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https://github.com/wassname/denoising-diffusion-pytorch.git
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@@ -7,6 +7,7 @@ from inspect import isfunction
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from functools import partial
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from torch.utils import data
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from multiprocessing import cpu_count
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from torch.cuda.amp import autocast, GradScaler
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from pathlib import Path
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@@ -598,7 +599,7 @@ class Trainer(object):
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self.train_num_steps = train_num_steps
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self.ds = Dataset(folder, image_size, augment_horizontal_flip = augment_horizontal_flip)
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self.dl = cycle(data.DataLoader(self.ds, batch_size = train_batch_size, shuffle=True, pin_memory=True))
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self.dl = cycle(data.DataLoader(self.ds, batch_size = train_batch_size, shuffle = True, pin_memory = True, num_workers = cpu_count()))
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self.opt = Adam(diffusion_model.parameters(), lr=train_lr)
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self.step = 0
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@@ -3,7 +3,7 @@ from setuptools import setup, find_packages
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setup(
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name = 'denoising-diffusion-pytorch',
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packages = find_packages(),
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version = '0.18.2',
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version = '0.18.3',
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license='MIT',
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description = 'Denoising Diffusion Probabilistic Models - Pytorch',
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author = 'Phil Wang',
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