2023-02-12 10:56:45,006	32k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'kokona': 0}, 'model_dir': './logs\\32k'}
2023-02-12 10:56:49,681	32k	INFO	Loaded checkpoint './logs\32k\G_0.pth' (iteration 1)
2023-02-12 10:56:50,100	32k	INFO	Loaded checkpoint './logs\32k\D_0.pth' (iteration 1)
2023-02-12 10:56:57,971	32k	INFO	Train Epoch: 1 [0%]
2023-02-12 10:56:57,972	32k	INFO	[5.542299270629883, 2.665985584259033, 25.682283401489258, 61.07982635498047, 23.713857650756836, 0, 0.0001]
2023-02-12 10:57:02,683	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\G_0.pth
2023-02-12 10:57:20,546	32k	INFO	Saving model and optimizer state at iteration 1 to ./logs\32k\D_0.pth
2023-02-12 10:57:33,150	32k	INFO	====> Epoch: 1
2023-02-12 10:57:44,832	32k	INFO	====> Epoch: 2
2023-02-12 10:57:56,786	32k	INFO	====> Epoch: 3
2023-02-12 10:58:08,535	32k	INFO	====> Epoch: 4
2023-02-12 10:58:20,086	32k	INFO	====> Epoch: 5
2023-02-12 10:58:31,611	32k	INFO	====> Epoch: 6
2023-02-12 10:58:43,440	32k	INFO	====> Epoch: 7
2023-02-12 10:58:55,041	32k	INFO	====> Epoch: 8
2023-02-12 10:59:06,941	32k	INFO	====> Epoch: 9
2023-02-12 10:59:18,739	32k	INFO	====> Epoch: 10
2023-02-12 10:59:30,357	32k	INFO	====> Epoch: 11
2023-02-12 10:59:41,930	32k	INFO	====> Epoch: 12
2023-02-12 10:59:53,467	32k	INFO	====> Epoch: 13
2023-02-12 11:00:05,013	32k	INFO	====> Epoch: 14
2023-02-12 11:00:16,524	32k	INFO	====> Epoch: 15
2023-02-12 11:00:28,026	32k	INFO	====> Epoch: 16
2023-02-12 11:00:39,562	32k	INFO	====> Epoch: 17
2023-02-12 11:00:51,286	32k	INFO	====> Epoch: 18
2023-02-12 11:01:03,137	32k	INFO	====> Epoch: 19
2023-02-12 11:01:15,001	32k	INFO	====> Epoch: 20
2023-02-12 11:01:18,938	32k	INFO	Train Epoch: 21 [0%]
2023-02-12 11:01:18,938	32k	INFO	[2.2646379470825195, 2.8810572624206543, 21.821720123291016, 28.875865936279297, 1.5514765977859497, 200, 9.975029665246193e-05]
2023-02-12 11:01:27,081	32k	INFO	====> Epoch: 21
2023-02-12 11:01:38,907	32k	INFO	====> Epoch: 22
2023-02-12 11:01:50,710	32k	INFO	====> Epoch: 23
2023-02-12 11:02:02,465	32k	INFO	====> Epoch: 24
2023-02-12 11:02:14,323	32k	INFO	====> Epoch: 25
2023-02-12 11:02:26,150	32k	INFO	====> Epoch: 26
2023-02-12 11:02:37,975	32k	INFO	====> Epoch: 27
2023-02-12 11:02:49,723	32k	INFO	====> Epoch: 28
2023-02-12 11:03:01,503	32k	INFO	====> Epoch: 29
2023-02-12 11:03:13,297	32k	INFO	====> Epoch: 30
2023-02-12 11:03:25,140	32k	INFO	====> Epoch: 31
2023-02-12 11:03:37,002	32k	INFO	====> Epoch: 32
2023-02-12 11:03:48,848	32k	INFO	====> Epoch: 33
2023-02-12 11:04:00,694	32k	INFO	====> Epoch: 34
2023-02-12 11:04:12,600	32k	INFO	====> Epoch: 35
2023-02-12 11:04:24,461	32k	INFO	====> Epoch: 36
2023-02-12 11:04:36,311	32k	INFO	====> Epoch: 37
2023-02-12 11:04:48,169	32k	INFO	====> Epoch: 38
2023-02-12 11:05:00,013	32k	INFO	====> Epoch: 39
2023-02-12 11:05:11,908	32k	INFO	====> Epoch: 40
2023-02-12 11:05:15,875	32k	INFO	Train Epoch: 41 [0%]
2023-02-12 11:05:15,876	32k	INFO	[2.6570241451263428, 2.4744293689727783, 17.774166107177734, 24.35066032409668, 0.9465541839599609, 400, 9.950121682254156e-05]
2023-02-12 11:05:24,041	32k	INFO	====> Epoch: 41
2023-02-12 11:05:35,917	32k	INFO	====> Epoch: 42
2023-02-12 11:05:47,768	32k	INFO	====> Epoch: 43
2023-02-12 11:05:59,533	32k	INFO	====> Epoch: 44
2023-02-12 11:06:11,381	32k	INFO	====> Epoch: 45
2023-02-12 11:06:23,242	32k	INFO	====> Epoch: 46
2023-02-12 11:06:35,129	32k	INFO	====> Epoch: 47
2023-02-12 11:06:47,035	32k	INFO	====> Epoch: 48
2023-02-12 11:06:59,085	32k	INFO	====> Epoch: 49
2023-02-12 11:07:10,938	32k	INFO	====> Epoch: 50
2023-02-12 11:07:22,738	32k	INFO	====> Epoch: 51
2023-02-12 11:07:34,563	32k	INFO	====> Epoch: 52
2023-02-12 11:07:46,508	32k	INFO	====> Epoch: 53
2023-02-12 11:07:58,340	32k	INFO	====> Epoch: 54
2023-02-12 11:08:10,167	32k	INFO	====> Epoch: 55
2023-02-12 11:08:22,002	32k	INFO	====> Epoch: 56
2023-02-12 11:08:33,799	32k	INFO	====> Epoch: 57
2023-02-12 11:08:45,645	32k	INFO	====> Epoch: 58
2023-02-12 11:08:57,520	32k	INFO	====> Epoch: 59
2023-02-12 11:09:09,331	32k	INFO	====> Epoch: 60
2023-02-12 11:09:13,330	32k	INFO	Train Epoch: 61 [0%]
2023-02-12 11:09:13,331	32k	INFO	[2.2702250480651855, 2.8278610706329346, 21.250120162963867, 24.127765655517578, 1.1770193576812744, 600, 9.92527589532945e-05]
2023-02-12 11:09:21,468	32k	INFO	====> Epoch: 61
2023-02-12 11:09:33,308	32k	INFO	====> Epoch: 62
2023-02-12 11:09:45,117	32k	INFO	====> Epoch: 63
2023-02-12 11:09:57,348	32k	INFO	====> Epoch: 64
2023-02-12 11:10:09,164	32k	INFO	====> Epoch: 65
2023-02-12 11:10:21,011	32k	INFO	====> Epoch: 66
2023-02-12 11:10:32,891	32k	INFO	====> Epoch: 67
2023-02-12 11:10:44,736	32k	INFO	====> Epoch: 68
2023-02-12 11:10:56,547	32k	INFO	====> Epoch: 69
2023-02-12 11:11:08,388	32k	INFO	====> Epoch: 70
2023-02-12 11:11:20,256	32k	INFO	====> Epoch: 71
2023-02-12 11:11:32,063	32k	INFO	====> Epoch: 72
2023-02-12 11:11:43,887	32k	INFO	====> Epoch: 73
2023-02-12 11:11:55,686	32k	INFO	====> Epoch: 74
2023-02-12 11:12:07,497	32k	INFO	====> Epoch: 75
2023-02-12 11:12:19,331	32k	INFO	====> Epoch: 76
2023-02-12 11:12:31,152	32k	INFO	====> Epoch: 77
2023-02-12 11:12:43,409	32k	INFO	====> Epoch: 78
2023-02-12 11:12:55,162	32k	INFO	====> Epoch: 79
2023-02-12 11:13:06,925	32k	INFO	====> Epoch: 80
2023-02-12 11:13:11,149	32k	INFO	Train Epoch: 81 [0%]
2023-02-12 11:13:11,149	32k	INFO	[2.0064303874969482, 2.8905510902404785, 21.634431838989258, 27.9136905670166, 0.8381181359291077, 800, 9.900492149166423e-05]
2023-02-12 11:13:19,220	32k	INFO	====> Epoch: 81
2023-02-12 11:13:31,164	32k	INFO	====> Epoch: 82
2023-02-12 11:13:43,146	32k	INFO	====> Epoch: 83
2023-02-12 11:13:55,115	32k	INFO	====> Epoch: 84
2023-02-12 11:14:06,864	32k	INFO	====> Epoch: 85
2023-02-12 11:14:18,651	32k	INFO	====> Epoch: 86
2023-02-12 11:14:30,897	32k	INFO	====> Epoch: 87
2023-02-12 11:14:42,625	32k	INFO	====> Epoch: 88
2023-02-12 11:14:54,406	32k	INFO	====> Epoch: 89
2023-02-12 11:15:06,167	32k	INFO	====> Epoch: 90
2023-02-12 11:15:17,940	32k	INFO	====> Epoch: 91
2023-02-12 11:15:29,747	32k	INFO	====> Epoch: 92
2023-02-12 11:15:41,489	32k	INFO	====> Epoch: 93
2023-02-12 11:15:53,219	32k	INFO	====> Epoch: 94
2023-02-12 11:16:05,065	32k	INFO	====> Epoch: 95
2023-02-12 11:16:16,788	32k	INFO	====> Epoch: 96
2023-02-12 11:16:28,545	32k	INFO	====> Epoch: 97
2023-02-12 11:16:40,278	32k	INFO	====> Epoch: 98
2023-02-12 11:16:52,067	32k	INFO	====> Epoch: 99
2023-02-12 11:17:03,841	32k	INFO	====> Epoch: 100
2023-02-12 11:17:07,825	32k	INFO	Train Epoch: 101 [0%]
2023-02-12 11:17:07,825	32k	INFO	[2.1760404109954834, 2.7696290016174316, 19.465646743774414, 26.03284454345703, 0.6845554113388062, 1000, 9.875770288847208e-05]
2023-02-12 11:17:11,834	32k	INFO	Saving model and optimizer state at iteration 101 to ./logs\32k\G_1000.pth
2023-02-12 11:17:30,193	32k	INFO	Saving model and optimizer state at iteration 101 to ./logs\32k\D_1000.pth
2023-02-12 11:17:41,848	32k	INFO	====> Epoch: 101
2023-02-12 11:17:53,661	32k	INFO	====> Epoch: 102
2023-02-12 11:18:05,405	32k	INFO	====> Epoch: 103
2023-02-12 11:18:17,193	32k	INFO	====> Epoch: 104
2023-02-12 11:18:29,145	32k	INFO	====> Epoch: 105
2023-02-12 11:18:41,026	32k	INFO	====> Epoch: 106
2023-02-12 11:18:53,081	32k	INFO	====> Epoch: 107
2023-02-12 11:19:04,984	32k	INFO	====> Epoch: 108
2023-02-12 11:19:16,806	32k	INFO	====> Epoch: 109
2023-02-12 11:19:28,539	32k	INFO	====> Epoch: 110
2023-02-12 11:19:40,250	32k	INFO	====> Epoch: 111
2023-02-12 11:19:52,079	32k	INFO	====> Epoch: 112
2023-02-12 11:20:04,137	32k	INFO	====> Epoch: 113
2023-02-12 11:20:16,221	32k	INFO	====> Epoch: 114
2023-02-12 11:20:27,961	32k	INFO	====> Epoch: 115
2023-02-12 11:20:39,811	32k	INFO	====> Epoch: 116
2023-02-12 11:20:51,685	32k	INFO	====> Epoch: 117
2023-02-12 11:21:03,450	32k	INFO	====> Epoch: 118
2023-02-12 11:21:15,321	32k	INFO	====> Epoch: 119
2023-02-12 11:21:27,585	32k	INFO	====> Epoch: 120
2023-02-12 11:21:31,953	32k	INFO	Train Epoch: 121 [0%]
2023-02-12 11:21:31,954	32k	INFO	[2.2874832153320312, 2.9262359142303467, 16.725116729736328, 20.911989212036133, 1.0630743503570557, 1200, 9.851110159840781e-05]
2023-02-12 11:21:40,124	32k	INFO	====> Epoch: 121
2023-02-12 11:21:51,979	32k	INFO	====> Epoch: 122
2023-02-12 11:22:03,684	32k	INFO	====> Epoch: 123
2023-02-12 11:22:15,443	32k	INFO	====> Epoch: 124
2023-02-12 11:22:27,207	32k	INFO	====> Epoch: 125
2023-02-12 11:22:39,081	32k	INFO	====> Epoch: 126
2023-02-12 11:22:50,811	32k	INFO	====> Epoch: 127
2023-02-12 11:23:02,623	32k	INFO	====> Epoch: 128
2023-02-12 11:23:14,394	32k	INFO	====> Epoch: 129
2023-02-12 11:23:26,133	32k	INFO	====> Epoch: 130
2023-02-12 11:23:37,871	32k	INFO	====> Epoch: 131
2023-02-12 11:23:49,646	32k	INFO	====> Epoch: 132
2023-02-12 11:24:01,537	32k	INFO	====> Epoch: 133
2023-02-12 11:24:13,431	32k	INFO	====> Epoch: 134
2023-02-12 11:24:25,132	32k	INFO	====> Epoch: 135
2023-02-12 11:24:36,919	32k	INFO	====> Epoch: 136
2023-02-12 11:24:48,897	32k	INFO	====> Epoch: 137
2023-02-12 11:25:00,870	32k	INFO	====> Epoch: 138
2023-02-12 11:25:12,829	32k	INFO	====> Epoch: 139
2023-02-12 11:25:24,618	32k	INFO	====> Epoch: 140
2023-02-12 11:25:28,637	32k	INFO	Train Epoch: 141 [0%]
2023-02-12 11:25:28,638	32k	INFO	[2.105891704559326, 2.802135467529297, 18.534683227539062, 23.033945083618164, 0.7122542858123779, 1400, 9.826511608001993e-05]
2023-02-12 11:25:36,725	32k	INFO	====> Epoch: 141
2023-02-12 11:25:48,480	32k	INFO	====> Epoch: 142
2023-02-12 11:26:00,535	32k	INFO	====> Epoch: 143
2023-02-12 11:26:12,581	32k	INFO	====> Epoch: 144
2023-02-12 11:26:24,644	32k	INFO	====> Epoch: 145
2023-02-12 11:26:36,422	32k	INFO	====> Epoch: 146
2023-02-12 11:26:48,474	32k	INFO	====> Epoch: 147
2023-02-12 11:27:00,575	32k	INFO	====> Epoch: 148
2023-02-12 11:27:12,318	32k	INFO	====> Epoch: 149
2023-02-12 11:27:24,125	32k	INFO	====> Epoch: 150
2023-02-12 11:27:35,921	32k	INFO	====> Epoch: 151
2023-02-12 11:27:47,698	32k	INFO	====> Epoch: 152
2023-02-12 11:27:59,449	32k	INFO	====> Epoch: 153
2023-02-12 11:28:11,180	32k	INFO	====> Epoch: 154
2023-02-12 11:28:23,312	32k	INFO	====> Epoch: 155
2023-02-12 11:28:35,503	32k	INFO	====> Epoch: 156
2023-02-12 11:28:47,439	32k	INFO	====> Epoch: 157
2023-02-12 11:28:59,318	32k	INFO	====> Epoch: 158
2023-02-12 11:29:11,184	32k	INFO	====> Epoch: 159
2023-02-12 11:29:23,070	32k	INFO	====> Epoch: 160
2023-02-12 11:29:27,061	32k	INFO	Train Epoch: 161 [0%]
2023-02-12 11:29:27,061	32k	INFO	[2.12371826171875, 2.916212320327759, 16.768640518188477, 23.12175178527832, 0.5789794921875, 1600, 9.801974479570593e-05]
2023-02-12 11:29:35,217	32k	INFO	====> Epoch: 161
2023-02-12 11:29:47,083	32k	INFO	====> Epoch: 162
2023-02-12 11:29:58,968	32k	INFO	====> Epoch: 163
2023-02-12 11:30:11,007	32k	INFO	====> Epoch: 164
2023-02-12 11:30:22,794	32k	INFO	====> Epoch: 165
2023-02-12 11:30:34,605	32k	INFO	====> Epoch: 166
2023-02-12 11:30:46,411	32k	INFO	====> Epoch: 167
2023-02-12 11:30:58,244	32k	INFO	====> Epoch: 168
2023-02-12 11:31:10,094	32k	INFO	====> Epoch: 169
2023-02-12 11:31:21,918	32k	INFO	====> Epoch: 170
2023-02-12 11:31:33,722	32k	INFO	====> Epoch: 171
2023-02-12 11:31:45,581	32k	INFO	====> Epoch: 172
2023-02-12 11:31:57,450	32k	INFO	====> Epoch: 173
2023-02-12 11:32:09,314	32k	INFO	====> Epoch: 174
2023-02-12 11:32:21,340	32k	INFO	====> Epoch: 175
2023-02-12 11:32:33,599	32k	INFO	====> Epoch: 176
2023-02-12 11:32:45,619	32k	INFO	====> Epoch: 177
2023-02-12 11:32:57,591	32k	INFO	====> Epoch: 178
2023-02-12 11:33:09,508	32k	INFO	====> Epoch: 179
2023-02-12 11:33:24,067	32k	INFO	====> Epoch: 180
2023-02-12 11:33:28,651	32k	INFO	Train Epoch: 181 [0%]
2023-02-12 11:33:28,651	32k	INFO	[2.2422454357147217, 2.668048143386841, 21.7828311920166, 24.486221313476562, 0.616005539894104, 1800, 9.777498621170277e-05]
2023-02-12 11:33:40,856	32k	INFO	====> Epoch: 181
2023-02-12 11:33:55,025	32k	INFO	====> Epoch: 182
2023-02-12 11:34:07,656	32k	INFO	====> Epoch: 183
2023-02-12 11:34:20,021	32k	INFO	====> Epoch: 184
2023-02-12 11:34:32,365	32k	INFO	====> Epoch: 185
2023-02-12 11:34:48,941	32k	INFO	====> Epoch: 186
2023-02-12 11:35:01,259	32k	INFO	====> Epoch: 187
2023-02-12 11:35:16,591	32k	INFO	====> Epoch: 188
2023-02-12 11:35:29,032	32k	INFO	====> Epoch: 189
2023-02-12 11:35:41,850	32k	INFO	====> Epoch: 190
2023-02-12 11:35:54,858	32k	INFO	====> Epoch: 191
2023-02-12 11:36:06,921	32k	INFO	====> Epoch: 192
