training epoch 1010, recon_loss:0.774118, zinb_loss:0.639831, cluster_loss:0.153528
Clustering   1010: ASW= 0.8224, DB= 0.2451, CH= 50669.9318
Training epoch 1011, recon_loss:0.775077, zinb_loss:0.640449, cluster_loss:0.152924
Clustering   1011: ASW= 0.8235, DB= 0.2414, CH= 51081.0035
Training epoch 1012, recon_loss:0.774010, zinb_loss:0.639937, cluster_loss:0.153440
Clustering   1012: ASW= 0.8224, DB= 0.2452, CH= 50823.8857
Training epoch 1013, recon_loss:0.775031, zinb_loss:0.640563, cluster_loss:0.153040
Clustering   1013: ASW= 0.8238, DB= 0.2414, CH= 51139.0150
Training epoch 1014, recon_loss:0.774251, zinb_loss:0.640280, cluster_loss:0.153439
Clustering   1014: ASW= 0.8225, DB= 0.2444, CH= 50925.8907
Training epoch 1015, recon_loss:0.775307, zinb_loss:0.640821, cluster_loss:0.153284
Clustering   1015: ASW= 0.8238, DB= 0.2414, CH= 51105.4937
Training epoch 1016, recon_loss:0.774991, zinb_loss:0.640868, cluster_loss:0.153498
Clustering   1016: ASW= 0.8227, DB= 0.2437, CH= 51133.6367
Training epoch 1017, recon_loss:0.775943, zinb_loss:0.641317, cluster_loss:0.153719
Clustering   1017: ASW= 0.8238, DB= 0.2419, CH= 51000.1370
Training epoch 1018, recon_loss:0.775815, zinb_loss:0.641657, cluster_loss:0.153689
Clustering   1018: ASW= 0.8227, DB= 0.2434, CH= 51217.3950
Training epoch 1019, recon_loss:0.776512, zinb_loss:0.641917, cluster_loss:0.154245
Clustering   1019: ASW= 0.8235, DB= 0.2427, CH= 50728.5421
Training epoch 1020, recon_loss:0.776355, zinb_loss:0.642495, cluster_loss:0.153775
Clustering   1020: ASW= 0.8229, DB= 0.2428, CH= 51365.9575
Training epoch 1021, recon_loss:0.776758, zinb_loss:0.642362, cluster_loss:0.154420
Clustering   1021: ASW= 0.8233, DB= 0.2429, CH= 50529.7505
Training epoch 1022, recon_loss:0.776063, zinb_loss:0.642713, cluster_loss:0.153677
Clustering   1022: ASW= 0.8229, DB= 0.2427, CH= 51345.4629
Training epoch 1023, recon_loss:0.776250, zinb_loss:0.642265, cluster_loss:0.154222
Clustering   1023: ASW= 0.8232, DB= 0.2432, CH= 50448.4959
Training epoch 1024, recon_loss:0.775208, zinb_loss:0.642434, cluster_loss:0.153395
Clustering   1024: ASW= 0.8230, DB= 0.2426, CH= 51360.8792
Training epoch 1025, recon_loss:0.775333, zinb_loss:0.641856, cluster_loss:0.153865
Clustering   1025: ASW= 0.8232, DB= 0.2433, CH= 50535.0558
Training epoch 1026, recon_loss:0.774392, zinb_loss:0.642016, cluster_loss:0.153109
Clustering   1026: ASW= 0.8231, DB= 0.2425, CH= 51379.5732
Training epoch 1027, recon_loss:0.774608, zinb_loss:0.641495, cluster_loss:0.153566
Clustering   1027: ASW= 0.8232, DB= 0.2432, CH= 50645.3112
Training epoch 1028, recon_loss:0.773931, zinb_loss:0.641739, cluster_loss:0.152941
Clustering   1028: ASW= 0.8231, DB= 0.2424, CH= 51406.4381
Training epoch 1029, recon_loss:0.774152, zinb_loss:0.641274, cluster_loss:0.153398
Clustering   1029: ASW= 0.8231, DB= 0.2435, CH= 50729.9048
Training epoch 1030, recon_loss:0.773753, zinb_loss:0.641649, cluster_loss:0.152848
Clustering   1030: ASW= 0.8234, DB= 0.2420, CH= 51450.8016
Training epoch 1031, recon_loss:0.774161, zinb_loss:0.641222, cluster_loss:0.153375
Clustering   1031: ASW= 0.8226, DB= 0.2429, CH= 50657.3865
Training epoch 1032, recon_loss:0.773908, zinb_loss:0.641620, cluster_loss:0.152852
Clustering   1032: ASW= 0.8233, DB= 0.2422, CH= 51445.9065
Training epoch 1033, recon_loss:0.774363, zinb_loss:0.641182, cluster_loss:0.153409
Clustering   1033: ASW= 0.8226, DB= 0.2441, CH= 50726.6793
Training epoch 1034, recon_loss:0.774273, zinb_loss:0.641693, cluster_loss:0.152939
Clustering   1034: ASW= 0.8237, DB= 0.2420, CH= 51445.7000
Training epoch 1035, recon_loss:0.774909, zinb_loss:0.641179, cluster_loss:0.153614
Clustering   1035: ASW= 0.8221, DB= 0.2441, CH= 50640.6332
Training epoch 1036, recon_loss:0.774827, zinb_loss:0.641639, cluster_loss:0.153193
Clustering   1036: ASW= 0.8237, DB= 0.2410, CH= 51328.6195
Training epoch 1037, recon_loss:0.775599, zinb_loss:0.641076, cluster_loss:0.153754
Clustering   1037: ASW= 0.8220, DB= 0.2447, CH= 50645.0992
Training epoch 1038, recon_loss:0.775457, zinb_loss:0.641503, cluster_loss:0.153392
Clustering   1038: ASW= 0.8238, DB= 0.2412, CH= 51317.1885
Training epoch 1039, recon_loss:0.776150, zinb_loss:0.640891, cluster_loss:0.153924
Clustering   1039: ASW= 0.8215, DB= 0.2444, CH= 50439.6038
Training epoch 1040, recon_loss:0.775409, zinb_loss:0.641043, cluster_loss:0.153610
Clustering   1040: ASW= 0.8236, DB= 0.2414, CH= 51142.4569
Training epoch 1041, recon_loss:0.776085, zinb_loss:0.640597, cluster_loss:0.153765
Clustering   1041: ASW= 0.8218, DB= 0.2442, CH= 50534.2116
Training epoch 1042, recon_loss:0.775227, zinb_loss:0.640506, cluster_loss:0.153550
Clustering   1042: ASW= 0.8234, DB= 0.2420, CH= 50946.9501
Training epoch 1043, recon_loss:0.775270, zinb_loss:0.640090, cluster_loss:0.153450
Clustering   1043: ASW= 0.8220, DB= 0.2449, CH= 50615.6787
Training epoch 1044, recon_loss:0.775073, zinb_loss:0.640136, cluster_loss:0.153444
Clustering   1044: ASW= 0.8236, DB= 0.2422, CH= 51139.0971
Training epoch 1045, recon_loss:0.775178, zinb_loss:0.640066, cluster_loss:0.153327
Clustering   1045: ASW= 0.8226, DB= 0.2437, CH= 50918.9657
Training epoch 1046, recon_loss:0.775118, zinb_loss:0.639966, cluster_loss:0.153562
Clustering   1046: ASW= 0.8234, DB= 0.2426, CH= 50914.6717
Training epoch 1047, recon_loss:0.775040, zinb_loss:0.640179, cluster_loss:0.153307
Clustering   1047: ASW= 0.8231, DB= 0.2437, CH= 50909.4443
Training epoch 1048, recon_loss:0.774894, zinb_loss:0.640003, cluster_loss:0.153475
Clustering   1048: ASW= 0.8235, DB= 0.2427, CH= 50978.8432
Training epoch 1049, recon_loss:0.775082, zinb_loss:0.640514, cluster_loss:0.153313
Clustering   1049: ASW= 0.8236, DB= 0.2428, CH= 50998.7662
Training epoch 1050, recon_loss:0.774542, zinb_loss:0.640175, cluster_loss:0.153407
Clustering   1050: ASW= 0.8226, DB= 0.2441, CH= 50527.4209
Training epoch 1051, recon_loss:0.774207, zinb_loss:0.640311, cluster_loss:0.153117
Clustering   1051: ASW= 0.8230, DB= 0.2427, CH= 50615.8578
Training epoch 1052, recon_loss:0.774763, zinb_loss:0.640424, cluster_loss:0.153562
Clustering   1052: ASW= 0.8227, DB= 0.2430, CH= 50726.0921
Training epoch 1053, recon_loss:0.774962, zinb_loss:0.640882, cluster_loss:0.153375
Clustering   1053: ASW= 0.8237, DB= 0.2428, CH= 50846.7273
Training epoch 1054, recon_loss:0.774569, zinb_loss:0.640683, cluster_loss:0.153771
Clustering   1054: ASW= 0.8223, DB= 0.2427, CH= 50592.4757
Training epoch 1055, recon_loss:0.774593, zinb_loss:0.640904, cluster_loss:0.153288
Clustering   1055: ASW= 0.8244, DB= 0.2420, CH= 51085.2438
Training epoch 1056, recon_loss:0.774126, zinb_loss:0.640694, cluster_loss:0.153757
Clustering   1056: ASW= 0.8219, DB= 0.2428, CH= 50617.1630
Training epoch 1057, recon_loss:0.774238, zinb_loss:0.640874, cluster_loss:0.153069
Clustering   1057: ASW= 0.8246, DB= 0.2416, CH= 51191.7610
Training epoch 1058, recon_loss:0.773749, zinb_loss:0.640563, cluster_loss:0.153385
Clustering   1058: ASW= 0.8220, DB= 0.2427, CH= 50809.5882
Training epoch 1059, recon_loss:0.773707, zinb_loss:0.640579, cluster_loss:0.152936
Clustering   1059: ASW= 0.8247, DB= 0.2408, CH= 51349.3776
Training epoch 1060, recon_loss:0.773702, zinb_loss:0.640581, cluster_loss:0.153265
Clustering   1060: ASW= 0.8221, DB= 0.2424, CH= 51002.1613
Training epoch 1061, recon_loss:0.773891, zinb_loss:0.640587, cluster_loss:0.152985
Clustering   1061: ASW= 0.8246, DB= 0.2414, CH= 51511.6095
Training epoch 1062, recon_loss:0.774019, zinb_loss:0.640683, cluster_loss:0.153377
Clustering   1062: ASW= 0.8220, DB= 0.2417, CH= 50940.9325
Training epoch 1063, recon_loss:0.774221, zinb_loss:0.640612, cluster_loss:0.153107
Clustering   1063: ASW= 0.8240, DB= 0.2429, CH= 51431.4129
Training epoch 1064, recon_loss:0.774509, zinb_loss:0.640865, cluster_loss:0.153341
Clustering   1064: ASW= 0.8223, DB= 0.2406, CH= 51057.2812
Training epoch 1065, recon_loss:0.774559, zinb_loss:0.640687, cluster_loss:0.153104
Clustering   1065: ASW= 0.8239, DB= 0.2429, CH= 51534.6099
Training epoch 1066, recon_loss:0.774634, zinb_loss:0.640854, cluster_loss:0.153398
Clustering   1066: ASW= 0.8225, DB= 0.2410, CH= 50923.8774
Training epoch 1067, recon_loss:0.774593, zinb_loss:0.640601, cluster_loss:0.153095
Clustering   1067: ASW= 0.8235, DB= 0.2435, CH= 51388.3023
Training epoch 1068, recon_loss:0.774729, zinb_loss:0.640764, cluster_loss:0.153330
Clustering   1068: ASW= 0.8230, DB= 0.2399, CH= 51054.2692
Training epoch 1069, recon_loss:0.774364, zinb_loss:0.640619, cluster_loss:0.152938
Clustering   1069: ASW= 0.8239, DB= 0.2430, CH= 51659.7362
Training epoch 1070, recon_loss:0.774401, zinb_loss:0.640605, cluster_loss:0.153222
Clustering   1070: ASW= 0.8232, DB= 0.2402, CH= 51050.6337
Training epoch 1071, recon_loss:0.774138, zinb_loss:0.640660, cluster_loss:0.152782
Clustering   1071: ASW= 0.8243, DB= 0.2429, CH= 51846.1960
Training epoch 1072, recon_loss:0.774420, zinb_loss:0.640596, cluster_loss:0.153217
Clustering   1072: ASW= 0.8234, DB= 0.2400, CH= 51082.2987
Training epoch 1073, recon_loss:0.774229, zinb_loss:0.640792, cluster_loss:0.152731
Clustering   1073: ASW= 0.8245, DB= 0.2424, CH= 51937.3765
Training epoch 1074, recon_loss:0.774712, zinb_loss:0.640671, cluster_loss:0.153346
Clustering   1074: ASW= 0.8235, DB= 0.2402, CH= 51088.7055
Training epoch 1075, recon_loss:0.774490, zinb_loss:0.640942, cluster_loss:0.152768
Clustering   1075: ASW= 0.8243, DB= 0.2417, CH= 51883.9524
Training epoch 1076, recon_loss:0.774980, zinb_loss:0.640764, cluster_loss:0.153382
Clustering   1076: ASW= 0.8239, DB= 0.2400, CH= 51142.7324
Training epoch 1077, recon_loss:0.774598, zinb_loss:0.640989, cluster_loss:0.152789
Clustering   1077: ASW= 0.8243, DB= 0.2418, CH= 51869.1058
Training epoch 1078, recon_loss:0.774833, zinb_loss:0.640711, cluster_loss:0.153492
Clustering   1078: ASW= 0.8238, DB= 0.2404, CH= 51108.9723
Training epoch 1079, recon_loss:0.774583, zinb_loss:0.640901, cluster_loss:0.152872
Clustering   1079: ASW= 0.8239, DB= 0.2421, CH= 51719.8050
Training epoch 1080, recon_loss:0.774981, zinb_loss:0.640761, cluster_loss:0.153492
Clustering   1080: ASW= 0.8243, DB= 0.2398, CH= 51259.6815
Training epoch 1081, recon_loss:0.774704, zinb_loss:0.640871, cluster_loss:0.152948
Clustering   1081: ASW= 0.8236, DB= 0.2422, CH= 51605.4614
Training epoch 1082, recon_loss:0.774981, zinb_loss:0.640852, cluster_loss:0.153420
Clustering   1082: ASW= 0.8250, DB= 0.2394, CH= 51509.9498
Training epoch 1083, recon_loss:0.774794, zinb_loss:0.640819, cluster_loss:0.153038
Clustering   1083: ASW= 0.8233, DB= 0.2424, CH= 51507.7788
Training epoch 1084, recon_loss:0.775162, zinb_loss:0.640915, cluster_loss:0.153370
Clustering   1084: ASW= 0.8253, DB= 0.2391, CH= 51659.6416
Training epoch 1085, recon_loss:0.775069, zinb_loss:0.640713, cluster_loss:0.153158
Clustering   1085: ASW= 0.8231, DB= 0.2425, CH= 51503.0449
Training epoch 1086, recon_loss:0.775363, zinb_loss:0.640967, cluster_loss:0.153366
Clustering   1086: ASW= 0.8256, DB= 0.2386, CH= 51760.6702
Training epoch 1087, recon_loss:0.775365, zinb_loss:0.640588, cluster_loss:0.153284
Clustering   1087: ASW= 0.8228, DB= 0.2431, CH= 51419.6931
Training epoch 1088, recon_loss:0.775667, zinb_loss:0.640988, cluster_loss:0.153335
Clustering   1088: ASW= 0.8257, DB= 0.2390, CH= 51803.2571
Training epoch 1089, recon_loss:0.775316, zinb_loss:0.640372, cluster_loss:0.153329
Clustering   1089: ASW= 0.8227, DB= 0.2437, CH= 51351.8570
Training epoch 1090, recon_loss:0.775607, zinb_loss:0.640937, cluster_loss:0.153221
Clustering   1090: ASW= 0.8259, DB= 0.2383, CH= 51901.4069
Training epoch 1091, recon_loss:0.774640, zinb_loss:0.640090, cluster_loss:0.153346
Clustering   1091: ASW= 0.8224, DB= 0.2442, CH= 51165.4304
Training epoch 1092, recon_loss:0.775006, zinb_loss:0.640767, cluster_loss:0.153085
Clustering   1092: ASW= 0.8257, DB= 0.2388, CH= 51866.0391
Training epoch 1093, recon_loss:0.774432, zinb_loss:0.639868, cluster_loss:0.153382
Clustering   1093: ASW= 0.8223, DB= 0.2446, CH= 51167.3338
Training epoch 1094, recon_loss:0.774701, zinb_loss:0.640543, cluster_loss:0.152940
Clustering   1094: ASW= 0.8260, DB= 0.2385, CH= 52017.7733
Training epoch 1095, recon_loss:0.773701, zinb_loss:0.639661, cluster_loss:0.153250
Clustering   1095: ASW= 0.8223, DB= 0.2442, CH= 51244.8684
Training epoch 1096, recon_loss:0.774248, zinb_loss:0.640361, cluster_loss:0.152779
Clustering   1096: ASW= 0.8262, DB= 0.2385, CH= 52104.3727
Training epoch 1097, recon_loss:0.773344, zinb_loss:0.639556, cluster_loss:0.153161
Clustering   1097: ASW= 0.8227, DB= 0.2436, CH= 51361.3292
Training epoch 1098, recon_loss:0.774044, zinb_loss:0.640206, cluster_loss:0.152743
Clustering   1098: ASW= 0.8262, DB= 0.2386, CH= 52137.9762
Training epoch 1099, recon_loss:0.773376, zinb_loss:0.639533, cluster_loss:0.153263
Clustering   1099: ASW= 0.8227, DB= 0.2437, CH= 51428.4399
Training epoch 1100, recon_loss:0.774526, zinb_loss:0.640167, cluster_loss:0.152879
Clustering   1100: ASW= 0.8261, DB= 0.2388, CH= 52086.6075
Training epoch 1101, recon_loss:0.773812, zinb_loss:0.639569, cluster_loss:0.153430
Clustering   1101: ASW= 0.8227, DB= 0.2439, CH= 51406.2934
Training epoch 1102, recon_loss:0.775028, zinb_loss:0.640084, cluster_loss:0.152991
Clustering   1102: ASW= 0.8259, DB= 0.2381, CH= 51996.2657
Training epoch 1103, recon_loss:0.774034, zinb_loss:0.639585, cluster_loss:0.153513
Clustering   1103: ASW= 0.8227, DB= 0.2436, CH= 51429.1156
Training epoch 1104, recon_loss:0.775141, zinb_loss:0.640104, cluster_loss:0.152937
Clustering   1104: ASW= 0.8260, DB= 0.2381, CH= 52029.6968
Training epoch 1105, recon_loss:0.774218, zinb_loss:0.639716, cluster_loss:0.153393
Clustering   1105: ASW= 0.8231, DB= 0.2427, CH= 51449.5722
Training epoch 1106, recon_loss:0.775279, zinb_loss:0.640196, cluster_loss:0.152881
Clustering   1106: ASW= 0.8257, DB= 0.2385, CH= 52018.8848
Training epoch 1107, recon_loss:0.774670, zinb_loss:0.639990, cluster_loss:0.153325
Clustering   1107: ASW= 0.8236, DB= 0.2425, CH= 51643.5129
Training epoch 1108, recon_loss:0.775963, zinb_loss:0.640750, cluster_loss:0.152927
Clustering   1108: ASW= 0.8258, DB= 0.2386, CH= 52141.6058
Training epoch 1109, recon_loss:0.775591, zinb_loss:0.640705, cluster_loss:0.153502
Clustering   1109: ASW= 0.8236, DB= 0.2421, CH= 51470.9866
Training epoch 1110, recon_loss:0.776680, zinb_loss:0.641447, cluster_loss:0.153176
Clustering   1110: ASW= 0.8255, DB= 0.2391, CH= 52054.1761
Training epoch 1111, recon_loss:0.776127, zinb_loss:0.641302, cluster_loss:0.153557
Clustering   1111: ASW= 0.8240, DB= 0.2415, CH= 51653.9585
Training epoch 1112, recon_loss:0.776176, zinb_loss:0.641567, cluster_loss:0.153269
Clustering   1112: ASW= 0.8253, DB= 0.2394, CH= 52059.3186
Training epoch 1113, recon_loss:0.775525, zinb_loss:0.641375, cluster_loss:0.153512
Clustering   1113: ASW= 0.8240, DB= 0.2417, CH= 51611.5281
Training epoch 1114, recon_loss:0.775458, zinb_loss:0.641543, cluster_loss:0.153236
Clustering   1114: ASW= 0.8256, DB= 0.2394, CH= 52091.8983
Training epoch 1115, recon_loss:0.775129, zinb_loss:0.641331, cluster_loss:0.153353
Clustering   1115: ASW= 0.8242, DB= 0.2406, CH= 51698.4322
Training epoch 1116, recon_loss:0.774855, zinb_loss:0.641166, cluster_loss:0.153240
Clustering   1116: ASW= 0.8254, DB= 0.2398, CH= 52120.3927
Training epoch 1117, recon_loss:0.775041, zinb_loss:0.641037, cluster_loss:0.153251
Clustering   1117: ASW= 0.8242, DB= 0.2403, CH= 51823.8278
Training epoch 1118, recon_loss:0.774369, zinb_loss:0.640735, cluster_loss:0.153305
Clustering   1118: ASW= 0.8253, DB= 0.2402, CH= 52125.7374
Training epoch 1119, recon_loss:0.774744, zinb_loss:0.640754, cluster_loss:0.153174
Clustering   1119: ASW= 0.8242, DB= 0.2394, CH= 51918.3676
Training epoch 1120, recon_loss:0.773992, zinb_loss:0.640414, cluster_loss:0.153438
Clustering   1120: ASW= 0.8254, DB= 0.2406, CH= 52084.5068
Training epoch 1121, recon_loss:0.774311, zinb_loss:0.640638, cluster_loss:0.153123
Clustering   1121: ASW= 0.8244, DB= 0.2392, CH= 51884.4798
Training epoch 1122, recon_loss:0.773832, zinb_loss:0.640374, cluster_loss:0.153533
Clustering   1122: ASW= 0.8250, DB= 0.2414, CH= 52085.3913
Training epoch 1123, recon_loss:0.774137, zinb_loss:0.640543, cluster_loss:0.153118
Clustering   1123: ASW= 0.8242, DB= 0.2389, CH= 51808.9576
Training epoch 1124, recon_loss:0.773502, zinb_loss:0.640161, cluster_loss:0.153528
Clustering   1124: ASW= 0.8249, DB= 0.2416, CH= 52095.1682
Training epoch 1125, recon_loss:0.773787, zinb_loss:0.640369, cluster_loss:0.153102
Clustering   1125: ASW= 0.8240, DB= 0.2388, CH= 51683.2277
Training epoch 1126, recon_loss:0.773275, zinb_loss:0.639947, cluster_loss:0.153599
Clustering   1126: ASW= 0.8247, DB= 0.2421, CH= 52004.1862
Training epoch 1127, recon_loss:0.773484, zinb_loss:0.640274, cluster_loss:0.153079
Clustering   1127: ASW= 0.8242, DB= 0.2387, CH= 51574.9759
Training epoch 1128, recon_loss:0.773219, zinb_loss:0.639899, cluster_loss:0.153571
Clustering   1128: ASW= 0.8243, DB= 0.2425, CH= 52028.4084
Training epoch 1129, recon_loss:0.773344, zinb_loss:0.640147, cluster_loss:0.153046
Clustering   1129: ASW= 0.8242, DB= 0.2386, CH= 51502.4272
Training epoch 1130, recon_loss:0.773360, zinb_loss:0.639836, cluster_loss:0.153498
Clustering   1130: ASW= 0.8244, DB= 0.2426, CH= 52084.3247
Training epoch 1131, recon_loss:0.773414, zinb_loss:0.640045, cluster_loss:0.153024
Clustering   1131: ASW= 0.8243, DB= 0.2387, CH= 51423.7873
Training epoch 1132, recon_loss:0.773593, zinb_loss:0.639898, cluster_loss:0.153372
Clustering   1132: ASW= 0.8245, DB= 0.2423, CH= 52180.8246
Training epoch 1133, recon_loss:0.773553, zinb_loss:0.640044, cluster_loss:0.153000
Clustering   1133: ASW= 0.8244, DB= 0.2390, CH= 51377.4795
Training epoch 1134, recon_loss:0.773899, zinb_loss:0.640093, cluster_loss:0.153252
Clustering   1134: ASW= 0.8246, DB= 0.2419, CH= 52253.0278
Training epoch 1135, recon_loss:0.773864, zinb_loss:0.640183, cluster_loss:0.152996
Clustering   1135: ASW= 0.8245, DB= 0.2399, CH= 51392.7580
Training epoch 1136, recon_loss:0.774363, zinb_loss:0.640392, cluster_loss:0.153210
Clustering   1136: ASW= 0.8245, DB= 0.2411, CH= 52216.9799
Training epoch 1137, recon_loss:0.774300, zinb_loss:0.640426, cluster_loss:0.153007
Clustering   1137: ASW= 0.8246, DB= 0.2404, CH= 51458.0421
Training epoch 1138, recon_loss:0.774738, zinb_loss:0.640647, cluster_loss:0.153197
Clustering   1138: ASW= 0.8244, DB= 0.2407, CH= 52109.0542
Training epoch 1139, recon_loss:0.774380, zinb_loss:0.640560, cluster_loss:0.152934
Clustering   1139: ASW= 0.8247, DB= 0.2405, CH= 51568.8514
Training epoch 1140, recon_loss:0.774525, zinb_loss:0.640571, cluster_loss:0.153064
Clustering   1140: ASW= 0.8242, DB= 0.2401, CH= 52082.4063
Training epoch 1141, recon_loss:0.774184, zinb_loss:0.640517, cluster_loss:0.152812
Clustering   1141: ASW= 0.8249, DB= 0.2405, CH= 51760.1324
Training epoch 1142, recon_loss:0.774208, zinb_loss:0.640438, cluster_loss:0.152979
Clustering   1142: ASW= 0.8241, DB= 0.2401, CH= 51950.2610
Training epoch 1143, recon_loss:0.773986, zinb_loss:0.640333, cluster_loss:0.152676
Clustering   1143: ASW= 0.8250, DB= 0.2396, CH= 51850.7547
Training epoch 1144, recon_loss:0.774106, zinb_loss:0.640246, cluster_loss:0.152929
Clustering   1144: ASW= 0.8241, DB= 0.2397, CH= 52004.6299
Training epoch 1145, recon_loss:0.773952, zinb_loss:0.640201, cluster_loss:0.152657
Clustering   1145: ASW= 0.8252, DB= 0.2389, CH= 52035.3136
Training epoch 1146, recon_loss:0.774066, zinb_loss:0.640100, cluster_loss:0.152965
Clustering   1146: ASW= 0.8240, DB= 0.2400, CH= 51909.4906
Training epoch 1147, recon_loss:0.774043, zinb_loss:0.640134, cluster_loss:0.152655
Clustering   1147: ASW= 0.8255, DB= 0.2389, CH= 52294.2629
Training epoch 1148, recon_loss:0.774168, zinb_loss:0.640008, cluster_loss:0.153148
Clustering   1148: ASW= 0.8239, DB= 0.2396, CH= 51718.4139
Training epoch 1149, recon_loss:0.773959, zinb_loss:0.640101, cluster_loss:0.152732
Clustering   1149: ASW= 0.8256, DB= 0.2392, CH= 52487.7063
Training epoch 1150, recon_loss:0.774141, zinb_loss:0.639915, cluster_loss:0.153341
Clustering   1150: ASW= 0.8238, DB= 0.2397, CH= 51595.1088
Training epoch 1151, recon_loss:0.773750, zinb_loss:0.640059, cluster_loss:0.152834
