Robotics
LeRobot
Safetensors
act
jjjeonghi commited on
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1 Parent(s): e3481f3

Upload policy weights, train config and readme

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Files changed (4) hide show
  1. README.md +4 -4
  2. config.json +44 -24
  3. model.safetensors +2 -2
  4. train_config.json +55 -31
README.md CHANGED
@@ -2,20 +2,20 @@
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  datasets: data/merged_multitask
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  library_name: lerobot
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  license: apache-2.0
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- model_name: act
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  pipeline_tag: robotics
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  tags:
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  - lerobot
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- - act
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  - robotics
 
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  ---
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- # Model Card for act
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  <!-- Provide a quick summary of what the model is/does. -->
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- [Action Chunking with Transformers (ACT)](https://huggingface.co/papers/2304.13705) is an imitation-learning method that predicts short action chunks instead of single steps. It learns from teleoperated data and often achieves high success rates.
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  This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
 
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  datasets: data/merged_multitask
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  library_name: lerobot
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  license: apache-2.0
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+ model_name: diffusion
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  pipeline_tag: robotics
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  tags:
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  - lerobot
 
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  - robotics
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+ - diffusion
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  ---
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+ # Model Card for diffusion
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  <!-- Provide a quick summary of what the model is/does. -->
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+ [Diffusion Policy](https://huggingface.co/papers/2303.04137) treats visuomotor control as a generative diffusion process, producing smooth, multi-step action trajectories that excel at contact-rich manipulation.
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  This policy has been trained and pushed to the Hub using [LeRobot](https://github.com/huggingface/lerobot).
config.json CHANGED
@@ -1,6 +1,6 @@
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  {
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- "type": "act",
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- "n_obs_steps": 1,
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  "input_features": {
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  "observation.state": {
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  "type": "STATE",
@@ -49,30 +49,50 @@
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  "tags": null,
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  "license": null,
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  "pretrained_path": null,
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- "chunk_size": 100,
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- "n_action_steps": 100,
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  "normalization_mapping": {
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  "VISUAL": "MEAN_STD",
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- "STATE": "MEAN_STD",
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- "ACTION": "MEAN_STD"
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  },
 
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  "vision_backbone": "resnet18",
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- "pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
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- "replace_final_stride_with_dilation": false,
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- "pre_norm": false,
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- "dim_model": 512,
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- "n_heads": 8,
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- "dim_feedforward": 3200,
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- "feedforward_activation": "relu",
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- "n_encoder_layers": 4,
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- "n_decoder_layers": 1,
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- "use_vae": true,
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- "latent_dim": 32,
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- "n_vae_encoder_layers": 4,
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- "temporal_ensemble_coeff": null,
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- "dropout": 0.1,
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- "kl_weight": 10.0,
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- "optimizer_lr": 1e-05,
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- "optimizer_weight_decay": 0.0001,
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- "optimizer_lr_backbone": 1e-05
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
 
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  {
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+ "type": "diffusion",
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+ "n_obs_steps": 2,
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  "input_features": {
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  "observation.state": {
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  "type": "STATE",
 
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  "tags": null,
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  "license": null,
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  "pretrained_path": null,
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+ "horizon": 16,
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+ "n_action_steps": 8,
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  "normalization_mapping": {
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  "VISUAL": "MEAN_STD",
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+ "STATE": "MIN_MAX",
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+ "ACTION": "MIN_MAX"
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  },
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+ "drop_n_last_frames": 7,
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  "vision_backbone": "resnet18",
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+ "crop_shape": [
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+ 84,
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+ 84
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+ ],
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+ "crop_is_random": true,
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+ "pretrained_backbone_weights": null,
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+ "use_group_norm": true,
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+ "spatial_softmax_num_keypoints": 32,
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+ "use_separate_rgb_encoder_per_camera": false,
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+ "down_dims": [
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+ 512,
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+ 1024,
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+ 2048
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+ ],
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+ "kernel_size": 5,
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+ "n_groups": 8,
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+ "diffusion_step_embed_dim": 128,
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+ "use_film_scale_modulation": true,
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+ "noise_scheduler_type": "DDPM",
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+ "num_train_timesteps": 100,
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+ "beta_schedule": "squaredcos_cap_v2",
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+ "beta_start": 0.0001,
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+ "beta_end": 0.02,
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+ "prediction_type": "epsilon",
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+ "clip_sample": true,
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+ "clip_sample_range": 1.0,
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+ "num_inference_steps": null,
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+ "do_mask_loss_for_padding": false,
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+ "optimizer_lr": 0.0001,
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+ "optimizer_betas": [
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+ 0.95,
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+ 0.999
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+ "optimizer_eps": 1e-08,
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+ "optimizer_weight_decay": 1e-06,
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+ "scheduler_name": "cosine",
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+ "scheduler_warmup_steps": 500
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  }
model.safetensors CHANGED
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train_config.json CHANGED
@@ -81,8 +81,8 @@
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  },
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  "env": null,
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  "policy": {
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- "type": "act",
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- "n_obs_steps": 1,
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  "input_features": {
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  "observation.state": {
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  "type": "STATE",
@@ -131,35 +131,55 @@
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  "tags": null,
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  "license": null,
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  "pretrained_path": null,
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- "chunk_size": 100,
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- "n_action_steps": 100,
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  "normalization_mapping": {
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  "VISUAL": "MEAN_STD",
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- "STATE": "MEAN_STD",
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- "ACTION": "MEAN_STD"
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  },
 
