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@@ -68,3 +68,54 @@ w3dz1sd1/wandb/run-20250107_174546-w3dz1sd1/files/media/videos/eval/1_eval_1_f49
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2inskug9/.hydra/config.yaml

@@ -0,0 +1,350 @@
+root_dir: /home/${oc.env:USER}/fish_leon
+nstep: 3
+seed: 41
+dataset_shuffle_seed: ${seed}
+device: cuda
+save_video: true
+save_buffer: true
+use_tb: true
+baseline: false
+use_wandb: true
+eval: true
+process_contact_features: ${eval}
+obs_type: pixels
+use_color: true
+use_depth: true
+use_masks: false
+mask_list:
+- EE_obj_mask
+mask_representation: channels
+crop_hw:
+- 144
+- 144
+crop_down_offset: 48
+color_crop_type: null
+depth_crop_type: null
+segmask_crop_type: null
+add_crop_binary_mask: false
+add_coord_conv_map: false
+use_context_color: false
+use_context_depth: false
+use_context_segmask: false
+context_color_crop_type: null
+context_depth_crop_type: null
+context_segmask_crop_type: null
+context_add_crop_binary_mask: false
+context_add_coord_conv_map: false
+use_contact_map: false
+use_sdf_maps: false
+use_normals_maps: false
+which_objects: both
+max_contact_prob: 0.1
+max_depth: 2.0
+grasped_dtc_max_value: 0.105
+env_dtc_max_value: 0.425
+grasped_normals_mask_max_dtc_value: 0.105
+env_normals_mask_max_dtc_value: 0.425
+clamp_dtc: true
+dtc_adaptive_normalization: false
+mask_normals_within_sdf: true
+adaptive_normals_mask: true
+learnable_contact_preprocess_params: false
+contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_ctxt_seed_183386_epoch_9
+contact_estimation_model_ckpt_path: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
+num_eval: 5
+debug_timestamps: false
+open_loop: false
+action_trajectories: true
+stop_after_action: false
+interpolation_frequency: 25
+policy_frequency: 5
+wait_for_new_camera_frames: true
+random_start: false
+eval_starts: ${root_dir}/FISH/eval_starts/${suite.name}_${obs_type}/${task_name}
+train_demo_idxs_list_or_num: null
+num_valid_demos: null
+val_num_groups: 3
+name_of_expert_demo: 112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
+expert_dataset_dirpath: ${root_dir}/FISH/expert_demos/${suite.name}/${task_name}/${name_of_expert_demo}
+expert_dataset: ${expert_dataset_dirpath}/demos.zarr
+action_key: ${oc.if_else:${action_trajectories}, 'action_trajectory_${interpolation_frequency}hz',
+  'action'}
+semantic_demo_grouping_name: semantic_demo_grouping.yaml
+semantic_demo_grouping: ${expert_dataset_dirpath}/${semantic_demo_grouping_name}
+expert_dataset_config: ${expert_dataset_dirpath}/demo_config.yaml
+bc_regularize: false
+bc_weight_type: qfilter
+load_checkpoint: ${agent.load_checkpoint}
+wandb_run_id: '1009_1'
+true_action_history: false
+wandb_notes: null
+checkpoint_epoch: 12000
+load_residual_weight: false
+checkpoint_root_dir: /home/${oc.env:USER}/fish_leon/FISH
+checkpoint_weight_dir: ${checkpoint_root_dir}/exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
+residual_weight: ${root_dir}/FISH/weights/${suite.name}_${obs_type}/${task_name}/weight.pt
+experiment_dir: ./exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
+final_experiment_dir: ${experiment_dir}/${oc.generate_run_id:}
+agent:
+  _target_: agent.diffusion_policy.DiffusionPolicyAgent
+  name: diffusion_policy
+  load_checkpoint: ${eval}
+  device: ${device}
+  n_obs_steps: ${.config.policy_cfg.n_obs_steps}
+  suite_name: ${suite.name}
+  obs_type: ${obs_type}
+  enable_arm: ${eval}
+  enable_camera: ${eval}
+  use_tb: ${use_tb}
+  desired_image_shape:
+  - 13
+  - 180
+  - 240
+  orig_cam_shape:
+  - 3
+  - 240
+  - 320
+  config:
+    _target_: agent.diffusion_policy.DiffusionPolicyAgentConfig
+    compile: false
+    device: ${device}
+    cam_resize_shape: ${agent.desired_image_shape}
+    orig_cam_shape: ${agent.orig_cam_shape}
+    policy_frequency: ${policy_frequency}
+    interpolation_frequency: ${interpolation_frequency}
+    policy_cfg:
+      _target_: lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig
+      n_obs_steps: 1
+      horizon: 36
+      n_action_steps: ${agent.config.policy_cfg.horizon}
+      input_shapes:
+        observation.image: ${agent.config.cam_resize_shape}
+        context_observation.image: ${agent.config.cam_resize_shape}