Clustering   1151: ASW= 0.8257, DB= 0.2399, CH= 52606.6785
Training epoch 1152, recon_loss:0.773956, zinb_loss:0.639880, cluster_loss:0.153417
Clustering   1152: ASW= 0.8241, DB= 0.2394, CH= 51578.1339
Training epoch 1153, recon_loss:0.773477, zinb_loss:0.640064, cluster_loss:0.152847
Clustering   1153: ASW= 0.8259, DB= 0.2403, CH= 52772.0409
Training epoch 1154, recon_loss:0.773696, zinb_loss:0.639894, cluster_loss:0.153479
Clustering   1154: ASW= 0.8243, DB= 0.2390, CH= 51520.3428
Training epoch 1155, recon_loss:0.773269, zinb_loss:0.640124, cluster_loss:0.152838
Clustering   1155: ASW= 0.8260, DB= 0.2404, CH= 52870.6729
Training epoch 1156, recon_loss:0.773541, zinb_loss:0.639966, cluster_loss:0.153552
Clustering   1156: ASW= 0.8244, DB= 0.2389, CH= 51449.2789
Training epoch 1157, recon_loss:0.773215, zinb_loss:0.640260, cluster_loss:0.152786
Clustering   1157: ASW= 0.8261, DB= 0.2405, CH= 53005.3532
Training epoch 1158, recon_loss:0.773522, zinb_loss:0.640055, cluster_loss:0.153602
Clustering   1158: ASW= 0.8245, DB= 0.2390, CH= 51399.6881
Training epoch 1159, recon_loss:0.773254, zinb_loss:0.640402, cluster_loss:0.152654
Clustering   1159: ASW= 0.8263, DB= 0.2401, CH= 53121.8767
Training epoch 1160, recon_loss:0.773560, zinb_loss:0.640101, cluster_loss:0.153592
Clustering   1160: ASW= 0.8247, DB= 0.2388, CH= 51385.4219
Training epoch 1161, recon_loss:0.773378, zinb_loss:0.640503, cluster_loss:0.152484
Clustering   1161: ASW= 0.8264, DB= 0.2401, CH= 53180.5796
Training epoch 1162, recon_loss:0.773661, zinb_loss:0.640116, cluster_loss:0.153474
Clustering   1162: ASW= 0.8250, DB= 0.2387, CH= 51484.4627
Training epoch 1163, recon_loss:0.773558, zinb_loss:0.640579, cluster_loss:0.152345
Clustering   1163: ASW= 0.8263, DB= 0.2398, CH= 53178.2999
Training epoch 1164, recon_loss:0.774011, zinb_loss:0.640125, cluster_loss:0.153435
Clustering   1164: ASW= 0.8251, DB= 0.2390, CH= 51575.4033
Training epoch 1165, recon_loss:0.773865, zinb_loss:0.640670, cluster_loss:0.152360
Clustering   1165: ASW= 0.8261, DB= 0.2396, CH= 53002.7730
Training epoch 1166, recon_loss:0.774536, zinb_loss:0.640079, cluster_loss:0.153543
Clustering   1166: ASW= 0.8251, DB= 0.2389, CH= 51588.9712
Training epoch 1167, recon_loss:0.774139, zinb_loss:0.640731, cluster_loss:0.152510
Clustering   1167: ASW= 0.8259, DB= 0.2391, CH= 52780.4065
Training epoch 1168, recon_loss:0.774274, zinb_loss:0.639958, cluster_loss:0.153537
Clustering   1168: ASW= 0.8251, DB= 0.2396, CH= 51602.0208
Training epoch 1169, recon_loss:0.773977, zinb_loss:0.640550, cluster_loss:0.152580
Clustering   1169: ASW= 0.8257, DB= 0.2396, CH= 52601.1868
Training epoch 1170, recon_loss:0.773890, zinb_loss:0.639770, cluster_loss:0.153393
Clustering   1170: ASW= 0.8251, DB= 0.2396, CH= 51761.1263
Training epoch 1171, recon_loss:0.773642, zinb_loss:0.640298, cluster_loss:0.152523
Clustering   1171: ASW= 0.8256, DB= 0.2389, CH= 52577.2820
Training epoch 1172, recon_loss:0.773540, zinb_loss:0.639665, cluster_loss:0.153175
Clustering   1172: ASW= 0.8254, DB= 0.2397, CH= 51933.4751
Training epoch 1173, recon_loss:0.773283, zinb_loss:0.640143, cluster_loss:0.152420
Clustering   1173: ASW= 0.8257, DB= 0.2384, CH= 52632.3763
Training epoch 1174, recon_loss:0.773275, zinb_loss:0.639574, cluster_loss:0.153075
Clustering   1174: ASW= 0.8253, DB= 0.2399, CH= 51936.4637
Training epoch 1175, recon_loss:0.773104, zinb_loss:0.640052, cluster_loss:0.152398
Clustering   1175: ASW= 0.8256, DB= 0.2382, CH= 52619.7743
Training epoch 1176, recon_loss:0.773389, zinb_loss:0.639558, cluster_loss:0.152984
Clustering   1176: ASW= 0.8253, DB= 0.2403, CH= 52035.9552
Training epoch 1177, recon_loss:0.773411, zinb_loss:0.640104, cluster_loss:0.152410
Clustering   1177: ASW= 0.8256, DB= 0.2379, CH= 52658.8310
Training epoch 1178, recon_loss:0.773879, zinb_loss:0.639723, cluster_loss:0.153041
Clustering   1178: ASW= 0.8250, DB= 0.2410, CH= 51940.5408
Training epoch 1179, recon_loss:0.773628, zinb_loss:0.640301, cluster_loss:0.152513
Clustering   1179: ASW= 0.8255, DB= 0.2384, CH= 52565.1082
Training epoch 1180, recon_loss:0.773520, zinb_loss:0.639959, cluster_loss:0.152949
Clustering   1180: ASW= 0.8254, DB= 0.2406, CH= 52130.1792
Training epoch 1181, recon_loss:0.773253, zinb_loss:0.640443, cluster_loss:0.152514
Clustering   1181: ASW= 0.8257, DB= 0.2374, CH= 52714.9296
Training epoch 1182, recon_loss:0.773152, zinb_loss:0.640021, cluster_loss:0.152951
Clustering   1182: ASW= 0.8251, DB= 0.2408, CH= 52030.9084
Training epoch 1183, recon_loss:0.772849, zinb_loss:0.640276, cluster_loss:0.152601
Clustering   1183: ASW= 0.8253, DB= 0.2377, CH= 52599.8909
Training epoch 1184, recon_loss:0.772800, zinb_loss:0.640041, cluster_loss:0.152884
Clustering   1184: ASW= 0.8254, DB= 0.2405, CH= 52247.6021
Training epoch 1185, recon_loss:0.772670, zinb_loss:0.640430, cluster_loss:0.152589
Clustering   1185: ASW= 0.8257, DB= 0.2379, CH= 52674.3102
Training epoch 1186, recon_loss:0.772657, zinb_loss:0.640146, cluster_loss:0.152762
Clustering   1186: ASW= 0.8258, DB= 0.2407, CH= 52360.1836
Training epoch 1187, recon_loss:0.772596, zinb_loss:0.640497, cluster_loss:0.152742
Clustering   1187: ASW= 0.8256, DB= 0.2375, CH= 52806.4751
Training epoch 1188, recon_loss:0.772822, zinb_loss:0.640424, cluster_loss:0.152858
Clustering   1188: ASW= 0.8260, DB= 0.2405, CH= 52340.2728
Training epoch 1189, recon_loss:0.773038, zinb_loss:0.640818, cluster_loss:0.153066
Clustering   1189: ASW= 0.8253, DB= 0.2378, CH= 52832.2911
Training epoch 1190, recon_loss:0.773270, zinb_loss:0.640767, cluster_loss:0.153074
Clustering   1190: ASW= 0.8260, DB= 0.2395, CH= 52142.9966
Training epoch 1191, recon_loss:0.773345, zinb_loss:0.641056, cluster_loss:0.153225
Clustering   1191: ASW= 0.8252, DB= 0.2380, CH= 52942.3564
Training epoch 1192, recon_loss:0.773540, zinb_loss:0.640889, cluster_loss:0.153168
Clustering   1192: ASW= 0.8259, DB= 0.2391, CH= 51871.2018
Training epoch 1193, recon_loss:0.773318, zinb_loss:0.641006, cluster_loss:0.153224
Clustering   1193: ASW= 0.8251, DB= 0.2385, CH= 52875.4583
Training epoch 1194, recon_loss:0.773589, zinb_loss:0.640727, cluster_loss:0.153052
Clustering   1194: ASW= 0.8258, DB= 0.2389, CH= 51822.6577
Training epoch 1195, recon_loss:0.772884, zinb_loss:0.640557, cluster_loss:0.152927
Clustering   1195: ASW= 0.8252, DB= 0.2387, CH= 52918.3441
Training epoch 1196, recon_loss:0.773222, zinb_loss:0.640231, cluster_loss:0.152723
Clustering   1196: ASW= 0.8258, DB= 0.2387, CH= 51940.3220
Training epoch 1197, recon_loss:0.772581, zinb_loss:0.640128, cluster_loss:0.152647
Clustering   1197: ASW= 0.8255, DB= 0.2387, CH= 53020.6417
Training epoch 1198, recon_loss:0.772796, zinb_loss:0.639813, cluster_loss:0.152464
Clustering   1198: ASW= 0.8260, DB= 0.2387, CH= 52148.0125
Training epoch 1199, recon_loss:0.772579, zinb_loss:0.639864, cluster_loss:0.152505
Clustering   1199: ASW= 0.8257, DB= 0.2385, CH= 53060.7496
Training epoch 1200, recon_loss:0.772887, zinb_loss:0.639630, cluster_loss:0.152383
Clustering   1200: ASW= 0.8261, DB= 0.2386, CH= 52342.0570
Training epoch 1201, recon_loss:0.772740, zinb_loss:0.639710, cluster_loss:0.152498
Clustering   1201: ASW= 0.8258, DB= 0.2384, CH= 53054.3929
Training epoch 1202, recon_loss:0.773177, zinb_loss:0.639517, cluster_loss:0.152350
Clustering   1202: ASW= 0.8264, DB= 0.2383, CH= 52525.6678
Training epoch 1203, recon_loss:0.773056, zinb_loss:0.639618, cluster_loss:0.152557
Clustering   1203: ASW= 0.8257, DB= 0.2387, CH= 52997.4996
Training epoch 1204, recon_loss:0.773416, zinb_loss:0.639457, cluster_loss:0.152367
Clustering   1204: ASW= 0.8266, DB= 0.2382, CH= 52673.7909
Training epoch 1205, recon_loss:0.773211, zinb_loss:0.639555, cluster_loss:0.152562
Clustering   1205: ASW= 0.8259, DB= 0.2383, CH= 53015.3574
Training epoch 1206, recon_loss:0.773785, zinb_loss:0.639489, cluster_loss:0.152404
Clustering   1206: ASW= 0.8268, DB= 0.2379, CH= 52876.1055
Training epoch 1207, recon_loss:0.773613, zinb_loss:0.639596, cluster_loss:0.152666
Clustering   1207: ASW= 0.8259, DB= 0.2384, CH= 52886.9848
Training epoch 1208, recon_loss:0.774213, zinb_loss:0.639492, cluster_loss:0.152541
Clustering   1208: ASW= 0.8268, DB= 0.2380, CH= 52925.3192
Training epoch 1209, recon_loss:0.773710, zinb_loss:0.639605, cluster_loss:0.152738
Clustering   1209: ASW= 0.8263, DB= 0.2375, CH= 52946.4231
Training epoch 1210, recon_loss:0.774354, zinb_loss:0.639542, cluster_loss:0.152632
Clustering   1210: ASW= 0.8271, DB= 0.2377, CH= 53189.4076
Training epoch 1211, recon_loss:0.773974, zinb_loss:0.639543, cluster_loss:0.152907
Clustering   1211: ASW= 0.8257, DB= 0.2383, CH= 52588.4641
Training epoch 1212, recon_loss:0.774335, zinb_loss:0.639426, cluster_loss:0.152831
Clustering   1212: ASW= 0.8268, DB= 0.2385, CH= 53142.3723
Training epoch 1213, recon_loss:0.773912, zinb_loss:0.639539, cluster_loss:0.153169
Clustering   1213: ASW= 0.8261, DB= 0.2377, CH= 52659.0462
Training epoch 1214, recon_loss:0.773850, zinb_loss:0.639419, cluster_loss:0.152867
Clustering   1214: ASW= 0.8271, DB= 0.2379, CH= 53315.1462
Training epoch 1215, recon_loss:0.773142, zinb_loss:0.639278, cluster_loss:0.153091
Clustering   1215: ASW= 0.8257, DB= 0.2380, CH= 52534.3408
Training epoch 1216, recon_loss:0.773420, zinb_loss:0.639421, cluster_loss:0.152793
Clustering   1216: ASW= 0.8273, DB= 0.2376, CH= 53459.8552
Training epoch 1217, recon_loss:0.773014, zinb_loss:0.639235, cluster_loss:0.153052
Clustering   1217: ASW= 0.8252, DB= 0.2386, CH= 52374.6546
Training epoch 1218, recon_loss:0.773343, zinb_loss:0.639507, cluster_loss:0.152872
Clustering   1218: ASW= 0.8266, DB= 0.2381, CH= 53149.4360
Training epoch 1219, recon_loss:0.773039, zinb_loss:0.639406, cluster_loss:0.153256
Clustering   1219: ASW= 0.8252, DB= 0.2390, CH= 52374.6408
Training epoch 1220, recon_loss:0.773708, zinb_loss:0.639991, cluster_loss:0.152914
Clustering   1220: ASW= 0.8268, DB= 0.2375, CH= 53144.2294
Training epoch 1221, recon_loss:0.773598, zinb_loss:0.639668, cluster_loss:0.153368
Clustering   1221: ASW= 0.8246, DB= 0.2400, CH= 52233.1000
Training epoch 1222, recon_loss:0.774698, zinb_loss:0.640606, cluster_loss:0.153103
Clustering   1222: ASW= 0.8270, DB= 0.2374, CH= 53012.3100
Training epoch 1223, recon_loss:0.774425, zinb_loss:0.639995, cluster_loss:0.153472
Clustering   1223: ASW= 0.8243, DB= 0.2407, CH= 52064.4050
Training epoch 1224, recon_loss:0.774816, zinb_loss:0.640711, cluster_loss:0.153293
Clustering   1224: ASW= 0.8261, DB= 0.2378, CH= 52477.4685
Training epoch 1225, recon_loss:0.774592, zinb_loss:0.639950, cluster_loss:0.153763
Clustering   1225: ASW= 0.8242, DB= 0.2409, CH= 51952.6897
Training epoch 1226, recon_loss:0.774813, zinb_loss:0.640743, cluster_loss:0.153189
Clustering   1226: ASW= 0.8271, DB= 0.2374, CH= 52623.0317
Training epoch 1227, recon_loss:0.773425, zinb_loss:0.639822, cluster_loss:0.153026
Clustering   1227: ASW= 0.8253, DB= 0.2399, CH= 52455.9489
Training epoch 1228, recon_loss:0.773228, zinb_loss:0.640115, cluster_loss:0.152722
Clustering   1228: ASW= 0.8274, DB= 0.2365, CH= 52887.0687
Training epoch 1229, recon_loss:0.772639, zinb_loss:0.639721, cluster_loss:0.152655
Clustering   1229: ASW= 0.8258, DB= 0.2395, CH= 52896.5378
Training epoch 1230, recon_loss:0.772949, zinb_loss:0.639846, cluster_loss:0.152633
Clustering   1230: ASW= 0.8274, DB= 0.2373, CH= 52772.0216
Training epoch 1231, recon_loss:0.772962, zinb_loss:0.639751, cluster_loss:0.152544
Clustering   1231: ASW= 0.8263, DB= 0.2389, CH= 53189.2710
Training epoch 1232, recon_loss:0.773304, zinb_loss:0.639794, cluster_loss:0.152812
Clustering   1232: ASW= 0.8274, DB= 0.2367, CH= 52749.8823
Training epoch 1233, recon_loss:0.773529, zinb_loss:0.639899, cluster_loss:0.152616
Clustering   1233: ASW= 0.8262, DB= 0.2391, CH= 53288.3904
Training epoch 1234, recon_loss:0.773822, zinb_loss:0.639714, cluster_loss:0.153080
Clustering   1234: ASW= 0.8273, DB= 0.2370, CH= 52651.1027
Training epoch 1235, recon_loss:0.773946, zinb_loss:0.640035, cluster_loss:0.152630
Clustering   1235: ASW= 0.8263, DB= 0.2388, CH= 53336.6790
Training epoch 1236, recon_loss:0.773905, zinb_loss:0.639551, cluster_loss:0.153211
Clustering   1236: ASW= 0.8267, DB= 0.2373, CH= 52404.9179
Training epoch 1237, recon_loss:0.773953, zinb_loss:0.639922, cluster_loss:0.152549
Clustering   1237: ASW= 0.8265, DB= 0.2382, CH= 53397.7540
Training epoch 1238, recon_loss:0.773323, zinb_loss:0.639355, cluster_loss:0.152972
Clustering   1238: ASW= 0.8270, DB= 0.2371, CH= 52532.7435
Training epoch 1239, recon_loss:0.774101, zinb_loss:0.639987, cluster_loss:0.152722
Clustering   1239: ASW= 0.8255, DB= 0.2386, CH= 53064.5111
Training epoch 1240, recon_loss:0.774628, zinb_loss:0.640008, cluster_loss:0.153295
Clustering   1240: ASW= 0.8260, DB= 0.2395, CH= 51811.1712
Training epoch 1241, recon_loss:0.773324, zinb_loss:0.639445, cluster_loss:0.152822
Clustering   1241: ASW= 0.8242, DB= 0.2426, CH= 52168.5521
Training epoch 1242, recon_loss:0.772676, zinb_loss:0.638777, cluster_loss:0.153262
Clustering   1242: ASW= 0.8255, DB= 0.2388, CH= 51957.5249
Training epoch 1243, recon_loss:0.772486, zinb_loss:0.639272, cluster_loss:0.152500
Clustering   1243: ASW= 0.8257, DB= 0.2394, CH= 52653.6044
Training epoch 1244, recon_loss:0.773146, zinb_loss:0.638788, cluster_loss:0.153501
Clustering   1244: ASW= 0.8249, DB= 0.2392, CH= 52034.6760
Training epoch 1245, recon_loss:0.773426, zinb_loss:0.639563, cluster_loss:0.152544
Clustering   1245: ASW= 0.8260, DB= 0.2381, CH= 52526.4345
Training epoch 1246, recon_loss:0.773649, zinb_loss:0.639096, cluster_loss:0.153369
Clustering   1246: ASW= 0.8255, DB= 0.2398, CH= 52351.5216
Training epoch 1247, recon_loss:0.773961, zinb_loss:0.639814, cluster_loss:0.152561
Clustering   1247: ASW= 0.8262, DB= 0.2375, CH= 52407.5617
Training epoch 1248, recon_loss:0.774013, zinb_loss:0.639358, cluster_loss:0.153368
Clustering   1248: ASW= 0.8260, DB= 0.2397, CH= 52689.2571
Training epoch 1249, recon_loss:0.773997, zinb_loss:0.639811, cluster_loss:0.152558
Clustering   1249: ASW= 0.8264, DB= 0.2375, CH= 52461.2553
Training epoch 1250, recon_loss:0.773667, zinb_loss:0.639438, cluster_loss:0.153083
Clustering   1250: ASW= 0.8266, DB= 0.2388, CH= 53076.7576
Training epoch 1251, recon_loss:0.773416, zinb_loss:0.639648, cluster_loss:0.152423
Clustering   1251: ASW= 0.8265, DB= 0.2374, CH= 52582.8023
Training epoch 1252, recon_loss:0.772978, zinb_loss:0.639434, cluster_loss:0.152670
Clustering   1252: ASW= 0.8272, DB= 0.2376, CH= 53417.0460
Training epoch 1253, recon_loss:0.772728, zinb_loss:0.639524, cluster_loss:0.152293
Clustering   1253: ASW= 0.8266, DB= 0.2367, CH= 52727.7179
Training epoch 1254, recon_loss:0.772517, zinb_loss:0.639570, cluster_loss:0.152370
Clustering   1254: ASW= 0.8277, DB= 0.2370, CH= 53702.9134
Training epoch 1255, recon_loss:0.772389, zinb_loss:0.639589, cluster_loss:0.152299
Clustering   1255: ASW= 0.8264, DB= 0.2372, CH= 52805.5919
Training epoch 1256, recon_loss:0.772415, zinb_loss:0.639931, cluster_loss:0.152212
Clustering   1256: ASW= 0.8281, DB= 0.2368, CH= 53937.5637
Training epoch 1257, recon_loss:0.772301, zinb_loss:0.639809, cluster_loss:0.152425
Clustering   1257: ASW= 0.8261, DB= 0.2379, CH= 52791.8541
Training epoch 1258, recon_loss:0.772394, zinb_loss:0.640348, cluster_loss:0.152157
Clustering   1258: ASW= 0.8286, DB= 0.2360, CH= 54090.0269
Training epoch 1259, recon_loss:0.772317, zinb_loss:0.640022, cluster_loss:0.152675
Clustering   1259: ASW= 0.8257, DB= 0.2382, CH= 52719.9984
Training epoch 1260, recon_loss:0.772589, zinb_loss:0.640748, cluster_loss:0.152245
Clustering   1260: ASW= 0.8289, DB= 0.2354, CH= 54110.5618
Training epoch 1261, recon_loss:0.772501, zinb_loss:0.640235, cluster_loss:0.152989
Clustering   1261: ASW= 0.8253, DB= 0.2388, CH= 52503.8430
Training epoch 1262, recon_loss:0.772872, zinb_loss:0.641080, cluster_loss:0.152337
Clustering   1262: ASW= 0.8289, DB= 0.2358, CH= 54088.8497
Training epoch 1263, recon_loss:0.772502, zinb_loss:0.640396, cluster_loss:0.152952
Clustering   1263: ASW= 0.8255, DB= 0.2386, CH= 52562.5212
Training epoch 1264, recon_loss:0.773030, zinb_loss:0.641141, cluster_loss:0.152329
Clustering   1264: ASW= 0.8287, DB= 0.2359, CH= 54056.4323
Training epoch 1265, recon_loss:0.772856, zinb_loss:0.640495, cluster_loss:0.152845
Clustering   1265: ASW= 0.8258, DB= 0.2384, CH= 52725.7372
Training epoch 1266, recon_loss:0.773502, zinb_loss:0.641165, cluster_loss:0.152383
Clustering   1266: ASW= 0.8284, DB= 0.2359, CH= 53995.8184
Training epoch 1267, recon_loss:0.773494, zinb_loss:0.640582, cluster_loss:0.152812
Clustering   1267: ASW= 0.8262, DB= 0.2380, CH= 52915.8851
Training epoch 1268, recon_loss:0.773869, zinb_loss:0.641102, cluster_loss:0.152513
Clustering   1268: ASW= 0.8280, DB= 0.2355, CH= 53882.6223
Training epoch 1269, recon_loss:0.773748, zinb_loss:0.640538, cluster_loss:0.152821
Clustering   1269: ASW= 0.8263, DB= 0.2384, CH= 53082.1690
Training epoch 1270, recon_loss:0.773672, zinb_loss:0.640943, cluster_loss:0.152649
Clustering   1270: ASW= 0.8277, DB= 0.2355, CH= 53744.7216
Training epoch 1271, recon_loss:0.773310, zinb_loss:0.640458, cluster_loss:0.152809
Clustering   1271: ASW= 0.8265, DB= 0.2389, CH= 53222.3117
Training epoch 1272, recon_loss:0.773422, zinb_loss:0.640722, cluster_loss:0.152884
Clustering   1272: ASW= 0.8273, DB= 0.2350, CH= 53528.4201
Training epoch 1273, recon_loss:0.773282, zinb_loss:0.640418, cluster_loss:0.152903
Clustering   1273: ASW= 0.8267, DB= 0.2388, CH= 53301.7142
Training epoch 1274, recon_loss:0.773491, zinb_loss:0.640629, cluster_loss:0.153232
Clustering   1274: ASW= 0.8269, DB= 0.2352, CH= 53184.5450
Training epoch 1275, recon_loss:0.773307, zinb_loss:0.640555, cluster_loss:0.152861
Clustering   1275: ASW= 0.8270, DB= 0.2387, CH= 53387.3448
Training epoch 1276, recon_loss:0.773480, zinb_loss:0.640504, cluster_loss:0.153292
Clustering   1276: ASW= 0.8270, DB= 0.2355, CH= 53058.0262
Training epoch 1277, recon_loss:0.773318, zinb_loss:0.640609, cluster_loss:0.152715
Clustering   1277: ASW= 0.8273, DB= 0.2378, CH= 53474.8746
Training epoch 1278, recon_loss:0.772959, zinb_loss:0.640230, cluster_loss:0.153171
Clustering   1278: ASW= 0.8267, DB= 0.2362, CH= 52878.1257
Training epoch 1279, recon_loss:0.772881, zinb_loss:0.640450, cluster_loss:0.152897
Clustering   1279: ASW= 0.8264, DB= 0.2396, CH= 52774.7447
Training epoch 1280, recon_loss:0.773896, zinb_loss:0.640306, cluster_loss:0.154097
Clustering   1280: ASW= 0.8257, DB= 0.2374, CH= 52421.0435
Training epoch 1281, recon_loss:0.773564, zinb_loss:0.640496, cluster_loss:0.153063
Clustering   1281: ASW= 0.8269, DB= 0.2391, CH= 52717.4841
Training epoch 1282, recon_loss:0.772661, zinb_loss:0.639780, cluster_loss:0.153154
Clustering   1282: ASW= 0.8268, DB= 0.2368, CH= 52809.8158
Training epoch 1283, recon_loss:0.772273, zinb_loss:0.639690, cluster_loss:0.152395
Clustering   1283: ASW= 0.8272, DB= 0.2377, CH= 53055.1454
Training epoch 1284, recon_loss:0.772092, zinb_loss:0.639456, cluster_loss:0.152493
Clustering   1284: ASW= 0.8273, DB= 0.2363, CH= 53371.9518
Training epoch 1285, recon_loss:0.771819, zinb_loss:0.639249, cluster_loss:0.152105
Clustering   1285: ASW= 0.8274, DB= 0.2370, CH= 53229.8145
Training epoch 1286, recon_loss:0.772043, zinb_loss:0.639325, cluster_loss:0.152227
Clustering   1286: ASW= 0.8276, DB= 0.2359, CH= 53696.5370
Training epoch 1287, recon_loss:0.771912, zinb_loss:0.639081, cluster_loss:0.152052
Clustering   1287: ASW= 0.8274, DB= 0.2373, CH= 53339.9386
Training epoch 1288, recon_loss:0.772246, zinb_loss:0.639355, cluster_loss:0.152115
Clustering   1288: ASW= 0.8278, DB= 0.2356, CH= 53926.4121
Training epoch 1289, recon_loss:0.772178, zinb_loss:0.639042, cluster_loss:0.152085
Clustering   1289: ASW= 0.8273, DB= 0.2373, CH= 53364.1451
Training epoch 1290, recon_loss:0.772543, zinb_loss:0.639401, cluster_loss:0.152101
Clustering   1290: ASW= 0.8277, DB= 0.2351, CH= 54006.8839
Training epoch 1291, recon_loss:0.772459, zinb_loss:0.639086, cluster_loss:0.152177
Clustering   1291: ASW= 0.8272, DB= 0.2371, CH= 53350.7648
Training epoch 1292, recon_loss:0.772801, zinb_loss:0.639496, cluster_loss:0.152151
Clustering   1292: ASW= 0.8275, DB= 0.2353, CH= 54019.5404