2023-02-12 11:36:18,922	32k	INFO	====> Epoch: 193
2023-02-12 11:36:32,051	32k	INFO	====> Epoch: 194
2023-02-12 11:36:44,856	32k	INFO	====> Epoch: 195
2023-02-12 11:36:56,694	32k	INFO	====> Epoch: 196
2023-02-12 11:37:09,214	32k	INFO	====> Epoch: 197
2023-02-12 11:37:22,723	32k	INFO	====> Epoch: 198
2023-02-12 11:37:36,261	32k	INFO	====> Epoch: 199
2023-02-12 11:37:50,831	32k	INFO	====> Epoch: 200
2023-02-12 11:37:55,521	32k	INFO	Train Epoch: 201 [0%]
2023-02-12 11:37:55,522	32k	INFO	[2.0545427799224854, 2.9191207885742188, 18.014545440673828, 22.382339477539062, 1.145055890083313, 2000, 9.753083879807726e-05]
2023-02-12 11:37:59,920	32k	INFO	Saving model and optimizer state at iteration 201 to ./logs\32k\G_2000.pth
2023-02-12 11:38:16,144	32k	INFO	Saving model and optimizer state at iteration 201 to ./logs\32k\D_2000.pth
2023-02-12 11:38:30,348	32k	INFO	====> Epoch: 201
2023-02-12 11:38:43,817	32k	INFO	====> Epoch: 202
2023-02-12 11:38:57,290	32k	INFO	====> Epoch: 203
2023-02-12 11:39:10,783	32k	INFO	====> Epoch: 204
2023-02-12 11:39:24,353	32k	INFO	====> Epoch: 205
2023-02-12 11:39:38,012	32k	INFO	====> Epoch: 206
2023-02-12 11:39:51,464	32k	INFO	====> Epoch: 207
2023-02-12 11:40:04,919	32k	INFO	====> Epoch: 208
2023-02-12 11:40:18,279	32k	INFO	====> Epoch: 209
2023-02-12 11:40:31,783	32k	INFO	====> Epoch: 210
2023-02-12 11:40:45,205	32k	INFO	====> Epoch: 211
2023-02-12 11:40:58,570	32k	INFO	====> Epoch: 212
2023-02-12 11:41:11,970	32k	INFO	====> Epoch: 213
2023-02-12 11:41:25,491	32k	INFO	====> Epoch: 214
2023-02-12 11:41:38,900	32k	INFO	====> Epoch: 215
2023-02-12 11:41:52,375	32k	INFO	====> Epoch: 216
2023-02-12 11:42:05,789	32k	INFO	====> Epoch: 217
2023-02-12 11:42:19,197	32k	INFO	====> Epoch: 218
2023-02-12 11:42:32,682	32k	INFO	====> Epoch: 219
2023-02-12 11:42:46,135	32k	INFO	====> Epoch: 220
2023-02-12 11:42:50,366	32k	INFO	Train Epoch: 221 [0%]
2023-02-12 11:42:50,367	32k	INFO	[2.090278148651123, 2.901176691055298, 18.832168579101562, 21.155336380004883, 0.886482298374176, 2200, 9.728730102871649e-05]
2023-02-12 11:42:59,902	32k	INFO	====> Epoch: 221
2023-02-12 11:43:13,295	32k	INFO	====> Epoch: 222
2023-02-12 11:43:26,687	32k	INFO	====> Epoch: 223
2023-02-12 11:43:40,183	32k	INFO	====> Epoch: 224
2023-02-12 11:43:53,653	32k	INFO	====> Epoch: 225
2023-02-12 11:44:07,139	32k	INFO	====> Epoch: 226
2023-02-12 11:44:20,539	32k	INFO	====> Epoch: 227
2023-02-12 11:44:34,040	32k	INFO	====> Epoch: 228
2023-02-12 11:44:47,520	32k	INFO	====> Epoch: 229
2023-02-12 11:45:00,992	32k	INFO	====> Epoch: 230
2023-02-12 11:45:14,510	32k	INFO	====> Epoch: 231
2023-02-12 11:45:27,845	32k	INFO	====> Epoch: 232
2023-02-12 11:45:41,334	32k	INFO	====> Epoch: 233
2023-02-12 11:45:54,721	32k	INFO	====> Epoch: 234
2023-02-12 11:46:08,166	32k	INFO	====> Epoch: 235
2023-02-12 11:46:21,620	32k	INFO	====> Epoch: 236
2023-02-12 11:46:35,080	32k	INFO	====> Epoch: 237
2023-02-12 11:46:48,502	32k	INFO	====> Epoch: 238
2023-02-12 11:47:01,777	32k	INFO	====> Epoch: 239
2023-02-12 11:47:15,303	32k	INFO	====> Epoch: 240
2023-02-12 11:47:19,521	32k	INFO	Train Epoch: 241 [0%]
2023-02-12 11:47:19,522	32k	INFO	[2.164433240890503, 2.935574531555176, 19.110923767089844, 23.871938705444336, 0.7375960350036621, 2400, 9.704437138131832e-05]
2023-02-12 11:47:29,199	32k	INFO	====> Epoch: 241
2023-02-12 11:47:42,638	32k	INFO	====> Epoch: 242
2023-02-12 11:47:56,029	32k	INFO	====> Epoch: 243
2023-02-12 11:48:09,546	32k	INFO	====> Epoch: 244
2023-02-12 11:48:23,026	32k	INFO	====> Epoch: 245
2023-02-12 11:48:36,437	32k	INFO	====> Epoch: 246
2023-02-12 11:48:49,748	32k	INFO	====> Epoch: 247
2023-02-12 11:49:03,238	32k	INFO	====> Epoch: 248
2023-02-12 11:49:16,702	32k	INFO	====> Epoch: 249
2023-02-12 11:49:30,243	32k	INFO	====> Epoch: 250
2023-02-12 11:49:43,768	32k	INFO	====> Epoch: 251
2023-02-12 11:49:57,209	32k	INFO	====> Epoch: 252
2023-02-12 11:50:10,687	32k	INFO	====> Epoch: 253
2023-02-12 11:50:24,149	32k	INFO	====> Epoch: 254
2023-02-12 11:50:37,717	32k	INFO	====> Epoch: 255
2023-02-12 11:50:51,220	32k	INFO	====> Epoch: 256
2023-02-12 11:51:04,603	32k	INFO	====> Epoch: 257
2023-02-12 11:51:18,055	32k	INFO	====> Epoch: 258
2023-02-12 11:51:31,538	32k	INFO	====> Epoch: 259
2023-02-12 11:51:45,012	32k	INFO	====> Epoch: 260
2023-02-12 11:51:49,168	32k	INFO	Train Epoch: 261 [0%]
2023-02-12 11:51:49,168	32k	INFO	[2.2391364574432373, 2.84315824508667, 20.665061950683594, 24.793420791625977, 1.078212857246399, 2600, 9.680204833738185e-05]
2023-02-12 11:51:58,658	32k	INFO	====> Epoch: 261
2023-02-12 11:52:12,032	32k	INFO	====> Epoch: 262
2023-02-12 11:52:25,558	32k	INFO	====> Epoch: 263
2023-02-12 11:52:38,852	32k	INFO	====> Epoch: 264
2023-02-12 11:52:52,345	32k	INFO	====> Epoch: 265
2023-02-12 11:53:05,738	32k	INFO	====> Epoch: 266
2023-02-12 11:53:19,237	32k	INFO	====> Epoch: 267
2023-02-12 11:53:32,698	32k	INFO	====> Epoch: 268
2023-02-12 11:53:46,167	32k	INFO	====> Epoch: 269
2023-02-12 11:53:59,556	32k	INFO	====> Epoch: 270
2023-02-12 11:54:12,926	32k	INFO	====> Epoch: 271
2023-02-12 11:54:26,432	32k	INFO	====> Epoch: 272
2023-02-12 11:54:39,713	32k	INFO	====> Epoch: 273
2023-02-12 11:54:53,215	32k	INFO	====> Epoch: 274
2023-02-12 11:55:06,750	32k	INFO	====> Epoch: 275
2023-02-12 11:55:20,235	32k	INFO	====> Epoch: 276
2023-02-12 11:55:33,747	32k	INFO	====> Epoch: 277
2023-02-12 11:55:47,270	32k	INFO	====> Epoch: 278
2023-02-12 11:56:00,654	32k	INFO	====> Epoch: 279
2023-02-12 11:56:14,083	32k	INFO	====> Epoch: 280
2023-02-12 11:56:18,314	32k	INFO	Train Epoch: 281 [0%]
2023-02-12 11:56:18,314	32k	INFO	[2.089102268218994, 3.0276288986206055, 18.402175903320312, 22.983383178710938, 0.877465009689331, 2800, 9.656033038219798e-05]
2023-02-12 11:56:27,805	32k	INFO	====> Epoch: 281
2023-02-12 11:56:41,247	32k	INFO	====> Epoch: 282
2023-02-12 11:56:54,716	32k	INFO	====> Epoch: 283
2023-02-12 11:57:08,217	32k	INFO	====> Epoch: 284
2023-02-12 11:57:21,621	32k	INFO	====> Epoch: 285
2023-02-12 11:57:35,076	32k	INFO	====> Epoch: 286
2023-02-12 11:57:48,581	32k	INFO	====> Epoch: 287
2023-02-12 11:58:02,183	32k	INFO	====> Epoch: 288
2023-02-12 11:58:15,702	32k	INFO	====> Epoch: 289
2023-02-12 11:58:29,205	32k	INFO	====> Epoch: 290
2023-02-12 11:58:42,696	32k	INFO	====> Epoch: 291
2023-02-12 11:58:56,116	32k	INFO	====> Epoch: 292
2023-02-12 11:59:09,523	32k	INFO	====> Epoch: 293
2023-02-12 11:59:22,955	32k	INFO	====> Epoch: 294
2023-02-12 11:59:36,318	32k	INFO	====> Epoch: 295
2023-02-12 11:59:49,639	32k	INFO	====> Epoch: 296
2023-02-12 12:00:01,466	32k	INFO	====> Epoch: 297
2023-02-12 12:00:13,257	32k	INFO	====> Epoch: 298
2023-02-12 12:00:25,042	32k	INFO	====> Epoch: 299
2023-02-12 12:00:36,786	32k	INFO	====> Epoch: 300
2023-02-12 12:00:40,787	32k	INFO	Train Epoch: 301 [0%]
2023-02-12 12:00:40,788	32k	INFO	[2.2152934074401855, 2.5910556316375732, 20.002161026000977, 23.172073364257812, 0.6147266626358032, 3000, 9.631921600483981e-05]
2023-02-12 12:00:44,718	32k	INFO	Saving model and optimizer state at iteration 301 to ./logs\32k\G_3000.pth
2023-02-12 12:00:59,794	32k	INFO	Saving model and optimizer state at iteration 301 to ./logs\32k\D_3000.pth
2023-02-12 12:01:11,669	32k	INFO	====> Epoch: 301
2023-02-12 12:01:23,534	32k	INFO	====> Epoch: 302
2023-02-12 12:01:35,415	32k	INFO	====> Epoch: 303
2023-02-12 12:01:47,201	32k	INFO	====> Epoch: 304
2023-02-12 12:01:58,984	32k	INFO	====> Epoch: 305
2023-02-12 12:02:10,709	32k	INFO	====> Epoch: 306
2023-02-12 12:02:22,474	32k	INFO	====> Epoch: 307
2023-02-12 12:02:34,219	32k	INFO	====> Epoch: 308
2023-02-12 12:02:46,062	32k	INFO	====> Epoch: 309
2023-02-12 12:02:57,818	32k	INFO	====> Epoch: 310
2023-02-12 12:03:09,564	32k	INFO	====> Epoch: 311
2023-02-12 12:03:21,340	32k	INFO	====> Epoch: 312
2023-02-12 12:03:33,144	32k	INFO	====> Epoch: 313
2023-02-12 12:03:44,939	32k	INFO	====> Epoch: 314
2023-02-12 12:03:56,791	32k	INFO	====> Epoch: 315
2023-02-12 12:04:08,553	32k	INFO	====> Epoch: 316
2023-02-12 12:04:20,303	32k	INFO	====> Epoch: 317
2023-02-12 12:04:32,051	32k	INFO	====> Epoch: 318
2023-02-12 12:04:43,783	32k	INFO	====> Epoch: 319
2023-02-12 12:04:55,571	32k	INFO	====> Epoch: 320
2023-02-12 12:04:59,569	32k	INFO	Train Epoch: 321 [0%]
2023-02-12 12:04:59,569	32k	INFO	[2.1514697074890137, 2.755525588989258, 20.714019775390625, 23.780593872070312, 0.9267673492431641, 3200, 9.60787036981533e-05]
2023-02-12 12:05:07,741	32k	INFO	====> Epoch: 321
2023-02-12 12:05:19,499	32k	INFO	====> Epoch: 322
2023-02-12 12:05:31,230	32k	INFO	====> Epoch: 323
2023-02-12 12:05:43,319	32k	INFO	====> Epoch: 324
2023-02-12 12:05:55,102	32k	INFO	====> Epoch: 325
2023-02-12 12:06:06,864	32k	INFO	====> Epoch: 326
2023-02-12 12:06:18,598	32k	INFO	====> Epoch: 327
2023-02-12 12:06:30,332	32k	INFO	====> Epoch: 328
2023-02-12 12:06:42,124	32k	INFO	====> Epoch: 329
2023-02-12 12:06:53,858	32k	INFO	====> Epoch: 330
2023-02-12 12:07:05,636	32k	INFO	====> Epoch: 331
2023-02-12 12:07:17,420	32k	INFO	====> Epoch: 332
2023-02-12 12:07:29,158	32k	INFO	====> Epoch: 333
2023-02-12 12:07:40,909	32k	INFO	====> Epoch: 334
2023-02-12 12:07:52,617	32k	INFO	====> Epoch: 335
2023-02-12 12:08:04,417	32k	INFO	====> Epoch: 336
2023-02-12 12:08:16,164	32k	INFO	====> Epoch: 337
2023-02-12 12:08:27,982	32k	INFO	====> Epoch: 338
2023-02-12 12:08:39,744	32k	INFO	====> Epoch: 339
2023-02-12 12:08:51,555	32k	INFO	====> Epoch: 340
2023-02-12 12:08:55,574	32k	INFO	Train Epoch: 341 [0%]
2023-02-12 12:08:55,575	32k	INFO	[1.99088454246521, 3.1391944885253906, 19.213172912597656, 24.016939163208008, 0.2595030963420868, 3400, 9.583879195874782e-05]
2023-02-12 12:09:03,708	32k	INFO	====> Epoch: 341
2023-02-12 12:09:15,477	32k	INFO	====> Epoch: 342
2023-02-12 12:09:27,383	32k	INFO	====> Epoch: 343
2023-02-12 12:09:39,115	32k	INFO	====> Epoch: 344
2023-02-12 12:09:50,910	32k	INFO	====> Epoch: 345
2023-02-12 12:10:02,683	32k	INFO	====> Epoch: 346
2023-02-12 12:10:14,426	32k	INFO	====> Epoch: 347
2023-02-12 12:10:26,251	32k	INFO	====> Epoch: 348
2023-02-12 12:10:38,029	32k	INFO	====> Epoch: 349
2023-02-12 12:10:49,778	32k	INFO	====> Epoch: 350
2023-02-12 12:11:01,528	32k	INFO	====> Epoch: 351
2023-02-12 12:11:13,290	32k	INFO	====> Epoch: 352
2023-02-12 12:11:25,082	32k	INFO	====> Epoch: 353
2023-02-12 12:11:36,872	32k	INFO	====> Epoch: 354
2023-02-12 12:11:48,625	32k	INFO	====> Epoch: 355
2023-02-12 12:12:00,416	32k	INFO	====> Epoch: 356
2023-02-12 12:12:12,204	32k	INFO	====> Epoch: 357
2023-02-12 12:12:23,984	32k	INFO	====> Epoch: 358
2023-02-12 12:12:35,736	32k	INFO	====> Epoch: 359
2023-02-12 12:12:47,487	32k	INFO	====> Epoch: 360
2023-02-12 12:12:51,460	32k	INFO	Train Epoch: 361 [0%]
2023-02-12 12:12:51,460	32k	INFO	[2.2517716884613037, 3.1543078422546387, 17.141902923583984, 21.33304786682129, 0.61845463514328, 3600, 9.559947928698674e-05]
2023-02-12 12:12:59,561	32k	INFO	====> Epoch: 361
2023-02-12 12:13:11,307	32k	INFO	====> Epoch: 362
2023-02-12 12:13:23,047	32k	INFO	====> Epoch: 363
2023-02-12 12:13:34,932	32k	INFO	====> Epoch: 364
2023-02-12 12:13:46,693	32k	INFO	====> Epoch: 365
2023-02-12 12:13:58,434	32k	INFO	====> Epoch: 366
2023-02-12 12:14:10,215	32k	INFO	====> Epoch: 367
2023-02-12 12:14:21,979	32k	INFO	====> Epoch: 368
2023-02-12 12:14:33,709	32k	INFO	====> Epoch: 369
2023-02-12 12:14:45,488	32k	INFO	====> Epoch: 370
2023-02-12 12:14:57,284	32k	INFO	====> Epoch: 371
2023-02-12 12:15:09,114	32k	INFO	====> Epoch: 372
2023-02-12 12:15:20,878	32k	INFO	====> Epoch: 373
2023-02-12 12:15:32,664	32k	INFO	====> Epoch: 374
2023-02-12 12:15:44,442	32k	INFO	====> Epoch: 375
2023-02-12 12:15:56,221	32k	INFO	====> Epoch: 376
2023-02-12 12:16:07,957	32k	INFO	====> Epoch: 377
2023-02-12 12:16:19,738	32k	INFO	====> Epoch: 378
2023-02-12 12:16:31,483	32k	INFO	====> Epoch: 379
2023-02-12 12:16:43,206	32k	INFO	====> Epoch: 380
2023-02-12 12:16:47,249	32k	INFO	Train Epoch: 381 [0%]
2023-02-12 12:16:47,249	32k	INFO	[1.902297854423523, 3.237359046936035, 22.288528442382812, 24.29983139038086, 0.8269789218902588, 3800, 9.536076418697815e-05]
2023-02-12 12:16:55,364	32k	INFO	====> Epoch: 381
2023-02-12 12:17:07,188	32k	INFO	====> Epoch: 382
2023-02-12 12:17:18,981	32k	INFO	====> Epoch: 383
2023-02-12 12:17:30,762	32k	INFO	====> Epoch: 384
2023-02-12 12:17:42,525	32k	INFO	====> Epoch: 385
2023-02-12 12:17:54,323	32k	INFO	====> Epoch: 386
