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https://github.com/labmlai/annotated_deep_learning_paper_implementations.git
synced 2025-08-14 17:41:37 +08:00
loop timing
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@ -493,7 +493,7 @@ class Configs(BaseConfigs):
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# Loop through epochs
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for epoch in monit.loop(self.epochs):
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# Loop through the dataset
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for i, batch in enumerate(self.dataloader):
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for i, batch in monit.enum('Train', self.dataloader):
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# Move images to the device
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data_x, data_y = batch['x'].to(self.device), batch['y'].to(self.device)
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@ -528,6 +528,8 @@ class Configs(BaseConfigs):
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# Update learning rates
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self.generator_lr_scheduler.step()
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self.discriminator_lr_scheduler.step()
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# New line
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tracker.new_line()
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def optimize_generators(self, data_x: torch.Tensor, data_y: torch.Tensor, true_labels: torch.Tensor):
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"""
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2
setup.py
2
setup.py
@ -5,7 +5,7 @@ with open("readme.md", "r") as f:
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setuptools.setup(
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name='labml-nn',
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version='0.4.80',
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version='0.4.81',
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author="Varuna Jayasiri, Nipun Wijerathne",
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author_email="vpjayasiri@gmail.com, hnipun@gmail.com",
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description="A collection of PyTorch implementations of neural network architectures and layers.",
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