Training epoch 1293, recon_loss:0.772689, zinb_loss:0.639241, cluster_loss:0.152321
Clustering   1293: ASW= 0.8271, DB= 0.2370, CH= 53315.4273
Training epoch 1294, recon_loss:0.772979, zinb_loss:0.639685, cluster_loss:0.152234
Clustering   1294: ASW= 0.8273, DB= 0.2355, CH= 53972.5431
Training epoch 1295, recon_loss:0.772866, zinb_loss:0.639509, cluster_loss:0.152482
Clustering   1295: ASW= 0.8270, DB= 0.2369, CH= 53299.0114
Training epoch 1296, recon_loss:0.773143, zinb_loss:0.639984, cluster_loss:0.152344
Clustering   1296: ASW= 0.8271, DB= 0.2361, CH= 53848.2824
Training epoch 1297, recon_loss:0.772974, zinb_loss:0.639883, cluster_loss:0.152628
Clustering   1297: ASW= 0.8271, DB= 0.2370, CH= 53315.5827
Training epoch 1298, recon_loss:0.773333, zinb_loss:0.640344, cluster_loss:0.152419
Clustering   1298: ASW= 0.8270, DB= 0.2363, CH= 53787.1338
Training epoch 1299, recon_loss:0.773021, zinb_loss:0.640223, cluster_loss:0.152656
Clustering   1299: ASW= 0.8273, DB= 0.2367, CH= 53401.7473
Training epoch 1300, recon_loss:0.773605, zinb_loss:0.640603, cluster_loss:0.152450
Clustering   1300: ASW= 0.8270, DB= 0.2362, CH= 53769.2998
Training epoch 1301, recon_loss:0.772661, zinb_loss:0.640328, cluster_loss:0.152517
Clustering   1301: ASW= 0.8277, DB= 0.2364, CH= 53576.5167
Training epoch 1302, recon_loss:0.773202, zinb_loss:0.640488, cluster_loss:0.152412
Clustering   1302: ASW= 0.8271, DB= 0.2359, CH= 53795.1628
Training epoch 1303, recon_loss:0.772223, zinb_loss:0.640331, cluster_loss:0.152307
Clustering   1303: ASW= 0.8283, DB= 0.2361, CH= 53832.6853
Training epoch 1304, recon_loss:0.772725, zinb_loss:0.640236, cluster_loss:0.152400
Clustering   1304: ASW= 0.8270, DB= 0.2369, CH= 53773.9855
Training epoch 1305, recon_loss:0.772202, zinb_loss:0.640420, cluster_loss:0.152171
Clustering   1305: ASW= 0.8287, DB= 0.2356, CH= 53990.6917
Training epoch 1306, recon_loss:0.772838, zinb_loss:0.640102, cluster_loss:0.152653
Clustering   1306: ASW= 0.8262, DB= 0.2371, CH= 53502.7436
Training epoch 1307, recon_loss:0.772959, zinb_loss:0.640773, cluster_loss:0.152296
Clustering   1307: ASW= 0.8290, DB= 0.2349, CH= 53907.6272
Training epoch 1308, recon_loss:0.773748, zinb_loss:0.640093, cluster_loss:0.153133
Clustering   1308: ASW= 0.8253, DB= 0.2386, CH= 53067.1000
Training epoch 1309, recon_loss:0.773581, zinb_loss:0.640816, cluster_loss:0.152492
Clustering   1309: ASW= 0.8282, DB= 0.2349, CH= 53563.2506
Training epoch 1310, recon_loss:0.773248, zinb_loss:0.639795, cluster_loss:0.153240
Clustering   1310: ASW= 0.8248, DB= 0.2392, CH= 52722.9944
Training epoch 1311, recon_loss:0.773191, zinb_loss:0.640545, cluster_loss:0.152304
Clustering   1311: ASW= 0.8284, DB= 0.2350, CH= 53737.9445
Training epoch 1312, recon_loss:0.772790, zinb_loss:0.639521, cluster_loss:0.153062
Clustering   1312: ASW= 0.8251, DB= 0.2390, CH= 52739.0572
Training epoch 1313, recon_loss:0.772648, zinb_loss:0.640186, cluster_loss:0.152071
Clustering   1313: ASW= 0.8288, DB= 0.2347, CH= 54016.0657
Training epoch 1314, recon_loss:0.772170, zinb_loss:0.639200, cluster_loss:0.152844
Clustering   1314: ASW= 0.8256, DB= 0.2383, CH= 52916.8695
Training epoch 1315, recon_loss:0.772117, zinb_loss:0.639795, cluster_loss:0.151918
Clustering   1315: ASW= 0.8289, DB= 0.2349, CH= 54147.0361
Training epoch 1316, recon_loss:0.771709, zinb_loss:0.638938, cluster_loss:0.152639
Clustering   1316: ASW= 0.8260, DB= 0.2374, CH= 53151.3073
Training epoch 1317, recon_loss:0.771604, zinb_loss:0.639517, cluster_loss:0.151812
Clustering   1317: ASW= 0.8292, DB= 0.2347, CH= 54357.3798
Training epoch 1318, recon_loss:0.771231, zinb_loss:0.638732, cluster_loss:0.152560
Clustering   1318: ASW= 0.8261, DB= 0.2372, CH= 53226.9599
Training epoch 1319, recon_loss:0.771289, zinb_loss:0.639319, cluster_loss:0.151772
Clustering   1319: ASW= 0.8293, DB= 0.2348, CH= 54439.6854
Training epoch 1320, recon_loss:0.771004, zinb_loss:0.638622, cluster_loss:0.152536
Clustering   1320: ASW= 0.8263, DB= 0.2364, CH= 53291.3935
Training epoch 1321, recon_loss:0.771117, zinb_loss:0.639178, cluster_loss:0.151792
Clustering   1321: ASW= 0.8295, DB= 0.2349, CH= 54602.5150
Training epoch 1322, recon_loss:0.770955, zinb_loss:0.638579, cluster_loss:0.152606
Clustering   1322: ASW= 0.8262, DB= 0.2363, CH= 53163.9338
Training epoch 1323, recon_loss:0.771075, zinb_loss:0.639052, cluster_loss:0.151846
Clustering   1323: ASW= 0.8293, DB= 0.2360, CH= 54509.1654
Training epoch 1324, recon_loss:0.771129, zinb_loss:0.638660, cluster_loss:0.152708
Clustering   1324: ASW= 0.8266, DB= 0.2357, CH= 53344.0206
Training epoch 1325, recon_loss:0.771259, zinb_loss:0.639023, cluster_loss:0.151957
Clustering   1325: ASW= 0.8293, DB= 0.2363, CH= 54741.7416
Training epoch 1326, recon_loss:0.771313, zinb_loss:0.638748, cluster_loss:0.152673
Clustering   1326: ASW= 0.8267, DB= 0.2356, CH= 53140.5080
Training epoch 1327, recon_loss:0.771661, zinb_loss:0.638906, cluster_loss:0.152217
Clustering   1327: ASW= 0.8283, DB= 0.2377, CH= 54396.1820
Training epoch 1328, recon_loss:0.772621, zinb_loss:0.639121, cluster_loss:0.153482
Clustering   1328: ASW= 0.8269, DB= 0.2346, CH= 53108.1177
Training epoch 1329, recon_loss:0.772317, zinb_loss:0.639056, cluster_loss:0.152412
Clustering   1329: ASW= 0.8282, DB= 0.2383, CH= 54493.1348
Training epoch 1330, recon_loss:0.772259, zinb_loss:0.639088, cluster_loss:0.153074
Clustering   1330: ASW= 0.8274, DB= 0.2341, CH= 53189.7430
Training epoch 1331, recon_loss:0.771799, zinb_loss:0.638923, cluster_loss:0.152269
Clustering   1331: ASW= 0.8282, DB= 0.2381, CH= 54563.5728
Training epoch 1332, recon_loss:0.772087, zinb_loss:0.639045, cluster_loss:0.152708
Clustering   1332: ASW= 0.8280, DB= 0.2343, CH= 53228.3962
Training epoch 1333, recon_loss:0.772107, zinb_loss:0.638757, cluster_loss:0.152475
Clustering   1333: ASW= 0.8274, DB= 0.2390, CH= 54335.8374
Training epoch 1334, recon_loss:0.772799, zinb_loss:0.639118, cluster_loss:0.152771
Clustering   1334: ASW= 0.8284, DB= 0.2344, CH= 53235.2281
Training epoch 1335, recon_loss:0.772561, zinb_loss:0.638542, cluster_loss:0.152761
Clustering   1335: ASW= 0.8269, DB= 0.2395, CH= 54019.1946
Training epoch 1336, recon_loss:0.772946, zinb_loss:0.638963, cluster_loss:0.152696
Clustering   1336: ASW= 0.8286, DB= 0.2349, CH= 53253.3780
Training epoch 1337, recon_loss:0.772281, zinb_loss:0.638362, cluster_loss:0.152574
Clustering   1337: ASW= 0.8271, DB= 0.2390, CH= 54024.4060
Training epoch 1338, recon_loss:0.772488, zinb_loss:0.638792, cluster_loss:0.152385
Clustering   1338: ASW= 0.8289, DB= 0.2341, CH= 53407.9346
Training epoch 1339, recon_loss:0.772009, zinb_loss:0.638395, cluster_loss:0.152352
Clustering   1339: ASW= 0.8273, DB= 0.2384, CH= 54087.7310
Training epoch 1340, recon_loss:0.772294, zinb_loss:0.638841, cluster_loss:0.152222
Clustering   1340: ASW= 0.8290, DB= 0.2339, CH= 53503.1926
Training epoch 1341, recon_loss:0.772069, zinb_loss:0.638627, cluster_loss:0.152261
Clustering   1341: ASW= 0.8273, DB= 0.2385, CH= 54165.7747
Training epoch 1342, recon_loss:0.772464, zinb_loss:0.639116, cluster_loss:0.152235
Clustering   1342: ASW= 0.8291, DB= 0.2341, CH= 53496.7086
Training epoch 1343, recon_loss:0.772215, zinb_loss:0.639002, cluster_loss:0.152238
Clustering   1343: ASW= 0.8275, DB= 0.2384, CH= 54259.7082
Training epoch 1344, recon_loss:0.772485, zinb_loss:0.639393, cluster_loss:0.152354
Clustering   1344: ASW= 0.8289, DB= 0.2341, CH= 53534.9030
Training epoch 1345, recon_loss:0.772231, zinb_loss:0.639366, cluster_loss:0.152308
Clustering   1345: ASW= 0.8276, DB= 0.2383, CH= 54283.5878
Training epoch 1346, recon_loss:0.772503, zinb_loss:0.639520, cluster_loss:0.152580
Clustering   1346: ASW= 0.8286, DB= 0.2341, CH= 53443.5884
Training epoch 1347, recon_loss:0.772475, zinb_loss:0.639645, cluster_loss:0.152489
Clustering   1347: ASW= 0.8275, DB= 0.2376, CH= 54256.0822
Training epoch 1348, recon_loss:0.772724, zinb_loss:0.639736, cluster_loss:0.152739
Clustering   1348: ASW= 0.8287, DB= 0.2340, CH= 53414.8077
Training epoch 1349, recon_loss:0.772372, zinb_loss:0.639763, cluster_loss:0.152453
Clustering   1349: ASW= 0.8277, DB= 0.2371, CH= 54233.5372
Training epoch 1350, recon_loss:0.772237, zinb_loss:0.639666, cluster_loss:0.152681
Clustering   1350: ASW= 0.8288, DB= 0.2333, CH= 53678.8647
Training epoch 1351, recon_loss:0.772123, zinb_loss:0.639805, cluster_loss:0.152406
Clustering   1351: ASW= 0.8278, DB= 0.2371, CH= 54191.3282
Training epoch 1352, recon_loss:0.772381, zinb_loss:0.639551, cluster_loss:0.152765
Clustering   1352: ASW= 0.8287, DB= 0.2342, CH= 53831.7886
Training epoch 1353, recon_loss:0.772489, zinb_loss:0.639781, cluster_loss:0.152451
Clustering   1353: ASW= 0.8278, DB= 0.2364, CH= 54028.8505
Training epoch 1354, recon_loss:0.772211, zinb_loss:0.639389, cluster_loss:0.152781
Clustering   1354: ASW= 0.8286, DB= 0.2350, CH= 53883.4986
Training epoch 1355, recon_loss:0.772476, zinb_loss:0.639586, cluster_loss:0.152365
Clustering   1355: ASW= 0.8280, DB= 0.2358, CH= 54031.2378
Training epoch 1356, recon_loss:0.771945, zinb_loss:0.639173, cluster_loss:0.152677
Clustering   1356: ASW= 0.8288, DB= 0.2349, CH= 53970.0474
Training epoch 1357, recon_loss:0.772143, zinb_loss:0.639446, cluster_loss:0.152306
Clustering   1357: ASW= 0.8275, DB= 0.2358, CH= 53898.5450
Training epoch 1358, recon_loss:0.771996, zinb_loss:0.639219, cluster_loss:0.152726
Clustering   1358: ASW= 0.8289, DB= 0.2354, CH= 53885.0351
Training epoch 1359, recon_loss:0.772407, zinb_loss:0.639474, cluster_loss:0.152217
Clustering   1359: ASW= 0.8279, DB= 0.2354, CH= 53920.3606
Training epoch 1360, recon_loss:0.772296, zinb_loss:0.639357, cluster_loss:0.152701
Clustering   1360: ASW= 0.8290, DB= 0.2353, CH= 54077.9333
Training epoch 1361, recon_loss:0.772598, zinb_loss:0.639454, cluster_loss:0.152200
Clustering   1361: ASW= 0.8279, DB= 0.2354, CH= 53861.2428
Training epoch 1362, recon_loss:0.772201, zinb_loss:0.639188, cluster_loss:0.152631
Clustering   1362: ASW= 0.8290, DB= 0.2356, CH= 54163.8676
Training epoch 1363, recon_loss:0.772340, zinb_loss:0.639220, cluster_loss:0.152070
Clustering   1363: ASW= 0.8281, DB= 0.2354, CH= 53934.7163
Training epoch 1364, recon_loss:0.771886, zinb_loss:0.638910, cluster_loss:0.152486
Clustering   1364: ASW= 0.8290, DB= 0.2355, CH= 54186.3529
Training epoch 1365, recon_loss:0.771984, zinb_loss:0.638978, cluster_loss:0.151931
Clustering   1365: ASW= 0.8283, DB= 0.2355, CH= 54102.8711
Training epoch 1366, recon_loss:0.771751, zinb_loss:0.638725, cluster_loss:0.152391
Clustering   1366: ASW= 0.8290, DB= 0.2347, CH= 54151.0044
Training epoch 1367, recon_loss:0.771773, zinb_loss:0.638776, cluster_loss:0.151826
Clustering   1367: ASW= 0.8284, DB= 0.2356, CH= 54209.7089
Training epoch 1368, recon_loss:0.771647, zinb_loss:0.638549, cluster_loss:0.152264
Clustering   1368: ASW= 0.8290, DB= 0.2349, CH= 54267.3439
Training epoch 1369, recon_loss:0.771651, zinb_loss:0.638662, cluster_loss:0.151805
Clustering   1369: ASW= 0.8285, DB= 0.2352, CH= 54291.2511
Training epoch 1370, recon_loss:0.771663, zinb_loss:0.638513, cluster_loss:0.152191
Clustering   1370: ASW= 0.8291, DB= 0.2348, CH= 54306.3594
Training epoch 1371, recon_loss:0.771562, zinb_loss:0.638600, cluster_loss:0.151768
Clustering   1371: ASW= 0.8286, DB= 0.2346, CH= 54370.0542
Training epoch 1372, recon_loss:0.771643, zinb_loss:0.638477, cluster_loss:0.152142
Clustering   1372: ASW= 0.8291, DB= 0.2353, CH= 54415.1828
Training epoch 1373, recon_loss:0.771579, zinb_loss:0.638609, cluster_loss:0.151799
Clustering   1373: ASW= 0.8286, DB= 0.2351, CH= 54454.6469
Training epoch 1374, recon_loss:0.771753, zinb_loss:0.638597, cluster_loss:0.152159
Clustering   1374: ASW= 0.8291, DB= 0.2349, CH= 54347.4044
Training epoch 1375, recon_loss:0.771631, zinb_loss:0.638704, cluster_loss:0.151851
Clustering   1375: ASW= 0.8285, DB= 0.2357, CH= 54514.7884
Training epoch 1376, recon_loss:0.772086, zinb_loss:0.638876, cluster_loss:0.152300
Clustering   1376: ASW= 0.8291, DB= 0.2352, CH= 54379.2300
Training epoch 1377, recon_loss:0.771992, zinb_loss:0.639027, cluster_loss:0.151972
Clustering   1377: ASW= 0.8285, DB= 0.2359, CH= 54619.0368
Training epoch 1378, recon_loss:0.772404, zinb_loss:0.639248, cluster_loss:0.152374
Clustering   1378: ASW= 0.8292, DB= 0.2345, CH= 54299.0085
Training epoch 1379, recon_loss:0.772835, zinb_loss:0.639553, cluster_loss:0.152250
Clustering   1379: ASW= 0.8283, DB= 0.2366, CH= 54669.4939
Training epoch 1380, recon_loss:0.773144, zinb_loss:0.639691, cluster_loss:0.152723
Clustering   1380: ASW= 0.8282, DB= 0.2348, CH= 53425.9921
Training epoch 1381, recon_loss:0.773066, zinb_loss:0.639559, cluster_loss:0.152447
Clustering   1381: ASW= 0.8273, DB= 0.2379, CH= 54511.7982
Training epoch 1382, recon_loss:0.774201, zinb_loss:0.640286, cluster_loss:0.152549
Clustering   1382: ASW= 0.8296, DB= 0.2331, CH= 53949.9548
Training epoch 1383, recon_loss:0.773321, zinb_loss:0.639825, cluster_loss:0.152426
Clustering   1383: ASW= 0.8272, DB= 0.2386, CH= 54586.2291
Training epoch 1384, recon_loss:0.773336, zinb_loss:0.640328, cluster_loss:0.152405
Clustering   1384: ASW= 0.8296, DB= 0.2330, CH= 53904.2068
Training epoch 1385, recon_loss:0.772507, zinb_loss:0.639978, cluster_loss:0.152176
Clustering   1385: ASW= 0.8278, DB= 0.2372, CH= 54733.3690
Training epoch 1386, recon_loss:0.772887, zinb_loss:0.640298, cluster_loss:0.152376
Clustering   1386: ASW= 0.8296, DB= 0.2330, CH= 54114.7877
Training epoch 1387, recon_loss:0.772312, zinb_loss:0.640075, cluster_loss:0.152264
Clustering   1387: ASW= 0.8281, DB= 0.2365, CH= 54779.2037
Training epoch 1388, recon_loss:0.772854, zinb_loss:0.640248, cluster_loss:0.152553
Clustering   1388: ASW= 0.8298, DB= 0.2335, CH= 54215.1935
Training epoch 1389, recon_loss:0.772104, zinb_loss:0.640141, cluster_loss:0.152399
Clustering   1389: ASW= 0.8283, DB= 0.2357, CH= 54736.5597
Training epoch 1390, recon_loss:0.772619, zinb_loss:0.640005, cluster_loss:0.152631
Clustering   1390: ASW= 0.8298, DB= 0.2348, CH= 54384.8279
Training epoch 1391, recon_loss:0.772085, zinb_loss:0.640213, cluster_loss:0.152488
Clustering   1391: ASW= 0.8284, DB= 0.2346, CH= 54721.8953
Training epoch 1392, recon_loss:0.772427, zinb_loss:0.639817, cluster_loss:0.152825
Clustering   1392: ASW= 0.8295, DB= 0.2356, CH= 54297.4635
Training epoch 1393, recon_loss:0.772256, zinb_loss:0.640200, cluster_loss:0.152467
Clustering   1393: ASW= 0.8285, DB= 0.2345, CH= 54644.4699
Training epoch 1394, recon_loss:0.772506, zinb_loss:0.639754, cluster_loss:0.152980
Clustering   1394: ASW= 0.8290, DB= 0.2357, CH= 54064.9132
Training epoch 1395, recon_loss:0.772247, zinb_loss:0.640269, cluster_loss:0.152309
Clustering   1395: ASW= 0.8287, DB= 0.2344, CH= 54614.6933
Training epoch 1396, recon_loss:0.772559, zinb_loss:0.639751, cluster_loss:0.153014
Clustering   1396: ASW= 0.8286, DB= 0.2359, CH= 53910.2489
Training epoch 1397, recon_loss:0.772225, zinb_loss:0.640218, cluster_loss:0.152192
Clustering   1397: ASW= 0.8288, DB= 0.2344, CH= 54555.9312
Training epoch 1398, recon_loss:0.772444, zinb_loss:0.639629, cluster_loss:0.153082
Clustering   1398: ASW= 0.8280, DB= 0.2361, CH= 53665.6823
Training epoch 1399, recon_loss:0.771805, zinb_loss:0.640190, cluster_loss:0.152012
Clustering   1399: ASW= 0.8288, DB= 0.2338, CH= 54472.5884
Training epoch 1400, recon_loss:0.772179, zinb_loss:0.639541, cluster_loss:0.152912
Clustering   1400: ASW= 0.8277, DB= 0.2359, CH= 53660.7053
Training epoch 1401, recon_loss:0.771531, zinb_loss:0.639928, cluster_loss:0.152004
Clustering   1401: ASW= 0.8286, DB= 0.2344, CH= 54253.1947
Training epoch 1402, recon_loss:0.771881, zinb_loss:0.639451, cluster_loss:0.152713
Clustering   1402: ASW= 0.8278, DB= 0.2353, CH= 53763.1419
Training epoch 1403, recon_loss:0.771235, zinb_loss:0.639777, cluster_loss:0.151784
Clustering   1403: ASW= 0.8289, DB= 0.2344, CH= 54454.4181
Training epoch 1404, recon_loss:0.771695, zinb_loss:0.639306, cluster_loss:0.152505
Clustering   1404: ASW= 0.8278, DB= 0.2350, CH= 53912.0201
Training epoch 1405, recon_loss:0.770906, zinb_loss:0.639534, cluster_loss:0.151721
Clustering   1405: ASW= 0.8290, DB= 0.2341, CH= 54464.7775
Training epoch 1406, recon_loss:0.771493, zinb_loss:0.639203, cluster_loss:0.152312
Clustering   1406: ASW= 0.8281, DB= 0.2345, CH= 54193.3249
Training epoch 1407, recon_loss:0.770836, zinb_loss:0.639415, cluster_loss:0.151635
Clustering   1407: ASW= 0.8293, DB= 0.2346, CH= 54666.8438
Training epoch 1408, recon_loss:0.771380, zinb_loss:0.639143, cluster_loss:0.152154
Clustering   1408: ASW= 0.8283, DB= 0.2340, CH= 54451.6608
Training epoch 1409, recon_loss:0.770816, zinb_loss:0.639231, cluster_loss:0.151682
Clustering   1409: ASW= 0.8292, DB= 0.2346, CH= 54646.7350
Training epoch 1410, recon_loss:0.771443, zinb_loss:0.639096, cluster_loss:0.152075
Clustering   1410: ASW= 0.8285, DB= 0.2334, CH= 54604.9031
Training epoch 1411, recon_loss:0.770890, zinb_loss:0.639158, cluster_loss:0.151716
Clustering   1411: ASW= 0.8294, DB= 0.2346, CH= 54706.4227
Training epoch 1412, recon_loss:0.771499, zinb_loss:0.639153, cluster_loss:0.152013
Clustering   1412: ASW= 0.8285, DB= 0.2333, CH= 54792.2556
Training epoch 1413, recon_loss:0.771085, zinb_loss:0.639050, cluster_loss:0.151885
Clustering   1413: ASW= 0.8291, DB= 0.2356, CH= 54561.7477
Training epoch 1414, recon_loss:0.771887, zinb_loss:0.639223, cluster_loss:0.152052
Clustering   1414: ASW= 0.8286, DB= 0.2328, CH= 54874.3752
Training epoch 1415, recon_loss:0.771371, zinb_loss:0.639026, cluster_loss:0.152114
Clustering   1415: ASW= 0.8288, DB= 0.2360, CH= 54453.4938
Training epoch 1416, recon_loss:0.772349, zinb_loss:0.639457, cluster_loss:0.152063
Clustering   1416: ASW= 0.8288, DB= 0.2322, CH= 54898.2272
Training epoch 1417, recon_loss:0.771999, zinb_loss:0.638990, cluster_loss:0.152471
Clustering   1417: ASW= 0.8282, DB= 0.2377, CH= 54144.4925
Training epoch 1418, recon_loss:0.773227, zinb_loss:0.639582, cluster_loss:0.152191
Clustering   1418: ASW= 0.8290, DB= 0.2319, CH= 54865.1442
Training epoch 1419, recon_loss:0.772469, zinb_loss:0.638764, cluster_loss:0.152846
Clustering   1419: ASW= 0.8278, DB= 0.2389, CH= 53818.0596
Training epoch 1420, recon_loss:0.773526, zinb_loss:0.639486, cluster_loss:0.152219
Clustering   1420: ASW= 0.8296, DB= 0.2318, CH= 54813.2543
Training epoch 1421, recon_loss:0.772539, zinb_loss:0.638518, cluster_loss:0.152988
Clustering   1421: ASW= 0.8276, DB= 0.2392, CH= 53676.4965
Training epoch 1422, recon_loss:0.773251, zinb_loss:0.639302, cluster_loss:0.152174
Clustering   1422: ASW= 0.8299, DB= 0.2319, CH= 54764.5636
Training epoch 1423, recon_loss:0.772323, zinb_loss:0.638421, cluster_loss:0.152848
Clustering   1423: ASW= 0.8279, DB= 0.2386, CH= 53819.1749
Training epoch 1424, recon_loss:0.772838, zinb_loss:0.639342, cluster_loss:0.152017
Clustering   1424: ASW= 0.8303, DB= 0.2314, CH= 54877.3062
Training epoch 1425, recon_loss:0.771979, zinb_loss:0.638596, cluster_loss:0.152603
Clustering   1425: ASW= 0.8282, DB= 0.2375, CH= 54016.9811
Training epoch 1426, recon_loss:0.772317, zinb_loss:0.639475, cluster_loss:0.151859
Clustering   1426: ASW= 0.8306, DB= 0.2318, CH= 55070.8122
Training epoch 1427, recon_loss:0.771571, zinb_loss:0.638842, cluster_loss:0.152383
Clustering   1427: ASW= 0.8285, DB= 0.2370, CH= 54245.9790
Training epoch 1428, recon_loss:0.772037, zinb_loss:0.639590, cluster_loss:0.151766
Clustering   1428: ASW= 0.8308, DB= 0.2316, CH= 55225.0998
Training epoch 1429, recon_loss:0.771432, zinb_loss:0.638991, cluster_loss:0.152226
Clustering   1429: ASW= 0.8286, DB= 0.2363, CH= 54339.3585
Training epoch 1430, recon_loss:0.772133, zinb_loss:0.639512, cluster_loss:0.151766
Clustering   1430: ASW= 0.8306, DB= 0.2313, CH= 55301.0874
Training epoch 1431, recon_loss:0.771736, zinb_loss:0.639135, cluster_loss:0.152194
Clustering   1431: ASW= 0.8288, DB= 0.2362, CH= 54585.3976
Training epoch 1432, recon_loss:0.772542, zinb_loss:0.639696, cluster_loss:0.151780
Clustering   1432: ASW= 0.8308, DB= 0.2314, CH= 55356.2969
Training epoch 1433, recon_loss:0.772024, zinb_loss:0.639320, cluster_loss:0.152198
Clustering   1433: ASW= 0.8288, DB= 0.2358, CH= 54625.5232
Training epoch 1434, recon_loss:0.772652, zinb_loss:0.639797, cluster_loss:0.151862
Clustering   1434: ASW= 0.8307, DB= 0.2315, CH= 55378.2017
