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  1. media/result_grid.jpg +2 -2
  2. samples/unet_320x640_0.jpg +0 -3
  3. samples/unet_384x640_0.jpg +0 -3
  4. samples/unet_448x640_0.jpg +0 -3
  5. samples/unet_512x640_0.jpg +0 -3
  6. samples/unet_576x640_0.jpg +0 -3
  7. samples/unet_640x320_0.jpg +0 -3
  8. samples/unet_640x384_0.jpg +0 -3
  9. samples/unet_640x448_0.jpg +0 -3
  10. samples/unet_640x512_0.jpg +0 -3
  11. samples/unet_640x576_0.jpg +0 -3
  12. samples/unet_640x640_0.jpg +0 -3
  13. test.ipynb +2 -2
  14. train.py +3 -3
  15. unet/diffusion_pytorch_model.safetensors +1 -1
  16. {unet_very_old → unet640}/config.json +2 -2
  17. {unet_very_old → unet640}/diffusion_pytorch_model.safetensors +2 -2
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train.py CHANGED
@@ -26,13 +26,13 @@ from collections import deque
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  from transformers import AutoTokenizer, AutoModel
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  # --------------------------- Параметры ---------------------------
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- ds_path = "/workspace/sdxs/datasets/640"
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  project = "unet"
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- batch_size = 256
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  base_learning_rate = 3e-5
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  min_learning_rate = 2.5e-5
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  num_epochs = 10
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- sample_interval_share = 40
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  max_length = 192
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  use_wandb = True
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  use_comet_ml = False
 
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  from transformers import AutoTokenizer, AutoModel
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  # --------------------------- Параметры ---------------------------
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+ ds_path = "/workspace/sdxs/datasets/768"
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  project = "unet"
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+ batch_size = 384
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  base_learning_rate = 3e-5
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  min_learning_rate = 2.5e-5
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  num_epochs = 10
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+ sample_interval_share = 20
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  max_length = 192
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  use_wandb = True
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  use_comet_ml = False
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{unet_very_old → unet640}/config.json RENAMED
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{unet_very_old → unet640}/diffusion_pytorch_model.safetensors RENAMED
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