2023-02-12 12:18:06,103	32k	INFO	====> Epoch: 387
2023-02-12 12:18:17,936	32k	INFO	====> Epoch: 388
2023-02-12 12:18:29,690	32k	INFO	====> Epoch: 389
2023-02-12 12:18:41,464	32k	INFO	====> Epoch: 390
2023-02-12 12:18:53,254	32k	INFO	====> Epoch: 391
2023-02-12 12:19:05,026	32k	INFO	====> Epoch: 392
2023-02-12 12:19:16,809	32k	INFO	====> Epoch: 393
2023-02-12 12:19:28,560	32k	INFO	====> Epoch: 394
2023-02-12 12:19:40,325	32k	INFO	====> Epoch: 395
2023-02-12 12:19:52,085	32k	INFO	====> Epoch: 396
2023-02-12 12:20:03,833	32k	INFO	====> Epoch: 397
2023-02-12 12:20:15,623	32k	INFO	====> Epoch: 398
2023-02-12 12:20:27,466	32k	INFO	====> Epoch: 399
2023-02-12 12:20:39,260	32k	INFO	====> Epoch: 400
2023-02-12 12:20:43,250	32k	INFO	Train Epoch: 401 [0%]
2023-02-12 12:20:43,251	32k	INFO	[1.916421890258789, 2.9261367321014404, 19.459447860717773, 23.159435272216797, 0.879202127456665, 4000, 9.512264516656537e-05]
2023-02-12 12:20:47,146	32k	INFO	Saving model and optimizer state at iteration 401 to ./logs\32k\G_4000.pth
2023-02-12 12:21:05,039	32k	INFO	Saving model and optimizer state at iteration 401 to ./logs\32k\D_4000.pth
2023-02-12 12:21:16,566	32k	INFO	====> Epoch: 401
2023-02-12 12:21:28,993	32k	INFO	====> Epoch: 402
2023-02-12 12:21:40,713	32k	INFO	====> Epoch: 403
2023-02-12 12:21:52,866	32k	INFO	====> Epoch: 404
2023-02-12 12:22:04,667	32k	INFO	====> Epoch: 405
2023-02-12 12:22:16,847	32k	INFO	====> Epoch: 406
2023-02-12 12:22:28,694	32k	INFO	====> Epoch: 407
2023-02-12 12:22:40,471	32k	INFO	====> Epoch: 408
2023-02-12 12:22:52,246	32k	INFO	====> Epoch: 409
2023-02-12 12:23:04,023	32k	INFO	====> Epoch: 410
2023-02-12 12:23:15,769	32k	INFO	====> Epoch: 411
2023-02-12 12:23:27,569	32k	INFO	====> Epoch: 412
2023-02-12 12:23:39,778	32k	INFO	====> Epoch: 413
2023-02-12 12:23:51,508	32k	INFO	====> Epoch: 414
2023-02-12 12:24:03,294	32k	INFO	====> Epoch: 415
2023-02-12 12:24:15,082	32k	INFO	====> Epoch: 416
2023-02-12 12:24:27,284	32k	INFO	====> Epoch: 417
2023-02-12 12:24:39,073	32k	INFO	====> Epoch: 418
2023-02-12 12:24:50,839	32k	INFO	====> Epoch: 419
2023-02-12 12:25:02,582	32k	INFO	====> Epoch: 420
2023-02-12 12:25:06,572	32k	INFO	Train Epoch: 421 [0%]
2023-02-12 12:25:06,573	32k	INFO	[2.0300867557525635, 3.2276406288146973, 19.96863555908203, 20.07271957397461, 0.639214277267456, 4200, 9.488512073731768e-05]
2023-02-12 12:25:14,652	32k	INFO	====> Epoch: 421
2023-02-12 12:25:26,422	32k	INFO	====> Epoch: 422
2023-02-12 12:25:38,134	32k	INFO	====> Epoch: 423
2023-02-12 12:25:49,935	32k	INFO	====> Epoch: 424
2023-02-12 12:26:01,638	32k	INFO	====> Epoch: 425
2023-02-12 12:26:13,367	32k	INFO	====> Epoch: 426
2023-02-12 12:26:25,088	32k	INFO	====> Epoch: 427
2023-02-12 12:26:36,848	32k	INFO	====> Epoch: 428
2023-02-12 12:26:48,599	32k	INFO	====> Epoch: 429
2023-02-12 12:27:00,444	32k	INFO	====> Epoch: 430
2023-02-12 12:27:23,454	32k	INFO	====> Epoch: 431
2023-02-12 12:27:35,189	32k	INFO	====> Epoch: 432
2023-02-12 12:27:46,915	32k	INFO	====> Epoch: 433
2023-02-12 12:27:58,643	32k	INFO	====> Epoch: 434
2023-02-12 12:28:10,403	32k	INFO	====> Epoch: 435
2023-02-12 12:28:22,152	32k	INFO	====> Epoch: 436
2023-02-12 12:28:33,926	32k	INFO	====> Epoch: 437
2023-02-12 12:28:45,689	32k	INFO	====> Epoch: 438
2023-02-12 12:28:57,454	32k	INFO	====> Epoch: 439
2023-02-12 12:29:09,231	32k	INFO	====> Epoch: 440
2023-02-12 12:29:13,237	32k	INFO	Train Epoch: 441 [0%]
2023-02-12 12:29:13,237	32k	INFO	[2.1176722049713135, 2.8234519958496094, 18.18788719177246, 20.257896423339844, 0.7644371390342712, 4400, 9.464818941452107e-05]
2023-02-12 12:29:21,388	32k	INFO	====> Epoch: 441
2023-02-12 12:29:33,168	32k	INFO	====> Epoch: 442
2023-02-12 12:29:44,942	32k	INFO	====> Epoch: 443
2023-02-12 12:29:56,685	32k	INFO	====> Epoch: 444
2023-02-12 12:30:08,435	32k	INFO	====> Epoch: 445
2023-02-12 12:30:20,199	32k	INFO	====> Epoch: 446
2023-02-12 12:30:31,966	32k	INFO	====> Epoch: 447
2023-02-12 12:30:43,676	32k	INFO	====> Epoch: 448
2023-02-12 12:30:55,419	32k	INFO	====> Epoch: 449
2023-02-12 12:31:07,197	32k	INFO	====> Epoch: 450
2023-02-12 12:31:18,959	32k	INFO	====> Epoch: 451
2023-02-12 12:31:30,727	32k	INFO	====> Epoch: 452
2023-02-12 12:31:42,495	32k	INFO	====> Epoch: 453
2023-02-12 12:31:54,269	32k	INFO	====> Epoch: 454
2023-02-12 12:32:06,060	32k	INFO	====> Epoch: 455
2023-02-12 12:32:17,840	32k	INFO	====> Epoch: 456
2023-02-12 12:32:29,603	32k	INFO	====> Epoch: 457
2023-02-12 12:32:41,333	32k	INFO	====> Epoch: 458
2023-02-12 12:32:53,089	32k	INFO	====> Epoch: 459
2023-02-12 12:33:04,871	32k	INFO	====> Epoch: 460
2023-02-12 12:33:08,834	32k	INFO	Train Epoch: 461 [0%]
2023-02-12 12:33:08,835	32k	INFO	[1.9140055179595947, 3.1123974323272705, 19.443544387817383, 22.496755599975586, 0.9423781633377075, 4600, 9.441184971716882e-05]
2023-02-12 12:33:16,924	32k	INFO	====> Epoch: 461
2023-02-12 12:33:28,664	32k	INFO	====> Epoch: 462
2023-02-12 12:33:40,492	32k	INFO	====> Epoch: 463
2023-02-12 12:33:52,212	32k	INFO	====> Epoch: 464
2023-02-12 12:34:03,966	32k	INFO	====> Epoch: 465
2023-02-12 12:34:15,726	32k	INFO	====> Epoch: 466
2023-02-12 12:34:27,509	32k	INFO	====> Epoch: 467
2023-02-12 12:34:39,331	32k	INFO	====> Epoch: 468
2023-02-12 12:34:51,135	32k	INFO	====> Epoch: 469
2023-02-12 12:35:03,015	32k	INFO	====> Epoch: 470
2023-02-12 12:35:14,748	32k	INFO	====> Epoch: 471
2023-02-12 12:35:26,518	32k	INFO	====> Epoch: 472
2023-02-12 12:35:38,266	32k	INFO	====> Epoch: 473
2023-02-12 12:35:50,042	32k	INFO	====> Epoch: 474
2023-02-12 12:36:01,803	32k	INFO	====> Epoch: 475
2023-02-12 12:36:13,496	32k	INFO	====> Epoch: 476
2023-02-12 12:36:25,233	32k	INFO	====> Epoch: 477
2023-02-12 12:36:37,014	32k	INFO	====> Epoch: 478
2023-02-12 12:36:48,820	32k	INFO	====> Epoch: 479
2023-02-12 12:37:00,559	32k	INFO	====> Epoch: 480
2023-02-12 12:37:04,548	32k	INFO	Train Epoch: 481 [0%]
2023-02-12 12:37:04,548	32k	INFO	[1.9500179290771484, 3.4552860260009766, 20.399255752563477, 20.194480895996094, 0.5144003629684448, 4800, 9.417610016795242e-05]
2023-02-12 12:37:12,632	32k	INFO	====> Epoch: 481
2023-02-12 12:37:24,421	32k	INFO	====> Epoch: 482
2023-02-12 12:37:36,228	32k	INFO	====> Epoch: 483
2023-02-12 12:37:48,054	32k	INFO	====> Epoch: 484
2023-02-12 12:37:59,831	32k	INFO	====> Epoch: 485
2023-02-12 12:38:11,565	32k	INFO	====> Epoch: 486
2023-02-12 12:38:23,371	32k	INFO	====> Epoch: 487
2023-02-12 12:38:35,147	32k	INFO	====> Epoch: 488
2023-02-12 12:38:46,975	32k	INFO	====> Epoch: 489
2023-02-12 12:38:58,659	32k	INFO	====> Epoch: 490
2023-02-12 12:39:10,415	32k	INFO	====> Epoch: 491
2023-02-12 12:39:22,157	32k	INFO	====> Epoch: 492
2023-02-12 12:39:33,923	32k	INFO	====> Epoch: 493
2023-02-12 12:39:45,775	32k	INFO	====> Epoch: 494
2023-02-12 12:39:57,517	32k	INFO	====> Epoch: 495
2023-02-12 12:40:09,305	32k	INFO	====> Epoch: 496
2023-02-12 12:40:21,072	32k	INFO	====> Epoch: 497
2023-02-12 12:40:32,874	32k	INFO	====> Epoch: 498
2023-02-12 12:40:44,597	32k	INFO	====> Epoch: 499
2023-02-12 12:40:56,357	32k	INFO	====> Epoch: 500
2023-02-12 12:41:00,319	32k	INFO	Train Epoch: 501 [0%]
2023-02-12 12:41:00,320	32k	INFO	[1.8311638832092285, 3.359696626663208, 24.659854888916016, 22.42967414855957, 0.8215926289558411, 5000, 9.394093929325224e-05]
2023-02-12 12:41:04,287	32k	INFO	Saving model and optimizer state at iteration 501 to ./logs\32k\G_5000.pth
2023-02-12 12:41:21,513	32k	INFO	Saving model and optimizer state at iteration 501 to ./logs\32k\D_5000.pth
2023-02-12 12:41:32,844	32k	INFO	====> Epoch: 501
2023-02-12 12:41:45,081	32k	INFO	====> Epoch: 502
2023-02-12 12:41:56,945	32k	INFO	====> Epoch: 503
2023-02-12 12:42:08,693	32k	INFO	====> Epoch: 504
2023-02-12 12:42:20,455	32k	INFO	====> Epoch: 505
2023-02-12 12:42:32,175	32k	INFO	====> Epoch: 506
2023-02-12 12:42:43,971	32k	INFO	====> Epoch: 507
2023-02-12 12:42:55,683	32k	INFO	====> Epoch: 508
2023-02-12 12:43:07,487	32k	INFO	====> Epoch: 509
2023-02-12 12:43:19,231	32k	INFO	====> Epoch: 510
2023-02-12 12:43:30,981	32k	INFO	====> Epoch: 511
2023-02-12 12:43:42,736	32k	INFO	====> Epoch: 512
2023-02-12 12:43:54,924	32k	INFO	====> Epoch: 513
2023-02-12 12:44:06,650	32k	INFO	====> Epoch: 514
2023-02-12 12:44:18,399	32k	INFO	====> Epoch: 515
2023-02-12 12:44:30,619	32k	INFO	====> Epoch: 516
2023-02-12 12:44:42,468	32k	INFO	====> Epoch: 517
2023-02-12 12:44:54,219	32k	INFO	====> Epoch: 518
2023-02-12 12:45:06,046	32k	INFO	====> Epoch: 519
2023-02-12 12:45:17,798	32k	INFO	====> Epoch: 520
2023-02-12 12:45:21,801	32k	INFO	Train Epoch: 521 [0%]
2023-02-12 12:45:21,801	32k	INFO	[2.0353856086730957, 3.0476789474487305, 18.870141983032227, 19.65450096130371, 0.9559214115142822, 5200, 9.370636562312829e-05]
2023-02-12 12:45:30,012	32k	INFO	====> Epoch: 521
2023-02-12 12:45:41,722	32k	INFO	====> Epoch: 522
2023-02-12 12:45:53,926	32k	INFO	====> Epoch: 523
2023-02-12 12:46:05,667	32k	INFO	====> Epoch: 524
2023-02-12 12:46:17,428	32k	INFO	====> Epoch: 525
2023-02-12 12:46:29,198	32k	INFO	====> Epoch: 526
2023-02-12 12:46:40,967	32k	INFO	====> Epoch: 527
2023-02-12 12:46:52,679	32k	INFO	====> Epoch: 528
2023-02-12 12:47:04,444	32k	INFO	====> Epoch: 529
2023-02-12 12:47:16,231	32k	INFO	====> Epoch: 530
2023-02-12 12:47:27,959	32k	INFO	====> Epoch: 531
2023-02-12 12:47:39,672	32k	INFO	====> Epoch: 532
2023-02-12 12:47:51,475	32k	INFO	====> Epoch: 533
2023-02-12 12:48:03,293	32k	INFO	====> Epoch: 534
2023-02-12 12:48:15,035	32k	INFO	====> Epoch: 535
2023-02-12 12:48:26,836	32k	INFO	====> Epoch: 536
2023-02-12 12:48:38,582	32k	INFO	====> Epoch: 537
2023-02-12 12:48:50,348	32k	INFO	====> Epoch: 538
2023-02-12 12:49:02,103	32k	INFO	====> Epoch: 539
2023-02-12 12:49:13,851	32k	INFO	====> Epoch: 540
2023-02-12 12:49:17,806	32k	INFO	Train Epoch: 541 [0%]
2023-02-12 12:49:17,806	32k	INFO	[1.7957911491394043, 3.381453037261963, 21.269289016723633, 22.524919509887695, 0.49808651208877563, 5400, 9.347237769131105e-05]
2023-02-12 12:49:25,900	32k	INFO	====> Epoch: 541
2023-02-12 12:49:37,640	32k	INFO	====> Epoch: 542
2023-02-12 12:49:49,750	32k	INFO	====> Epoch: 543
2023-02-12 12:50:01,606	32k	INFO	====> Epoch: 544
2023-02-12 12:50:13,340	32k	INFO	====> Epoch: 545
2023-02-12 12:50:25,083	32k	INFO	====> Epoch: 546
2023-02-12 12:50:36,843	32k	INFO	====> Epoch: 547
2023-02-12 12:50:48,578	32k	INFO	====> Epoch: 548
2023-02-12 12:51:00,379	32k	INFO	====> Epoch: 549
2023-02-12 12:51:12,138	32k	INFO	====> Epoch: 550
2023-02-12 12:51:23,893	32k	INFO	====> Epoch: 551
2023-02-12 12:51:35,766	32k	INFO	====> Epoch: 552
2023-02-12 12:51:47,620	32k	INFO	====> Epoch: 553
2023-02-12 12:51:59,364	32k	INFO	====> Epoch: 554
2023-02-12 12:52:11,138	32k	INFO	====> Epoch: 555
2023-02-12 12:52:23,026	32k	INFO	====> Epoch: 556
2023-02-12 12:52:34,763	32k	INFO	====> Epoch: 557
2023-02-12 12:52:46,587	32k	INFO	====> Epoch: 558
2023-02-12 12:52:58,322	32k	INFO	====> Epoch: 559
2023-02-12 12:53:10,105	32k	INFO	====> Epoch: 560
2023-02-12 12:53:14,117	32k	INFO	Train Epoch: 561 [0%]
2023-02-12 12:53:14,117	32k	INFO	[1.8477137088775635, 3.027604103088379, 22.85782241821289, 20.13661003112793, 0.6123890280723572, 5600, 9.323897403519238e-05]
2023-02-12 12:53:22,272	32k	INFO	====> Epoch: 561
2023-02-12 12:53:34,035	32k	INFO	====> Epoch: 562
2023-02-12 12:53:45,904	32k	INFO	====> Epoch: 563
2023-02-12 12:53:57,612	32k	INFO	====> Epoch: 564
2023-02-12 12:54:09,348	32k	INFO	====> Epoch: 565
2023-02-12 12:54:21,237	32k	INFO	====> Epoch: 566
2023-02-12 12:54:33,070	32k	INFO	====> Epoch: 567
2023-02-12 12:54:44,845	32k	INFO	====> Epoch: 568
2023-02-12 12:54:56,691	32k	INFO	====> Epoch: 569
2023-02-12 12:55:08,421	32k	INFO	====> Epoch: 570
2023-02-12 12:55:20,301	32k	INFO	====> Epoch: 571
2023-02-12 12:55:32,043	32k	INFO	====> Epoch: 572
2023-02-12 12:55:43,787	32k	INFO	====> Epoch: 573
2023-02-12 12:55:55,516	32k	INFO	====> Epoch: 574
2023-02-12 12:56:07,374	32k	INFO	====> Epoch: 575
2023-02-12 12:56:19,094	32k	INFO	====> Epoch: 576
2023-02-12 12:56:30,954	32k	INFO	====> Epoch: 577
2023-02-12 12:56:42,653	32k	INFO	====> Epoch: 578
2023-02-12 12:56:54,435	32k	INFO	====> Epoch: 579
2023-02-12 12:57:06,181	32k	INFO	====> Epoch: 580
2023-02-12 12:57:10,159	32k	INFO	Train Epoch: 581 [0%]
2023-02-12 12:57:10,159	32k	INFO	[1.8909555673599243, 2.789243221282959, 20.457439422607422, 20.004791259765625, 0.9085174202919006, 5800, 9.300615319581631e-05]