Training epoch 1435, recon_loss:0.772109, zinb_loss:0.639419, cluster_loss:0.152228
Clustering   1435: ASW= 0.8288, DB= 0.2360, CH= 54634.2800
Training epoch 1436, recon_loss:0.772615, zinb_loss:0.639803, cluster_loss:0.151946
Clustering   1436: ASW= 0.8307, DB= 0.2315, CH= 55364.8789
Training epoch 1437, recon_loss:0.772186, zinb_loss:0.639450, cluster_loss:0.152217
Clustering   1437: ASW= 0.8289, DB= 0.2357, CH= 54667.3469
Training epoch 1438, recon_loss:0.772624, zinb_loss:0.639638, cluster_loss:0.152112
Clustering   1438: ASW= 0.8304, DB= 0.2315, CH= 55245.2957
Training epoch 1439, recon_loss:0.772491, zinb_loss:0.639424, cluster_loss:0.152257
Clustering   1439: ASW= 0.8292, DB= 0.2353, CH= 54706.4187
Training epoch 1440, recon_loss:0.772881, zinb_loss:0.639403, cluster_loss:0.152371
Clustering   1440: ASW= 0.8300, DB= 0.2323, CH= 55020.8940
Training epoch 1441, recon_loss:0.772932, zinb_loss:0.639434, cluster_loss:0.152328
Clustering   1441: ASW= 0.8293, DB= 0.2346, CH= 54581.0326
Training epoch 1442, recon_loss:0.772795, zinb_loss:0.639016, cluster_loss:0.152637
Clustering   1442: ASW= 0.8295, DB= 0.2332, CH= 54678.1546
Training epoch 1443, recon_loss:0.772662, zinb_loss:0.639197, cluster_loss:0.152522
Clustering   1443: ASW= 0.8293, DB= 0.2352, CH= 54346.2627
Training epoch 1444, recon_loss:0.771920, zinb_loss:0.638727, cluster_loss:0.152515
Clustering   1444: ASW= 0.8288, DB= 0.2342, CH= 54147.9193
Training epoch 1445, recon_loss:0.771788, zinb_loss:0.638959, cluster_loss:0.152561
Clustering   1445: ASW= 0.8276, DB= 0.2378, CH= 53844.2491
Training epoch 1446, recon_loss:0.772936, zinb_loss:0.638988, cluster_loss:0.153884
Clustering   1446: ASW= 0.8280, DB= 0.2348, CH= 53354.0016
Training epoch 1447, recon_loss:0.772248, zinb_loss:0.639176, cluster_loss:0.152610
Clustering   1447: ASW= 0.8290, DB= 0.2357, CH= 54002.2283
Training epoch 1448, recon_loss:0.773897, zinb_loss:0.639109, cluster_loss:0.154721
Clustering   1448: ASW= 0.8266, DB= 0.2352, CH= 52883.8802
Training epoch 1449, recon_loss:0.777321, zinb_loss:0.639760, cluster_loss:0.154381
Clustering   1449: ASW= 0.8224, DB= 0.2433, CH= 51861.2071
Training epoch 1450, recon_loss:0.775597, zinb_loss:0.639327, cluster_loss:0.153430
Clustering   1450: ASW= 0.8259, DB= 0.2381, CH= 52838.2194
Training epoch 1451, recon_loss:0.772094, zinb_loss:0.638829, cluster_loss:0.152364
Clustering   1451: ASW= 0.8261, DB= 0.2389, CH= 52607.6735
Training epoch 1452, recon_loss:0.770926, zinb_loss:0.638589, cluster_loss:0.152091
Clustering   1452: ASW= 0.8275, DB= 0.2361, CH= 53903.0808
Training epoch 1453, recon_loss:0.770454, zinb_loss:0.638291, cluster_loss:0.151875
Clustering   1453: ASW= 0.8277, DB= 0.2361, CH= 53563.0658
Training epoch 1454, recon_loss:0.770039, zinb_loss:0.638421, cluster_loss:0.151669
Clustering   1454: ASW= 0.8286, DB= 0.2347, CH= 54531.1569
Training epoch 1455, recon_loss:0.769956, zinb_loss:0.638136, cluster_loss:0.151758
Clustering   1455: ASW= 0.8283, DB= 0.2354, CH= 53942.9018
Training epoch 1456, recon_loss:0.769886, zinb_loss:0.638518, cluster_loss:0.151486
Clustering   1456: ASW= 0.8293, DB= 0.2340, CH= 54921.4944
Training epoch 1457, recon_loss:0.769926, zinb_loss:0.638240, cluster_loss:0.151816
Clustering   1457: ASW= 0.8286, DB= 0.2353, CH= 54131.3247
Training epoch 1458, recon_loss:0.770206, zinb_loss:0.638897, cluster_loss:0.151431
Clustering   1458: ASW= 0.8298, DB= 0.2338, CH= 55220.3378
Training epoch 1459, recon_loss:0.770463, zinb_loss:0.638607, cluster_loss:0.152103
Clustering   1459: ASW= 0.8285, DB= 0.2357, CH= 54110.6906
Training epoch 1460, recon_loss:0.771299, zinb_loss:0.639628, cluster_loss:0.151572
Clustering   1460: ASW= 0.8301, DB= 0.2332, CH= 55251.4032
Training epoch 1461, recon_loss:0.771987, zinb_loss:0.639261, cluster_loss:0.152608
Clustering   1461: ASW= 0.8281, DB= 0.2366, CH= 53877.5904
Training epoch 1462, recon_loss:0.773203, zinb_loss:0.640359, cluster_loss:0.151897
Clustering   1462: ASW= 0.8300, DB= 0.2336, CH= 55016.5840
Training epoch 1463, recon_loss:0.773890, zinb_loss:0.639701, cluster_loss:0.152999
Clustering   1463: ASW= 0.8280, DB= 0.2368, CH= 53717.1440
Training epoch 1464, recon_loss:0.773658, zinb_loss:0.640287, cluster_loss:0.151989
Clustering   1464: ASW= 0.8301, DB= 0.2332, CH= 54827.6680
Training epoch 1465, recon_loss:0.773532, zinb_loss:0.639236, cluster_loss:0.152768
Clustering   1465: ASW= 0.8283, DB= 0.2366, CH= 54007.1876
Training epoch 1466, recon_loss:0.772617, zinb_loss:0.639637, cluster_loss:0.151759
Clustering   1466: ASW= 0.8304, DB= 0.2325, CH= 54978.0967
Training epoch 1467, recon_loss:0.771911, zinb_loss:0.638607, cluster_loss:0.152299
Clustering   1467: ASW= 0.8287, DB= 0.2364, CH= 54348.6262
Training epoch 1468, recon_loss:0.771728, zinb_loss:0.639071, cluster_loss:0.151544
Clustering   1468: ASW= 0.8306, DB= 0.2321, CH= 55166.5309
Training epoch 1469, recon_loss:0.771511, zinb_loss:0.638383, cluster_loss:0.151988
Clustering   1469: ASW= 0.8292, DB= 0.2354, CH= 54741.2045
Training epoch 1470, recon_loss:0.771677, zinb_loss:0.638753, cluster_loss:0.151469
Clustering   1470: ASW= 0.8307, DB= 0.2319, CH= 55269.0282
Training epoch 1471, recon_loss:0.771672, zinb_loss:0.638344, cluster_loss:0.151806
Clustering   1471: ASW= 0.8296, DB= 0.2348, CH= 55068.2689
Training epoch 1472, recon_loss:0.772098, zinb_loss:0.638704, cluster_loss:0.151551
Clustering   1472: ASW= 0.8307, DB= 0.2314, CH= 55320.1890
Training epoch 1473, recon_loss:0.772111, zinb_loss:0.638602, cluster_loss:0.151777
Clustering   1473: ASW= 0.8301, DB= 0.2344, CH= 55326.3990
Training epoch 1474, recon_loss:0.772626, zinb_loss:0.638941, cluster_loss:0.151835
Clustering   1474: ASW= 0.8304, DB= 0.2317, CH= 55192.0030
Training epoch 1475, recon_loss:0.772546, zinb_loss:0.639146, cluster_loss:0.151820
Clustering   1475: ASW= 0.8305, DB= 0.2341, CH= 55600.1142
Training epoch 1476, recon_loss:0.773071, zinb_loss:0.639313, cluster_loss:0.152297
Clustering   1476: ASW= 0.8300, DB= 0.2321, CH= 54886.5920
Training epoch 1477, recon_loss:0.772701, zinb_loss:0.639666, cluster_loss:0.151941
Clustering   1477: ASW= 0.8308, DB= 0.2334, CH= 55710.4009
Training epoch 1478, recon_loss:0.772924, zinb_loss:0.639418, cluster_loss:0.152765
Clustering   1478: ASW= 0.8295, DB= 0.2324, CH= 54477.0440
Training epoch 1479, recon_loss:0.772358, zinb_loss:0.639804, cluster_loss:0.152054
Clustering   1479: ASW= 0.8308, DB= 0.2336, CH= 55654.1050
Training epoch 1480, recon_loss:0.772299, zinb_loss:0.639218, cluster_loss:0.153102
Clustering   1480: ASW= 0.8291, DB= 0.2332, CH= 54068.6999
Training epoch 1481, recon_loss:0.771817, zinb_loss:0.639626, cluster_loss:0.152104
Clustering   1481: ASW= 0.8307, DB= 0.2334, CH= 55480.8532
Training epoch 1482, recon_loss:0.771602, zinb_loss:0.638895, cluster_loss:0.153181
Clustering   1482: ASW= 0.8288, DB= 0.2335, CH= 53833.4347
Training epoch 1483, recon_loss:0.771263, zinb_loss:0.639295, cluster_loss:0.152030
Clustering   1483: ASW= 0.8307, DB= 0.2333, CH= 55396.4697
Training epoch 1484, recon_loss:0.770999, zinb_loss:0.638703, cluster_loss:0.152880
Clustering   1484: ASW= 0.8291, DB= 0.2336, CH= 53980.6921
Training epoch 1485, recon_loss:0.770917, zinb_loss:0.639077, cluster_loss:0.151835
Clustering   1485: ASW= 0.8306, DB= 0.2335, CH= 55424.1083
Training epoch 1486, recon_loss:0.770758, zinb_loss:0.638671, cluster_loss:0.152770
Clustering   1486: ASW= 0.8292, DB= 0.2329, CH= 54166.6173
Training epoch 1487, recon_loss:0.770732, zinb_loss:0.638919, cluster_loss:0.151696
Clustering   1487: ASW= 0.8307, DB= 0.2332, CH= 55538.8257
Training epoch 1488, recon_loss:0.770634, zinb_loss:0.638627, cluster_loss:0.152366
Clustering   1488: ASW= 0.8297, DB= 0.2329, CH= 54531.2592
Training epoch 1489, recon_loss:0.770802, zinb_loss:0.638824, cluster_loss:0.151586
Clustering   1489: ASW= 0.8306, DB= 0.2337, CH= 55663.8326
Training epoch 1490, recon_loss:0.771036, zinb_loss:0.638755, cluster_loss:0.152185
Clustering   1490: ASW= 0.8302, DB= 0.2323, CH= 54790.8168
Training epoch 1491, recon_loss:0.771299, zinb_loss:0.638857, cluster_loss:0.151592
Clustering   1491: ASW= 0.8304, DB= 0.2342, CH= 55736.1367
Training epoch 1492, recon_loss:0.771659, zinb_loss:0.638938, cluster_loss:0.152160
Clustering   1492: ASW= 0.8305, DB= 0.2318, CH= 54915.6403
Training epoch 1493, recon_loss:0.771696, zinb_loss:0.638954, cluster_loss:0.151685
Clustering   1493: ASW= 0.8300, DB= 0.2350, CH= 55766.9713
Training epoch 1494, recon_loss:0.771913, zinb_loss:0.639188, cluster_loss:0.152233
Clustering   1494: ASW= 0.8307, DB= 0.2320, CH= 54907.7332
Training epoch 1495, recon_loss:0.772037, zinb_loss:0.639103, cluster_loss:0.151798
Clustering   1495: ASW= 0.8297, DB= 0.2348, CH= 55745.1994
Training epoch 1496, recon_loss:0.772467, zinb_loss:0.639348, cluster_loss:0.152308
Clustering   1496: ASW= 0.8309, DB= 0.2318, CH= 54890.7813
Training epoch 1497, recon_loss:0.772404, zinb_loss:0.639149, cluster_loss:0.151925
Clustering   1497: ASW= 0.8294, DB= 0.2357, CH= 55740.5966
Training epoch 1498, recon_loss:0.772332, zinb_loss:0.639419, cluster_loss:0.152376
Clustering   1498: ASW= 0.8309, DB= 0.2319, CH= 54660.5209
Training epoch 1499, recon_loss:0.772242, zinb_loss:0.639168, cluster_loss:0.151998
Clustering   1499: ASW= 0.8292, DB= 0.2356, CH= 55597.6126
Training epoch 1500, recon_loss:0.772234, zinb_loss:0.639390, cluster_loss:0.152354
Clustering   1500: ASW= 0.8309, DB= 0.2316, CH= 54614.2404
Training epoch 1501, recon_loss:0.771942, zinb_loss:0.638997, cluster_loss:0.151949
Clustering   1501: ASW= 0.8292, DB= 0.2357, CH= 55507.2467
Training epoch 1502, recon_loss:0.771585, zinb_loss:0.639148, cluster_loss:0.152174
Clustering   1502: ASW= 0.8310, DB= 0.2315, CH= 54688.5617
Training epoch 1503, recon_loss:0.771387, zinb_loss:0.638870, cluster_loss:0.151776
Clustering   1503: ASW= 0.8293, DB= 0.2356, CH= 55558.1030
Training epoch 1504, recon_loss:0.770958, zinb_loss:0.638929, cluster_loss:0.151985
Clustering   1504: ASW= 0.8312, DB= 0.2314, CH= 54845.1961
Training epoch 1505, recon_loss:0.771068, zinb_loss:0.638847, cluster_loss:0.151629
Clustering   1505: ASW= 0.8296, DB= 0.2353, CH= 55650.9120
Training epoch 1506, recon_loss:0.770752, zinb_loss:0.638751, cluster_loss:0.151973
Clustering   1506: ASW= 0.8310, DB= 0.2313, CH= 54954.2454
Training epoch 1507, recon_loss:0.771196, zinb_loss:0.638987, cluster_loss:0.151681
Clustering   1507: ASW= 0.8293, DB= 0.2350, CH= 55501.4372
Training epoch 1508, recon_loss:0.770929, zinb_loss:0.638906, cluster_loss:0.152014
Clustering   1508: ASW= 0.8302, DB= 0.2329, CH= 54448.9850
Training epoch 1509, recon_loss:0.771017, zinb_loss:0.638960, cluster_loss:0.151671
Clustering   1509: ASW= 0.8295, DB= 0.2348, CH= 55558.0561
Training epoch 1510, recon_loss:0.770633, zinb_loss:0.639007, cluster_loss:0.151926
Clustering   1510: ASW= 0.8311, DB= 0.2318, CH= 54925.2463
Training epoch 1511, recon_loss:0.771042, zinb_loss:0.639220, cluster_loss:0.151618
Clustering   1511: ASW= 0.8296, DB= 0.2341, CH= 55531.7540
Training epoch 1512, recon_loss:0.771349, zinb_loss:0.639359, cluster_loss:0.151979
Clustering   1512: ASW= 0.8311, DB= 0.2316, CH= 55208.2002
Training epoch 1513, recon_loss:0.771845, zinb_loss:0.639604, cluster_loss:0.151732
Clustering   1513: ASW= 0.8296, DB= 0.2333, CH= 55276.1432
Training epoch 1514, recon_loss:0.772170, zinb_loss:0.639526, cluster_loss:0.152207
Clustering   1514: ASW= 0.8308, DB= 0.2324, CH= 55316.7699
Training epoch 1515, recon_loss:0.772437, zinb_loss:0.639711, cluster_loss:0.151834
Clustering   1515: ASW= 0.8299, DB= 0.2326, CH= 55083.7788
Training epoch 1516, recon_loss:0.772015, zinb_loss:0.639113, cluster_loss:0.152435
Clustering   1516: ASW= 0.8302, DB= 0.2335, CH= 55234.3056
Training epoch 1517, recon_loss:0.771876, zinb_loss:0.639194, cluster_loss:0.151884
Clustering   1517: ASW= 0.8301, DB= 0.2325, CH= 54809.6581
Training epoch 1518, recon_loss:0.770984, zinb_loss:0.638289, cluster_loss:0.152413
Clustering   1518: ASW= 0.8297, DB= 0.2339, CH= 55064.2249
Training epoch 1519, recon_loss:0.770999, zinb_loss:0.638546, cluster_loss:0.151786
Clustering   1519: ASW= 0.8306, DB= 0.2319, CH= 54903.3539
Training epoch 1520, recon_loss:0.770280, zinb_loss:0.637760, cluster_loss:0.152288
Clustering   1520: ASW= 0.8296, DB= 0.2339, CH= 55031.9780
Training epoch 1521, recon_loss:0.770497, zinb_loss:0.638158, cluster_loss:0.151679
Clustering   1521: ASW= 0.8311, DB= 0.2317, CH= 55114.4178
Training epoch 1522, recon_loss:0.770128, zinb_loss:0.637595, cluster_loss:0.152093
Clustering   1522: ASW= 0.8296, DB= 0.2331, CH= 55167.4511
Training epoch 1523, recon_loss:0.770623, zinb_loss:0.638001, cluster_loss:0.151664
Clustering   1523: ASW= 0.8314, DB= 0.2319, CH= 55304.7215
Training epoch 1524, recon_loss:0.770709, zinb_loss:0.637679, cluster_loss:0.152053
Clustering   1524: ASW= 0.8297, DB= 0.2327, CH= 55308.4663
Training epoch 1525, recon_loss:0.771233, zinb_loss:0.638000, cluster_loss:0.151807
Clustering   1525: ASW= 0.8315, DB= 0.2321, CH= 55393.5116
Training epoch 1526, recon_loss:0.771215, zinb_loss:0.637864, cluster_loss:0.152045
Clustering   1526: ASW= 0.8298, DB= 0.2321, CH= 55411.1288
Training epoch 1527, recon_loss:0.771298, zinb_loss:0.637991, cluster_loss:0.151889
Clustering   1527: ASW= 0.8314, DB= 0.2329, CH= 55413.0791
Training epoch 1528, recon_loss:0.770950, zinb_loss:0.638025, cluster_loss:0.151909
Clustering   1528: ASW= 0.8301, DB= 0.2320, CH= 55562.8749
Training epoch 1529, recon_loss:0.770981, zinb_loss:0.637977, cluster_loss:0.151831
Clustering   1529: ASW= 0.8312, DB= 0.2336, CH= 55465.9097
Training epoch 1530, recon_loss:0.770621, zinb_loss:0.638176, cluster_loss:0.151744
Clustering   1530: ASW= 0.8304, DB= 0.2318, CH= 55688.3857
Training epoch 1531, recon_loss:0.770783, zinb_loss:0.638020, cluster_loss:0.151758
Clustering   1531: ASW= 0.8310, DB= 0.2338, CH= 55535.5689
Training epoch 1532, recon_loss:0.770536, zinb_loss:0.638393, cluster_loss:0.151630
Clustering   1532: ASW= 0.8306, DB= 0.2316, CH= 55773.6534
Training epoch 1533, recon_loss:0.770799, zinb_loss:0.638155, cluster_loss:0.151754
Clustering   1533: ASW= 0.8307, DB= 0.2342, CH= 55589.5773
Training epoch 1534, recon_loss:0.770587, zinb_loss:0.638687, cluster_loss:0.151576
Clustering   1534: ASW= 0.8309, DB= 0.2315, CH= 55829.8543
Training epoch 1535, recon_loss:0.770948, zinb_loss:0.638373, cluster_loss:0.151876
Clustering   1535: ASW= 0.8303, DB= 0.2349, CH= 55582.4980
Training epoch 1536, recon_loss:0.770849, zinb_loss:0.639092, cluster_loss:0.151585
Clustering   1536: ASW= 0.8312, DB= 0.2309, CH= 55791.2720
Training epoch 1537, recon_loss:0.771306, zinb_loss:0.638676, cluster_loss:0.152169
Clustering   1537: ASW= 0.8298, DB= 0.2356, CH= 55403.5113
Training epoch 1538, recon_loss:0.771371, zinb_loss:0.639545, cluster_loss:0.151725
Clustering   1538: ASW= 0.8313, DB= 0.2309, CH= 55528.1209
Training epoch 1539, recon_loss:0.771778, zinb_loss:0.638989, cluster_loss:0.152549
Clustering   1539: ASW= 0.8292, DB= 0.2366, CH= 55036.9383
Training epoch 1540, recon_loss:0.771756, zinb_loss:0.639789, cluster_loss:0.151911
Clustering   1540: ASW= 0.8311, DB= 0.2316, CH= 55153.9741
Training epoch 1541, recon_loss:0.772131, zinb_loss:0.639164, cluster_loss:0.152642
Clustering   1541: ASW= 0.8292, DB= 0.2355, CH= 54937.6862
Training epoch 1542, recon_loss:0.771431, zinb_loss:0.639625, cluster_loss:0.151834
Clustering   1542: ASW= 0.8311, DB= 0.2312, CH= 55145.5394
Training epoch 1543, recon_loss:0.771500, zinb_loss:0.639088, cluster_loss:0.152285
Clustering   1543: ASW= 0.8298, DB= 0.2343, CH= 55241.7947
Training epoch 1544, recon_loss:0.770674, zinb_loss:0.639249, cluster_loss:0.151570
Clustering   1544: ASW= 0.8313, DB= 0.2310, CH= 55408.8152
Training epoch 1545, recon_loss:0.770898, zinb_loss:0.638904, cluster_loss:0.151900
Clustering   1545: ASW= 0.8303, DB= 0.2334, CH= 55626.4227
Training epoch 1546, recon_loss:0.770306, zinb_loss:0.638985, cluster_loss:0.151428
Clustering   1546: ASW= 0.8311, DB= 0.2310, CH= 55601.3726
Training epoch 1547, recon_loss:0.770606, zinb_loss:0.638939, cluster_loss:0.151700
Clustering   1547: ASW= 0.8305, DB= 0.2327, CH= 55851.0166
Training epoch 1548, recon_loss:0.770487, zinb_loss:0.638911, cluster_loss:0.151466
Clustering   1548: ASW= 0.8307, DB= 0.2319, CH= 55570.6681
Training epoch 1549, recon_loss:0.771068, zinb_loss:0.639106, cluster_loss:0.151669
Clustering   1549: ASW= 0.8306, DB= 0.2327, CH= 56040.2589
Training epoch 1550, recon_loss:0.771138, zinb_loss:0.638966, cluster_loss:0.151734
Clustering   1550: ASW= 0.8299, DB= 0.2325, CH= 55352.5163
Training epoch 1551, recon_loss:0.771838, zinb_loss:0.639509, cluster_loss:0.151808
Clustering   1551: ASW= 0.8305, DB= 0.2318, CH= 56002.4530
Training epoch 1552, recon_loss:0.772156, zinb_loss:0.639136, cluster_loss:0.152185
Clustering   1552: ASW= 0.8288, DB= 0.2339, CH= 54941.6100
Training epoch 1553, recon_loss:0.772611, zinb_loss:0.639795, cluster_loss:0.152047
Clustering   1553: ASW= 0.8305, DB= 0.2306, CH= 55729.7692
Training epoch 1554, recon_loss:0.772318, zinb_loss:0.639087, cluster_loss:0.152327
Clustering   1554: ASW= 0.8287, DB= 0.2341, CH= 54800.6317
Training epoch 1555, recon_loss:0.772329, zinb_loss:0.639584, cluster_loss:0.151976
Clustering   1555: ASW= 0.8308, DB= 0.2304, CH= 55793.2278
Training epoch 1556, recon_loss:0.771456, zinb_loss:0.638802, cluster_loss:0.152052
Clustering   1556: ASW= 0.8296, DB= 0.2331, CH= 55100.3608
Training epoch 1557, recon_loss:0.771473, zinb_loss:0.639037, cluster_loss:0.151742
Clustering   1557: ASW= 0.8311, DB= 0.2305, CH= 56000.9700
Training epoch 1558, recon_loss:0.770689, zinb_loss:0.638491, cluster_loss:0.151799
Clustering   1558: ASW= 0.8303, DB= 0.2326, CH= 55408.2188
Training epoch 1559, recon_loss:0.770940, zinb_loss:0.638621, cluster_loss:0.151601
Clustering   1559: ASW= 0.8313, DB= 0.2307, CH= 56192.4526
Training epoch 1560, recon_loss:0.770313, zinb_loss:0.638310, cluster_loss:0.151638
Clustering   1560: ASW= 0.8309, DB= 0.2324, CH= 55675.6703
Training epoch 1561, recon_loss:0.770726, zinb_loss:0.638355, cluster_loss:0.151600
Clustering   1561: ASW= 0.8313, DB= 0.2308, CH= 56252.0157
Training epoch 1562, recon_loss:0.770281, zinb_loss:0.638245, cluster_loss:0.151591
Clustering   1562: ASW= 0.8313, DB= 0.2320, CH= 55857.3025
Training epoch 1563, recon_loss:0.770865, zinb_loss:0.638207, cluster_loss:0.151738
Clustering   1563: ASW= 0.8311, DB= 0.2310, CH= 56204.6150
Training epoch 1564, recon_loss:0.770499, zinb_loss:0.638292, cluster_loss:0.151659
Clustering   1564: ASW= 0.8316, DB= 0.2315, CH= 55950.7342
Training epoch 1565, recon_loss:0.771067, zinb_loss:0.638133, cluster_loss:0.151944
Clustering   1565: ASW= 0.8309, DB= 0.2310, CH= 56090.9688
Training epoch 1566, recon_loss:0.770704, zinb_loss:0.638344, cluster_loss:0.151737
Clustering   1566: ASW= 0.8317, DB= 0.2314, CH= 55990.6069
Training epoch 1567, recon_loss:0.771079, zinb_loss:0.638106, cluster_loss:0.152058
Clustering   1567: ASW= 0.8310, DB= 0.2309, CH= 56021.8463
Training epoch 1568, recon_loss:0.770724, zinb_loss:0.638327, cluster_loss:0.151755
Clustering   1568: ASW= 0.8317, DB= 0.2316, CH= 56030.4685
Training epoch 1569, recon_loss:0.771030, zinb_loss:0.638079, cluster_loss:0.152140
Clustering   1569: ASW= 0.8311, DB= 0.2306, CH= 55931.4126
Training epoch 1570, recon_loss:0.770662, zinb_loss:0.638284, cluster_loss:0.151739
Clustering   1570: ASW= 0.8315, DB= 0.2315, CH= 56019.6934
Training epoch 1571, recon_loss:0.770933, zinb_loss:0.638106, cluster_loss:0.152130
Clustering   1571: ASW= 0.8314, DB= 0.2306, CH= 55953.1675
Training epoch 1572, recon_loss:0.770594, zinb_loss:0.638254, cluster_loss:0.151694
Clustering   1572: ASW= 0.8313, DB= 0.2321, CH= 56049.7122
Training epoch 1573, recon_loss:0.770832, zinb_loss:0.638156, cluster_loss:0.152134
Clustering   1573: ASW= 0.8317, DB= 0.2301, CH= 55888.0989
Training epoch 1574, recon_loss:0.770504, zinb_loss:0.638280, cluster_loss:0.151651
Clustering   1574: ASW= 0.8310, DB= 0.2326, CH= 56044.7681
Training epoch 1575, recon_loss:0.770850, zinb_loss:0.638431, cluster_loss:0.152044
Clustering   1575: ASW= 0.8321, DB= 0.2294, CH= 55944.1099
Training epoch 1576, recon_loss:0.770529, zinb_loss:0.638475, cluster_loss:0.151575
