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@@ -52,9 +52,7 @@ model:
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horizon_steps: ${horizon_steps}
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obs_dim: ${obs_dim}
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action_dim: ${action_dim}
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transition_dim: ${transition_dim}
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denoising_steps: ${denoising_steps}
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cond_steps: ${cond_steps}
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device: ${device}
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ema:
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@@ -18,6 +18,7 @@ transition_dim: ${action_dim}
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denoising_steps: 100
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horizon_steps: 4
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cond_steps: 1
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img_cond_steps: 1
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wandb:
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entity: ${oc.env:DPPO_WANDB_ENTITY}
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@@ -27,7 +28,7 @@ wandb:
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shape_meta:
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obs:
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rgb:
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shape: [3, 96, 96]
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shape: [3, 96, 96] # not counting img_cond_steps
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state:
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shape: [9]
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action:
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@@ -55,6 +56,7 @@ model:
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backbone:
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_target_: model.common.vit.VitEncoder
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obs_shape: ${shape_meta.obs.rgb.shape}
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num_channel: ${eval:'${shape_meta.obs.rgb.shape[0]} * ${img_cond_steps}'} # each image patch is history concatenated
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cfg:
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patch_size: 8
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depth: 1
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@@ -62,6 +64,7 @@ model:
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num_heads: 4
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embed_style: embed2
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embed_norm: 0
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img_cond_steps: ${img_cond_steps}
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augment: True
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spatial_emb: 128
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time_dim: 32
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@@ -73,9 +76,7 @@ model:
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horizon_steps: ${horizon_steps}
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obs_dim: ${obs_dim}
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action_dim: ${action_dim}
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transition_dim: ${transition_dim}
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denoising_steps: ${denoising_steps}
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cond_steps: ${cond_steps}
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device: ${device}
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ema:
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@@ -88,4 +89,5 @@ train_dataset:
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horizon_steps: ${horizon_steps}
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max_n_episodes: 100
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cond_steps: ${cond_steps}
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img_cond_steps: ${img_cond_steps}
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device: ${device}
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@@ -51,13 +51,11 @@ model:
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smaller_encoder: False
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cond_predict_scale: True
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transition_dim: ${transition_dim}
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cond_dim: ${obs_dim}
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cond_dim: ${eval:'${obs_dim} * ${cond_steps}'}
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horizon_steps: ${horizon_steps}
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obs_dim: ${obs_dim}
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action_dim: ${action_dim}
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transition_dim: ${transition_dim}
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denoising_steps: ${denoising_steps}
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cond_steps: ${cond_steps}
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device: ${device}
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ema:
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@@ -17,6 +17,7 @@ action_dim: 7
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transition_dim: ${action_dim}
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horizon_steps: 4
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cond_steps: 1
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img_cond_steps: 1
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wandb:
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entity: ${oc.env:DPPO_WANDB_ENTITY}
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@@ -52,6 +53,7 @@ model:
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backbone:
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_target_: model.common.vit.VitEncoder
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obs_shape: ${shape_meta.obs.rgb.shape}
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num_channel: ${eval:'${shape_meta.obs.rgb.shape[0]} * ${img_cond_steps}'} # each image patch is history concatenated
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cfg:
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patch_size: 8
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depth: 1
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@@ -64,6 +66,7 @@ model:
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mlp_dims: [512, 512, 512]
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residual_style: True
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fixed_std: 0.1
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img_cond_steps: ${img_cond_steps}
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cond_dim: ${eval:'${obs_dim} * ${cond_steps}'}
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horizon_steps: ${horizon_steps}
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transition_dim: ${transition_dim}
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@@ -80,4 +83,5 @@ train_dataset:
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horizon_steps: ${horizon_steps}
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max_n_episodes: 100
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cond_steps: ${cond_steps}
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img_cond_steps: ${img_cond_steps}
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device: ${device}
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