Upload ddpm_ip_cifar10 checkpoints and training logs

ddpm_ip_cifar10/ckpt/step079999/ema.pt

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ddpm_ip_cifar10/ckpt/step079999/meta.pt

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ddpm_ip_cifar10/ckpt/step079999/model.pt

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ddpm_ip_cifar10/ckpt/step079999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step159999/ema.pt

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ddpm_ip_cifar10/ckpt/step159999/meta.pt

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ddpm_ip_cifar10/ckpt/step159999/model.pt

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ddpm_ip_cifar10/ckpt/step159999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step239999/ema.pt

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ddpm_ip_cifar10/ckpt/step239999/meta.pt

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ddpm_ip_cifar10/ckpt/step239999/model.pt

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ddpm_ip_cifar10/ckpt/step239999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step319999/ema.pt

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ddpm_ip_cifar10/ckpt/step319999/meta.pt

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ddpm_ip_cifar10/ckpt/step319999/model.pt

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ddpm_ip_cifar10/ckpt/step319999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step399999/ema.pt

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ddpm_ip_cifar10/ckpt/step399999/meta.pt

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ddpm_ip_cifar10/ckpt/step399999/model.pt

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ddpm_ip_cifar10/ckpt/step399999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step479999/ema.pt

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ddpm_ip_cifar10/ckpt/step479999/meta.pt

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ddpm_ip_cifar10/ckpt/step479999/model.pt

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ddpm_ip_cifar10/ckpt/step479999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step559999/ema.pt

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ddpm_ip_cifar10/ckpt/step559999/meta.pt

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ddpm_ip_cifar10/ckpt/step559999/model.pt

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ddpm_ip_cifar10/ckpt/step559999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step639999/ema.pt

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ddpm_ip_cifar10/ckpt/step639999/meta.pt

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ddpm_ip_cifar10/ckpt/step639999/model.pt

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ddpm_ip_cifar10/ckpt/step639999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step719999/ema.pt

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ddpm_ip_cifar10/ckpt/step719999/meta.pt

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ddpm_ip_cifar10/ckpt/step719999/model.pt

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ddpm_ip_cifar10/ckpt/step719999/optimizer.pt

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ddpm_ip_cifar10/ckpt/step799999/ema.pt

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ddpm_ip_cifar10/ckpt/step799999/meta.pt

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ddpm_ip_cifar10/ckpt/step799999/model.pt

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ddpm_ip_cifar10/ckpt/step799999/optimizer.pt

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ddpm_ip_cifar10/config-2023-08-19-07-26-49.yaml

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+seed: 2022
+data:
+  name: CIFAR-10
+  dataroot: /data1/xuyifeng/data/CIFAR-10/
+  img_size: 32
+  img_channels: 3
+  num_classes: 10
+dataloader:
+  num_workers: 4
+  pin_memory: true
+  prefetch_factor: 2
+  micro_batch: 0
+model:
+  target: models.unet.UNet
+  params:
+    in_channels: 3
+    out_channels: 3
+    dim: 128
+    dim_mults:
+    - 1
+    - 2
+    - 2
+    - 2
+    use_attn:
+    - false
+    - true
+    - false
+    - false
+    num_res_blocks: 2
+    n_heads: 1
+    dropout: 0.1
+  ema_decay: 0.9999
+  ema_gradual: true
+diffusion:
+  target: diffusions.ddpm_ip.DDPM_IP
+  params:
+    total_steps: 1000
+    beta_schedule: linear
+    beta_start: 0.0001
+    beta_end: 0.02
+    objective: pred_eps
+    var_type: fixed_large
+train:
+  n_steps: 800000
+  batch_size: 128
+  clip_grad_norm: 1.0
+  print_freq: 400
+  save_freq: 10000
+  sample_freq: 5000
+  n_samples: 64
+  optim:
+    target: torch.optim.Adam
+    params:
+      lr: 0.0002

ddpm_ip_cifar10/samples.zip

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ddpm_ip_cifar10/tensorboard/events.out.tfevents.1692444413.aa-ESC4000-G4.19571.0

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