Clustering   1576: ASW= 0.8308, DB= 0.2323, CH= 56118.4888
Training epoch 1577, recon_loss:0.770770, zinb_loss:0.638614, cluster_loss:0.152052
Clustering   1577: ASW= 0.8320, DB= 0.2299, CH= 55852.9902
Training epoch 1578, recon_loss:0.770645, zinb_loss:0.638696, cluster_loss:0.151636
Clustering   1578: ASW= 0.8303, DB= 0.2338, CH= 56111.0675
Training epoch 1579, recon_loss:0.771273, zinb_loss:0.639163, cluster_loss:0.152047
Clustering   1579: ASW= 0.8324, DB= 0.2298, CH= 55731.1507
Training epoch 1580, recon_loss:0.771346, zinb_loss:0.639163, cluster_loss:0.151740
Clustering   1580: ASW= 0.8300, DB= 0.2345, CH= 56011.9364
Training epoch 1581, recon_loss:0.771802, zinb_loss:0.639657, cluster_loss:0.152176
Clustering   1581: ASW= 0.8321, DB= 0.2304, CH= 55540.1757
Training epoch 1582, recon_loss:0.772081, zinb_loss:0.639690, cluster_loss:0.152007
Clustering   1582: ASW= 0.8301, DB= 0.2337, CH= 56093.6077
Training epoch 1583, recon_loss:0.772565, zinb_loss:0.640191, cluster_loss:0.152392
Clustering   1583: ASW= 0.8321, DB= 0.2301, CH= 55300.5527
Training epoch 1584, recon_loss:0.772544, zinb_loss:0.639764, cluster_loss:0.152314
Clustering   1584: ASW= 0.8297, DB= 0.2344, CH= 55777.6551
Training epoch 1585, recon_loss:0.772187, zinb_loss:0.639910, cluster_loss:0.152444
Clustering   1585: ASW= 0.8319, DB= 0.2304, CH= 54962.6357
Training epoch 1586, recon_loss:0.772646, zinb_loss:0.639876, cluster_loss:0.152833
Clustering   1586: ASW= 0.8287, DB= 0.2346, CH= 55096.5719
Training epoch 1587, recon_loss:0.774406, zinb_loss:0.640095, cluster_loss:0.153536
Clustering   1587: ASW= 0.8288, DB= 0.2349, CH= 53272.9338
Training epoch 1588, recon_loss:0.772588, zinb_loss:0.638809, cluster_loss:0.152257
Clustering   1588: ASW= 0.8292, DB= 0.2360, CH= 54339.3411
Training epoch 1589, recon_loss:0.771132, zinb_loss:0.638414, cluster_loss:0.152148
Clustering   1589: ASW= 0.8299, DB= 0.2329, CH= 54761.9965
Training epoch 1590, recon_loss:0.771052, zinb_loss:0.638576, cluster_loss:0.151766
Clustering   1590: ASW= 0.8306, DB= 0.2332, CH= 55340.8002
Training epoch 1591, recon_loss:0.770910, zinb_loss:0.638325, cluster_loss:0.152164
Clustering   1591: ASW= 0.8301, DB= 0.2334, CH= 55193.5861
Training epoch 1592, recon_loss:0.770916, zinb_loss:0.638664, cluster_loss:0.151878
Clustering   1592: ASW= 0.8306, DB= 0.2325, CH= 55291.7209
Training epoch 1593, recon_loss:0.771125, zinb_loss:0.638385, cluster_loss:0.152154
Clustering   1593: ASW= 0.8305, DB= 0.2341, CH= 55634.9919
Training epoch 1594, recon_loss:0.771097, zinb_loss:0.638666, cluster_loss:0.152061
Clustering   1594: ASW= 0.8305, DB= 0.2316, CH= 55174.5046
Training epoch 1595, recon_loss:0.771215, zinb_loss:0.638407, cluster_loss:0.152318
Clustering   1595: ASW= 0.8305, DB= 0.2347, CH= 55799.7640
Training epoch 1596, recon_loss:0.771186, zinb_loss:0.638574, cluster_loss:0.152400
Clustering   1596: ASW= 0.8302, DB= 0.2313, CH= 54857.1873
Training epoch 1597, recon_loss:0.771265, zinb_loss:0.638416, cluster_loss:0.152387
Clustering   1597: ASW= 0.8309, DB= 0.2345, CH= 56151.9025
Training epoch 1598, recon_loss:0.771154, zinb_loss:0.638394, cluster_loss:0.152710
Clustering   1598: ASW= 0.8299, DB= 0.2313, CH= 54637.3756
Training epoch 1599, recon_loss:0.770842, zinb_loss:0.638340, cluster_loss:0.152211
Clustering   1599: ASW= 0.8313, DB= 0.2340, CH= 56393.1242
Training epoch 1600, recon_loss:0.770623, zinb_loss:0.638154, cluster_loss:0.152608
Clustering   1600: ASW= 0.8299, DB= 0.2314, CH= 54650.1162
Training epoch 1601, recon_loss:0.770174, zinb_loss:0.638265, cluster_loss:0.151776
Clustering   1601: ASW= 0.8319, DB= 0.2334, CH= 56620.1042
Training epoch 1602, recon_loss:0.769887, zinb_loss:0.637980, cluster_loss:0.152255
Clustering   1602: ASW= 0.8300, DB= 0.2318, CH= 54877.8790
Training epoch 1603, recon_loss:0.769719, zinb_loss:0.638302, cluster_loss:0.151413
Clustering   1603: ASW= 0.8324, DB= 0.2321, CH= 56808.8364
Training epoch 1604, recon_loss:0.769485, zinb_loss:0.637986, cluster_loss:0.152039
Clustering   1604: ASW= 0.8301, DB= 0.2322, CH= 55059.8098
Training epoch 1605, recon_loss:0.769699, zinb_loss:0.638531, cluster_loss:0.151232
Clustering   1605: ASW= 0.8327, DB= 0.2317, CH= 56951.5883
Training epoch 1606, recon_loss:0.769619, zinb_loss:0.638235, cluster_loss:0.152007
Clustering   1606: ASW= 0.8302, DB= 0.2322, CH= 55120.6269
Training epoch 1607, recon_loss:0.770178, zinb_loss:0.638973, cluster_loss:0.151192
Clustering   1607: ASW= 0.8329, DB= 0.2312, CH= 57040.0228
Training epoch 1608, recon_loss:0.770262, zinb_loss:0.638647, cluster_loss:0.152109
Clustering   1608: ASW= 0.8302, DB= 0.2324, CH= 55126.7691
Training epoch 1609, recon_loss:0.770924, zinb_loss:0.639386, cluster_loss:0.151249
Clustering   1609: ASW= 0.8328, DB= 0.2305, CH= 57006.8973
Training epoch 1610, recon_loss:0.770989, zinb_loss:0.638963, cluster_loss:0.152174
Clustering   1610: ASW= 0.8304, DB= 0.2324, CH= 55132.5569
Training epoch 1611, recon_loss:0.771444, zinb_loss:0.639637, cluster_loss:0.151273
Clustering   1611: ASW= 0.8328, DB= 0.2302, CH= 57061.1098
Training epoch 1612, recon_loss:0.771460, zinb_loss:0.639066, cluster_loss:0.152188
Clustering   1612: ASW= 0.8305, DB= 0.2326, CH= 55184.3293
Training epoch 1613, recon_loss:0.771440, zinb_loss:0.639497, cluster_loss:0.151334
Clustering   1613: ASW= 0.8323, DB= 0.2305, CH= 56865.8570
Training epoch 1614, recon_loss:0.771446, zinb_loss:0.638826, cluster_loss:0.152046
Clustering   1614: ASW= 0.8308, DB= 0.2322, CH= 55368.5911
Training epoch 1615, recon_loss:0.771504, zinb_loss:0.639388, cluster_loss:0.151291
Clustering   1615: ASW= 0.8324, DB= 0.2297, CH= 57013.2568
Training epoch 1616, recon_loss:0.770887, zinb_loss:0.638787, cluster_loss:0.151875
Clustering   1616: ASW= 0.8311, DB= 0.2326, CH= 55512.8815
Training epoch 1617, recon_loss:0.770613, zinb_loss:0.639145, cluster_loss:0.151268
Clustering   1617: ASW= 0.8325, DB= 0.2294, CH= 56900.2553
Training epoch 1618, recon_loss:0.770505, zinb_loss:0.638645, cluster_loss:0.151667
Clustering   1618: ASW= 0.8314, DB= 0.2318, CH= 55813.7164
Training epoch 1619, recon_loss:0.770317, zinb_loss:0.638883, cluster_loss:0.151179
Clustering   1619: ASW= 0.8324, DB= 0.2293, CH= 56919.6323
Training epoch 1620, recon_loss:0.770200, zinb_loss:0.638511, cluster_loss:0.151517
Clustering   1620: ASW= 0.8317, DB= 0.2314, CH= 56069.8930
Training epoch 1621, recon_loss:0.770113, zinb_loss:0.638642, cluster_loss:0.151186
Clustering   1621: ASW= 0.8323, DB= 0.2296, CH= 56930.2633
Training epoch 1622, recon_loss:0.770017, zinb_loss:0.638426, cluster_loss:0.151388
Clustering   1622: ASW= 0.8320, DB= 0.2310, CH= 56232.4816
Training epoch 1623, recon_loss:0.769977, zinb_loss:0.638439, cluster_loss:0.151257
Clustering   1623: ASW= 0.8320, DB= 0.2299, CH= 56857.4420
Training epoch 1624, recon_loss:0.769949, zinb_loss:0.638444, cluster_loss:0.151286
Clustering   1624: ASW= 0.8323, DB= 0.2304, CH= 56353.4079
Training epoch 1625, recon_loss:0.770079, zinb_loss:0.638375, cluster_loss:0.151490
Clustering   1625: ASW= 0.8317, DB= 0.2301, CH= 56680.9751
Training epoch 1626, recon_loss:0.770317, zinb_loss:0.638654, cluster_loss:0.151407
Clustering   1626: ASW= 0.8322, DB= 0.2302, CH= 56172.8841
Training epoch 1627, recon_loss:0.770244, zinb_loss:0.638345, cluster_loss:0.151947
Clustering   1627: ASW= 0.8310, DB= 0.2310, CH= 56174.6695
Training epoch 1628, recon_loss:0.770653, zinb_loss:0.638865, cluster_loss:0.151724
Clustering   1628: ASW= 0.8318, DB= 0.2301, CH= 55706.1215
Training epoch 1629, recon_loss:0.770169, zinb_loss:0.638277, cluster_loss:0.152341
Clustering   1629: ASW= 0.8306, DB= 0.2319, CH= 55708.7751
Training epoch 1630, recon_loss:0.770492, zinb_loss:0.638816, cluster_loss:0.151771
Clustering   1630: ASW= 0.8313, DB= 0.2304, CH= 55515.6856
Training epoch 1631, recon_loss:0.770147, zinb_loss:0.638216, cluster_loss:0.152336
Clustering   1631: ASW= 0.8306, DB= 0.2319, CH= 55574.4789
Training epoch 1632, recon_loss:0.770352, zinb_loss:0.638617, cluster_loss:0.151528
Clustering   1632: ASW= 0.8313, DB= 0.2303, CH= 55658.1852
Training epoch 1633, recon_loss:0.770265, zinb_loss:0.638217, cluster_loss:0.152130
Clustering   1633: ASW= 0.8309, DB= 0.2313, CH= 55737.8702
Training epoch 1634, recon_loss:0.770345, zinb_loss:0.638450, cluster_loss:0.151301
Clustering   1634: ASW= 0.8313, DB= 0.2305, CH= 55899.3523
Training epoch 1635, recon_loss:0.770231, zinb_loss:0.638102, cluster_loss:0.151893
Clustering   1635: ASW= 0.8311, DB= 0.2309, CH= 55949.0231
Training epoch 1636, recon_loss:0.770250, zinb_loss:0.638202, cluster_loss:0.151211
Clustering   1636: ASW= 0.8314, DB= 0.2306, CH= 56049.1601
Training epoch 1637, recon_loss:0.770261, zinb_loss:0.638025, cluster_loss:0.151705
Clustering   1637: ASW= 0.8314, DB= 0.2306, CH= 56126.1620
Training epoch 1638, recon_loss:0.770425, zinb_loss:0.638042, cluster_loss:0.151154
Clustering   1638: ASW= 0.8315, DB= 0.2305, CH= 56279.7242
Training epoch 1639, recon_loss:0.770384, zinb_loss:0.637941, cluster_loss:0.151574
Clustering   1639: ASW= 0.8314, DB= 0.2303, CH= 56224.6343
Training epoch 1640, recon_loss:0.770651, zinb_loss:0.637913, cluster_loss:0.151214
Clustering   1640: ASW= 0.8316, DB= 0.2307, CH= 56413.2112
Training epoch 1641, recon_loss:0.770648, zinb_loss:0.638014, cluster_loss:0.151547
Clustering   1641: ASW= 0.8315, DB= 0.2299, CH= 56204.9497
Training epoch 1642, recon_loss:0.771019, zinb_loss:0.637913, cluster_loss:0.151418
Clustering   1642: ASW= 0.8315, DB= 0.2307, CH= 56456.4862
Training epoch 1643, recon_loss:0.771226, zinb_loss:0.638253, cluster_loss:0.151690
Clustering   1643: ASW= 0.8315, DB= 0.2292, CH= 56001.4068
Training epoch 1644, recon_loss:0.771596, zinb_loss:0.637969, cluster_loss:0.151842
Clustering   1644: ASW= 0.8311, DB= 0.2320, CH= 56307.7916
Training epoch 1645, recon_loss:0.771955, zinb_loss:0.638502, cluster_loss:0.152037
Clustering   1645: ASW= 0.8314, DB= 0.2301, CH= 55545.5936
Training epoch 1646, recon_loss:0.771684, zinb_loss:0.637909, cluster_loss:0.152070
Clustering   1646: ASW= 0.8310, DB= 0.2332, CH= 56178.3783
Training epoch 1647, recon_loss:0.771474, zinb_loss:0.638323, cluster_loss:0.151933
Clustering   1647: ASW= 0.8318, DB= 0.2298, CH= 55575.0934
Training epoch 1648, recon_loss:0.770580, zinb_loss:0.637706, cluster_loss:0.151750
Clustering   1648: ASW= 0.8315, DB= 0.2328, CH= 56385.2826
Training epoch 1649, recon_loss:0.770398, zinb_loss:0.637975, cluster_loss:0.151566
Clustering   1649: ASW= 0.8322, DB= 0.2284, CH= 55975.2145
Training epoch 1650, recon_loss:0.769755, zinb_loss:0.637630, cluster_loss:0.151469
Clustering   1650: ASW= 0.8320, DB= 0.2322, CH= 56680.0193
Training epoch 1651, recon_loss:0.769968, zinb_loss:0.637812, cluster_loss:0.151480
Clustering   1651: ASW= 0.8323, DB= 0.2286, CH= 56212.9997
Training epoch 1652, recon_loss:0.769633, zinb_loss:0.637684, cluster_loss:0.151403
Clustering   1652: ASW= 0.8324, DB= 0.2319, CH= 56886.3414
Training epoch 1653, recon_loss:0.770028, zinb_loss:0.637795, cluster_loss:0.151606
Clustering   1653: ASW= 0.8322, DB= 0.2288, CH= 56259.5148
Training epoch 1654, recon_loss:0.769829, zinb_loss:0.637825, cluster_loss:0.151461
Clustering   1654: ASW= 0.8325, DB= 0.2321, CH= 57001.7429
Training epoch 1655, recon_loss:0.770307, zinb_loss:0.637875, cluster_loss:0.151868
Clustering   1655: ASW= 0.8320, DB= 0.2295, CH= 56193.8020
Training epoch 1656, recon_loss:0.770046, zinb_loss:0.638021, cluster_loss:0.151562
Clustering   1656: ASW= 0.8324, DB= 0.2320, CH= 56950.8587
Training epoch 1657, recon_loss:0.770651, zinb_loss:0.638036, cluster_loss:0.152069
Clustering   1657: ASW= 0.8320, DB= 0.2303, CH= 56129.7716
Training epoch 1658, recon_loss:0.770301, zinb_loss:0.638252, cluster_loss:0.151610
Clustering   1658: ASW= 0.8321, DB= 0.2320, CH= 56744.8793
Training epoch 1659, recon_loss:0.770926, zinb_loss:0.638196, cluster_loss:0.152136
Clustering   1659: ASW= 0.8320, DB= 0.2303, CH= 56090.4722
Training epoch 1660, recon_loss:0.770471, zinb_loss:0.638473, cluster_loss:0.151543
Clustering   1660: ASW= 0.8319, DB= 0.2315, CH= 56618.5035
Training epoch 1661, recon_loss:0.770879, zinb_loss:0.638309, cluster_loss:0.152063
Clustering   1661: ASW= 0.8321, DB= 0.2303, CH= 56100.3900
Training epoch 1662, recon_loss:0.770461, zinb_loss:0.638506, cluster_loss:0.151464
Clustering   1662: ASW= 0.8316, DB= 0.2314, CH= 56370.6700
Training epoch 1663, recon_loss:0.770582, zinb_loss:0.638233, cluster_loss:0.151930
Clustering   1663: ASW= 0.8321, DB= 0.2301, CH= 56113.8545
Training epoch 1664, recon_loss:0.770511, zinb_loss:0.638428, cluster_loss:0.151274
Clustering   1664: ASW= 0.8319, DB= 0.2315, CH= 56462.8819
Training epoch 1665, recon_loss:0.770450, zinb_loss:0.638075, cluster_loss:0.151736
Clustering   1665: ASW= 0.8322, DB= 0.2300, CH= 56292.1795
Training epoch 1666, recon_loss:0.770594, zinb_loss:0.638202, cluster_loss:0.151203
Clustering   1666: ASW= 0.8320, DB= 0.2313, CH= 56472.2717
Training epoch 1667, recon_loss:0.770641, zinb_loss:0.637881, cluster_loss:0.151679
Clustering   1667: ASW= 0.8321, DB= 0.2299, CH= 56329.6259
Training epoch 1668, recon_loss:0.770840, zinb_loss:0.638069, cluster_loss:0.151160
Clustering   1668: ASW= 0.8324, DB= 0.2307, CH= 56644.0672
Training epoch 1669, recon_loss:0.770923, zinb_loss:0.637721, cluster_loss:0.151718
Clustering   1669: ASW= 0.8319, DB= 0.2298, CH= 56333.1850
Training epoch 1670, recon_loss:0.770975, zinb_loss:0.637929, cluster_loss:0.151236
Clustering   1670: ASW= 0.8326, DB= 0.2303, CH= 56670.7962
Training epoch 1671, recon_loss:0.770966, zinb_loss:0.637559, cluster_loss:0.151800
Clustering   1671: ASW= 0.8316, DB= 0.2301, CH= 56242.8785
Training epoch 1672, recon_loss:0.771193, zinb_loss:0.637922, cluster_loss:0.151271
Clustering   1672: ASW= 0.8332, DB= 0.2299, CH= 56861.3801
Training epoch 1673, recon_loss:0.770859, zinb_loss:0.637494, cluster_loss:0.151857
Clustering   1673: ASW= 0.8313, DB= 0.2308, CH= 56236.5120
Training epoch 1674, recon_loss:0.771239, zinb_loss:0.637926, cluster_loss:0.151389
Clustering   1674: ASW= 0.8333, DB= 0.2299, CH= 56789.3649
Training epoch 1675, recon_loss:0.770702, zinb_loss:0.637491, cluster_loss:0.151864
Clustering   1675: ASW= 0.8309, DB= 0.2310, CH= 56188.6124
Training epoch 1676, recon_loss:0.771117, zinb_loss:0.637972, cluster_loss:0.151389
Clustering   1676: ASW= 0.8337, DB= 0.2294, CH= 56937.3040
Training epoch 1677, recon_loss:0.770281, zinb_loss:0.637484, cluster_loss:0.151749
Clustering   1677: ASW= 0.8309, DB= 0.2313, CH= 56328.4641
Training epoch 1678, recon_loss:0.770687, zinb_loss:0.637886, cluster_loss:0.151421
Clustering   1678: ASW= 0.8336, DB= 0.2296, CH= 56861.3095
Training epoch 1679, recon_loss:0.770022, zinb_loss:0.637497, cluster_loss:0.151592
Clustering   1679: ASW= 0.8310, DB= 0.2308, CH= 56434.3613
Training epoch 1680, recon_loss:0.770383, zinb_loss:0.637826, cluster_loss:0.151392
Clustering   1680: ASW= 0.8337, DB= 0.2292, CH= 56966.7895
Training epoch 1681, recon_loss:0.769784, zinb_loss:0.637552, cluster_loss:0.151421
Clustering   1681: ASW= 0.8312, DB= 0.2306, CH= 56619.6128
Training epoch 1682, recon_loss:0.770288, zinb_loss:0.637766, cluster_loss:0.151541
Clustering   1682: ASW= 0.8335, DB= 0.2295, CH= 56924.8402
Training epoch 1683, recon_loss:0.770226, zinb_loss:0.637787, cluster_loss:0.151453
Clustering   1683: ASW= 0.8313, DB= 0.2303, CH= 56495.9768
Training epoch 1684, recon_loss:0.771132, zinb_loss:0.637815, cluster_loss:0.152191
Clustering   1684: ASW= 0.8328, DB= 0.2306, CH= 56423.9918
Training epoch 1685, recon_loss:0.771994, zinb_loss:0.638307, cluster_loss:0.152156
Clustering   1685: ASW= 0.8307, DB= 0.2324, CH= 55563.3971
Training epoch 1686, recon_loss:0.772044, zinb_loss:0.637759, cluster_loss:0.152744
Clustering   1686: ASW= 0.8322, DB= 0.2312, CH= 55814.7295
Training epoch 1687, recon_loss:0.771631, zinb_loss:0.638233, cluster_loss:0.152089
Clustering   1687: ASW= 0.8310, DB= 0.2320, CH= 55516.9378
Training epoch 1688, recon_loss:0.770501, zinb_loss:0.637587, cluster_loss:0.152068
Clustering   1688: ASW= 0.8326, DB= 0.2315, CH= 55958.3464
Training epoch 1689, recon_loss:0.770112, zinb_loss:0.638003, cluster_loss:0.151271
Clustering   1689: ASW= 0.8319, DB= 0.2301, CH= 56400.0686
Training epoch 1690, recon_loss:0.770101, zinb_loss:0.637936, cluster_loss:0.151650
Clustering   1690: ASW= 0.8329, DB= 0.2309, CH= 56344.1191
Training epoch 1691, recon_loss:0.770264, zinb_loss:0.638606, cluster_loss:0.151116
Clustering   1691: ASW= 0.8323, DB= 0.2291, CH= 56820.6809
Training epoch 1692, recon_loss:0.770479, zinb_loss:0.638903, cluster_loss:0.151597
Clustering   1692: ASW= 0.8330, DB= 0.2303, CH= 56578.8421
Training epoch 1693, recon_loss:0.770542, zinb_loss:0.639426, cluster_loss:0.151177
Clustering   1693: ASW= 0.8326, DB= 0.2289, CH= 57008.1041
Training epoch 1694, recon_loss:0.770972, zinb_loss:0.639729, cluster_loss:0.151617
Clustering   1694: ASW= 0.8332, DB= 0.2300, CH= 56694.0766
Training epoch 1695, recon_loss:0.770528, zinb_loss:0.639676, cluster_loss:0.151270
Clustering   1695: ASW= 0.8324, DB= 0.2298, CH= 57126.2269
Training epoch 1696, recon_loss:0.771007, zinb_loss:0.639874, cluster_loss:0.151655
Clustering   1696: ASW= 0.8331, DB= 0.2300, CH= 56673.3355
Training epoch 1697, recon_loss:0.770333, zinb_loss:0.639599, cluster_loss:0.151356
Clustering   1697: ASW= 0.8321, DB= 0.2306, CH= 57051.2279
Training epoch 1698, recon_loss:0.770806, zinb_loss:0.639687, cluster_loss:0.151559
Clustering   1698: ASW= 0.8332, DB= 0.2294, CH= 56633.1917
Training epoch 1699, recon_loss:0.769994, zinb_loss:0.639262, cluster_loss:0.151346
Clustering   1699: ASW= 0.8321, DB= 0.2307, CH= 57105.5004
Training epoch 1700, recon_loss:0.770634, zinb_loss:0.639445, cluster_loss:0.151503
Clustering   1700: ASW= 0.8332, DB= 0.2289, CH= 56669.0357
Training epoch 1701, recon_loss:0.770062, zinb_loss:0.639138, cluster_loss:0.151367
Clustering   1701: ASW= 0.8320, DB= 0.2313, CH= 56996.3163
Training epoch 1702, recon_loss:0.770829, zinb_loss:0.639356, cluster_loss:0.151424
Clustering   1702: ASW= 0.8332, DB= 0.2287, CH= 56650.1569
Training epoch 1703, recon_loss:0.769805, zinb_loss:0.638908, cluster_loss:0.151425
Clustering   1703: ASW= 0.8321, DB= 0.2312, CH= 57078.2940
Training epoch 1704, recon_loss:0.770250, zinb_loss:0.639028, cluster_loss:0.151342
Clustering   1704: ASW= 0.8334, DB= 0.2282, CH= 56793.4144
Training epoch 1705, recon_loss:0.769636, zinb_loss:0.638806, cluster_loss:0.151362
Clustering   1705: ASW= 0.8324, DB= 0.2308, CH= 57100.0732
Training epoch 1706, recon_loss:0.769985, zinb_loss:0.638849, cluster_loss:0.151314
Clustering   1706: ASW= 0.8331, DB= 0.2282, CH= 56880.8331
Training epoch 1707, recon_loss:0.769330, zinb_loss:0.638541, cluster_loss:0.151332
Clustering   1707: ASW= 0.8326, DB= 0.2304, CH= 57130.8785
Training epoch 1708, recon_loss:0.769784, zinb_loss:0.638581, cluster_loss:0.151314
Clustering   1708: ASW= 0.8331, DB= 0.2280, CH= 57031.5683
Training epoch 1709, recon_loss:0.769406, zinb_loss:0.638501, cluster_loss:0.151261
Clustering   1709: ASW= 0.8329, DB= 0.2300, CH= 57198.2714
Training epoch 1710, recon_loss:0.769880, zinb_loss:0.638460, cluster_loss:0.151363
Clustering   1710: ASW= 0.8329, DB= 0.2280, CH= 57084.8855
Training epoch 1711, recon_loss:0.769460, zinb_loss:0.638385, cluster_loss:0.151275
Clustering   1711: ASW= 0.8332, DB= 0.2294, CH= 57246.5715
Training epoch 1712, recon_loss:0.770049, zinb_loss:0.638273, cluster_loss:0.151533
Clustering   1712: ASW= 0.8326, DB= 0.2282, CH= 57143.1718
Training epoch 1713, recon_loss:0.769705, zinb_loss:0.638414, cluster_loss:0.151364
Clustering   1713: ASW= 0.8334, DB= 0.2291, CH= 57171.6516
Training epoch 1714, recon_loss:0.770517, zinb_loss:0.638179, cluster_loss:0.151825
Clustering   1714: ASW= 0.8321, DB= 0.2291, CH= 57043.0790
Training epoch 1715, recon_loss:0.770015, zinb_loss:0.638460, cluster_loss:0.151515
Clustering   1715: ASW= 0.8334, DB= 0.2290, CH= 56924.0429
Training epoch 1716, recon_loss:0.770772, zinb_loss:0.638005, cluster_loss:0.152181
Clustering   1716: ASW= 0.8314, DB= 0.2302, CH= 56686.8663
Training epoch 1717, recon_loss:0.770111, zinb_loss:0.638551, cluster_loss:0.151551
Clustering   1717: ASW= 0.8334, DB= 0.2287, CH= 56620.7630