2023-02-12 12:57:18,239	32k	INFO	====> Epoch: 581
2023-02-12 12:57:30,018	32k	INFO	====> Epoch: 582
2023-02-12 12:57:41,791	32k	INFO	====> Epoch: 583
2023-02-12 12:57:53,558	32k	INFO	====> Epoch: 584
2023-02-12 12:58:05,297	32k	INFO	====> Epoch: 585
2023-02-12 12:58:17,167	32k	INFO	====> Epoch: 586
2023-02-12 12:58:28,997	32k	INFO	====> Epoch: 587
2023-02-12 12:58:40,725	32k	INFO	====> Epoch: 588
2023-02-12 12:58:52,620	32k	INFO	====> Epoch: 589
2023-02-12 12:59:04,497	32k	INFO	====> Epoch: 590
2023-02-12 12:59:16,258	32k	INFO	====> Epoch: 591
2023-02-12 12:59:28,012	32k	INFO	====> Epoch: 592
2023-02-12 12:59:39,752	32k	INFO	====> Epoch: 593
2023-02-12 12:59:51,493	32k	INFO	====> Epoch: 594
2023-02-12 13:00:03,241	32k	INFO	====> Epoch: 595
2023-02-12 13:00:15,013	32k	INFO	====> Epoch: 596
2023-02-12 13:00:26,901	32k	INFO	====> Epoch: 597
2023-02-12 13:00:38,641	32k	INFO	====> Epoch: 598
2023-02-12 13:00:50,418	32k	INFO	====> Epoch: 599
2023-02-12 13:01:02,201	32k	INFO	====> Epoch: 600
2023-02-12 13:01:06,180	32k	INFO	Train Epoch: 601 [0%]
2023-02-12 13:01:06,180	32k	INFO	[1.8251646757125854, 3.1473886966705322, 21.676952362060547, 23.428668975830078, 0.9191310405731201, 6000, 9.277391371786995e-05]
2023-02-12 13:01:10,203	32k	INFO	Saving model and optimizer state at iteration 601 to ./logs\32k\G_6000.pth
2023-02-12 13:01:28,265	32k	INFO	Saving model and optimizer state at iteration 601 to ./logs\32k\D_6000.pth
2023-02-12 13:01:39,649	32k	INFO	====> Epoch: 601
2023-02-12 13:01:51,868	32k	INFO	====> Epoch: 602
2023-02-12 13:02:03,623	32k	INFO	====> Epoch: 603
2023-02-12 13:02:15,444	32k	INFO	====> Epoch: 604
2023-02-12 13:02:27,178	32k	INFO	====> Epoch: 605
2023-02-12 13:02:39,074	32k	INFO	====> Epoch: 606
2023-02-12 13:02:50,848	32k	INFO	====> Epoch: 607
2023-02-12 13:03:02,719	32k	INFO	====> Epoch: 608
2023-02-12 13:03:14,587	32k	INFO	====> Epoch: 609
2023-02-12 13:03:26,412	32k	INFO	====> Epoch: 610
2023-02-12 13:03:38,171	32k	INFO	====> Epoch: 611
2023-02-12 13:03:50,036	32k	INFO	====> Epoch: 612
2023-02-12 13:04:01,814	32k	INFO	====> Epoch: 613
2023-02-12 13:04:13,534	32k	INFO	====> Epoch: 614
2023-02-12 13:04:25,272	32k	INFO	====> Epoch: 615
2023-02-12 13:04:37,019	32k	INFO	====> Epoch: 616
2023-02-12 13:04:48,771	32k	INFO	====> Epoch: 617
2023-02-12 13:05:00,499	32k	INFO	====> Epoch: 618
2023-02-12 13:05:12,269	32k	INFO	====> Epoch: 619
2023-02-12 13:05:24,067	32k	INFO	====> Epoch: 620
2023-02-12 13:05:28,084	32k	INFO	Train Epoch: 621 [0%]
2023-02-12 13:05:28,084	32k	INFO	[1.9839898347854614, 3.0866353511810303, 17.705488204956055, 19.657512664794922, 1.0067795515060425, 6200, 9.254225414967431e-05]
2023-02-12 13:05:36,170	32k	INFO	====> Epoch: 621
2023-02-12 13:05:47,929	32k	INFO	====> Epoch: 622
2023-02-12 13:05:59,678	32k	INFO	====> Epoch: 623
2023-02-12 13:06:11,454	32k	INFO	====> Epoch: 624
2023-02-12 13:06:23,192	32k	INFO	====> Epoch: 625
2023-02-12 13:06:34,979	32k	INFO	====> Epoch: 626
2023-02-12 13:06:46,680	32k	INFO	====> Epoch: 627
2023-02-12 13:06:58,456	32k	INFO	====> Epoch: 628
2023-02-12 13:07:10,188	32k	INFO	====> Epoch: 629
2023-02-12 13:07:21,939	32k	INFO	====> Epoch: 630
2023-02-12 13:07:33,705	32k	INFO	====> Epoch: 631
2023-02-12 13:07:45,482	32k	INFO	====> Epoch: 632
2023-02-12 13:07:57,287	32k	INFO	====> Epoch: 633
2023-02-12 13:08:09,075	32k	INFO	====> Epoch: 634
2023-02-12 13:08:20,826	32k	INFO	====> Epoch: 635
2023-02-12 13:08:32,603	32k	INFO	====> Epoch: 636
2023-02-12 13:08:44,364	32k	INFO	====> Epoch: 637
2023-02-12 13:08:56,116	32k	INFO	====> Epoch: 638
2023-02-12 13:09:07,862	32k	INFO	====> Epoch: 639
2023-02-12 13:09:19,576	32k	INFO	====> Epoch: 640
2023-02-12 13:09:23,525	32k	INFO	Train Epoch: 641 [0%]
2023-02-12 13:09:23,525	32k	INFO	[1.7782466411590576, 3.4183971881866455, 22.802471160888672, 22.295732498168945, 0.6453914642333984, 6400, 9.231117304317535e-05]
2023-02-12 13:09:31,710	32k	INFO	====> Epoch: 641
2023-02-12 13:09:43,466	32k	INFO	====> Epoch: 642
2023-02-12 13:09:55,221	32k	INFO	====> Epoch: 643
2023-02-12 13:10:07,007	32k	INFO	====> Epoch: 644
2023-02-12 13:10:18,760	32k	INFO	====> Epoch: 645
2023-02-12 13:10:30,951	32k	INFO	====> Epoch: 646
2023-02-12 13:10:44,592	32k	INFO	====> Epoch: 647
2023-02-12 13:10:58,156	32k	INFO	====> Epoch: 648
2023-02-12 13:11:11,528	32k	INFO	====> Epoch: 649
2023-02-12 13:11:25,025	32k	INFO	====> Epoch: 650
2023-02-12 13:11:38,460	32k	INFO	====> Epoch: 651
2023-02-12 13:11:51,942	32k	INFO	====> Epoch: 652
2023-02-12 13:12:05,357	32k	INFO	====> Epoch: 653
2023-02-12 13:12:18,749	32k	INFO	====> Epoch: 654
2023-02-12 13:12:32,225	32k	INFO	====> Epoch: 655
2023-02-12 13:12:45,600	32k	INFO	====> Epoch: 656
2023-02-12 13:12:59,218	32k	INFO	====> Epoch: 657
2023-02-12 13:13:12,707	32k	INFO	====> Epoch: 658
2023-02-12 13:13:26,173	32k	INFO	====> Epoch: 659
2023-02-12 13:13:39,603	32k	INFO	====> Epoch: 660
2023-02-12 13:13:43,788	32k	INFO	Train Epoch: 661 [0%]
2023-02-12 13:13:43,789	32k	INFO	[1.9264225959777832, 3.337991237640381, 18.480573654174805, 17.932666778564453, 0.616128146648407, 6600, 9.208066895393489e-05]
2023-02-12 13:13:53,389	32k	INFO	====> Epoch: 661
2023-02-12 13:14:06,806	32k	INFO	====> Epoch: 662
2023-02-12 13:14:20,261	32k	INFO	====> Epoch: 663
2023-02-12 13:14:33,693	32k	INFO	====> Epoch: 664
2023-02-12 13:14:47,091	32k	INFO	====> Epoch: 665
2023-02-12 13:15:00,543	32k	INFO	====> Epoch: 666
2023-02-12 13:15:14,015	32k	INFO	====> Epoch: 667
2023-02-12 13:15:27,535	32k	INFO	====> Epoch: 668
2023-02-12 13:15:40,953	32k	INFO	====> Epoch: 669
2023-02-12 13:15:54,405	32k	INFO	====> Epoch: 670
2023-02-12 13:16:07,793	32k	INFO	====> Epoch: 671
2023-02-12 13:16:21,322	32k	INFO	====> Epoch: 672
2023-02-12 13:16:34,763	32k	INFO	====> Epoch: 673
2023-02-12 13:16:48,396	32k	INFO	====> Epoch: 674
2023-02-12 13:17:01,954	32k	INFO	====> Epoch: 675
2023-02-12 13:17:15,398	32k	INFO	====> Epoch: 676
2023-02-12 13:17:28,769	32k	INFO	====> Epoch: 677
2023-02-12 13:17:42,210	32k	INFO	====> Epoch: 678
2023-02-12 13:17:55,643	32k	INFO	====> Epoch: 679
2023-02-12 13:18:09,050	32k	INFO	====> Epoch: 680
2023-02-12 13:18:13,256	32k	INFO	Train Epoch: 681 [0%]
2023-02-12 13:18:13,257	32k	INFO	[1.9855132102966309, 3.214656114578247, 20.562849044799805, 22.693315505981445, 0.7239395976066589, 6800, 9.185074044112143e-05]
2023-02-12 13:18:22,652	32k	INFO	====> Epoch: 681
2023-02-12 13:18:36,193	32k	INFO	====> Epoch: 682
2023-02-12 13:18:49,682	32k	INFO	====> Epoch: 683
2023-02-12 13:19:03,198	32k	INFO	====> Epoch: 684
2023-02-12 13:19:16,615	32k	INFO	====> Epoch: 685
2023-02-12 13:19:30,145	32k	INFO	====> Epoch: 686
2023-02-12 13:19:43,713	32k	INFO	====> Epoch: 687
2023-02-12 13:19:57,126	32k	INFO	====> Epoch: 688
2023-02-12 13:20:10,388	32k	INFO	====> Epoch: 689
2023-02-12 13:20:23,799	32k	INFO	====> Epoch: 690
2023-02-12 13:20:37,306	32k	INFO	====> Epoch: 691
2023-02-12 13:20:50,636	32k	INFO	====> Epoch: 692
2023-02-12 13:21:03,898	32k	INFO	====> Epoch: 693
2023-02-12 13:21:17,348	32k	INFO	====> Epoch: 694
2023-02-12 13:21:30,647	32k	INFO	====> Epoch: 695
2023-02-12 13:21:44,206	32k	INFO	====> Epoch: 696
2023-02-12 13:21:57,663	32k	INFO	====> Epoch: 697
2023-02-12 13:22:11,052	32k	INFO	====> Epoch: 698
2023-02-12 13:22:24,423	32k	INFO	====> Epoch: 699
2023-02-12 13:22:37,745	32k	INFO	====> Epoch: 700
2023-02-12 13:22:41,886	32k	INFO	Train Epoch: 701 [0%]
2023-02-12 13:22:41,886	32k	INFO	[2.178258180618286, 2.519909620285034, 15.551091194152832, 18.360708236694336, 0.7272467017173767, 7000, 9.162138606750142e-05]
2023-02-12 13:22:45,982	32k	INFO	Saving model and optimizer state at iteration 701 to ./logs\32k\G_7000.pth
2023-02-12 13:23:03,195	32k	INFO	Saving model and optimizer state at iteration 701 to ./logs\32k\D_7000.pth
2023-02-12 13:23:15,842	32k	INFO	====> Epoch: 701
2023-02-12 13:23:29,826	32k	INFO	====> Epoch: 702
2023-02-12 13:23:43,397	32k	INFO	====> Epoch: 703
2023-02-12 13:23:56,847	32k	INFO	====> Epoch: 704
2023-02-12 13:24:10,369	32k	INFO	====> Epoch: 705
2023-02-12 13:24:23,734	32k	INFO	====> Epoch: 706
2023-02-12 13:24:37,238	32k	INFO	====> Epoch: 707
2023-02-12 13:24:50,742	32k	INFO	====> Epoch: 708
2023-02-12 13:25:04,262	32k	INFO	====> Epoch: 709
2023-02-12 13:25:17,726	32k	INFO	====> Epoch: 710
2023-02-12 13:25:31,221	32k	INFO	====> Epoch: 711
2023-02-12 13:25:44,906	32k	INFO	====> Epoch: 712
2023-02-12 13:25:58,477	32k	INFO	====> Epoch: 713
2023-02-12 13:26:12,123	32k	INFO	====> Epoch: 714
2023-02-12 13:26:25,548	32k	INFO	====> Epoch: 715
2023-02-12 13:26:39,125	32k	INFO	====> Epoch: 716
2023-02-12 13:26:52,664	32k	INFO	====> Epoch: 717
2023-02-12 13:27:06,124	32k	INFO	====> Epoch: 718
2023-02-12 13:27:19,777	32k	INFO	====> Epoch: 719
2023-02-12 13:27:33,160	32k	INFO	====> Epoch: 720
2023-02-12 13:27:37,379	32k	INFO	Train Epoch: 721 [0%]
2023-02-12 13:27:37,379	32k	INFO	[1.8394410610198975, 3.2603728771209717, 22.712038040161133, 20.24898910522461, 1.0083003044128418, 7200, 9.139260439943005e-05]
2023-02-12 13:27:46,934	32k	INFO	====> Epoch: 721
2023-02-12 13:28:00,414	32k	INFO	====> Epoch: 722
2023-02-12 13:28:13,964	32k	INFO	====> Epoch: 723
2023-02-12 13:28:27,359	32k	INFO	====> Epoch: 724
2023-02-12 13:28:40,802	32k	INFO	====> Epoch: 725
2023-02-12 13:28:54,378	32k	INFO	====> Epoch: 726
2023-02-12 13:29:07,814	32k	INFO	====> Epoch: 727
2023-02-12 13:29:21,400	32k	INFO	====> Epoch: 728
2023-02-12 13:29:35,032	32k	INFO	====> Epoch: 729
2023-02-12 13:29:48,482	32k	INFO	====> Epoch: 730
2023-02-12 13:30:01,881	32k	INFO	====> Epoch: 731
2023-02-12 13:30:15,487	32k	INFO	====> Epoch: 732
2023-02-12 13:30:29,077	32k	INFO	====> Epoch: 733
2023-02-12 13:30:42,532	32k	INFO	====> Epoch: 734
2023-02-12 13:30:56,043	32k	INFO	====> Epoch: 735
2023-02-12 13:31:09,484	32k	INFO	====> Epoch: 736
2023-02-12 13:31:22,841	32k	INFO	====> Epoch: 737
2023-02-12 13:31:36,393	32k	INFO	====> Epoch: 738
2023-02-12 13:31:49,668	32k	INFO	====> Epoch: 739
2023-02-12 13:32:03,245	32k	INFO	====> Epoch: 740
2023-02-12 13:32:07,437	32k	INFO	Train Epoch: 741 [0%]
2023-02-12 13:32:07,438	32k	INFO	[1.9900994300842285, 3.2577409744262695, 21.37356185913086, 19.953445434570312, 0.7022988200187683, 7400, 9.116439400684243e-05]
2023-02-12 13:32:16,979	32k	INFO	====> Epoch: 741
2023-02-12 13:32:30,215	32k	INFO	====> Epoch: 742
2023-02-12 13:32:43,706	32k	INFO	====> Epoch: 743
2023-02-12 13:32:57,204	32k	INFO	====> Epoch: 744
2023-02-12 13:33:10,610	32k	INFO	====> Epoch: 745
2023-02-12 13:33:23,911	32k	INFO	====> Epoch: 746
2023-02-12 13:33:37,477	32k	INFO	====> Epoch: 747
2023-02-12 13:33:50,979	32k	INFO	====> Epoch: 748
2023-02-12 13:34:04,488	32k	INFO	====> Epoch: 749
2023-02-12 13:34:18,080	32k	INFO	====> Epoch: 750
2023-02-12 13:34:31,582	32k	INFO	====> Epoch: 751
2023-02-12 13:34:44,955	32k	INFO	====> Epoch: 752
2023-02-12 13:34:58,315	32k	INFO	====> Epoch: 753
2023-02-12 13:35:11,776	32k	INFO	====> Epoch: 754
2023-02-12 13:35:25,220	32k	INFO	====> Epoch: 755
2023-02-12 13:35:38,697	32k	INFO	====> Epoch: 756
2023-02-12 13:35:52,330	32k	INFO	====> Epoch: 757
2023-02-12 13:36:05,632	32k	INFO	====> Epoch: 758
2023-02-12 13:36:19,847	32k	INFO	====> Epoch: 759
2023-02-12 13:36:34,887	32k	INFO	====> Epoch: 760
2023-02-12 13:36:39,150	32k	INFO	Train Epoch: 761 [0%]
2023-02-12 13:36:39,151	32k	INFO	[2.1635007858276367, 3.062483549118042, 18.44725799560547, 20.376346588134766, 0.5196554660797119, 7600, 9.093675346324454e-05]
2023-02-12 13:36:49,645	32k	INFO	====> Epoch: 761
2023-02-12 13:37:04,174	32k	INFO	====> Epoch: 762
2023-02-12 13:37:19,843	32k	INFO	====> Epoch: 763
2023-02-12 13:37:33,164	32k	INFO	====> Epoch: 764
2023-02-12 13:37:46,528	32k	INFO	====> Epoch: 765
2023-02-12 13:37:59,990	32k	INFO	====> Epoch: 766
2023-02-12 13:38:13,519	32k	INFO	====> Epoch: 767
2023-02-12 13:38:26,899	32k	INFO	====> Epoch: 768
2023-02-12 13:38:40,373	32k	INFO	====> Epoch: 769
2023-02-12 13:38:53,784	32k	INFO	====> Epoch: 770
2023-02-12 13:39:07,289	32k	INFO	====> Epoch: 771
2023-02-12 13:39:20,611	32k	INFO	====> Epoch: 772
2023-02-12 13:39:33,996	32k	INFO	====> Epoch: 773
2023-02-12 13:39:47,533	32k	INFO	====> Epoch: 774
2023-02-12 13:40:00,907	32k	INFO	====> Epoch: 775
2023-02-12 13:40:14,365	32k	INFO	====> Epoch: 776
2023-02-12 13:40:27,799	32k	INFO	====> Epoch: 777
2023-02-12 13:40:41,239	32k	INFO	====> Epoch: 778
2023-02-12 13:40:54,716	32k	INFO	====> Epoch: 779
