TF之pix2pix：基于TF利用Facades数据集训练pix2pix模型、测试并进行生成过程全记录
【摘要】 TF之pix2pix：基于TF利用Facades数据集训练pix2pix模型、测试并进行生成过程全记录
目录
TB监控
1、SCALARS
2、IMAGES
3、GRAPHS
4、DISTRIBUTIONS
输出结果
训练代码运行过程全记录
测试代码全记录
TB监控
1、SCALARS
2、IMAGES
inpu...
TF之pix2pix：基于TF利用Facades数据集训练pix2pix模型、测试并进行生成过程全记录
目录
TB监控
1、SCALARS
2、IMAGES
| inputs_summary |
 |
outputs_summary |  |
| predict_fake_summary |  |
predict_real_summary |  |
| targets_summary |  |
3、GRAPHS
4、DISTRIBUTIONS
输出结果
训练代码运行过程全记录
2 epoch：2126~2218
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开始训练
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aspect_ratio = 1.0
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batch_size = 1
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beta1 = 0.5
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checkpoint = None
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display_freq = 0
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flip = True
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gan_weight = 1.0
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input_dir = facades/train
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l1_weight = 100.0
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lab_colorization = False
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lr = 0.0002
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max_epochs = 200
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max_steps = None
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mode = train
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ndf = 64
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ngf = 64
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output_dir = facades_train
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output_filetype = png
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progress_freq = 50
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save_freq = 5000
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scale_size = 286
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seed = 407313043
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summary_freq = 100
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trace_freq = 0
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which_direction = BtoA
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-
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2018-10-07 21:26:49.558601:
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parameter_count = 57183616
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progress epoch 1 step 50 image/sec 0.4 remaining 35m
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discrim_loss 0.59409106
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gen_loss_GAN 0.3667453
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gen_loss_L1 0.14627346
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recording summary
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progress epoch 1 step 100 image/sec 0.3 remaining 33m
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discrim_loss 0.77973217
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gen_loss_GAN 0.74193096
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gen_loss_L1 0.21620709
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progress epoch 1 step 150 image/sec 0.4 remaining 30m
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discrim_loss 0.7097481
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gen_loss_GAN 1.2259353
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gen_loss_L1 0.27181715
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recording summary
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progress epoch 1 step 200 image/sec 0.4 remaining 28m
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discrim_loss 0.6670909
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gen_loss_GAN 1.5955695
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gen_loss_L1 0.30515844
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progress epoch 1 step 250 image/sec 0.4 remaining 25m
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discrim_loss 0.5505945
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gen_loss_GAN 1.897398
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gen_loss_L1 0.3195855
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recording summary
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progress epoch 1 step 300 image/sec 0.4 remaining 23m
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discrim_loss 0.54358536
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gen_loss_GAN 2.1270702
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gen_loss_L1 0.33635142
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progress epoch 1 step 350 image/sec 0.4 remaining 21m
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discrim_loss 0.53915083
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gen_loss_GAN 2.234504
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gen_loss_L1 0.33556485
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recording summary
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progress epoch 1 step 400 image/sec 0.4 remaining 18m
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discrim_loss 0.5494336
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gen_loss_GAN 2.349324
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gen_loss_L1 0.33941123
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progress epoch 2 step 50 image/sec 0.4 remaining 16m
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discrim_loss 0.5763757
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gen_loss_GAN 2.3618762
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gen_loss_L1 0.3413253
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recording summary
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progress epoch 2 step 100 image/sec 0.4 remaining 14m
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discrim_loss 0.63876843
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gen_loss_GAN 2.2650375
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gen_loss_L1 0.3409966
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progress epoch 2 step 150 image/sec 0.4 remaining 11m
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discrim_loss 0.6011929
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gen_loss_GAN 2.264903
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gen_loss_L1 0.34726414
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recording summary
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progress epoch 2 step 200 image/sec 0.4 remaining 9m
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discrim_loss 0.59052
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gen_loss_GAN 2.302569
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gen_loss_L1 0.3522855
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progress epoch 2 step 250 image/sec 0.3 remaining 7m
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discrim_loss 0.57109314
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gen_loss_GAN 2.324084
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gen_loss_L1 0.35149702
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recording summary
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progress epoch 2 step 300 image/sec 0.3 remaining 4m
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discrim_loss 0.4946928
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gen_loss_GAN 2.5188313
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gen_loss_L1 0.3564302
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progress epoch 2 step 350 image/sec 0.3 remaining 2m
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discrim_loss 0.5365153
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gen_loss_GAN 2.5414586
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gen_loss_L1 0.35425124
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recording summary
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progress epoch 2 step 400 image/sec 0.3 remaining 0m
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discrim_loss 0.56210524
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gen_loss_GAN 2.5018184
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gen_loss_L1 0.35051015
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saving model
测试代码全记录
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开始测试
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loaded lab_colorization = False
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loaded ndf = 64
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loaded ngf = 64
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loaded which_direction = BtoA
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aspect_ratio = 1.0
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batch_size = 1
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beta1 = 0.5
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checkpoint = facades_train
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display_freq = 0
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flip = False
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gan_weight = 1.0
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input_dir = facades/val
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l1_weight = 100.0
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lab_colorization = False
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lr = 0.0002
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max_epochs = None
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max_steps = None
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mode = test
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ndf = 64
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ngf = 64
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output_dir = facades_test
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output_filetype = png
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progress_freq = 50
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save_freq = 5000
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scale_size = 256
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seed = 651085994
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summary_freq = 100
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trace_freq = 0
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which_direction = BtoA
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examples count = 100
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parameter_count = 57183616
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loading model from checkpoint
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wrote index at facades_test\index.html
文章来源: yunyaniu.blog.csdn.net，作者：一个处女座的程序猿，版权归原作者所有，如需转载，请联系作者。
原文链接：yunyaniu.blog.csdn.net/article/details/82960621
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