Training epoch 1718, recon_loss:0.770507, zinb_loss:0.637865, cluster_loss:0.152153
Clustering   1718: ASW= 0.8311, DB= 0.2310, CH= 56495.2593
Training epoch 1719, recon_loss:0.769865, zinb_loss:0.638334, cluster_loss:0.151459
Clustering   1719: ASW= 0.8329, DB= 0.2287, CH= 56317.1874
Training epoch 1720, recon_loss:0.769964, zinb_loss:0.637633, cluster_loss:0.151938
Clustering   1720: ASW= 0.8311, DB= 0.2311, CH= 56394.1188
Training epoch 1721, recon_loss:0.769569, zinb_loss:0.638262, cluster_loss:0.151122
Clustering   1721: ASW= 0.8332, DB= 0.2280, CH= 56629.8850
Training epoch 1722, recon_loss:0.769718, zinb_loss:0.637625, cluster_loss:0.151770
Clustering   1722: ASW= 0.8311, DB= 0.2314, CH= 56326.3005
Training epoch 1723, recon_loss:0.769609, zinb_loss:0.638222, cluster_loss:0.150998
Clustering   1723: ASW= 0.8331, DB= 0.2283, CH= 56805.4043
Training epoch 1724, recon_loss:0.769947, zinb_loss:0.637663, cluster_loss:0.151817
Clustering   1724: ASW= 0.8311, DB= 0.2311, CH= 56187.3206
Training epoch 1725, recon_loss:0.770364, zinb_loss:0.638448, cluster_loss:0.150989
Clustering   1725: ASW= 0.8332, DB= 0.2280, CH= 57065.2750
Training epoch 1726, recon_loss:0.770563, zinb_loss:0.637837, cluster_loss:0.151957
Clustering   1726: ASW= 0.8312, DB= 0.2313, CH= 56024.2940
Training epoch 1727, recon_loss:0.770891, zinb_loss:0.638546, cluster_loss:0.151130
Clustering   1727: ASW= 0.8330, DB= 0.2278, CH= 57181.2366
Training epoch 1728, recon_loss:0.770853, zinb_loss:0.637892, cluster_loss:0.152091
Clustering   1728: ASW= 0.8314, DB= 0.2312, CH= 55919.7538
Training epoch 1729, recon_loss:0.770997, zinb_loss:0.638440, cluster_loss:0.151259
Clustering   1729: ASW= 0.8331, DB= 0.2281, CH= 57250.8287
Training epoch 1730, recon_loss:0.770641, zinb_loss:0.637790, cluster_loss:0.151974
Clustering   1730: ASW= 0.8318, DB= 0.2308, CH= 56059.5386
Training epoch 1731, recon_loss:0.770615, zinb_loss:0.638202, cluster_loss:0.151227
Clustering   1731: ASW= 0.8332, DB= 0.2284, CH= 57414.6606
Training epoch 1732, recon_loss:0.770219, zinb_loss:0.637669, cluster_loss:0.151714
Clustering   1732: ASW= 0.8324, DB= 0.2305, CH= 56335.8564
Training epoch 1733, recon_loss:0.770168, zinb_loss:0.637949, cluster_loss:0.151188
Clustering   1733: ASW= 0.8333, DB= 0.2281, CH= 57458.7569
Training epoch 1734, recon_loss:0.770043, zinb_loss:0.637600, cluster_loss:0.151509
Clustering   1734: ASW= 0.8327, DB= 0.2304, CH= 56593.9155
Training epoch 1735, recon_loss:0.770049, zinb_loss:0.637762, cluster_loss:0.151293
Clustering   1735: ASW= 0.8332, DB= 0.2284, CH= 57320.9731
Training epoch 1736, recon_loss:0.770272, zinb_loss:0.637587, cluster_loss:0.151511
Clustering   1736: ASW= 0.8328, DB= 0.2308, CH= 56621.0243
Training epoch 1737, recon_loss:0.770246, zinb_loss:0.637596, cluster_loss:0.151601
Clustering   1737: ASW= 0.8329, DB= 0.2288, CH= 56922.6867
Training epoch 1738, recon_loss:0.770538, zinb_loss:0.637534, cluster_loss:0.151515
Clustering   1738: ASW= 0.8326, DB= 0.2308, CH= 56589.5566
Training epoch 1739, recon_loss:0.770084, zinb_loss:0.637317, cluster_loss:0.151801
Clustering   1739: ASW= 0.8328, DB= 0.2293, CH= 56611.3928
Training epoch 1740, recon_loss:0.770415, zinb_loss:0.637355, cluster_loss:0.151493
Clustering   1740: ASW= 0.8325, DB= 0.2309, CH= 56695.3959
Training epoch 1741, recon_loss:0.769763, zinb_loss:0.637174, cluster_loss:0.151845
Clustering   1741: ASW= 0.8325, DB= 0.2303, CH= 56309.4346
Training epoch 1742, recon_loss:0.770074, zinb_loss:0.637317, cluster_loss:0.151378
Clustering   1742: ASW= 0.8324, DB= 0.2310, CH= 56820.0197
Training epoch 1743, recon_loss:0.770198, zinb_loss:0.637345, cluster_loss:0.152173
Clustering   1743: ASW= 0.8328, DB= 0.2294, CH= 56339.2180
Training epoch 1744, recon_loss:0.770368, zinb_loss:0.637496, cluster_loss:0.151252
Clustering   1744: ASW= 0.8327, DB= 0.2304, CH= 57002.2047
Training epoch 1745, recon_loss:0.769823, zinb_loss:0.637283, cluster_loss:0.151761
Clustering   1745: ASW= 0.8331, DB= 0.2289, CH= 56564.1329
Training epoch 1746, recon_loss:0.770033, zinb_loss:0.637492, cluster_loss:0.151111
Clustering   1746: ASW= 0.8330, DB= 0.2296, CH= 57157.3011
Training epoch 1747, recon_loss:0.769821, zinb_loss:0.637243, cluster_loss:0.151610
Clustering   1747: ASW= 0.8331, DB= 0.2298, CH= 56690.4776
Training epoch 1748, recon_loss:0.770299, zinb_loss:0.637612, cluster_loss:0.151100
Clustering   1748: ASW= 0.8330, DB= 0.2299, CH= 57131.9893
Training epoch 1749, recon_loss:0.770294, zinb_loss:0.637496, cluster_loss:0.151671
Clustering   1749: ASW= 0.8331, DB= 0.2295, CH= 56774.1517
Training epoch 1750, recon_loss:0.770533, zinb_loss:0.637789, cluster_loss:0.151096
Clustering   1750: ASW= 0.8331, DB= 0.2288, CH= 57116.1055
Training epoch 1751, recon_loss:0.770181, zinb_loss:0.637480, cluster_loss:0.151518
Clustering   1751: ASW= 0.8332, DB= 0.2303, CH= 56962.0872
Training epoch 1752, recon_loss:0.770406, zinb_loss:0.637840, cluster_loss:0.151025
Clustering   1752: ASW= 0.8335, DB= 0.2282, CH= 57255.2126
Training epoch 1753, recon_loss:0.770021, zinb_loss:0.637445, cluster_loss:0.151429
Clustering   1753: ASW= 0.8332, DB= 0.2302, CH= 57098.0949
Training epoch 1754, recon_loss:0.770175, zinb_loss:0.637786, cluster_loss:0.151080
Clustering   1754: ASW= 0.8334, DB= 0.2281, CH= 57189.4197
Training epoch 1755, recon_loss:0.769785, zinb_loss:0.637417, cluster_loss:0.151466
Clustering   1755: ASW= 0.8332, DB= 0.2310, CH= 57184.8633
Training epoch 1756, recon_loss:0.770161, zinb_loss:0.637993, cluster_loss:0.151084
Clustering   1756: ASW= 0.8340, DB= 0.2275, CH= 57250.2176
Training epoch 1757, recon_loss:0.769760, zinb_loss:0.637576, cluster_loss:0.151561
Clustering   1757: ASW= 0.8328, DB= 0.2314, CH= 57070.2410
Training epoch 1758, recon_loss:0.770159, zinb_loss:0.638231, cluster_loss:0.151252
Clustering   1758: ASW= 0.8340, DB= 0.2270, CH= 57232.0298
Training epoch 1759, recon_loss:0.769833, zinb_loss:0.637822, cluster_loss:0.151714
Clustering   1759: ASW= 0.8326, DB= 0.2323, CH= 57053.3032
Training epoch 1760, recon_loss:0.770333, zinb_loss:0.638551, cluster_loss:0.151379
Clustering   1760: ASW= 0.8341, DB= 0.2268, CH= 57234.4912
Training epoch 1761, recon_loss:0.769898, zinb_loss:0.638173, cluster_loss:0.151759
Clustering   1761: ASW= 0.8323, DB= 0.2324, CH= 56976.8936
Training epoch 1762, recon_loss:0.770391, zinb_loss:0.639049, cluster_loss:0.151395
Clustering   1762: ASW= 0.8343, DB= 0.2267, CH= 57299.4520
Training epoch 1763, recon_loss:0.769949, zinb_loss:0.638796, cluster_loss:0.151667
Clustering   1763: ASW= 0.8323, DB= 0.2325, CH= 56973.2918
Training epoch 1764, recon_loss:0.770345, zinb_loss:0.639431, cluster_loss:0.151456
Clustering   1764: ASW= 0.8340, DB= 0.2266, CH= 57388.6577
Training epoch 1765, recon_loss:0.770261, zinb_loss:0.639231, cluster_loss:0.151697
Clustering   1765: ASW= 0.8320, DB= 0.2329, CH= 56778.8489
Training epoch 1766, recon_loss:0.770710, zinb_loss:0.639908, cluster_loss:0.151413
Clustering   1766: ASW= 0.8341, DB= 0.2269, CH= 57494.5579
Training epoch 1767, recon_loss:0.770630, zinb_loss:0.639695, cluster_loss:0.151603
Clustering   1767: ASW= 0.8322, DB= 0.2324, CH= 56739.6303
Training epoch 1768, recon_loss:0.770541, zinb_loss:0.639980, cluster_loss:0.151394
Clustering   1768: ASW= 0.8338, DB= 0.2271, CH= 57634.3328
Training epoch 1769, recon_loss:0.770442, zinb_loss:0.639657, cluster_loss:0.151602
Clustering   1769: ASW= 0.8320, DB= 0.2320, CH= 56620.7073
Training epoch 1770, recon_loss:0.770532, zinb_loss:0.640203, cluster_loss:0.151285
Clustering   1770: ASW= 0.8343, DB= 0.2272, CH= 57750.3631
Training epoch 1771, recon_loss:0.770319, zinb_loss:0.639763, cluster_loss:0.151466
Clustering   1771: ASW= 0.8322, DB= 0.2316, CH= 56602.7831
Training epoch 1772, recon_loss:0.770424, zinb_loss:0.640182, cluster_loss:0.151231
Clustering   1772: ASW= 0.8341, DB= 0.2275, CH= 58029.9758
Training epoch 1773, recon_loss:0.770311, zinb_loss:0.639737, cluster_loss:0.151441
Clustering   1773: ASW= 0.8327, DB= 0.2306, CH= 56778.3773
Training epoch 1774, recon_loss:0.770355, zinb_loss:0.640149, cluster_loss:0.151353
Clustering   1774: ASW= 0.8341, DB= 0.2275, CH= 57996.2578
Training epoch 1775, recon_loss:0.770441, zinb_loss:0.639817, cluster_loss:0.151614
Clustering   1775: ASW= 0.8319, DB= 0.2310, CH= 56476.7423
Training epoch 1776, recon_loss:0.770646, zinb_loss:0.640112, cluster_loss:0.151457
Clustering   1776: ASW= 0.8341, DB= 0.2278, CH= 57699.5953
Training epoch 1777, recon_loss:0.770432, zinb_loss:0.639699, cluster_loss:0.151544
Clustering   1777: ASW= 0.8330, DB= 0.2292, CH= 57002.5827
Training epoch 1778, recon_loss:0.770038, zinb_loss:0.639744, cluster_loss:0.151588
Clustering   1778: ASW= 0.8336, DB= 0.2285, CH= 57637.0496
Training epoch 1779, recon_loss:0.770440, zinb_loss:0.639646, cluster_loss:0.151640
Clustering   1779: ASW= 0.8331, DB= 0.2285, CH= 56877.1449
Training epoch 1780, recon_loss:0.770247, zinb_loss:0.639570, cluster_loss:0.151700
Clustering   1780: ASW= 0.8335, DB= 0.2289, CH= 57609.6320
Training epoch 1781, recon_loss:0.770928, zinb_loss:0.639619, cluster_loss:0.151887
Clustering   1781: ASW= 0.8328, DB= 0.2293, CH= 56657.7491
Training epoch 1782, recon_loss:0.770621, zinb_loss:0.639222, cluster_loss:0.152202
Clustering   1782: ASW= 0.8321, DB= 0.2299, CH= 56966.8947
Training epoch 1783, recon_loss:0.770900, zinb_loss:0.639294, cluster_loss:0.151900
Clustering   1783: ASW= 0.8328, DB= 0.2285, CH= 56514.4549
Training epoch 1784, recon_loss:0.770164, zinb_loss:0.638671, cluster_loss:0.151982
Clustering   1784: ASW= 0.8327, DB= 0.2290, CH= 57147.4709
Training epoch 1785, recon_loss:0.769959, zinb_loss:0.638587, cluster_loss:0.151582
Clustering   1785: ASW= 0.8330, DB= 0.2290, CH= 56745.4120
Training epoch 1786, recon_loss:0.769380, zinb_loss:0.638118, cluster_loss:0.151437
Clustering   1786: ASW= 0.8332, DB= 0.2287, CH= 57358.9526
Training epoch 1787, recon_loss:0.769625, zinb_loss:0.638470, cluster_loss:0.151796
Clustering   1787: ASW= 0.8322, DB= 0.2295, CH= 56728.0998
Training epoch 1788, recon_loss:0.770239, zinb_loss:0.638301, cluster_loss:0.151735
Clustering   1788: ASW= 0.8324, DB= 0.2307, CH= 56012.7127
Training epoch 1789, recon_loss:0.769760, zinb_loss:0.637721, cluster_loss:0.151679
Clustering   1789: ASW= 0.8326, DB= 0.2295, CH= 56793.4254
Training epoch 1790, recon_loss:0.769888, zinb_loss:0.638009, cluster_loss:0.151400
Clustering   1790: ASW= 0.8335, DB= 0.2290, CH= 56807.9043
Training epoch 1791, recon_loss:0.769793, zinb_loss:0.637625, cluster_loss:0.151874
Clustering   1791: ASW= 0.8322, DB= 0.2299, CH= 56572.6451
Training epoch 1792, recon_loss:0.770219, zinb_loss:0.638021, cluster_loss:0.151619
Clustering   1792: ASW= 0.8338, DB= 0.2296, CH= 56804.5054
Training epoch 1793, recon_loss:0.769529, zinb_loss:0.637267, cluster_loss:0.151472
Clustering   1793: ASW= 0.8316, DB= 0.2316, CH= 56491.5108
Training epoch 1794, recon_loss:0.769446, zinb_loss:0.637440, cluster_loss:0.151020
Clustering   1794: ASW= 0.8333, DB= 0.2289, CH= 57083.6928
Training epoch 1795, recon_loss:0.769803, zinb_loss:0.637147, cluster_loss:0.151593
Clustering   1795: ASW= 0.8320, DB= 0.2318, CH= 56638.8992
Training epoch 1796, recon_loss:0.770086, zinb_loss:0.637549, cluster_loss:0.151097
Clustering   1796: ASW= 0.8333, DB= 0.2288, CH= 57081.3641
Training epoch 1797, recon_loss:0.769904, zinb_loss:0.637227, cluster_loss:0.151778
Clustering   1797: ASW= 0.8326, DB= 0.2309, CH= 56842.8822
Training epoch 1798, recon_loss:0.770386, zinb_loss:0.637652, cluster_loss:0.151235
Clustering   1798: ASW= 0.8337, DB= 0.2288, CH= 57250.7113
Training epoch 1799, recon_loss:0.770231, zinb_loss:0.637427, cluster_loss:0.152110
Clustering   1799: ASW= 0.8324, DB= 0.2304, CH= 56774.4181
Training epoch 1800, recon_loss:0.770621, zinb_loss:0.637746, cluster_loss:0.151341
Clustering   1800: ASW= 0.8340, DB= 0.2283, CH= 57261.9369
Training epoch 1801, recon_loss:0.770169, zinb_loss:0.637437, cluster_loss:0.152122
Clustering   1801: ASW= 0.8322, DB= 0.2303, CH= 56776.4431
Training epoch 1802, recon_loss:0.770400, zinb_loss:0.637633, cluster_loss:0.151238
Clustering   1802: ASW= 0.8343, DB= 0.2282, CH= 57392.0723
Training epoch 1803, recon_loss:0.769730, zinb_loss:0.637262, cluster_loss:0.151719
Clustering   1803: ASW= 0.8324, DB= 0.2296, CH= 57002.6752
Training epoch 1804, recon_loss:0.770026, zinb_loss:0.637443, cluster_loss:0.151069
Clustering   1804: ASW= 0.8346, DB= 0.2280, CH= 57555.6880
Training epoch 1805, recon_loss:0.769463, zinb_loss:0.637117, cluster_loss:0.151334
Clustering   1805: ASW= 0.8326, DB= 0.2294, CH= 57332.5751
Training epoch 1806, recon_loss:0.769946, zinb_loss:0.637345, cluster_loss:0.150998
Clustering   1806: ASW= 0.8346, DB= 0.2280, CH= 57608.0179
Training epoch 1807, recon_loss:0.769655, zinb_loss:0.637184, cluster_loss:0.151168
Clustering   1807: ASW= 0.8328, DB= 0.2289, CH= 57516.0318
Training epoch 1808, recon_loss:0.770328, zinb_loss:0.637464, cluster_loss:0.151061
Clustering   1808: ASW= 0.8344, DB= 0.2282, CH= 57555.6134
Training epoch 1809, recon_loss:0.770149, zinb_loss:0.637425, cluster_loss:0.151157
Clustering   1809: ASW= 0.8328, DB= 0.2288, CH= 57626.0272
Training epoch 1810, recon_loss:0.770809, zinb_loss:0.637655, cluster_loss:0.151276
Clustering   1810: ASW= 0.8340, DB= 0.2289, CH= 57348.9826
Training epoch 1811, recon_loss:0.770629, zinb_loss:0.637756, cluster_loss:0.151249
Clustering   1811: ASW= 0.8328, DB= 0.2281, CH= 57578.9874
Training epoch 1812, recon_loss:0.770942, zinb_loss:0.637795, cluster_loss:0.151525
Clustering   1812: ASW= 0.8336, DB= 0.2297, CH= 57048.2373
Training epoch 1813, recon_loss:0.770591, zinb_loss:0.638002, cluster_loss:0.151296
Clustering   1813: ASW= 0.8329, DB= 0.2281, CH= 57558.5392
Training epoch 1814, recon_loss:0.770477, zinb_loss:0.637800, cluster_loss:0.151606
Clustering   1814: ASW= 0.8334, DB= 0.2295, CH= 56827.4333
Training epoch 1815, recon_loss:0.770106, zinb_loss:0.638139, cluster_loss:0.151148
Clustering   1815: ASW= 0.8333, DB= 0.2284, CH= 57752.6969
Training epoch 1816, recon_loss:0.769861, zinb_loss:0.637810, cluster_loss:0.151534
Clustering   1816: ASW= 0.8335, DB= 0.2292, CH= 56828.4266
Training epoch 1817, recon_loss:0.769705, zinb_loss:0.638238, cluster_loss:0.150946
Clustering   1817: ASW= 0.8340, DB= 0.2279, CH= 58099.7173
Training epoch 1818, recon_loss:0.769549, zinb_loss:0.637877, cluster_loss:0.151508
Clustering   1818: ASW= 0.8335, DB= 0.2291, CH= 56873.1990
Training epoch 1819, recon_loss:0.769553, zinb_loss:0.638346, cluster_loss:0.150848
Clustering   1819: ASW= 0.8344, DB= 0.2279, CH= 58398.4806
Training epoch 1820, recon_loss:0.769627, zinb_loss:0.637922, cluster_loss:0.151640
Clustering   1820: ASW= 0.8333, DB= 0.2291, CH= 56766.2153
Training epoch 1821, recon_loss:0.769624, zinb_loss:0.638292, cluster_loss:0.150871
Clustering   1821: ASW= 0.8348, DB= 0.2280, CH= 58584.1731
Training epoch 1822, recon_loss:0.769789, zinb_loss:0.637743, cluster_loss:0.151807
Clustering   1822: ASW= 0.8332, DB= 0.2286, CH= 56668.2015
Training epoch 1823, recon_loss:0.769491, zinb_loss:0.638081, cluster_loss:0.150918
Clustering   1823: ASW= 0.8350, DB= 0.2277, CH= 58692.6577
Training epoch 1824, recon_loss:0.769534, zinb_loss:0.637487, cluster_loss:0.151923
Clustering   1824: ASW= 0.8330, DB= 0.2284, CH= 56547.8546
Training epoch 1825, recon_loss:0.769130, zinb_loss:0.637792, cluster_loss:0.150936
Clustering   1825: ASW= 0.8351, DB= 0.2275, CH= 58702.8390
Training epoch 1826, recon_loss:0.769094, zinb_loss:0.637199, cluster_loss:0.151884
Clustering   1826: ASW= 0.8330, DB= 0.2283, CH= 56573.7753
Training epoch 1827, recon_loss:0.768816, zinb_loss:0.637528, cluster_loss:0.150956
Clustering   1827: ASW= 0.8351, DB= 0.2276, CH= 58659.6510
Training epoch 1828, recon_loss:0.768897, zinb_loss:0.636998, cluster_loss:0.151783
Clustering   1828: ASW= 0.8330, DB= 0.2281, CH= 56648.8920
Training epoch 1829, recon_loss:0.768791, zinb_loss:0.637352, cluster_loss:0.150965
Clustering   1829: ASW= 0.8352, DB= 0.2276, CH= 58688.0276
Training epoch 1830, recon_loss:0.768976, zinb_loss:0.636864, cluster_loss:0.151695
Clustering   1830: ASW= 0.8331, DB= 0.2281, CH= 56765.6304
Training epoch 1831, recon_loss:0.768952, zinb_loss:0.637204, cluster_loss:0.151050
Clustering   1831: ASW= 0.8351, DB= 0.2276, CH= 58584.6865
Training epoch 1832, recon_loss:0.769167, zinb_loss:0.636809, cluster_loss:0.151620
Clustering   1832: ASW= 0.8333, DB= 0.2279, CH= 56854.8939
Training epoch 1833, recon_loss:0.769083, zinb_loss:0.637113, cluster_loss:0.151117
Clustering   1833: ASW= 0.8349, DB= 0.2278, CH= 58531.9392
Training epoch 1834, recon_loss:0.769327, zinb_loss:0.636848, cluster_loss:0.151534
Clustering   1834: ASW= 0.8335, DB= 0.2278, CH= 56901.0920
Training epoch 1835, recon_loss:0.769088, zinb_loss:0.637022, cluster_loss:0.151219
Clustering   1835: ASW= 0.8346, DB= 0.2283, CH= 58382.8635
Training epoch 1836, recon_loss:0.769471, zinb_loss:0.636946, cluster_loss:0.151504
Clustering   1836: ASW= 0.8337, DB= 0.2273, CH= 56751.1283
Training epoch 1837, recon_loss:0.769169, zinb_loss:0.636934, cluster_loss:0.151389
Clustering   1837: ASW= 0.8341, DB= 0.2293, CH= 58148.7729
Training epoch 1838, recon_loss:0.769668, zinb_loss:0.637042, cluster_loss:0.151546
Clustering   1838: ASW= 0.8338, DB= 0.2284, CH= 56546.2786
Training epoch 1839, recon_loss:0.769155, zinb_loss:0.636737, cluster_loss:0.151460
Clustering   1839: ASW= 0.8337, DB= 0.2300, CH= 57874.7191
Training epoch 1840, recon_loss:0.769416, zinb_loss:0.636952, cluster_loss:0.151300
Clustering   1840: ASW= 0.8341, DB= 0.2275, CH= 56760.4241
Training epoch 1841, recon_loss:0.768838, zinb_loss:0.636557, cluster_loss:0.151284
Clustering   1841: ASW= 0.8333, DB= 0.2301, CH= 57638.2748
Training epoch 1842, recon_loss:0.768852, zinb_loss:0.636856, cluster_loss:0.150984
Clustering   1842: ASW= 0.8344, DB= 0.2271, CH= 57108.2309
Training epoch 1843, recon_loss:0.768589, zinb_loss:0.636625, cluster_loss:0.151145
Clustering   1843: ASW= 0.8334, DB= 0.2301, CH= 57782.7571
Training epoch 1844, recon_loss:0.768844, zinb_loss:0.637070, cluster_loss:0.150928
Clustering   1844: ASW= 0.8345, DB= 0.2271, CH= 57273.2021
Training epoch 1845, recon_loss:0.768759, zinb_loss:0.636960, cluster_loss:0.151193
Clustering   1845: ASW= 0.8334, DB= 0.2302, CH= 57790.2959
Training epoch 1846, recon_loss:0.769053, zinb_loss:0.637479, cluster_loss:0.151021
Clustering   1846: ASW= 0.8343, DB= 0.2265, CH= 57304.7055
Training epoch 1847, recon_loss:0.768928, zinb_loss:0.637469, cluster_loss:0.151304
Clustering   1847: ASW= 0.8334, DB= 0.2305, CH= 57777.7847
Training epoch 1848, recon_loss:0.769206, zinb_loss:0.637887, cluster_loss:0.151187
Clustering   1848: ASW= 0.8340, DB= 0.2269, CH= 57350.2003
Training epoch 1849, recon_loss:0.769162, zinb_loss:0.638012, cluster_loss:0.151345
Clustering   1849: ASW= 0.8336, DB= 0.2306, CH= 57755.0674
Training epoch 1850, recon_loss:0.769796, zinb_loss:0.638226, cluster_loss:0.151376
Clustering   1850: ASW= 0.8336, DB= 0.2277, CH= 57436.4788
Training epoch 1851, recon_loss:0.770242, zinb_loss:0.638581, cluster_loss:0.151400
Clustering   1851: ASW= 0.8340, DB= 0.2298, CH= 57696.0330
Training epoch 1852, recon_loss:0.770748, zinb_loss:0.638542, cluster_loss:0.151603
Clustering   1852: ASW= 0.8333, DB= 0.2286, CH= 57508.9618
Training epoch 1853, recon_loss:0.770692, zinb_loss:0.639021, cluster_loss:0.151513
Clustering   1853: ASW= 0.8342, DB= 0.2284, CH= 57385.3486
Training epoch 1854, recon_loss:0.770391, zinb_loss:0.638633, cluster_loss:0.151707
Clustering   1854: ASW= 0.8331, DB= 0.2287, CH= 57438.2441
Training epoch 1855, recon_loss:0.770239, zinb_loss:0.639024, cluster_loss:0.151446
Clustering   1855: ASW= 0.8343, DB= 0.2278, CH= 57115.5095
Training epoch 1856, recon_loss:0.769859, zinb_loss:0.638352, cluster_loss:0.151636
Clustering   1856: ASW= 0.8332, DB= 0.2294, CH= 57460.4348
Training epoch 1857, recon_loss:0.769911, zinb_loss:0.638656, cluster_loss:0.151315
Clustering   1857: ASW= 0.8343, DB= 0.2273, CH= 57194.1458
Training epoch 1858, recon_loss:0.769246, zinb_loss:0.637891, cluster_loss:0.151470
Clustering   1858: ASW= 0.8336, DB= 0.2292, CH= 57556.0447
Training epoch 1859, recon_loss:0.769144, zinb_loss:0.638173, cluster_loss:0.151046
