Misc
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from torch.utils.tensorboard import SummaryWriter
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if __name__ == "__main__":
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writer = SummaryWriter("../experiments/train_div2k_feat_nsgen_r3/recovered_tb")
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f = open("../experiments/train_div2k_feat_nsgen_r3/console.txt", encoding="utf8")
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writer = SummaryWriter("../experiments/recovered_tb")
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f = open("../experiments/recovered_tb.txt", encoding="utf8")
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console = f.readlines()
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search_terms = [
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("iter", ", iter: ", ", lr:"),
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("l_g_total", " l_g_total: ", " switch_temperature:")
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("l_g_total", " l_g_total: ", " switch_temperature:"),
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("l_d_fake", "l_d_fake: ", " D_fake:")
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]
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iter = 0
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for line in console:
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import torch
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from torch import nn
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import models.archs.SRG1_arch as srg1
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import models.archs.SwitchedResidualGenerator_arch as srg
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import models.archs.NestedSwitchGenerator as nsg
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import functools
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@ -96,15 +97,15 @@ if __name__ == "__main__":
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torch.randn(1, 3, 64, 64),
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device='cuda')
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'''
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test_stability(functools.partial(srg.ConfigurableSwitchedResidualGenerator2,
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switch_filters=[16,16,16,16,16],
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switch_growths=[32,32,32,32,32],
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switch_reductions=[1,1,1,1,1],
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switch_processing_layers=[5,5,5,5,5],
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trans_counts=[8,8,8,8,8],
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test_stability(functools.partial(srg1.ConfigurableSwitchedResidualGenerator,
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switch_filters=[32,32,32,32],
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switch_growths=[16,16,16,16],
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switch_reductions=[4,3,2,1],
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switch_processing_layers=[3,3,4,5],
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trans_counts=[16,16,16,16,16],
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trans_kernel_sizes=[3,3,3,3,3],
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trans_layers=[3,3,3,3,3],
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transformation_filters=64,
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trans_filters_mid=[24,24,24,24,24],
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initial_temp=10),
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torch.randn(1, 3, 64, 64),
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device='cuda')
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