2023-02-12 13:41:08,240	32k	INFO	====> Epoch: 780
2023-02-12 13:41:12,452	32k	INFO	Train Epoch: 781 [0%]
2023-02-12 13:41:12,452	32k	INFO	[2.048905611038208, 3.0901808738708496, 20.4196834564209, 18.905176162719727, 0.5383411645889282, 7800, 9.07096813457043e-05]
2023-02-12 13:41:22,035	32k	INFO	====> Epoch: 781
2023-02-12 13:41:35,598	32k	INFO	====> Epoch: 782
2023-02-12 13:41:49,169	32k	INFO	====> Epoch: 783
2023-02-12 13:42:02,928	32k	INFO	====> Epoch: 784
2023-02-12 13:42:16,517	32k	INFO	====> Epoch: 785
2023-02-12 13:42:30,017	32k	INFO	====> Epoch: 786
2023-02-12 13:42:43,474	32k	INFO	====> Epoch: 787
2023-02-12 13:42:56,844	32k	INFO	====> Epoch: 788
2023-02-12 13:43:10,294	32k	INFO	====> Epoch: 789
2023-02-12 13:43:23,713	32k	INFO	====> Epoch: 790
2023-02-12 13:43:37,129	32k	INFO	====> Epoch: 791
2023-02-12 13:46:44,643	32k	INFO	{'train': {'log_interval': 200, 'eval_interval': 1000, 'seed': 1234, 'epochs': 10000, 'learning_rate': 0.0001, 'betas': [0.8, 0.99], 'eps': 1e-09, 'batch_size': 6, 'fp16_run': False, 'lr_decay': 0.999875, 'segment_size': 17920, 'init_lr_ratio': 1, 'warmup_epochs': 0, 'c_mel': 45, 'c_kl': 1.0, 'use_sr': True, 'max_speclen': 384, 'port': '8001'}, 'data': {'training_files': 'filelists/train.txt', 'validation_files': 'filelists/val.txt', 'max_wav_value': 32768.0, 'sampling_rate': 32000, 'filter_length': 1280, 'hop_length': 320, 'win_length': 1280, 'n_mel_channels': 80, 'mel_fmin': 0.0, 'mel_fmax': None}, 'model': {'inter_channels': 192, 'hidden_channels': 192, 'filter_channels': 768, 'n_heads': 2, 'n_layers': 6, 'kernel_size': 3, 'p_dropout': 0.1, 'resblock': '1', 'resblock_kernel_sizes': [3, 7, 11], 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'upsample_rates': [10, 8, 2, 2], 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'n_layers_q': 3, 'use_spectral_norm': False, 'gin_channels': 256, 'ssl_dim': 256, 'n_speakers': 2}, 'spk': {'kokona': 0}, 'model_dir': './logs\\32k'}
2023-02-12 13:46:53,444	32k	INFO	Loaded checkpoint './logs\32k\G_7000.pth' (iteration 701)
2023-02-12 13:46:53,823	32k	INFO	Loaded checkpoint './logs\32k\D_7000.pth' (iteration 701)
2023-02-12 13:47:01,848	32k	INFO	Train Epoch: 701 [0%]
2023-02-12 13:47:01,848	32k	INFO	[2.0743532180786133, 2.8655288219451904, 21.489702224731445, 20.632448196411133, 0.9461040496826172, 7000, 9.160993339424298e-05]
2023-02-12 13:47:06,729	32k	INFO	Saving model and optimizer state at iteration 701 to ./logs\32k\G_7000.pth
2023-02-12 13:47:25,341	32k	INFO	Saving model and optimizer state at iteration 701 to ./logs\32k\D_7000.pth
2023-02-12 13:47:38,304	32k	INFO	====> Epoch: 701
2023-02-12 13:47:49,998	32k	INFO	====> Epoch: 702
2023-02-12 13:48:03,116	32k	INFO	====> Epoch: 703
2023-02-12 13:48:16,281	32k	INFO	====> Epoch: 704
2023-02-12 13:48:28,493	32k	INFO	====> Epoch: 705
2023-02-12 13:48:40,439	32k	INFO	====> Epoch: 706
2023-02-12 13:48:52,397	32k	INFO	====> Epoch: 707
2023-02-12 13:49:04,442	32k	INFO	====> Epoch: 708
2023-02-12 13:49:16,668	32k	INFO	====> Epoch: 709
2023-02-12 13:49:28,690	32k	INFO	====> Epoch: 710
2023-02-12 13:49:40,647	32k	INFO	====> Epoch: 711
2023-02-12 13:49:52,584	32k	INFO	====> Epoch: 712
2023-02-12 13:50:04,530	32k	INFO	====> Epoch: 713
2023-02-12 13:50:16,511	32k	INFO	====> Epoch: 714
2023-02-12 13:50:28,471	32k	INFO	====> Epoch: 715
2023-02-12 13:50:40,454	32k	INFO	====> Epoch: 716
2023-02-12 13:50:52,445	32k	INFO	====> Epoch: 717
2023-02-12 13:51:04,395	32k	INFO	====> Epoch: 718
2023-02-12 13:51:16,342	32k	INFO	====> Epoch: 719
2023-02-12 13:51:28,328	32k	INFO	====> Epoch: 720
2023-02-12 13:51:32,372	32k	INFO	Train Epoch: 721 [0%]
2023-02-12 13:51:32,373	32k	INFO	[1.9847931861877441, 2.781100273132324, 21.47286033630371, 20.723678588867188, 0.8959621787071228, 7200, 9.138118032388012e-05]
2023-02-12 13:51:40,661	32k	INFO	====> Epoch: 721
2023-02-12 13:51:52,570	32k	INFO	====> Epoch: 722
2023-02-12 13:52:04,552	32k	INFO	====> Epoch: 723
2023-02-12 13:52:16,526	32k	INFO	====> Epoch: 724
2023-02-12 13:52:28,499	32k	INFO	====> Epoch: 725
2023-02-12 13:52:40,534	32k	INFO	====> Epoch: 726
2023-02-12 13:52:52,475	32k	INFO	====> Epoch: 727
2023-02-12 13:53:04,430	32k	INFO	====> Epoch: 728
2023-02-12 13:53:16,394	32k	INFO	====> Epoch: 729
2023-02-12 13:53:28,383	32k	INFO	====> Epoch: 730
2023-02-12 13:53:40,305	32k	INFO	====> Epoch: 731
2023-02-12 13:53:52,292	32k	INFO	====> Epoch: 732
2023-02-12 13:54:04,237	32k	INFO	====> Epoch: 733
2023-02-12 13:54:16,180	32k	INFO	====> Epoch: 734
2023-02-12 13:54:28,199	32k	INFO	====> Epoch: 735
2023-02-12 13:54:40,161	32k	INFO	====> Epoch: 736
2023-02-12 13:54:52,191	32k	INFO	====> Epoch: 737
2023-02-12 13:55:04,150	32k	INFO	====> Epoch: 738
2023-02-12 13:55:16,113	32k	INFO	====> Epoch: 739
2023-02-12 13:55:28,092	32k	INFO	====> Epoch: 740
2023-02-12 13:55:32,161	32k	INFO	Train Epoch: 741 [0%]
2023-02-12 13:55:32,161	32k	INFO	[2.1115012168884277, 2.570882797241211, 17.793506622314453, 18.005401611328125, 0.47993040084838867, 7400, 9.115299845759157e-05]
2023-02-12 13:55:40,412	32k	INFO	====> Epoch: 741
2023-02-12 13:55:52,408	32k	INFO	====> Epoch: 742
2023-02-12 13:56:04,365	32k	INFO	====> Epoch: 743
2023-02-12 13:56:16,357	32k	INFO	====> Epoch: 744
2023-02-12 13:56:28,315	32k	INFO	====> Epoch: 745
2023-02-12 13:56:40,310	32k	INFO	====> Epoch: 746
2023-02-12 13:56:52,331	32k	INFO	====> Epoch: 747
2023-02-12 13:57:04,618	32k	INFO	====> Epoch: 748
2023-02-12 13:57:17,097	32k	INFO	====> Epoch: 749
2023-02-12 13:57:29,133	32k	INFO	====> Epoch: 750
2023-02-12 13:57:41,091	32k	INFO	====> Epoch: 751
2023-02-12 13:57:53,117	32k	INFO	====> Epoch: 752
2023-02-12 13:58:05,069	32k	INFO	====> Epoch: 753
2023-02-12 13:58:17,028	32k	INFO	====> Epoch: 754
2023-02-12 13:58:29,019	32k	INFO	====> Epoch: 755
2023-02-12 13:58:40,999	32k	INFO	====> Epoch: 756
2023-02-12 13:58:52,926	32k	INFO	====> Epoch: 757
2023-02-12 13:59:04,932	32k	INFO	====> Epoch: 758
2023-02-12 13:59:16,858	32k	INFO	====> Epoch: 759
2023-02-12 13:59:28,840	32k	INFO	====> Epoch: 760
2023-02-12 13:59:32,838	32k	INFO	Train Epoch: 761 [0%]
2023-02-12 13:59:32,838	32k	INFO	[1.8719170093536377, 2.988452911376953, 22.19683265686035, 18.409896850585938, 0.8148029446601868, 7600, 9.092538636906162e-05]
2023-02-12 13:59:41,087	32k	INFO	====> Epoch: 761
2023-02-12 13:59:53,045	32k	INFO	====> Epoch: 762
2023-02-12 14:00:05,078	32k	INFO	====> Epoch: 763
2023-02-12 14:00:17,047	32k	INFO	====> Epoch: 764
2023-02-12 14:00:28,990	32k	INFO	====> Epoch: 765
2023-02-12 14:00:40,914	32k	INFO	====> Epoch: 766
2023-02-12 14:00:52,823	32k	INFO	====> Epoch: 767
2023-02-12 14:01:04,785	32k	INFO	====> Epoch: 768
2023-02-12 14:01:16,750	32k	INFO	====> Epoch: 769
2023-02-12 14:01:28,735	32k	INFO	====> Epoch: 770
2023-02-12 14:01:40,718	32k	INFO	====> Epoch: 771
2023-02-12 14:01:52,670	32k	INFO	====> Epoch: 772
2023-02-12 14:02:04,558	32k	INFO	====> Epoch: 773
2023-02-12 14:02:16,522	32k	INFO	====> Epoch: 774
2023-02-12 14:02:28,528	32k	INFO	====> Epoch: 775
2023-02-12 14:02:40,525	32k	INFO	====> Epoch: 776
2023-02-12 14:02:52,498	32k	INFO	====> Epoch: 777
2023-02-12 14:03:04,529	32k	INFO	====> Epoch: 778
2023-02-12 14:03:16,568	32k	INFO	====> Epoch: 779
2023-02-12 14:03:28,565	32k	INFO	====> Epoch: 780
2023-02-12 14:03:32,627	32k	INFO	Train Epoch: 781 [0%]
2023-02-12 14:03:32,627	32k	INFO	[1.736820101737976, 3.68717098236084, 23.286638259887695, 22.309734344482422, 0.6430284976959229, 7800, 9.069834263553609e-05]
2023-02-12 14:03:40,853	32k	INFO	====> Epoch: 781
2023-02-12 14:03:52,810	32k	INFO	====> Epoch: 782
2023-02-12 14:04:04,790	32k	INFO	====> Epoch: 783
2023-02-12 14:04:16,751	32k	INFO	====> Epoch: 784
2023-02-12 14:04:28,671	32k	INFO	====> Epoch: 785
2023-02-12 14:04:40,989	32k	INFO	====> Epoch: 786
2023-02-12 14:04:52,937	32k	INFO	====> Epoch: 787
2023-02-12 14:05:04,887	32k	INFO	====> Epoch: 788
2023-02-12 14:05:16,805	32k	INFO	====> Epoch: 789
2023-02-12 14:05:28,751	32k	INFO	====> Epoch: 790
2023-02-12 14:05:40,815	32k	INFO	====> Epoch: 791
2023-02-12 14:05:53,120	32k	INFO	====> Epoch: 792
2023-02-12 14:06:05,095	32k	INFO	====> Epoch: 793
2023-02-12 14:06:17,067	32k	INFO	====> Epoch: 794
2023-02-12 14:06:28,986	32k	INFO	====> Epoch: 795
2023-02-12 14:06:40,929	32k	INFO	====> Epoch: 796
2023-02-12 14:06:52,938	32k	INFO	====> Epoch: 797
2023-02-12 14:07:04,844	32k	INFO	====> Epoch: 798
2023-02-12 14:07:16,843	32k	INFO	====> Epoch: 799
2023-02-12 14:07:28,779	32k	INFO	====> Epoch: 800
2023-02-12 14:07:32,802	32k	INFO	Train Epoch: 801 [0%]
2023-02-12 14:07:32,803	32k	INFO	[1.7944151163101196, 3.3288469314575195, 20.172019958496094, 21.2901668548584, 0.5095722675323486, 8000, 9.04718658378136e-05]
2023-02-12 14:07:36,897	32k	INFO	Saving model and optimizer state at iteration 801 to ./logs\32k\G_8000.pth
2023-02-12 14:07:55,722	32k	INFO	Saving model and optimizer state at iteration 801 to ./logs\32k\D_8000.pth
2023-02-12 14:08:07,658	32k	INFO	====> Epoch: 801
2023-02-12 14:08:20,145	32k	INFO	====> Epoch: 802
2023-02-12 14:08:32,165	32k	INFO	====> Epoch: 803
2023-02-12 14:08:44,544	32k	INFO	====> Epoch: 804
2023-02-12 14:08:56,721	32k	INFO	====> Epoch: 805
2023-02-12 14:09:09,410	32k	INFO	====> Epoch: 806
2023-02-12 14:09:21,895	32k	INFO	====> Epoch: 807
2023-02-12 14:09:34,301	32k	INFO	====> Epoch: 808
2023-02-12 14:09:46,346	32k	INFO	====> Epoch: 809
2023-02-12 14:09:58,505	32k	INFO	====> Epoch: 810
2023-02-12 14:10:10,435	32k	INFO	====> Epoch: 811
2023-02-12 14:10:22,442	32k	INFO	====> Epoch: 812
2023-02-12 14:10:34,395	32k	INFO	====> Epoch: 813
2023-02-12 14:10:46,348	32k	INFO	====> Epoch: 814
2023-02-12 14:10:58,308	32k	INFO	====> Epoch: 815
2023-02-12 14:11:10,260	32k	INFO	====> Epoch: 816
2023-02-12 14:11:22,249	32k	INFO	====> Epoch: 817
2023-02-12 14:11:34,168	32k	INFO	====> Epoch: 818
2023-02-12 14:11:46,108	32k	INFO	====> Epoch: 819
2023-02-12 14:11:58,102	32k	INFO	====> Epoch: 820
2023-02-12 14:12:02,151	32k	INFO	Train Epoch: 821 [0%]
2023-02-12 14:12:02,152	32k	INFO	[2.0393142700195312, 2.7750158309936523, 16.68890380859375, 16.175832748413086, 0.9834238886833191, 8200, 9.024595456023638e-05]
2023-02-12 14:12:10,492	32k	INFO	====> Epoch: 821
2023-02-12 14:12:22,445	32k	INFO	====> Epoch: 822
2023-02-12 14:12:34,444	32k	INFO	====> Epoch: 823
2023-02-12 14:12:46,418	32k	INFO	====> Epoch: 824
2023-02-12 14:12:58,376	32k	INFO	====> Epoch: 825
2023-02-12 14:13:10,334	32k	INFO	====> Epoch: 826
2023-02-12 14:13:22,341	32k	INFO	====> Epoch: 827
2023-02-12 14:13:34,397	32k	INFO	====> Epoch: 828
2023-02-12 14:13:46,374	32k	INFO	====> Epoch: 829
2023-02-12 14:13:58,342	32k	INFO	====> Epoch: 830
2023-02-12 14:14:10,294	32k	INFO	====> Epoch: 831
2023-02-12 14:14:22,281	32k	INFO	====> Epoch: 832
2023-02-12 14:14:34,194	32k	INFO	====> Epoch: 833
2023-02-12 14:14:46,141	32k	INFO	====> Epoch: 834
2023-02-12 14:14:58,122	32k	INFO	====> Epoch: 835
2023-02-12 14:15:10,096	32k	INFO	====> Epoch: 836
2023-02-12 14:15:22,038	32k	INFO	====> Epoch: 837
2023-02-12 14:15:34,005	32k	INFO	====> Epoch: 838
2023-02-12 14:15:46,016	32k	INFO	====> Epoch: 839
2023-02-12 14:15:57,970	32k	INFO	====> Epoch: 840
2023-02-12 14:16:01,973	32k	INFO	Train Epoch: 841 [0%]
2023-02-12 14:16:01,973	32k	INFO	[2.0190176963806152, 2.9155752658843994, 19.60703468322754, 19.409595489501953, 0.5518465638160706, 8400, 9.002060739068175e-05]
2023-02-12 14:16:10,200	32k	INFO	====> Epoch: 841
2023-02-12 14:16:22,139	32k	INFO	====> Epoch: 842
2023-02-12 14:16:34,089	32k	INFO	====> Epoch: 843
2023-02-12 14:16:46,051	32k	INFO	====> Epoch: 844
2023-02-12 14:16:58,040	32k	INFO	====> Epoch: 845
2023-02-12 14:17:09,949	32k	INFO	====> Epoch: 846
2023-02-12 14:17:21,936	32k	INFO	====> Epoch: 847
2023-02-12 14:17:33,933	32k	INFO	====> Epoch: 848
2023-02-12 14:17:45,919	32k	INFO	====> Epoch: 849
2023-02-12 14:17:57,862	32k	INFO	====> Epoch: 850
2023-02-12 14:18:10,199	32k	INFO	====> Epoch: 851
2023-02-12 14:18:22,246	32k	INFO	====> Epoch: 852
2023-02-12 14:18:34,220	32k	INFO	====> Epoch: 853
2023-02-12 14:18:46,197	32k	INFO	====> Epoch: 854
2023-02-12 14:18:58,191	32k	INFO	====> Epoch: 855
2023-02-12 14:19:10,258	32k	INFO	====> Epoch: 856
2023-02-12 14:19:22,399	32k	INFO	====> Epoch: 857
2023-02-12 14:19:34,461	32k	INFO	====> Epoch: 858
2023-02-12 14:19:46,609	32k	INFO	====> Epoch: 859
2023-02-12 14:19:58,608	32k	INFO	====> Epoch: 860