Clustering   1859: ASW= 0.8344, DB= 0.2265, CH= 57495.7504
Training epoch 1860, recon_loss:0.768723, zinb_loss:0.637583, cluster_loss:0.151277
Clustering   1860: ASW= 0.8340, DB= 0.2292, CH= 57706.0064
Training epoch 1861, recon_loss:0.768940, zinb_loss:0.637911, cluster_loss:0.150900
Clustering   1861: ASW= 0.8345, DB= 0.2264, CH= 57764.6823
Training epoch 1862, recon_loss:0.768603, zinb_loss:0.637460, cluster_loss:0.151204
Clustering   1862: ASW= 0.8342, DB= 0.2290, CH= 57789.4737
Training epoch 1863, recon_loss:0.769142, zinb_loss:0.637825, cluster_loss:0.150919
Clustering   1863: ASW= 0.8344, DB= 0.2255, CH= 57931.8225
Training epoch 1864, recon_loss:0.768689, zinb_loss:0.637477, cluster_loss:0.151216
Clustering   1864: ASW= 0.8345, DB= 0.2290, CH= 57844.7758
Training epoch 1865, recon_loss:0.769411, zinb_loss:0.637801, cluster_loss:0.151007
Clustering   1865: ASW= 0.8343, DB= 0.2259, CH= 57988.0656
Training epoch 1866, recon_loss:0.768848, zinb_loss:0.637625, cluster_loss:0.151221
Clustering   1866: ASW= 0.8348, DB= 0.2288, CH= 57937.7945
Training epoch 1867, recon_loss:0.769739, zinb_loss:0.637848, cluster_loss:0.151192
Clustering   1867: ASW= 0.8340, DB= 0.2256, CH= 58075.0533
Training epoch 1868, recon_loss:0.769078, zinb_loss:0.637803, cluster_loss:0.151265
Clustering   1868: ASW= 0.8352, DB= 0.2285, CH= 58057.1561
Training epoch 1869, recon_loss:0.769967, zinb_loss:0.637900, cluster_loss:0.151458
Clustering   1869: ASW= 0.8338, DB= 0.2263, CH= 58007.5293
Training epoch 1870, recon_loss:0.769353, zinb_loss:0.638154, cluster_loss:0.151307
Clustering   1870: ASW= 0.8353, DB= 0.2278, CH= 57935.3167
Training epoch 1871, recon_loss:0.770041, zinb_loss:0.638029, cluster_loss:0.151724
Clustering   1871: ASW= 0.8335, DB= 0.2269, CH= 57808.9607
Training epoch 1872, recon_loss:0.769574, zinb_loss:0.638508, cluster_loss:0.151386
Clustering   1872: ASW= 0.8348, DB= 0.2276, CH= 57581.0448
Training epoch 1873, recon_loss:0.770116, zinb_loss:0.638154, cluster_loss:0.151969
Clustering   1873: ASW= 0.8332, DB= 0.2274, CH= 57426.4847
Training epoch 1874, recon_loss:0.769822, zinb_loss:0.638970, cluster_loss:0.151447
Clustering   1874: ASW= 0.8348, DB= 0.2276, CH= 57528.0434
Training epoch 1875, recon_loss:0.770381, zinb_loss:0.638312, cluster_loss:0.152162
Clustering   1875: ASW= 0.8327, DB= 0.2303, CH= 56815.9054
Training epoch 1876, recon_loss:0.769683, zinb_loss:0.639021, cluster_loss:0.151487
Clustering   1876: ASW= 0.8333, DB= 0.2305, CH= 57059.6606
Training epoch 1877, recon_loss:0.771052, zinb_loss:0.638785, cluster_loss:0.152958
Clustering   1877: ASW= 0.8322, DB= 0.2281, CH= 56177.8559
Training epoch 1878, recon_loss:0.770320, zinb_loss:0.639217, cluster_loss:0.151445
Clustering   1878: ASW= 0.8337, DB= 0.2297, CH= 57046.4740
Training epoch 1879, recon_loss:0.770510, zinb_loss:0.638672, cluster_loss:0.152240
Clustering   1879: ASW= 0.8330, DB= 0.2270, CH= 56694.2280
Training epoch 1880, recon_loss:0.769889, zinb_loss:0.639014, cluster_loss:0.151023
Clustering   1880: ASW= 0.8341, DB= 0.2285, CH= 57548.6577
Training epoch 1881, recon_loss:0.770245, zinb_loss:0.638985, cluster_loss:0.151494
Clustering   1881: ASW= 0.8342, DB= 0.2263, CH= 57538.3953
Training epoch 1882, recon_loss:0.769861, zinb_loss:0.639180, cluster_loss:0.150864
Clustering   1882: ASW= 0.8343, DB= 0.2289, CH= 57905.8923
Training epoch 1883, recon_loss:0.770359, zinb_loss:0.639495, cluster_loss:0.151303
Clustering   1883: ASW= 0.8347, DB= 0.2265, CH= 57862.8488
Training epoch 1884, recon_loss:0.770375, zinb_loss:0.639652, cluster_loss:0.151002
Clustering   1884: ASW= 0.8342, DB= 0.2288, CH= 57988.6702
Training epoch 1885, recon_loss:0.771170, zinb_loss:0.640054, cluster_loss:0.151274
Clustering   1885: ASW= 0.8348, DB= 0.2258, CH= 57915.5406
Training epoch 1886, recon_loss:0.771230, zinb_loss:0.640061, cluster_loss:0.151215
Clustering   1886: ASW= 0.8339, DB= 0.2290, CH= 58140.0550
Training epoch 1887, recon_loss:0.771156, zinb_loss:0.640337, cluster_loss:0.151313
Clustering   1887: ASW= 0.8350, DB= 0.2263, CH= 57403.3491
Training epoch 1888, recon_loss:0.769877, zinb_loss:0.639244, cluster_loss:0.151215
Clustering   1888: ASW= 0.8335, DB= 0.2295, CH= 57803.0566
Training epoch 1889, recon_loss:0.769620, zinb_loss:0.639305, cluster_loss:0.151075
Clustering   1889: ASW= 0.8349, DB= 0.2262, CH= 57712.3329
Training epoch 1890, recon_loss:0.768785, zinb_loss:0.638573, cluster_loss:0.151003
Clustering   1890: ASW= 0.8338, DB= 0.2284, CH= 57952.7402
Training epoch 1891, recon_loss:0.768828, zinb_loss:0.638643, cluster_loss:0.150870
Clustering   1891: ASW= 0.8355, DB= 0.2257, CH= 58019.6368
Training epoch 1892, recon_loss:0.768418, zinb_loss:0.638177, cluster_loss:0.150806
Clustering   1892: ASW= 0.8342, DB= 0.2281, CH= 58169.3590
Training epoch 1893, recon_loss:0.768573, zinb_loss:0.638353, cluster_loss:0.150780
Clustering   1893: ASW= 0.8354, DB= 0.2253, CH= 58321.1122
Training epoch 1894, recon_loss:0.768252, zinb_loss:0.638179, cluster_loss:0.150635
Clustering   1894: ASW= 0.8344, DB= 0.2272, CH= 58341.9631
Training epoch 1895, recon_loss:0.768608, zinb_loss:0.638188, cluster_loss:0.150848
Clustering   1895: ASW= 0.8355, DB= 0.2256, CH= 58438.5488
Training epoch 1896, recon_loss:0.768623, zinb_loss:0.638151, cluster_loss:0.150663
Clustering   1896: ASW= 0.8339, DB= 0.2281, CH= 58166.6390
Training epoch 1897, recon_loss:0.768828, zinb_loss:0.638090, cluster_loss:0.150815
Clustering   1897: ASW= 0.8357, DB= 0.2267, CH= 58420.1429
Training epoch 1898, recon_loss:0.769114, zinb_loss:0.638411, cluster_loss:0.150746
Clustering   1898: ASW= 0.8344, DB= 0.2261, CH= 58284.9541
Training epoch 1899, recon_loss:0.769860, zinb_loss:0.638481, cluster_loss:0.151499
Clustering   1899: ASW= 0.8352, DB= 0.2283, CH= 58301.3694
Training epoch 1900, recon_loss:0.771110, zinb_loss:0.639330, cluster_loss:0.151623
Clustering   1900: ASW= 0.8334, DB= 0.2271, CH= 57283.2700
Training epoch 1901, recon_loss:0.771246, zinb_loss:0.638918, cluster_loss:0.152406
Clustering   1901: ASW= 0.8346, DB= 0.2297, CH= 57920.2612
Training epoch 1902, recon_loss:0.771318, zinb_loss:0.638888, cluster_loss:0.152250
Clustering   1902: ASW= 0.8316, DB= 0.2321, CH= 55923.5794
Training epoch 1903, recon_loss:0.771595, zinb_loss:0.637806, cluster_loss:0.153064
Clustering   1903: ASW= 0.8322, DB= 0.2309, CH= 57122.7869
Training epoch 1904, recon_loss:0.770531, zinb_loss:0.638521, cluster_loss:0.152605
Clustering   1904: ASW= 0.8322, DB= 0.2291, CH= 55735.5701
Training epoch 1905, recon_loss:0.769562, zinb_loss:0.638074, cluster_loss:0.151690
Clustering   1905: ASW= 0.8328, DB= 0.2313, CH= 56507.4032
Training epoch 1906, recon_loss:0.768438, zinb_loss:0.637894, cluster_loss:0.150965
Clustering   1906: ASW= 0.8331, DB= 0.2281, CH= 57168.1096
Training epoch 1907, recon_loss:0.768838, zinb_loss:0.637536, cluster_loss:0.151542
Clustering   1907: ASW= 0.8337, DB= 0.2293, CH= 57473.0762
Training epoch 1908, recon_loss:0.769733, zinb_loss:0.638150, cluster_loss:0.151365
Clustering   1908: ASW= 0.8338, DB= 0.2276, CH= 57178.5670
Training epoch 1909, recon_loss:0.771277, zinb_loss:0.637744, cluster_loss:0.152642
Clustering   1909: ASW= 0.8321, DB= 0.2298, CH= 56918.8256
Training epoch 1910, recon_loss:0.771203, zinb_loss:0.638284, cluster_loss:0.151649
Clustering   1910: ASW= 0.8347, DB= 0.2276, CH= 56877.9455
Training epoch 1911, recon_loss:0.769809, zinb_loss:0.637315, cluster_loss:0.151994
Clustering   1911: ASW= 0.8317, DB= 0.2299, CH= 56634.2748
Training epoch 1912, recon_loss:0.769400, zinb_loss:0.637639, cluster_loss:0.151039
Clustering   1912: ASW= 0.8348, DB= 0.2271, CH= 57437.9563
Training epoch 1913, recon_loss:0.768396, zinb_loss:0.636904, cluster_loss:0.151298
Clustering   1913: ASW= 0.8331, DB= 0.2281, CH= 57239.4991
Training epoch 1914, recon_loss:0.768542, zinb_loss:0.637246, cluster_loss:0.150704
Clustering   1914: ASW= 0.8354, DB= 0.2261, CH= 58041.3084
Training epoch 1915, recon_loss:0.767969, zinb_loss:0.636753, cluster_loss:0.151022
Clustering   1915: ASW= 0.8337, DB= 0.2275, CH= 57672.1955
Training epoch 1916, recon_loss:0.768326, zinb_loss:0.637119, cluster_loss:0.150627
Clustering   1916: ASW= 0.8356, DB= 0.2259, CH= 58308.3585
Training epoch 1917, recon_loss:0.768204, zinb_loss:0.636830, cluster_loss:0.150910
Clustering   1917: ASW= 0.8340, DB= 0.2271, CH= 57923.3822
Training epoch 1918, recon_loss:0.768757, zinb_loss:0.637211, cluster_loss:0.150618
Clustering   1918: ASW= 0.8357, DB= 0.2262, CH= 58479.7139
Training epoch 1919, recon_loss:0.768940, zinb_loss:0.637086, cluster_loss:0.150870
Clustering   1919: ASW= 0.8343, DB= 0.2271, CH= 58173.3248
Training epoch 1920, recon_loss:0.769651, zinb_loss:0.637442, cluster_loss:0.150733
Clustering   1920: ASW= 0.8356, DB= 0.2267, CH= 58464.6462
Training epoch 1921, recon_loss:0.769700, zinb_loss:0.637450, cluster_loss:0.150884
Clustering   1921: ASW= 0.8345, DB= 0.2268, CH= 58339.9083
Training epoch 1922, recon_loss:0.770076, zinb_loss:0.637649, cluster_loss:0.150840
Clustering   1922: ASW= 0.8354, DB= 0.2274, CH= 58373.8267
Training epoch 1923, recon_loss:0.769739, zinb_loss:0.637666, cluster_loss:0.150839
Clustering   1923: ASW= 0.8347, DB= 0.2269, CH= 58463.2502
Training epoch 1924, recon_loss:0.769951, zinb_loss:0.637678, cluster_loss:0.150865
Clustering   1924: ASW= 0.8352, DB= 0.2274, CH= 58340.8963
Training epoch 1925, recon_loss:0.769473, zinb_loss:0.637668, cluster_loss:0.150759
Clustering   1925: ASW= 0.8349, DB= 0.2267, CH= 58534.8114
Training epoch 1926, recon_loss:0.769647, zinb_loss:0.637560, cluster_loss:0.150851
Clustering   1926: ASW= 0.8350, DB= 0.2277, CH= 58389.8548
Training epoch 1927, recon_loss:0.769146, zinb_loss:0.637557, cluster_loss:0.150686
Clustering   1927: ASW= 0.8351, DB= 0.2264, CH= 58565.5004
Training epoch 1928, recon_loss:0.769357, zinb_loss:0.637387, cluster_loss:0.150837
Clustering   1928: ASW= 0.8347, DB= 0.2277, CH= 58439.4814
Training epoch 1929, recon_loss:0.768900, zinb_loss:0.637467, cluster_loss:0.150606
Clustering   1929: ASW= 0.8353, DB= 0.2262, CH= 58606.3940
Training epoch 1930, recon_loss:0.769195, zinb_loss:0.637258, cluster_loss:0.150918
Clustering   1930: ASW= 0.8344, DB= 0.2282, CH= 58383.9437
Training epoch 1931, recon_loss:0.768864, zinb_loss:0.637498, cluster_loss:0.150567
Clustering   1931: ASW= 0.8354, DB= 0.2258, CH= 58533.0763
Training epoch 1932, recon_loss:0.769345, zinb_loss:0.637183, cluster_loss:0.151275
Clustering   1932: ASW= 0.8337, DB= 0.2290, CH= 57940.4366
Training epoch 1933, recon_loss:0.769448, zinb_loss:0.637685, cluster_loss:0.150879
Clustering   1933: ASW= 0.8350, DB= 0.2265, CH= 57884.4448
Training epoch 1934, recon_loss:0.769667, zinb_loss:0.637067, cluster_loss:0.151962
Clustering   1934: ASW= 0.8329, DB= 0.2303, CH= 57138.2561
Training epoch 1935, recon_loss:0.769983, zinb_loss:0.637742, cluster_loss:0.151414
Clustering   1935: ASW= 0.8341, DB= 0.2278, CH= 56855.0262
Training epoch 1936, recon_loss:0.768838, zinb_loss:0.636645, cluster_loss:0.151873
Clustering   1936: ASW= 0.8331, DB= 0.2301, CH= 57009.0463
Training epoch 1937, recon_loss:0.768502, zinb_loss:0.637271, cluster_loss:0.150768
Clustering   1937: ASW= 0.8350, DB= 0.2267, CH= 57790.5302
Training epoch 1938, recon_loss:0.768035, zinb_loss:0.636544, cluster_loss:0.151435
Clustering   1938: ASW= 0.8341, DB= 0.2289, CH= 57499.0628
Training epoch 1939, recon_loss:0.768166, zinb_loss:0.637109, cluster_loss:0.150602
Clustering   1939: ASW= 0.8350, DB= 0.2263, CH= 58189.1817
Training epoch 1940, recon_loss:0.768120, zinb_loss:0.636658, cluster_loss:0.151448
Clustering   1940: ASW= 0.8345, DB= 0.2281, CH= 57666.8782
Training epoch 1941, recon_loss:0.768190, zinb_loss:0.637130, cluster_loss:0.150593
Clustering   1941: ASW= 0.8351, DB= 0.2259, CH= 58368.7032
Training epoch 1942, recon_loss:0.768077, zinb_loss:0.636696, cluster_loss:0.151205
Clustering   1942: ASW= 0.8350, DB= 0.2276, CH= 58024.6285
Training epoch 1943, recon_loss:0.768108, zinb_loss:0.637025, cluster_loss:0.150518
Clustering   1943: ASW= 0.8352, DB= 0.2254, CH= 58539.7395
Training epoch 1944, recon_loss:0.768417, zinb_loss:0.636841, cluster_loss:0.151025
Clustering   1944: ASW= 0.8353, DB= 0.2274, CH= 58317.0514
Training epoch 1945, recon_loss:0.768635, zinb_loss:0.637237, cluster_loss:0.150503
Clustering   1945: ASW= 0.8353, DB= 0.2262, CH= 58623.3216
Training epoch 1946, recon_loss:0.768946, zinb_loss:0.637434, cluster_loss:0.150854
Clustering   1946: ASW= 0.8358, DB= 0.2258, CH= 58771.9008
Training epoch 1947, recon_loss:0.769082, zinb_loss:0.637665, cluster_loss:0.150659
Clustering   1947: ASW= 0.8349, DB= 0.2265, CH= 58557.4373
Training epoch 1948, recon_loss:0.769596, zinb_loss:0.638126, cluster_loss:0.150810
Clustering   1948: ASW= 0.8357, DB= 0.2255, CH= 58876.0789
Training epoch 1949, recon_loss:0.769739, zinb_loss:0.638175, cluster_loss:0.150893
Clustering   1949: ASW= 0.8345, DB= 0.2277, CH= 58295.7341
Training epoch 1950, recon_loss:0.770230, zinb_loss:0.638775, cluster_loss:0.150852
Clustering   1950: ASW= 0.8353, DB= 0.2252, CH= 58793.8559
Training epoch 1951, recon_loss:0.770341, zinb_loss:0.638566, cluster_loss:0.151180
Clustering   1951: ASW= 0.8338, DB= 0.2294, CH= 57830.1228
Training epoch 1952, recon_loss:0.770628, zinb_loss:0.639164, cluster_loss:0.150896
Clustering   1952: ASW= 0.8351, DB= 0.2245, CH= 58759.0652
Training epoch 1953, recon_loss:0.770226, zinb_loss:0.638675, cluster_loss:0.151439
Clustering   1953: ASW= 0.8336, DB= 0.2303, CH= 57562.2314
Training epoch 1954, recon_loss:0.770253, zinb_loss:0.639192, cluster_loss:0.150933
Clustering   1954: ASW= 0.8349, DB= 0.2248, CH= 58777.1035
Training epoch 1955, recon_loss:0.770004, zinb_loss:0.638594, cluster_loss:0.151637
Clustering   1955: ASW= 0.8335, DB= 0.2306, CH= 57339.8506
Training epoch 1956, recon_loss:0.770061, zinb_loss:0.639223, cluster_loss:0.150979
Clustering   1956: ASW= 0.8348, DB= 0.2255, CH= 58774.4743
Training epoch 1957, recon_loss:0.769850, zinb_loss:0.638702, cluster_loss:0.151656
Clustering   1957: ASW= 0.8339, DB= 0.2302, CH= 57388.6280
Training epoch 1958, recon_loss:0.769705, zinb_loss:0.639285, cluster_loss:0.150950
Clustering   1958: ASW= 0.8349, DB= 0.2252, CH= 58868.6603
Training epoch 1959, recon_loss:0.769485, zinb_loss:0.638779, cluster_loss:0.151531
Clustering   1959: ASW= 0.8344, DB= 0.2296, CH= 57587.7969
Training epoch 1960, recon_loss:0.769251, zinb_loss:0.639165, cluster_loss:0.150893
Clustering   1960: ASW= 0.8349, DB= 0.2254, CH= 58966.3313
Training epoch 1961, recon_loss:0.769107, zinb_loss:0.638671, cluster_loss:0.151382
Clustering   1961: ASW= 0.8349, DB= 0.2288, CH= 57816.4580
Training epoch 1962, recon_loss:0.768931, zinb_loss:0.638873, cluster_loss:0.150876
Clustering   1962: ASW= 0.8349, DB= 0.2253, CH= 59086.9159
Training epoch 1963, recon_loss:0.768864, zinb_loss:0.638486, cluster_loss:0.151271
Clustering   1963: ASW= 0.8354, DB= 0.2281, CH= 58028.2366
Training epoch 1964, recon_loss:0.768827, zinb_loss:0.638589, cluster_loss:0.150983
Clustering   1964: ASW= 0.8347, DB= 0.2255, CH= 59105.2638
Training epoch 1965, recon_loss:0.768868, zinb_loss:0.638321, cluster_loss:0.151234
Clustering   1965: ASW= 0.8357, DB= 0.2273, CH= 58079.1630
Training epoch 1966, recon_loss:0.769073, zinb_loss:0.638275, cluster_loss:0.151289
Clustering   1966: ASW= 0.8343, DB= 0.2264, CH= 58850.4577
Training epoch 1967, recon_loss:0.769323, zinb_loss:0.638193, cluster_loss:0.151389
Clustering   1967: ASW= 0.8354, DB= 0.2272, CH= 57514.3187
Training epoch 1968, recon_loss:0.769329, zinb_loss:0.637766, cluster_loss:0.151686
Clustering   1968: ASW= 0.8337, DB= 0.2279, CH= 58342.7523
Training epoch 1969, recon_loss:0.769399, zinb_loss:0.637743, cluster_loss:0.151545
Clustering   1969: ASW= 0.8349, DB= 0.2274, CH= 56975.8918
Training epoch 1970, recon_loss:0.768877, zinb_loss:0.637227, cluster_loss:0.151441
Clustering   1970: ASW= 0.8343, DB= 0.2266, CH= 58345.5725
Training epoch 1971, recon_loss:0.768982, zinb_loss:0.637519, cluster_loss:0.151008
Clustering   1971: ASW= 0.8354, DB= 0.2271, CH= 57649.7366
Training epoch 1972, recon_loss:0.768708, zinb_loss:0.637044, cluster_loss:0.151429
Clustering   1972: ASW= 0.8340, DB= 0.2276, CH= 58177.2214
Training epoch 1973, recon_loss:0.768233, zinb_loss:0.637078, cluster_loss:0.150718
Clustering   1973: ASW= 0.8350, DB= 0.2264, CH= 57787.2610
Training epoch 1974, recon_loss:0.767982, zinb_loss:0.636650, cluster_loss:0.151035
Clustering   1974: ASW= 0.8348, DB= 0.2260, CH= 58412.4888
Training epoch 1975, recon_loss:0.768030, zinb_loss:0.636830, cluster_loss:0.150470
Clustering   1975: ASW= 0.8352, DB= 0.2265, CH= 58306.6470
Training epoch 1976, recon_loss:0.768113, zinb_loss:0.636543, cluster_loss:0.151014
Clustering   1976: ASW= 0.8351, DB= 0.2256, CH= 58390.4302
Training epoch 1977, recon_loss:0.768544, zinb_loss:0.636857, cluster_loss:0.150472
Clustering   1977: ASW= 0.8352, DB= 0.2262, CH= 58619.3071
Training epoch 1978, recon_loss:0.768970, zinb_loss:0.636646, cluster_loss:0.151316
Clustering   1978: ASW= 0.8352, DB= 0.2255, CH= 58123.3548
Training epoch 1979, recon_loss:0.769354, zinb_loss:0.637115, cluster_loss:0.150693
Clustering   1979: ASW= 0.8350, DB= 0.2269, CH= 58811.6559
Training epoch 1980, recon_loss:0.769724, zinb_loss:0.636973, cluster_loss:0.151797
Clustering   1980: ASW= 0.8351, DB= 0.2253, CH= 57710.9823
Training epoch 1981, recon_loss:0.769637, zinb_loss:0.637460, cluster_loss:0.150914
Clustering   1981: ASW= 0.8349, DB= 0.2273, CH= 58934.2546
Training epoch 1982, recon_loss:0.769869, zinb_loss:0.637328, cluster_loss:0.152082
Clustering   1982: ASW= 0.8350, DB= 0.2260, CH= 57427.7765
Training epoch 1983, recon_loss:0.769195, zinb_loss:0.637654, cluster_loss:0.150925
Clustering   1983: ASW= 0.8351, DB= 0.2274, CH= 58991.0786
Training epoch 1984, recon_loss:0.769311, zinb_loss:0.637486, cluster_loss:0.151933
Clustering   1984: ASW= 0.8352, DB= 0.2260, CH= 57544.3600
Training epoch 1985, recon_loss:0.768646, zinb_loss:0.637767, cluster_loss:0.150808
Clustering   1985: ASW= 0.8353, DB= 0.2273, CH= 59076.0323
Training epoch 1986, recon_loss:0.768776, zinb_loss:0.637717, cluster_loss:0.151531
Clustering   1986: ASW= 0.8357, DB= 0.2253, CH= 57931.4493
Training epoch 1987, recon_loss:0.768227, zinb_loss:0.637892, cluster_loss:0.150613
Clustering   1987: ASW= 0.8355, DB= 0.2271, CH= 59236.2225
Training epoch 1988, recon_loss:0.768627, zinb_loss:0.638033, cluster_loss:0.151187
Clustering   1988: ASW= 0.8361, DB= 0.2248, CH= 58292.1086
Training epoch 1989, recon_loss:0.768340, zinb_loss:0.638237, cluster_loss:0.150560
Clustering   1989: ASW= 0.8354, DB= 0.2273, CH= 59283.7958
Training epoch 1990, recon_loss:0.769171, zinb_loss:0.638558, cluster_loss:0.150972
Clustering   1990: ASW= 0.8365, DB= 0.2245, CH= 58624.7474
Training epoch 1991, recon_loss:0.768784, zinb_loss:0.638496, cluster_loss:0.150656
Clustering   1991: ASW= 0.8353, DB= 0.2274, CH= 59176.4936
Training epoch 1992, recon_loss:0.769866, zinb_loss:0.638848, cluster_loss:0.150976
Clustering   1992: ASW= 0.8367, DB= 0.2238, CH= 58882.8603
Training epoch 1993, recon_loss:0.769482, zinb_loss:0.638755, cluster_loss:0.150743
Clustering   1993: ASW= 0.8351, DB= 0.2280, CH= 59055.9768
Training epoch 1994, recon_loss:0.770182, zinb_loss:0.639064, cluster_loss:0.150861
Clustering   1994: ASW= 0.8368, DB= 0.2241, CH= 58971.7132
Training epoch 1995, recon_loss:0.769485, zinb_loss:0.638650, cluster_loss:0.150787
Clustering   1995: ASW= 0.8352, DB= 0.2273, CH= 58983.8484
Training epoch 1996, recon_loss:0.770352, zinb_loss:0.638888, cluster_loss:0.150945
Clustering   1996: ASW= 0.8368, DB= 0.2240, CH= 59127.6146
Training epoch 1997, recon_loss:0.769486, zinb_loss:0.638490, cluster_loss:0.150750
Clustering   1997: ASW= 0.8350, DB= 0.2276, CH= 58808.2613
Training epoch 1998, recon_loss:0.770200, zinb_loss:0.638635, cluster_loss:0.150786
Clustering   1998: ASW= 0.8367, DB= 0.2239, CH= 59205.3270
Training epoch 1999, recon_loss:0.769249, zinb_loss:0.638136, cluster_loss:0.150793
Clustering   1999: ASW= 0.8350, DB= 0.2275, CH= 58725.9285
Training epoch 2000, recon_loss:0.769908, zinb_loss:0.638326, cluster_loss:0.150852
Clustering   2000: ASW= 0.8367, DB= 0.2243, CH= 59218.0401
Final Result : ASW= 0.8367, DB= 0.2243, CH= 59218.0401