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  "vision_backbone": "resnet18",
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- "pretrained_backbone_weights": "ResNet18_Weights.IMAGENET1K_V1",
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- "replace_final_stride_with_dilation": false,
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- "pre_norm": false,
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- "dim_model": 512,
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- "n_heads": 8,
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- "dim_feedforward": 3200,
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- "feedforward_activation": "relu",
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- "n_encoder_layers": 4,
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- "n_decoder_layers": 1,
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- "use_vae": true,
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- "latent_dim": 32,
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- "n_vae_encoder_layers": 4,
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- "temporal_ensemble_coeff": null,
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- "dropout": 0.1,
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- "kl_weight": 10.0,
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- "optimizer_lr": 1e-05,
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- "optimizer_weight_decay": 0.0001,
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- "optimizer_lr_backbone": 1e-05
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  },
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- "output_dir": "/media/choi/HDD/outputs/train/ACT_merged",
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- "job_name": "act_merged",
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  "resume": false,
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  "seed": 1000,
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  "num_workers": 4,
@@ -171,17 +191,21 @@
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  "save_freq": 20000,
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  "use_policy_training_preset": true,
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  "optimizer": {
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- "type": "adamw",
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- "lr": 1e-05,
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- "weight_decay": 0.0001,
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  "grad_clip_norm": 10.0,
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  "betas": [
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- 0.9,
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  0.999
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  ],
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  "eps": 1e-08
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  },
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- "scheduler": null,
 
 
 
 
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  "eval": {
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  "n_episodes": 50,
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  "batch_size": 50,
 
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  },
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  "env": null,
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  "policy": {
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+ "type": "diffusion",
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+ "n_obs_steps": 2,
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  "input_features": {
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  "observation.state": {
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  "type": "STATE",
 
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  "tags": null,
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  "license": null,
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  "pretrained_path": null,
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+ "n_action_steps": 8,
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  "normalization_mapping": {
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  "VISUAL": "MEAN_STD",
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+ "STATE": "MIN_MAX",
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+ "ACTION": "MIN_MAX"
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  },
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+ "drop_n_last_frames": 7,
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  "vision_backbone": "resnet18",
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+ "crop_shape": [
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+ "kernel_size": 5,
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+ "n_groups": 8,
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+ "diffusion_step_embed_dim": 128,
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+ "use_film_scale_modulation": true,
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+ "noise_scheduler_type": "DDPM",
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+ "num_train_timesteps": 100,
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+ "beta_schedule": "squaredcos_cap_v2",
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+ "beta_start": 0.0001,
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+ "beta_end": 0.02,
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+ "prediction_type": "epsilon",
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+ "clip_sample": true,
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+ "clip_sample_range": 1.0,
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+ "num_inference_steps": null,
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+ "do_mask_loss_for_padding": false,
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+ "optimizer_lr": 0.0001,
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+ "optimizer_eps": 1e-08,
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+ "optimizer_weight_decay": 1e-06,
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+ "scheduler_name": "cosine",
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+ "scheduler_warmup_steps": 500
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  },
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+ "output_dir": "/media/choi/HDD/outputs/train/Diffusion_merged",
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+ "job_name": "diffusion_merged",
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  "resume": false,
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  "seed": 1000,
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  "num_workers": 4,
 
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  "save_freq": 20000,
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  "use_policy_training_preset": true,
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  "optimizer": {
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  "eval": {
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  "n_episodes": 50,
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  "batch_size": 50,