2023-02-12 14:20:02,685	32k	INFO	Train Epoch: 861 [0%]
2023-02-12 14:20:02,686	32k	INFO	[1.941718339920044, 2.9887161254882812, 17.11890983581543, 18.92049217224121, 0.47159188985824585, 8600, 8.979582292055309e-05]
2023-02-12 14:20:10,930	32k	INFO	====> Epoch: 861
2023-02-12 14:20:23,177	32k	INFO	====> Epoch: 862
2023-02-12 14:20:35,134	32k	INFO	====> Epoch: 863
2023-02-12 14:20:47,121	32k	INFO	====> Epoch: 864
2023-02-12 14:20:59,084	32k	INFO	====> Epoch: 865
2023-02-12 14:21:11,058	32k	INFO	====> Epoch: 866
2023-02-12 14:21:23,071	32k	INFO	====> Epoch: 867
2023-02-12 14:21:35,015	32k	INFO	====> Epoch: 868
2023-02-12 14:21:46,985	32k	INFO	====> Epoch: 869
2023-02-12 14:21:58,894	32k	INFO	====> Epoch: 870
2023-02-12 14:22:10,824	32k	INFO	====> Epoch: 871
2023-02-12 14:22:23,096	32k	INFO	====> Epoch: 872
2023-02-12 14:22:35,131	32k	INFO	====> Epoch: 873
2023-02-12 14:22:47,143	32k	INFO	====> Epoch: 874
2023-02-12 14:22:59,165	32k	INFO	====> Epoch: 875
2023-02-12 14:23:11,414	32k	INFO	====> Epoch: 876
2023-02-12 14:23:23,401	32k	INFO	====> Epoch: 877
2023-02-12 14:23:35,445	32k	INFO	====> Epoch: 878
2023-02-12 14:23:47,402	32k	INFO	====> Epoch: 879
2023-02-12 14:23:59,383	32k	INFO	====> Epoch: 880
2023-02-12 14:24:03,358	32k	INFO	Train Epoch: 881 [0%]
2023-02-12 14:24:03,359	32k	INFO	[1.8067156076431274, 3.42271089553833, 22.4112548828125, 20.323345184326172, 0.5746048092842102, 8800, 8.957159974477111e-05]
2023-02-12 14:24:11,619	32k	INFO	====> Epoch: 881
2023-02-12 14:24:23,600	32k	INFO	====> Epoch: 882
2023-02-12 14:24:35,576	32k	INFO	====> Epoch: 883
2023-02-12 14:24:47,519	32k	INFO	====> Epoch: 884
2023-02-12 14:24:59,475	32k	INFO	====> Epoch: 885
2023-02-12 14:25:11,437	32k	INFO	====> Epoch: 886
2023-02-12 14:25:23,456	32k	INFO	====> Epoch: 887
2023-02-12 14:25:35,432	32k	INFO	====> Epoch: 888
2023-02-12 14:25:47,389	32k	INFO	====> Epoch: 889
2023-02-12 14:25:59,327	32k	INFO	====> Epoch: 890
2023-02-12 14:26:11,282	32k	INFO	====> Epoch: 891
2023-02-12 14:26:23,289	32k	INFO	====> Epoch: 892
2023-02-12 14:26:35,291	32k	INFO	====> Epoch: 893
2023-02-12 14:26:47,293	32k	INFO	====> Epoch: 894
2023-02-12 14:26:59,280	32k	INFO	====> Epoch: 895
2023-02-12 14:27:11,276	32k	INFO	====> Epoch: 896
2023-02-12 14:27:23,283	32k	INFO	====> Epoch: 897
2023-02-12 14:27:35,285	32k	INFO	====> Epoch: 898
2023-02-12 14:27:47,245	32k	INFO	====> Epoch: 899
2023-02-12 14:27:59,207	32k	INFO	====> Epoch: 900
2023-02-12 14:28:03,213	32k	INFO	Train Epoch: 901 [0%]
2023-02-12 14:28:03,213	32k	INFO	[1.8195370435714722, 3.0551533699035645, 19.27685546875, 18.536165237426758, 1.1415036916732788, 9000, 8.934793646176498e-05]
2023-02-12 14:28:07,259	32k	INFO	Saving model and optimizer state at iteration 901 to ./logs\32k\G_9000.pth
2023-02-12 14:28:23,218	32k	INFO	Saving model and optimizer state at iteration 901 to ./logs\32k\D_9000.pth
2023-02-12 14:28:35,036	32k	INFO	====> Epoch: 901
2023-02-12 14:28:47,555	32k	INFO	====> Epoch: 902
2023-02-12 14:28:59,495	32k	INFO	====> Epoch: 903
2023-02-12 14:29:11,583	32k	INFO	====> Epoch: 904
2023-02-12 14:29:23,639	32k	INFO	====> Epoch: 905
2023-02-12 14:29:35,681	32k	INFO	====> Epoch: 906
2023-02-12 14:29:47,591	32k	INFO	====> Epoch: 907
2023-02-12 14:29:59,560	32k	INFO	====> Epoch: 908
2023-02-12 14:30:11,507	32k	INFO	====> Epoch: 909
2023-02-12 14:30:23,646	32k	INFO	====> Epoch: 910
2023-02-12 14:30:35,627	32k	INFO	====> Epoch: 911
2023-02-12 14:30:47,594	32k	INFO	====> Epoch: 912
2023-02-12 14:30:59,667	32k	INFO	====> Epoch: 913
2023-02-12 14:31:11,679	32k	INFO	====> Epoch: 914
2023-02-12 14:31:23,606	32k	INFO	====> Epoch: 915
2023-02-12 14:31:35,559	32k	INFO	====> Epoch: 916
2023-02-12 14:31:47,576	32k	INFO	====> Epoch: 917
2023-02-12 14:31:59,606	32k	INFO	====> Epoch: 918
2023-02-12 14:32:11,607	32k	INFO	====> Epoch: 919
2023-02-12 14:32:23,654	32k	INFO	====> Epoch: 920
2023-02-12 14:32:27,669	32k	INFO	Train Epoch: 921 [0%]
2023-02-12 14:32:27,669	32k	INFO	[1.7966740131378174, 3.115190029144287, 19.65473747253418, 17.708545684814453, 0.869736909866333, 9200, 8.912483167346374e-05]
2023-02-12 14:32:35,942	32k	INFO	====> Epoch: 921
2023-02-12 14:32:47,874	32k	INFO	====> Epoch: 922
2023-02-12 14:32:59,917	32k	INFO	====> Epoch: 923
2023-02-12 14:33:11,920	32k	INFO	====> Epoch: 924
2023-02-12 14:33:24,014	32k	INFO	====> Epoch: 925
2023-02-12 14:33:35,958	32k	INFO	====> Epoch: 926
2023-02-12 14:33:47,925	32k	INFO	====> Epoch: 927
2023-02-12 14:34:00,071	32k	INFO	====> Epoch: 928
2023-02-12 14:34:12,095	32k	INFO	====> Epoch: 929
2023-02-12 14:34:24,116	32k	INFO	====> Epoch: 930
2023-02-12 14:34:36,041	32k	INFO	====> Epoch: 931
2023-02-12 14:34:48,040	32k	INFO	====> Epoch: 932
2023-02-12 14:35:00,020	32k	INFO	====> Epoch: 933
2023-02-12 14:35:12,039	32k	INFO	====> Epoch: 934
2023-02-12 14:35:24,055	32k	INFO	====> Epoch: 935
2023-02-12 14:35:36,045	32k	INFO	====> Epoch: 936
2023-02-12 14:35:48,058	32k	INFO	====> Epoch: 937
2023-02-12 14:36:00,129	32k	INFO	====> Epoch: 938
2023-02-12 14:36:12,218	32k	INFO	====> Epoch: 939
2023-02-12 14:36:24,209	32k	INFO	====> Epoch: 940
2023-02-12 14:36:28,373	32k	INFO	Train Epoch: 941 [0%]
2023-02-12 14:36:28,373	32k	INFO	[1.8863221406936646, 3.113790512084961, 20.693424224853516, 20.36008644104004, 0.7652761936187744, 9400, 8.89022839852874e-05]
2023-02-12 14:36:36,644	32k	INFO	====> Epoch: 941
2023-02-12 14:36:48,635	32k	INFO	====> Epoch: 942
2023-02-12 14:37:00,711	32k	INFO	====> Epoch: 943
2023-02-12 14:37:12,676	32k	INFO	====> Epoch: 944
2023-02-12 14:37:24,622	32k	INFO	====> Epoch: 945
2023-02-12 14:37:36,806	32k	INFO	====> Epoch: 946
2023-02-12 14:37:48,860	32k	INFO	====> Epoch: 947
2023-02-12 14:38:15,470	32k	INFO	====> Epoch: 948
2023-02-12 14:38:27,465	32k	INFO	====> Epoch: 949
2023-02-12 14:38:39,494	32k	INFO	====> Epoch: 950
2023-02-12 14:38:51,476	32k	INFO	====> Epoch: 951
2023-02-12 14:39:03,448	32k	INFO	====> Epoch: 952
2023-02-12 14:39:15,382	32k	INFO	====> Epoch: 953
2023-02-12 14:39:27,371	32k	INFO	====> Epoch: 954
2023-02-12 14:39:39,335	32k	INFO	====> Epoch: 955
2023-02-12 14:39:51,477	32k	INFO	====> Epoch: 956
2023-02-12 14:40:03,418	32k	INFO	====> Epoch: 957
2023-02-12 14:40:15,410	32k	INFO	====> Epoch: 958
2023-02-12 14:40:27,341	32k	INFO	====> Epoch: 959
2023-02-12 14:40:39,315	32k	INFO	====> Epoch: 960
2023-02-12 14:40:43,363	32k	INFO	Train Epoch: 961 [0%]
2023-02-12 14:40:43,363	32k	INFO	[1.9441425800323486, 2.9773032665252686, 21.396255493164062, 21.15244483947754, 1.0561350584030151, 9600, 8.868029200613832e-05]
2023-02-12 14:40:51,598	32k	INFO	====> Epoch: 961
2023-02-12 14:41:03,626	32k	INFO	====> Epoch: 962
2023-02-12 14:41:15,549	32k	INFO	====> Epoch: 963
2023-02-12 14:41:27,507	32k	INFO	====> Epoch: 964
2023-02-12 14:41:39,542	32k	INFO	====> Epoch: 965
2023-02-12 14:41:51,524	32k	INFO	====> Epoch: 966
2023-02-12 14:42:03,498	32k	INFO	====> Epoch: 967
2023-02-12 14:42:15,485	32k	INFO	====> Epoch: 968
2023-02-12 14:42:27,466	32k	INFO	====> Epoch: 969
2023-02-12 14:42:39,487	32k	INFO	====> Epoch: 970
2023-02-12 14:42:51,443	32k	INFO	====> Epoch: 971
2023-02-12 14:43:03,462	32k	INFO	====> Epoch: 972
2023-02-12 14:43:15,461	32k	INFO	====> Epoch: 973
2023-02-12 14:43:27,439	32k	INFO	====> Epoch: 974
2023-02-12 14:43:39,481	32k	INFO	====> Epoch: 975
2023-02-12 14:43:51,496	32k	INFO	====> Epoch: 976
2023-02-12 14:44:03,551	32k	INFO	====> Epoch: 977
2023-02-12 14:44:15,544	32k	INFO	====> Epoch: 978
2023-02-12 14:44:27,494	32k	INFO	====> Epoch: 979
2023-02-12 14:44:39,490	32k	INFO	====> Epoch: 980
2023-02-12 14:44:43,532	32k	INFO	Train Epoch: 981 [0%]
2023-02-12 14:44:43,533	32k	INFO	[1.812034249305725, 3.1815125942230225, 19.23277473449707, 19.76807975769043, 0.9109163284301758, 9800, 8.845885434839242e-05]
2023-02-12 14:44:51,775	32k	INFO	====> Epoch: 981
2023-02-12 14:45:03,769	32k	INFO	====> Epoch: 982
2023-02-12 14:45:15,763	32k	INFO	====> Epoch: 983
2023-02-12 14:45:27,745	32k	INFO	====> Epoch: 984
2023-02-12 14:45:39,764	32k	INFO	====> Epoch: 985
2023-02-12 14:45:51,789	32k	INFO	====> Epoch: 986
2023-02-12 14:46:03,755	32k	INFO	====> Epoch: 987
2023-02-12 14:46:15,776	32k	INFO	====> Epoch: 988
2023-02-12 14:46:27,829	32k	INFO	====> Epoch: 989
2023-02-12 14:46:39,797	32k	INFO	====> Epoch: 990
2023-02-12 14:46:51,739	32k	INFO	====> Epoch: 991
2023-02-12 14:47:03,730	32k	INFO	====> Epoch: 992
2023-02-12 14:47:15,723	32k	INFO	====> Epoch: 993
2023-02-12 14:47:27,749	32k	INFO	====> Epoch: 994
2023-02-12 14:47:39,764	32k	INFO	====> Epoch: 995
2023-02-12 14:47:51,743	32k	INFO	====> Epoch: 996
2023-02-12 14:48:03,725	32k	INFO	====> Epoch: 997
2023-02-12 14:48:15,686	32k	INFO	====> Epoch: 998
2023-02-12 14:48:27,734	32k	INFO	====> Epoch: 999
2023-02-12 14:48:39,754	32k	INFO	====> Epoch: 1000
2023-02-12 14:48:43,794	32k	INFO	Train Epoch: 1001 [0%]
2023-02-12 14:48:43,794	32k	INFO	[1.8575782775878906, 3.2266526222229004, 21.58717918395996, 20.1503849029541, 0.5699613094329834, 10000, 8.823796962789062e-05]
2023-02-12 14:48:47,796	32k	INFO	Saving model and optimizer state at iteration 1001 to ./logs\32k\G_10000.pth
2023-02-12 14:49:05,105	32k	INFO	Saving model and optimizer state at iteration 1001 to ./logs\32k\D_10000.pth
2023-02-12 14:49:17,665	32k	INFO	====> Epoch: 1001
2023-02-12 14:49:30,015	32k	INFO	====> Epoch: 1002
2023-02-12 14:49:41,799	32k	INFO	====> Epoch: 1003
2023-02-12 14:49:53,593	32k	INFO	====> Epoch: 1004
2023-02-12 14:50:05,317	32k	INFO	====> Epoch: 1005
2023-02-12 14:50:17,071	32k	INFO	====> Epoch: 1006
2023-02-12 14:50:28,846	32k	INFO	====> Epoch: 1007
2023-02-12 14:50:40,616	32k	INFO	====> Epoch: 1008
2023-02-12 14:50:52,368	32k	INFO	====> Epoch: 1009
2023-02-12 14:51:04,166	32k	INFO	====> Epoch: 1010
2023-02-12 14:51:15,941	32k	INFO	====> Epoch: 1011
2023-02-12 14:51:27,691	32k	INFO	====> Epoch: 1012
2023-02-12 14:51:39,436	32k	INFO	====> Epoch: 1013
2023-02-12 14:51:51,315	32k	INFO	====> Epoch: 1014
2023-02-12 14:52:03,154	32k	INFO	====> Epoch: 1015
2023-02-12 14:52:14,955	32k	INFO	====> Epoch: 1016
2023-02-12 14:52:26,705	32k	INFO	====> Epoch: 1017
2023-02-12 14:52:38,476	32k	INFO	====> Epoch: 1018
2023-02-12 14:52:50,225	32k	INFO	====> Epoch: 1019
2023-02-12 14:53:02,055	32k	INFO	====> Epoch: 1020
2023-02-12 14:53:06,046	32k	INFO	Train Epoch: 1021 [0%]
2023-02-12 14:53:06,047	32k	INFO	[1.969978928565979, 3.3099782466888428, 22.197229385375977, 20.716018676757812, 0.9520759582519531, 10200, 8.801763646393014e-05]
2023-02-12 14:53:14,234	32k	INFO	====> Epoch: 1021
2023-02-12 14:53:26,028	32k	INFO	====> Epoch: 1022
2023-02-12 14:53:37,769	32k	INFO	====> Epoch: 1023
2023-02-12 14:53:49,693	32k	INFO	====> Epoch: 1024
2023-02-12 14:54:01,467	32k	INFO	====> Epoch: 1025
2023-02-12 14:54:13,256	32k	INFO	====> Epoch: 1026
2023-02-12 14:54:25,022	32k	INFO	====> Epoch: 1027
2023-02-12 14:54:36,824	32k	INFO	====> Epoch: 1028
2023-02-12 14:54:48,562	32k	INFO	====> Epoch: 1029
2023-02-12 14:55:00,346	32k	INFO	====> Epoch: 1030
2023-02-12 14:55:12,134	32k	INFO	====> Epoch: 1031
2023-02-12 14:55:23,927	32k	INFO	====> Epoch: 1032
2023-02-12 14:55:35,702	32k	INFO	====> Epoch: 1033
2023-02-12 14:55:47,505	32k	INFO	====> Epoch: 1034
2023-02-12 14:55:59,297	32k	INFO	====> Epoch: 1035
2023-02-12 14:56:11,084	32k	INFO	====> Epoch: 1036
2023-02-12 14:56:22,879	32k	INFO	====> Epoch: 1037
2023-02-12 14:56:34,670	32k	INFO	====> Epoch: 1038
2023-02-12 14:56:46,480	32k	INFO	====> Epoch: 1039
2023-02-12 14:56:58,233	32k	INFO	====> Epoch: 1040
2023-02-12 14:57:02,230	32k	INFO	Train Epoch: 1041 [0%]
2023-02-12 14:57:02,231	32k	INFO	[1.8475368022918701, 3.2396199703216553, 20.34634780883789, 20.80779266357422, 0.1730145364999771, 10400, 8.779785347925579e-05]
2023-02-12 14:57:10,645	32k	INFO	====> Epoch: 1041
2023-02-12 14:57:22,463	32k	INFO	====> Epoch: 1042
2023-02-12 14:57:34,280	32k	INFO	====> Epoch: 1043
2023-02-12 14:57:46,068	32k	INFO	====> Epoch: 1044
2023-02-12 14:57:58,020	32k	INFO	====> Epoch: 1045
2023-02-12 14:58:09,798	32k	INFO	====> Epoch: 1046
2023-02-12 14:58:21,590	32k	INFO	====> Epoch: 1047
2023-02-12 14:58:33,410	32k	INFO	====> Epoch: 1048
2023-02-12 14:58:45,209	32k	INFO	====> Epoch: 1049
2023-02-12 14:58:57,012	32k	INFO	====> Epoch: 1050
2023-02-12 14:59:08,797	32k	INFO	====> Epoch: 1051
2023-02-12 14:59:20,538	32k	INFO	====> Epoch: 1052
2023-02-12 14:59:32,354	32k	INFO	====> Epoch: 1053