import numpy as np

np.savetxt("../results/GSM4949911_pred.csv", y_pred, delimiter=",")
np.savetxt("../results/GSM4949911_embedding.csv", final_latent.cpu().detach().numpy(), delimiter=",")

library(anndata)
library(reticulate)
library(dplyr)
library(tidyr)
library(Seurat)
library(ggplot2)

use_condaenv("/home/zhouzeming/anaconda3")

sys <- import("sys")

ad <- import("anndata")

rna <- ad$read_h5ad('../datasets/GSM4949911/GSM4949911_rna.h5ad')
colnames(rna)[duplicated(colnames(rna))]
colnames(rna)<-make.unique(colnames(rna))
colnames(rna)[duplicated(colnames(rna))]
scRNA.rna <- rna$X

1. 'TBCE'
2. 'LINC01238'
3. 'CYB561D2'
4. 'MATR3'
5. 'LINC01505'
6. 'HSPA14'
7. 'GOLGA8M'
8. 'GGT1'
9. 'ARMCX5-GPRASP2'
10. 'TMSB15B'

Warning message in private$.anndata$obs_names$name <- attr(value, "name"):
“Coercing LHS to a list”
Warning message in private$.anndata$var_names$name <- attr(value, "name"):
“Coercing LHS to a list”

scRNA <- CreateSeuratObject(counts = t(scRNA.rna),project ="scRNA",min.cells = 3)
label <- read.csv("../results/GSM4949911_pred.csv",header = F)
scRNA@meta.data$clusters <- label
Idents(scRNA) <- as.factor(label$V1)
scRNA <- NormalizeData(scRNA, normalization.method = "LogNormalize")
scRNA <- FindVariableFeatures(scRNA, selection.method = "vst", nfeatures = 2000)
scRNA <- ScaleData(scRNA, features = rownames(scRNA))
all.genes <- rownames(scRNA)
variable.genes <- head(VariableFeatures(scRNA), 2000)

mds<- read.csv('../results/GSM4949911_embedding.csv',row.names=1)
mds <- as.matrix(mds)
colnames(mds) <- paste0("MDS_", 1:32)
scRNA[["mds"]] <- CreateDimReducObject(embeddings = mds, key = "MDS_", assay = DefaultAssay(scRNA))
scRNA <- RunUMAP(scRNA,dims = 1:30,label=T,reduction = "mds")

Warning message:
“Data is of class dgRMatrix. Coercing to dgCMatrix.”
Normalizing layer: counts

Finding variable features for layer counts

Centering and scaling data matrix

Warning message:
“The following arguments are not used: label”
Warning message:
“The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session”
20:39:51 UMAP embedding parameters a = 0.9922 b = 1.112

20:39:51 Read 8213 rows and found 30 numeric columns

20:39:51 Using Annoy for neighbor search, n_neighbors = 30

20:39:51 Building Annoy index with metric = cosine, n_trees = 50

0%   10   20   30   40   50   60   70   80   90   100%

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20:39:52 Writing NN index file to temp file /tmp/RtmpZ8OezE/file13ace15bcb7e37

20:39:52 Searching Annoy index using 1 thread, search_k = 3000

20:39:54 Annoy recall = 100%

20:39:54 Commencing smooth kNN distance calibration using 1 thread
 with target n_neighbors = 30

20:39:55 Initializing from normalized Laplacian + noise (using RSpectra)

20:39:56 Commencing optimization for 500 epochs, with 311344 positive edges

20:39:56 Using rng type: pcg

20:40:04 Optimization finished

scRNA.markers <- FindAllMarkers(scRNA,
                                ident.col = "clusters",
                                only.pos = T,
                                min.pct = 0.25,
                                logfc.threshold = 0.25,
                                features = variable.genes)
top.markers <- scRNA.markers %>% group_by(cluster) %>% top_n(n = 10, wt = avg_log2FC)

Calculating cluster 0

For a (much!) faster implementation of the Wilcoxon Rank Sum Test,
(default method for FindMarkers) please install the presto package
--------------------------------------------
install.packages('devtools')
devtools::install_github('immunogenomics/presto')
--------------------------------------------
After installation of presto, Seurat will automatically use the more
efficient implementation (no further action necessary).
This message will be shown once per session

Calculating cluster 1

Calculating cluster 2

Calculating cluster 3

Calculating cluster 4

Calculating cluster 5

new.cluster.ids <- c("Activated effector cell", "Naive B cell", "Activated memory B cell", "Naive CD4 T cell", "T follicular helper cell", "NK cell")
mycolors <- c("Activated effector cell"='#dc8e97', "Naive B cell"='#e3d1db', "Activated memory B cell"='#74a893', "Naive CD4 T cell"='#ac9141',
              "T follicular helper cell"='#5ac6e9', "NK cell"='#ebce8e')
names(new.cluster.ids) <- levels(scRNA)
scRNA <- RenameIdents(scRNA, new.cluster.ids)
Joint_umap <-DimPlot(scRNA, reduction = "umap", label = FALSE, cols = mycolors)
Joint_umap