Upload folder using huggingface_hub
Browse files- README.md +9 -0
- config.json +61 -0
- config.yaml +174 -0
- model.safetensors +3 -0
README.md
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---
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tags:
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- model_hub_mixin
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- pytorch_model_hub_mixin
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---
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This model has been pushed to the Hub using the [PytorchModelHubMixin](https://huggingface.co/docs/huggingface_hub/package_reference/mixins#huggingface_hub.PyTorchModelHubMixin) integration:
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- Library: [More Information Needed]
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- Docs: [More Information Needed]
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config.json
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{
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"beta_end": 0.02,
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"beta_schedule": "squaredcos_cap_v2",
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"beta_start": 0.0001,
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"clip_sample": true,
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"clip_sample_range": 1.0,
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"crop_is_random": false,
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"crop_shape": [
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320,
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320
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],
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"diffusion_step_embed_dim": 128,
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"do_mask_loss_for_padding": 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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"horizon": 16,
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"input_normalization_modes": {
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"observation.images.gripper": "mean_std",
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"observation.images.head": "mean_std",
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"observation.state": "min_max"
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},
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"input_shapes": {
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"observation.images.gripper": [
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3,
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320,
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320
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],
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"observation.images.head": [
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3,
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320,
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320
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],
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"observation.state": [
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]
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},
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"kernel_size": 5,
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"n_action_steps": 8,
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"n_groups": 8,
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"n_obs_steps": 2,
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"noise_scheduler_type": "DDPM",
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"num_inference_steps": 100,
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"num_train_timesteps": 100,
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"output_normalization_modes": {
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"action": "min_max"
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},
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"output_shapes": {
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"action": [
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9
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]
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},
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"prediction_type": "epsilon",
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"pretrained_backbone_weights": null,
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"spatial_softmax_num_keypoints": 32,
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"use_film_scale_modulation": true,
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"use_group_norm": true,
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"vision_backbone": "resnet18"
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}
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config.yaml
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resume: false
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device: cuda
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use_amp: false
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seed: 100000
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dataset_repo_id: hellorobotinc/kitchen_cabinet_diagonal
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video_backend: pyav
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training:
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offline_steps: 200000
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online_steps: 0
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online_steps_between_rollouts: 1
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online_sampling_ratio: 0.5
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online_env_seed: ???
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eval_freq: -1
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log_freq: 250
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save_checkpoint: true
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save_freq: 10000
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num_workers: 16
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batch_size: 64
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image_transforms:
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enable: true
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max_num_transforms: 3
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random_order: false
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brightness:
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weight: 1
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min_max:
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- 0.8
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- 1.2
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contrast:
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weight: 1
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min_max:
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- 0.8
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- 1.2
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saturation:
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weight: 1
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min_max:
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- 0.5
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- 1.5
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hue:
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weight: 1
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min_max:
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- -0.05
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- 0.05
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sharpness:
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weight: 1
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min_max:
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- 0.8
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- 1.2
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grad_clip_norm: 10
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lr: 0.0001
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lr_scheduler: cosine
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lr_warmup_steps: 500
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adam_betas:
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- 0.95
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- 0.999
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adam_eps: 1.0e-08
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adam_weight_decay: 1.0e-06
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delta_timestamps:
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observation.images.gripper:
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- -0.16666666666666666
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- 0.0
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observation.images.head:
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- -0.16666666666666666
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- 0.0
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observation.state:
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- -0.16666666666666666
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- 0.0
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action:
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- -0.16666666666666666
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- 0.0
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- 0.16666666666666666
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- 0.3333333333333333
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- 0.5
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- 0.6666666666666666
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- 0.8333333333333334
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- 1.0
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- 1.1666666666666667
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- 1.3333333333333333
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- 1.5
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- 1.6666666666666667
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- 1.8333333333333333
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- 2.0
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- 2.1666666666666665
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- 2.3333333333333335
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drop_n_last_frames: 7
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eval:
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n_episodes: 50
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batch_size: 50
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use_async_envs: false
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wandb:
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enable: true
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disable_artifact: true
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project: diffusion-kitchen-diagonal
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notes: no depth
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fps: 6
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env:
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name: stretch_real
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task: stretch_baseX
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state_dim: 9
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action_dim: 9
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fps: ${fps}
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episode_length: 400
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gym:
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fps: ${fps}
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repo_version: main
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override_dataset_stats:
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observation.images.gripper:
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mean:
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- - - 0.485
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- - - 0.456
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- - - 0.406
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std:
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- - - 0.229
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- - - 0.224
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- - - 0.225
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observation.images.head:
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mean:
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- - - 0.485
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- - - 0.456
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- - - 0.406
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std:
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- - - 0.229
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- - - 0.224
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- - - 0.225
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policy:
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name: diffusion
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n_obs_steps: 2
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horizon: 16
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n_action_steps: 8
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input_shapes:
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observation.images.gripper:
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- 3
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- 320
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- 320
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observation.images.head:
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- 3
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- 320
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- 320
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observation.state:
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- ${env.state_dim}
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output_shapes:
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action:
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- ${env.action_dim}
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input_normalization_modes:
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observation.images.gripper: mean_std
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observation.images.head: mean_std
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observation.state: min_max
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output_normalization_modes:
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action: min_max
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vision_backbone: resnet18
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crop_shape:
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- 320
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- 320
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crop_is_random: false
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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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down_dims:
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- 512
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- 1024
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- 2048
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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: 100
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do_mask_loss_for_padding: false
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model.safetensors
ADDED
@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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oid sha256:e15b8e7b5ba60ff1797b0569c90dd3732c3f8c2ff18e848ea61747dc854c949f
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size 1067249692
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