2023-02-12 14:59:44,150	32k	INFO	====> Epoch: 1054
2023-02-12 14:59:55,928	32k	INFO	====> Epoch: 1055
2023-02-12 15:00:07,729	32k	INFO	====> Epoch: 1056
2023-02-12 15:00:19,515	32k	INFO	====> Epoch: 1057
2023-02-12 15:00:31,296	32k	INFO	====> Epoch: 1058
2023-02-12 15:00:43,080	32k	INFO	====> Epoch: 1059
2023-02-12 15:00:54,852	32k	INFO	====> Epoch: 1060
2023-02-12 15:00:58,838	32k	INFO	Train Epoch: 1061 [0%]
2023-02-12 15:00:58,839	32k	INFO	[1.9275860786437988, 3.214001417160034, 17.869892120361328, 18.476543426513672, 0.5841421484947205, 10600, 8.75786193000515e-05]
2023-02-12 15:01:07,027	32k	INFO	====> Epoch: 1061
2023-02-12 15:01:18,808	32k	INFO	====> Epoch: 1062
2023-02-12 15:01:30,608	32k	INFO	====> Epoch: 1063
2023-02-12 15:01:42,435	32k	INFO	====> Epoch: 1064
2023-02-12 15:01:54,221	32k	INFO	====> Epoch: 1065
2023-02-12 15:02:06,025	32k	INFO	====> Epoch: 1066
2023-02-12 15:02:17,843	32k	INFO	====> Epoch: 1067
2023-02-12 15:02:29,583	32k	INFO	====> Epoch: 1068
2023-02-12 15:02:41,405	32k	INFO	====> Epoch: 1069
2023-02-12 15:02:53,191	32k	INFO	====> Epoch: 1070
2023-02-12 15:03:04,997	32k	INFO	====> Epoch: 1071
2023-02-12 15:03:16,748	32k	INFO	====> Epoch: 1072
2023-02-12 15:03:28,527	32k	INFO	====> Epoch: 1073
2023-02-12 15:03:40,315	32k	INFO	====> Epoch: 1074
2023-02-12 15:03:52,154	32k	INFO	====> Epoch: 1075
2023-02-12 15:04:04,046	32k	INFO	====> Epoch: 1076
2023-02-12 15:04:15,812	32k	INFO	====> Epoch: 1077
2023-02-12 15:04:27,640	32k	INFO	====> Epoch: 1078
2023-02-12 15:04:39,428	32k	INFO	====> Epoch: 1079
2023-02-12 15:04:51,217	32k	INFO	====> Epoch: 1080
2023-02-12 15:04:55,228	32k	INFO	Train Epoch: 1081 [0%]
2023-02-12 15:04:55,229	32k	INFO	[1.6546056270599365, 3.431957960128784, 23.878787994384766, 21.629281997680664, 0.8686769008636475, 10800, 8.735993255593163e-05]
2023-02-12 15:05:03,333	32k	INFO	====> Epoch: 1081
2023-02-12 15:05:15,166	32k	INFO	====> Epoch: 1082
2023-02-12 15:05:26,998	32k	INFO	====> Epoch: 1083
2023-02-12 15:05:38,796	32k	INFO	====> Epoch: 1084
2023-02-12 15:05:50,587	32k	INFO	====> Epoch: 1085
2023-02-12 15:06:02,394	32k	INFO	====> Epoch: 1086
2023-02-12 15:06:14,177	32k	INFO	====> Epoch: 1087
2023-02-12 15:06:25,959	32k	INFO	====> Epoch: 1088
2023-02-12 15:06:37,714	32k	INFO	====> Epoch: 1089
2023-02-12 15:06:49,435	32k	INFO	====> Epoch: 1090
2023-02-12 15:07:01,215	32k	INFO	====> Epoch: 1091
2023-02-12 15:07:13,037	32k	INFO	====> Epoch: 1092
2023-02-12 15:07:24,817	32k	INFO	====> Epoch: 1093
2023-02-12 15:07:36,590	32k	INFO	====> Epoch: 1094
2023-02-12 15:07:48,402	32k	INFO	====> Epoch: 1095
2023-02-12 15:08:00,233	32k	INFO	====> Epoch: 1096
2023-02-12 15:08:12,025	32k	INFO	====> Epoch: 1097
2023-02-12 15:08:23,838	32k	INFO	====> Epoch: 1098
2023-02-12 15:08:35,650	32k	INFO	====> Epoch: 1099
2023-02-12 15:08:47,410	32k	INFO	====> Epoch: 1100
2023-02-12 15:08:51,413	32k	INFO	Train Epoch: 1101 [0%]
2023-02-12 15:08:51,413	32k	INFO	[1.6967860460281372, 3.0881154537200928, 21.32900047302246, 20.41789436340332, 0.7912378311157227, 11000, 8.714179187993246e-05]
2023-02-12 15:08:55,447	32k	INFO	Saving model and optimizer state at iteration 1101 to ./logs\32k\G_11000.pth
2023-02-12 15:09:10,589	32k	INFO	Saving model and optimizer state at iteration 1101 to ./logs\32k\D_11000.pth
2023-02-12 15:09:22,285	32k	INFO	====> Epoch: 1101
2023-02-12 15:09:34,615	32k	INFO	====> Epoch: 1102
2023-02-12 15:09:46,387	32k	INFO	====> Epoch: 1103
2023-02-12 15:09:58,182	32k	INFO	====> Epoch: 1104
2023-02-12 15:10:10,581	32k	INFO	====> Epoch: 1105
2023-02-12 15:10:22,819	32k	INFO	====> Epoch: 1106
2023-02-12 15:10:34,689	32k	INFO	====> Epoch: 1107
2023-02-12 15:10:46,617	32k	INFO	====> Epoch: 1108
2023-02-12 15:10:58,482	32k	INFO	====> Epoch: 1109
2023-02-12 15:11:10,287	32k	INFO	====> Epoch: 1110
2023-02-12 15:11:22,259	32k	INFO	====> Epoch: 1111
2023-02-12 15:11:34,191	32k	INFO	====> Epoch: 1112
2023-02-12 15:11:46,096	32k	INFO	====> Epoch: 1113
2023-02-12 15:11:58,088	32k	INFO	====> Epoch: 1114
2023-02-12 15:12:09,985	32k	INFO	====> Epoch: 1115
2023-02-12 15:12:21,699	32k	INFO	====> Epoch: 1116
2023-02-12 15:12:33,465	32k	INFO	====> Epoch: 1117
2023-02-12 15:12:45,227	32k	INFO	====> Epoch: 1118
2023-02-12 15:12:57,087	32k	INFO	====> Epoch: 1119
2023-02-12 15:13:08,900	32k	INFO	====> Epoch: 1120
2023-02-12 15:13:12,876	32k	INFO	Train Epoch: 1121 [0%]
2023-02-12 15:13:12,877	32k	INFO	[2.064385414123535, 3.3436312675476074, 20.797239303588867, 17.69752311706543, 0.6319724917411804, 11200, 8.692419590850362e-05]
2023-02-12 15:13:20,985	32k	INFO	====> Epoch: 1121
2023-02-12 15:13:32,780	32k	INFO	====> Epoch: 1122
2023-02-12 15:13:44,560	32k	INFO	====> Epoch: 1123
2023-02-12 15:13:56,361	32k	INFO	====> Epoch: 1124
2023-02-12 15:14:08,144	32k	INFO	====> Epoch: 1125
2023-02-12 15:14:19,982	32k	INFO	====> Epoch: 1126
2023-02-12 15:14:31,687	32k	INFO	====> Epoch: 1127
2023-02-12 15:14:43,437	32k	INFO	====> Epoch: 1128
2023-02-12 15:14:55,204	32k	INFO	====> Epoch: 1129
2023-02-12 15:15:07,041	32k	INFO	====> Epoch: 1130
2023-02-12 15:15:18,867	32k	INFO	====> Epoch: 1131
2023-02-12 15:15:30,634	32k	INFO	====> Epoch: 1132
2023-02-12 15:15:42,495	32k	INFO	====> Epoch: 1133
2023-02-12 15:15:54,327	32k	INFO	====> Epoch: 1134
2023-02-12 15:16:06,123	32k	INFO	====> Epoch: 1135
2023-02-12 15:16:17,917	32k	INFO	====> Epoch: 1136
2023-02-12 15:16:29,716	32k	INFO	====> Epoch: 1137
2023-02-12 15:16:41,506	32k	INFO	====> Epoch: 1138
2023-02-12 15:16:53,315	32k	INFO	====> Epoch: 1139
2023-02-12 15:17:05,161	32k	INFO	====> Epoch: 1140
2023-02-12 15:17:09,216	32k	INFO	Train Epoch: 1141 [0%]
2023-02-12 15:17:09,216	32k	INFO	[1.7398513555526733, 3.237757682800293, 20.018566131591797, 18.319841384887695, 0.7208283543586731, 11400, 8.670714328149953e-05]
2023-02-12 15:17:17,414	32k	INFO	====> Epoch: 1141
2023-02-12 15:17:29,161	32k	INFO	====> Epoch: 1142
2023-02-12 15:17:40,922	32k	INFO	====> Epoch: 1143
2023-02-12 15:17:52,622	32k	INFO	====> Epoch: 1144
2023-02-12 15:18:04,399	32k	INFO	====> Epoch: 1145
2023-02-12 15:18:16,191	32k	INFO	====> Epoch: 1146
2023-02-12 15:18:27,982	32k	INFO	====> Epoch: 1147
2023-02-12 15:18:39,739	32k	INFO	====> Epoch: 1148
2023-02-12 15:18:51,523	32k	INFO	====> Epoch: 1149
2023-02-12 15:19:03,373	32k	INFO	====> Epoch: 1150
2023-02-12 15:19:15,143	32k	INFO	====> Epoch: 1151
2023-02-12 15:19:26,981	32k	INFO	====> Epoch: 1152
2023-02-12 15:19:38,776	32k	INFO	====> Epoch: 1153
2023-02-12 15:19:50,555	32k	INFO	====> Epoch: 1154
2023-02-12 15:20:02,352	32k	INFO	====> Epoch: 1155
2023-02-12 15:20:14,148	32k	INFO	====> Epoch: 1156
2023-02-12 15:20:25,953	32k	INFO	====> Epoch: 1157
2023-02-12 15:20:37,735	32k	INFO	====> Epoch: 1158
2023-02-12 15:20:49,569	32k	INFO	====> Epoch: 1159
2023-02-12 15:21:01,340	32k	INFO	====> Epoch: 1160
2023-02-12 15:21:05,333	32k	INFO	Train Epoch: 1161 [0%]
2023-02-12 15:21:05,333	32k	INFO	[1.8517743349075317, 3.1895899772644043, 20.230409622192383, 19.716575622558594, 0.8846036195755005, 11600, 8.649063264217098e-05]
2023-02-12 15:21:13,427	32k	INFO	====> Epoch: 1161
2023-02-12 15:21:25,189	32k	INFO	====> Epoch: 1162
2023-02-12 15:21:37,017	32k	INFO	====> Epoch: 1163
2023-02-12 15:21:48,813	32k	INFO	====> Epoch: 1164
2023-02-12 15:22:00,606	32k	INFO	====> Epoch: 1165
2023-02-12 15:22:12,341	32k	INFO	====> Epoch: 1166
2023-02-12 15:22:24,140	32k	INFO	====> Epoch: 1167
2023-02-12 15:22:35,958	32k	INFO	====> Epoch: 1168
2023-02-12 15:22:47,753	32k	INFO	====> Epoch: 1169
2023-02-12 15:22:59,718	32k	INFO	====> Epoch: 1170
2023-02-12 15:23:11,511	32k	INFO	====> Epoch: 1171
2023-02-12 15:23:23,286	32k	INFO	====> Epoch: 1172
2023-02-12 15:23:35,055	32k	INFO	====> Epoch: 1173
2023-02-12 15:23:46,835	32k	INFO	====> Epoch: 1174
2023-02-12 15:23:58,584	32k	INFO	====> Epoch: 1175
2023-02-12 15:24:10,388	32k	INFO	====> Epoch: 1176
2023-02-12 15:24:22,202	32k	INFO	====> Epoch: 1177
2023-02-12 15:24:34,013	32k	INFO	====> Epoch: 1178
2023-02-12 15:24:46,197	32k	INFO	====> Epoch: 1179
2023-02-12 15:24:58,135	32k	INFO	====> Epoch: 1180
2023-02-12 15:25:02,233	32k	INFO	Train Epoch: 1181 [0%]
2023-02-12 15:25:02,234	32k	INFO	[1.9411377906799316, 3.3260269165039062, 20.635011672973633, 17.542858123779297, 0.5514277219772339, 11800, 8.627466263715663e-05]
2023-02-12 15:25:10,313	32k	INFO	====> Epoch: 1181
2023-02-12 15:25:22,209	32k	INFO	====> Epoch: 1182
2023-02-12 15:25:34,029	32k	INFO	====> Epoch: 1183
2023-02-12 15:25:45,928	32k	INFO	====> Epoch: 1184
2023-02-12 15:25:57,688	32k	INFO	====> Epoch: 1185
2023-02-12 15:26:09,457	32k	INFO	====> Epoch: 1186
2023-02-12 15:26:21,278	32k	INFO	====> Epoch: 1187
2023-02-12 15:26:33,090	32k	INFO	====> Epoch: 1188
2023-02-12 15:26:45,070	32k	INFO	====> Epoch: 1189
2023-02-12 15:26:56,889	32k	INFO	====> Epoch: 1190
2023-02-12 15:27:08,835	32k	INFO	====> Epoch: 1191
2023-02-12 15:27:20,693	32k	INFO	====> Epoch: 1192
2023-02-12 15:27:32,543	32k	INFO	====> Epoch: 1193
2023-02-12 15:27:44,349	32k	INFO	====> Epoch: 1194
2023-02-12 15:27:56,232	32k	INFO	====> Epoch: 1195
2023-02-12 15:28:08,062	32k	INFO	====> Epoch: 1196
2023-02-12 15:28:19,836	32k	INFO	====> Epoch: 1197
2023-02-12 15:28:31,604	32k	INFO	====> Epoch: 1198
2023-02-12 15:28:43,383	32k	INFO	====> Epoch: 1199
2023-02-12 15:28:55,170	32k	INFO	====> Epoch: 1200
2023-02-12 15:28:59,181	32k	INFO	Train Epoch: 1201 [0%]
2023-02-12 15:28:59,181	32k	INFO	[1.7774322032928467, 3.481269121170044, 26.027238845825195, 20.089521408081055, 0.9175114035606384, 12000, 8.605923191647444e-05]
2023-02-12 15:29:03,115	32k	INFO	Saving model and optimizer state at iteration 1201 to ./logs\32k\G_12000.pth
2023-02-12 15:29:17,066	32k	INFO	Saving model and optimizer state at iteration 1201 to ./logs\32k\D_12000.pth
2023-02-12 15:29:28,779	32k	INFO	====> Epoch: 1201
2023-02-12 15:29:41,020	32k	INFO	====> Epoch: 1202
2023-02-12 15:29:52,878	32k	INFO	====> Epoch: 1203
2023-02-12 15:30:04,726	32k	INFO	====> Epoch: 1204
2023-02-12 15:30:16,621	32k	INFO	====> Epoch: 1205
2023-02-12 15:30:28,492	32k	INFO	====> Epoch: 1206
2023-02-12 15:30:40,272	32k	INFO	====> Epoch: 1207
2023-02-12 15:30:52,052	32k	INFO	====> Epoch: 1208
2023-02-12 15:31:03,819	32k	INFO	====> Epoch: 1209
2023-02-12 15:31:15,585	32k	INFO	====> Epoch: 1210
2023-02-12 15:31:27,393	32k	INFO	====> Epoch: 1211
2023-02-12 15:31:39,278	32k	INFO	====> Epoch: 1212
2023-02-12 15:31:51,133	32k	INFO	====> Epoch: 1213
2023-02-12 15:32:02,966	32k	INFO	====> Epoch: 1214
2023-02-12 15:32:14,732	32k	INFO	====> Epoch: 1215
2023-02-12 15:32:26,513	32k	INFO	====> Epoch: 1216
2023-02-12 15:32:38,335	32k	INFO	====> Epoch: 1217
2023-02-12 15:32:50,225	32k	INFO	====> Epoch: 1218
2023-02-12 15:33:02,115	32k	INFO	====> Epoch: 1219
2023-02-12 15:33:13,896	32k	INFO	====> Epoch: 1220
2023-02-12 15:33:17,840	32k	INFO	Train Epoch: 1221 [0%]
2023-02-12 15:33:17,841	32k	INFO	[2.010641574859619, 3.1379950046539307, 19.937978744506836, 17.576082229614258, 0.9196208119392395, 12200, 8.584433913351344e-05]
2023-02-12 15:33:26,027	32k	INFO	====> Epoch: 1221
2023-02-12 15:33:37,846	32k	INFO	====> Epoch: 1222
2023-02-12 15:33:49,617	32k	INFO	====> Epoch: 1223
2023-02-12 15:34:01,463	32k	INFO	====> Epoch: 1224
2023-02-12 15:34:13,362	32k	INFO	====> Epoch: 1225
2023-02-12 15:34:25,144	32k	INFO	====> Epoch: 1226
2023-02-12 15:34:36,924	32k	INFO	====> Epoch: 1227
2023-02-12 15:34:48,729	32k	INFO	====> Epoch: 1228
2023-02-12 15:35:00,528	32k	INFO	====> Epoch: 1229
2023-02-12 15:35:12,433	32k	INFO	====> Epoch: 1230
2023-02-12 15:35:24,266	32k	INFO	====> Epoch: 1231
2023-02-12 15:35:36,075	32k	INFO	====> Epoch: 1232
2023-02-12 15:35:47,930	32k	INFO	====> Epoch: 1233
2023-02-12 15:35:59,726	32k	INFO	====> Epoch: 1234
2023-02-12 15:36:11,548	32k	INFO	====> Epoch: 1235
2023-02-12 15:36:23,295	32k	INFO	====> Epoch: 1236
2023-02-12 15:36:35,101	32k	INFO	====> Epoch: 1237
2023-02-12 15:36:46,887	32k	INFO	====> Epoch: 1238
2023-02-12 15:36:58,670	32k	INFO	====> Epoch: 1239
2023-02-12 15:37:10,460	32k	INFO	====> Epoch: 1240
2023-02-12 15:37:14,450	32k	INFO	Train Epoch: 1241 [0%]
2023-02-12 15:37:14,450	32k	INFO	[1.6771478652954102, 3.300658941268921, 21.90500831604004, 20.171859741210938, 0.509969174861908, 12400, 8.562998294502507e-05]
2023-02-12 15:37:22,535	32k	INFO	====> Epoch: 1241
2023-02-12 15:37:34,303	32k	INFO	====> Epoch: 1242
2023-02-12 15:37:46,098	32k	INFO	====> Epoch: 1243
