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backwards pass is not recommended under the autocast context, per pytorch docs

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This commit is contained in:
Phil Wang
2022-05-14 18:26:19 -07:00
parent aee92dba4a
commit 4ec6d0ba81
2 changed files with 5 additions and 5 deletions
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8
dalle2_pytorch/train.py
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@@ -266,8 +266,8 @@ class DiffusionPriorTrainer(nn.Module):
loss = self.diffusion_prior(*chunked_args, **chunked_kwargs)
loss = loss * chunk_size_frac
total_loss += loss.item()
self.scaler.scale(loss).backward()
total_loss += loss.item()
self.scaler.scale(loss).backward()
return total_loss
@@ -390,7 +390,7 @@ class DecoderTrainer(nn.Module):
loss = self.decoder(*chunked_args, unet_number = unet_number, **chunked_kwargs)
loss = loss * chunk_size_frac
total_loss += loss.item()
self.scale(loss, unet_number = unet_number).backward()
total_loss += loss.item()
self.scale(loss, unet_number = unet_number).backward()
return total_loss

2
setup.py
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@@ -10,7 +10,7 @@ setup(
'dream = dalle2_pytorch.cli:dream'
],
},
version = '0.2.27',
version = '0.2.29',
license='MIT',
description = 'DALL-E 2',
author = 'Phil Wang',