2023-02-12 15:37:57,889	32k	INFO	====> Epoch: 1244
2023-02-12 15:38:09,660	32k	INFO	====> Epoch: 1245
2023-02-12 15:38:21,480	32k	INFO	====> Epoch: 1246
2023-02-12 15:38:33,254	32k	INFO	====> Epoch: 1247
2023-02-12 15:38:45,076	32k	INFO	====> Epoch: 1248
2023-02-12 15:38:56,951	32k	INFO	====> Epoch: 1249
2023-02-12 15:39:08,786	32k	INFO	====> Epoch: 1250
2023-02-12 15:39:20,601	32k	INFO	====> Epoch: 1251
2023-02-12 15:39:32,403	32k	INFO	====> Epoch: 1252
2023-02-12 15:39:44,197	32k	INFO	====> Epoch: 1253
2023-02-12 15:39:56,077	32k	INFO	====> Epoch: 1254
2023-02-12 15:40:07,858	32k	INFO	====> Epoch: 1255
2023-02-12 15:40:19,720	32k	INFO	====> Epoch: 1256
2023-02-12 15:40:31,470	32k	INFO	====> Epoch: 1257
2023-02-12 15:40:43,242	32k	INFO	====> Epoch: 1258
2023-02-12 15:40:55,061	32k	INFO	====> Epoch: 1259
2023-02-12 15:41:07,028	32k	INFO	====> Epoch: 1260
2023-02-12 15:41:10,996	32k	INFO	Train Epoch: 1261 [0%]
2023-02-12 15:41:10,997	32k	INFO	[1.753708839416504, 3.1686413288116455, 23.707977294921875, 18.282379150390625, 0.6658338308334351, 12600, 8.541616201111502e-05]
2023-02-12 15:41:19,110	32k	INFO	====> Epoch: 1261
2023-02-12 15:41:30,897	32k	INFO	====> Epoch: 1262
2023-02-12 15:41:42,795	32k	INFO	====> Epoch: 1263
2023-02-12 15:41:54,572	32k	INFO	====> Epoch: 1264
2023-02-12 15:42:06,357	32k	INFO	====> Epoch: 1265
2023-02-12 15:42:18,139	32k	INFO	====> Epoch: 1266
2023-02-12 15:42:29,999	32k	INFO	====> Epoch: 1267
2023-02-12 15:42:41,787	32k	INFO	====> Epoch: 1268
2023-02-12 15:42:53,549	32k	INFO	====> Epoch: 1269
2023-02-12 15:43:05,352	32k	INFO	====> Epoch: 1270
2023-02-12 15:43:17,079	32k	INFO	====> Epoch: 1271
2023-02-12 15:43:28,835	32k	INFO	====> Epoch: 1272
2023-02-12 15:43:40,597	32k	INFO	====> Epoch: 1273
2023-02-12 15:43:52,340	32k	INFO	====> Epoch: 1274
2023-02-12 15:44:04,110	32k	INFO	====> Epoch: 1275
2023-02-12 15:44:15,936	32k	INFO	====> Epoch: 1276
2023-02-12 15:44:27,817	32k	INFO	====> Epoch: 1277
2023-02-12 15:44:39,572	32k	INFO	====> Epoch: 1278
2023-02-12 15:44:51,381	32k	INFO	====> Epoch: 1279
2023-02-12 15:45:03,173	32k	INFO	====> Epoch: 1280
2023-02-12 15:45:07,177	32k	INFO	Train Epoch: 1281 [0%]
2023-02-12 15:45:07,177	32k	INFO	[1.7234199047088623, 3.08119797706604, 20.67536735534668, 17.942367553710938, 0.9086747765541077, 12800, 8.52028749952347e-05]
2023-02-12 15:45:15,257	32k	INFO	====> Epoch: 1281
2023-02-12 15:45:27,011	32k	INFO	====> Epoch: 1282
2023-02-12 15:45:38,805	32k	INFO	====> Epoch: 1283
2023-02-12 15:45:50,610	32k	INFO	====> Epoch: 1284
2023-02-12 15:46:02,417	32k	INFO	====> Epoch: 1285
2023-02-12 15:46:14,193	32k	INFO	====> Epoch: 1286
2023-02-12 15:46:25,982	32k	INFO	====> Epoch: 1287
2023-02-12 15:46:37,694	32k	INFO	====> Epoch: 1288
2023-02-12 15:46:49,478	32k	INFO	====> Epoch: 1289
2023-02-12 15:47:01,280	32k	INFO	====> Epoch: 1290
2023-02-12 15:47:13,081	32k	INFO	====> Epoch: 1291
2023-02-12 15:47:24,868	32k	INFO	====> Epoch: 1292
2023-02-12 15:47:36,613	32k	INFO	====> Epoch: 1293
2023-02-12 15:47:48,397	32k	INFO	====> Epoch: 1294
2023-02-12 15:48:00,253	32k	INFO	====> Epoch: 1295
2023-02-12 15:48:12,115	32k	INFO	====> Epoch: 1296
2023-02-12 15:48:23,906	32k	INFO	====> Epoch: 1297
2023-02-12 15:48:35,685	32k	INFO	====> Epoch: 1298
2023-02-12 15:48:47,428	32k	INFO	====> Epoch: 1299
2023-02-12 15:48:59,231	32k	INFO	====> Epoch: 1300
2023-02-12 15:49:03,239	32k	INFO	Train Epoch: 1301 [0%]
2023-02-12 15:49:03,240	32k	INFO	[1.8812379837036133, 3.4515433311462402, 22.568906784057617, 21.513614654541016, 0.9147152304649353, 13000, 8.499012056417291e-05]
2023-02-12 15:49:07,201	32k	INFO	Saving model and optimizer state at iteration 1301 to ./logs\32k\G_13000.pth
2023-02-12 15:49:25,205	32k	INFO	Saving model and optimizer state at iteration 1301 to ./logs\32k\D_13000.pth
2023-02-12 15:49:36,732	32k	INFO	====> Epoch: 1301
2023-02-12 15:49:49,000	32k	INFO	====> Epoch: 1302
2023-02-12 15:50:00,751	32k	INFO	====> Epoch: 1303
2023-02-12 15:50:12,575	32k	INFO	====> Epoch: 1304
2023-02-12 15:50:24,423	32k	INFO	====> Epoch: 1305
2023-02-12 15:50:36,197	32k	INFO	====> Epoch: 1306
2023-02-12 15:50:47,987	32k	INFO	====> Epoch: 1307
2023-02-12 15:50:59,734	32k	INFO	====> Epoch: 1308
2023-02-12 15:51:11,550	32k	INFO	====> Epoch: 1309
2023-02-12 15:51:23,317	32k	INFO	====> Epoch: 1310
2023-02-12 15:51:35,080	32k	INFO	====> Epoch: 1311
2023-02-12 15:51:46,817	32k	INFO	====> Epoch: 1312
2023-02-12 15:51:58,579	32k	INFO	====> Epoch: 1313
2023-02-12 15:52:10,338	32k	INFO	====> Epoch: 1314
2023-02-12 15:52:22,140	32k	INFO	====> Epoch: 1315
2023-02-12 15:52:33,928	32k	INFO	====> Epoch: 1316
2023-02-12 15:52:45,714	32k	INFO	====> Epoch: 1317
2023-02-12 15:52:57,488	32k	INFO	====> Epoch: 1318
2023-02-12 15:53:09,261	32k	INFO	====> Epoch: 1319
2023-02-12 15:53:21,058	32k	INFO	====> Epoch: 1320
2023-02-12 15:53:25,125	32k	INFO	Train Epoch: 1321 [0%]
2023-02-12 15:53:25,125	32k	INFO	[1.8744864463806152, 3.320587396621704, 18.410367965698242, 17.364992141723633, 1.0555418729782104, 13200, 8.477789738804749e-05]
2023-02-12 15:53:33,201	32k	INFO	====> Epoch: 1321
2023-02-12 15:53:45,069	32k	INFO	====> Epoch: 1322
2023-02-12 15:53:56,880	32k	INFO	====> Epoch: 1323
2023-02-12 15:54:08,660	32k	INFO	====> Epoch: 1324
2023-02-12 15:54:20,455	32k	INFO	====> Epoch: 1325
2023-02-12 15:54:32,240	32k	INFO	====> Epoch: 1326
2023-02-12 15:54:44,161	32k	INFO	====> Epoch: 1327
2023-02-12 15:54:56,019	32k	INFO	====> Epoch: 1328
2023-02-12 15:55:07,855	32k	INFO	====> Epoch: 1329
2023-02-12 15:55:19,581	32k	INFO	====> Epoch: 1330
2023-02-12 15:55:31,391	32k	INFO	====> Epoch: 1331
2023-02-12 15:55:43,200	32k	INFO	====> Epoch: 1332
2023-02-12 15:55:54,983	32k	INFO	====> Epoch: 1333
2023-02-12 15:56:06,757	32k	INFO	====> Epoch: 1334
2023-02-12 15:56:18,509	32k	INFO	====> Epoch: 1335
2023-02-12 15:56:30,353	32k	INFO	====> Epoch: 1336
2023-02-12 15:56:42,154	32k	INFO	====> Epoch: 1337
2023-02-12 15:56:53,964	32k	INFO	====> Epoch: 1338
2023-02-12 15:57:05,748	32k	INFO	====> Epoch: 1339
2023-02-12 15:57:17,502	32k	INFO	====> Epoch: 1340
2023-02-12 15:57:21,497	32k	INFO	Train Epoch: 1341 [0%]
2023-02-12 15:57:21,497	32k	INFO	[1.6354436874389648, 3.336968421936035, 23.863597869873047, 19.903148651123047, 0.6043044328689575, 13400, 8.456620414029713e-05]
2023-02-12 15:57:29,680	32k	INFO	====> Epoch: 1341
2023-02-12 15:57:41,435	32k	INFO	====> Epoch: 1342
2023-02-12 15:57:53,237	32k	INFO	====> Epoch: 1343
2023-02-12 15:58:05,011	32k	INFO	====> Epoch: 1344
2023-02-12 15:58:16,757	32k	INFO	====> Epoch: 1345
2023-02-12 15:58:28,570	32k	INFO	====> Epoch: 1346
2023-02-12 15:58:40,376	32k	INFO	====> Epoch: 1347
2023-02-12 15:58:52,265	32k	INFO	====> Epoch: 1348
2023-02-12 15:59:04,128	32k	INFO	====> Epoch: 1349
2023-02-12 15:59:15,924	32k	INFO	====> Epoch: 1350
2023-02-12 15:59:27,787	32k	INFO	====> Epoch: 1351
2023-02-12 15:59:39,579	32k	INFO	====> Epoch: 1352
2023-02-12 15:59:51,351	32k	INFO	====> Epoch: 1353
2023-02-12 16:00:03,166	32k	INFO	====> Epoch: 1354
2023-02-12 16:00:15,014	32k	INFO	====> Epoch: 1355
2023-02-12 16:00:26,737	32k	INFO	====> Epoch: 1356
2023-02-12 16:00:38,571	32k	INFO	====> Epoch: 1357
2023-02-12 16:00:50,326	32k	INFO	====> Epoch: 1358
2023-02-12 16:01:02,128	32k	INFO	====> Epoch: 1359
2023-02-12 16:01:14,025	32k	INFO	====> Epoch: 1360
2023-02-12 16:01:18,031	32k	INFO	Train Epoch: 1361 [0%]
2023-02-12 16:01:18,031	32k	INFO	[1.7485980987548828, 3.240476131439209, 19.417327880859375, 15.598264694213867, 0.5619482398033142, 13600, 8.43550394976729e-05]
2023-02-12 16:01:26,121	32k	INFO	====> Epoch: 1361
2023-02-12 16:01:37,918	32k	INFO	====> Epoch: 1362
2023-02-12 16:01:49,677	32k	INFO	====> Epoch: 1363
2023-02-12 16:02:01,432	32k	INFO	====> Epoch: 1364
2023-02-12 16:02:13,218	32k	INFO	====> Epoch: 1365
2023-02-12 16:02:25,013	32k	INFO	====> Epoch: 1366
2023-02-12 16:02:36,779	32k	INFO	====> Epoch: 1367
2023-02-12 16:02:48,546	32k	INFO	====> Epoch: 1368
2023-02-12 16:03:00,364	32k	INFO	====> Epoch: 1369
2023-02-12 16:03:12,141	32k	INFO	====> Epoch: 1370
2023-02-12 16:03:23,969	32k	INFO	====> Epoch: 1371
2023-02-12 16:03:35,723	32k	INFO	====> Epoch: 1372
2023-02-12 16:03:47,571	32k	INFO	====> Epoch: 1373
2023-02-12 16:03:59,394	32k	INFO	====> Epoch: 1374
2023-02-12 16:04:11,193	32k	INFO	====> Epoch: 1375
2023-02-12 16:04:23,001	32k	INFO	====> Epoch: 1376
2023-02-12 16:04:34,760	32k	INFO	====> Epoch: 1377
2023-02-12 16:04:46,517	32k	INFO	====> Epoch: 1378
2023-02-12 16:04:58,281	32k	INFO	====> Epoch: 1379
2023-02-12 16:05:10,046	32k	INFO	====> Epoch: 1380
2023-02-12 16:05:14,028	32k	INFO	Train Epoch: 1381 [0%]
2023-02-12 16:05:14,028	32k	INFO	[1.8243145942687988, 3.455235481262207, 21.25417709350586, 20.422574996948242, 0.8478912711143494, 13800, 8.41444021402301e-05]
2023-02-12 16:05:22,125	32k	INFO	====> Epoch: 1381
2023-02-12 16:05:33,961	32k	INFO	====> Epoch: 1382
2023-02-12 16:05:45,711	32k	INFO	====> Epoch: 1383
2023-02-12 16:05:57,469	32k	INFO	====> Epoch: 1384
2023-02-12 16:06:09,261	32k	INFO	====> Epoch: 1385
2023-02-12 16:06:21,077	32k	INFO	====> Epoch: 1386
2023-02-12 16:06:32,984	32k	INFO	====> Epoch: 1387
2023-02-12 16:06:44,746	32k	INFO	====> Epoch: 1388
2023-02-12 16:06:56,527	32k	INFO	====> Epoch: 1389
2023-02-12 16:07:08,313	32k	INFO	====> Epoch: 1390
2023-02-12 16:07:20,092	32k	INFO	====> Epoch: 1391
2023-02-12 16:07:31,861	32k	INFO	====> Epoch: 1392
2023-02-12 16:07:43,672	32k	INFO	====> Epoch: 1393
2023-02-12 16:07:55,477	32k	INFO	====> Epoch: 1394
2023-02-12 16:08:07,237	32k	INFO	====> Epoch: 1395
2023-02-12 16:08:19,049	32k	INFO	====> Epoch: 1396
2023-02-12 16:08:30,806	32k	INFO	====> Epoch: 1397
2023-02-12 16:08:42,569	32k	INFO	====> Epoch: 1398
2023-02-12 16:08:54,375	32k	INFO	====> Epoch: 1399
2023-02-12 16:09:06,184	32k	INFO	====> Epoch: 1400
2023-02-12 16:09:10,211	32k	INFO	Train Epoch: 1401 [0%]
2023-02-12 16:09:10,212	32k	INFO	[1.980910062789917, 2.867105007171631, 16.272972106933594, 16.36928367614746, 0.6712512969970703, 14000, 8.393429075132006e-05]
2023-02-12 16:09:14,146	32k	INFO	Saving model and optimizer state at iteration 1401 to ./logs\32k\G_14000.pth
2023-02-12 16:09:30,135	32k	INFO	Saving model and optimizer state at iteration 1401 to ./logs\32k\D_14000.pth
2023-02-12 16:09:41,839	32k	INFO	====> Epoch: 1401
2023-02-12 16:09:54,126	32k	INFO	====> Epoch: 1402
2023-02-12 16:10:05,910	32k	INFO	====> Epoch: 1403
2023-02-12 16:10:17,680	32k	INFO	====> Epoch: 1404
2023-02-12 16:10:29,419	32k	INFO	====> Epoch: 1405
2023-02-12 16:10:41,212	32k	INFO	====> Epoch: 1406
2023-02-12 16:10:52,958	32k	INFO	====> Epoch: 1407
2023-02-12 16:11:04,986	32k	INFO	====> Epoch: 1408
2023-02-12 16:11:16,698	32k	INFO	====> Epoch: 1409
2023-02-12 16:11:28,500	32k	INFO	====> Epoch: 1410
2023-02-12 16:11:40,246	32k	INFO	====> Epoch: 1411
2023-02-12 16:11:52,138	32k	INFO	====> Epoch: 1412
2023-02-12 16:12:03,964	32k	INFO	====> Epoch: 1413
2023-02-12 16:12:15,662	32k	INFO	====> Epoch: 1414
2023-02-12 16:12:27,435	32k	INFO	====> Epoch: 1415
2023-02-12 16:12:39,184	32k	INFO	====> Epoch: 1416
2023-02-12 16:12:50,978	32k	INFO	====> Epoch: 1417
2023-02-12 16:13:02,745	32k	INFO	====> Epoch: 1418
2023-02-12 16:13:14,535	32k	INFO	====> Epoch: 1419
2023-02-12 16:13:26,361	32k	INFO	====> Epoch: 1420
2023-02-12 16:13:30,324	32k	INFO	Train Epoch: 1421 [0%]
2023-02-12 16:13:30,325	32k	INFO	[1.7525862455368042, 3.5776731967926025, 23.730297088623047, 18.36430549621582, 1.0101344585418701, 14200, 8.372470401758169e-05]
2023-02-12 16:13:38,502	32k	INFO	====> Epoch: 1421
2023-02-12 16:13:50,246	32k	INFO	====> Epoch: 1422
2023-02-12 16:14:02,020	32k	INFO	====> Epoch: 1423
2023-02-12 16:14:13,734	32k	INFO	====> Epoch: 1424
2023-02-12 16:14:25,516	32k	INFO	====> Epoch: 1425
2023-02-12 16:14:37,247	32k	INFO	====> Epoch: 1426
2023-02-12 16:14:48,992	32k	INFO	====> Epoch: 1427
2023-02-12 16:15:00,760	32k	INFO	====> Epoch: 1428
2023-02-12 16:15:12,501	32k	INFO	====> Epoch: 1429
2023-02-12 16:15:24,332	32k	INFO	====> Epoch: 1430
2023-02-12 16:15:36,116	32k	INFO	====> Epoch: 1431
2023-02-12 16:15:47,908	32k	INFO	====> Epoch: 1432
2023-02-12 16:15:59,654	32k	INFO	====> Epoch: 1433
2023-02-12 16:16:11,404	32k	INFO	====> Epoch: 1434
2023-02-12 16:16:23,723	32k	INFO	====> Epoch: 1435
2023-02-12 16:16:35,641	32k	INFO	====> Epoch: 1436
2023-02-12 20:50:27,814	32k	INFO	====> Epoch: 1437