+        observation.state:
+        - 8
+        observation.action_history:
+        - 7
+      output_shapes:
+        action:
+        - 7
+      input_normalization_modes:
+        observation.image: mean_std
+        observation.state: min_max
+        observation.action_history: min_max
+      output_normalization_modes:
+        action: min_max
+      vision_backbone: resnet18
+      pretrained_backbone_weights: null
+      transforms:
+      - _target_: torchaug.transforms.RandomAffine
+        degrees:
+        - -5
+        - 5
+        translate:
+        - 0.05
+        - 0.05
+        batch_transform: true
+        num_chunks: -1
+        batch_inplace: true
+      - _target_: torchaug.transforms.RandomColorJitter
+        brightness: 0.3
+        contrast: 0.4
+        saturation: 0.5
+        hue: 0.08
+        batch_transform: true
+        num_chunks: -1
+        batch_inplace: true
+      use_group_norm: true
+      spatial_softmax_num_keypoints: 32
+      action_history_encoder_config:
+        _target_: lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig
+        in_channels: 7
+        out_channels: 32
+        history_length: ${agent.config.policy_cfg.n_action_steps}
+        kernel_size: ${agent.config.policy_cfg.kernel_size}
+        downsample_kernel_size: 3
+        downsample_stride: 2
+        downsample_padding: 1
+      down_dims:
+      - 256
+      - 512
+      - 1024
+      kernel_size: 5
+      n_groups: 8
+      diffusion_step_embed_dim: 128
+      use_film_scale_modulation: true
+      noise_scheduler_type: DDIM
+      beta_schedule: squaredcos_cap_v2
+      beta_start: 0.0001
+      beta_end: 0.02
+      prediction_type: epsilon
+      clip_sample: true
+      clip_sample_range: 1.0
+      num_train_timesteps: 50
+      num_inference_steps: 10
+      do_mask_loss_for_padding: false
+    train_cfg:
+      _target_: utils.TrainConfig
+      lr: 0.0001
+      lr_scheduler: cosine
+      lr_warmup_steps: 500
+      adam_betas:
+      - 0.95
+      - 0.999
+      adam_eps: 1.0e-08
+      adam_weight_decay: 1.0e-06
+      grad_clip_norm: 10
+      offline_steps: ${num_train_frames_diffusion}
+      use_amp: true
+    observation_cfg:
+      _target_: agent.encoder.VisualFeatureSet
+      use_depth: ${use_depth}
+      use_color: ${use_color}
+      mask_input_dict:
+        _target_: agent.encoder.MaskInputDict
+        enable: ${use_masks}
+        representation: ${mask_representation}
+        mask_list: ${mask_list}
+      crop_input_config:
+        _target_: agent.encoder.CropInputConfig
+        color_crop_type: ${color_crop_type}
+        depth_crop_type: ${depth_crop_type}
+        segmask_crop_type: ${segmask_crop_type}
+        crop_hw: ${crop_hw}
+        crop_down_offset: ${crop_down_offset}
+        add_crop_binary_mask: ${add_crop_binary_mask}
+        add_coord_conv_map: ${add_coord_conv_map}
+      context_input_config:
+        _target_: agent.encoder.ContextInputConfig
+        use_color: ${use_context_color}
+        use_depth: ${use_context_depth}
+        mask_input_dict:
+          _target_: agent.encoder.MaskInputDict
+          enable: ${use_context_segmask}
+          representation: ${mask_representation}
+          mask_list: ${mask_list}
+        crop_input_config:
+          _target_: agent.encoder.CropInputConfig
+          color_crop_type: ${context_color_crop_type}
+          depth_crop_type: ${context_depth_crop_type}
+          segmask_crop_type: ${context_segmask_crop_type}
+          crop_hw: ${crop_hw}
+          crop_down_offset: ${crop_down_offset}
+          add_crop_binary_mask: ${context_add_crop_binary_mask}
+          add_coord_conv_map: ${context_add_coord_conv_map}
+      mask_soft_approx_scheduler_config:
+        _target_: agent.encoder.MaskSoftApproxSchedulerConfig
+        num_steps: 40000
+        initial_value: 10.0
+        final_value: 1000.0
+        interpolation_scheme: constant
+      use_contact_map: ${use_contact_map}
+      use_sdf_maps: ${use_sdf_maps}
+      use_normals_maps: ${use_normals_maps}
+      which_objects: ${which_objects}
+      grasped_dtc_max_value: ${grasped_dtc_max_value}
+      env_dtc_max_value: ${env_dtc_max_value}
+      grasped_normals_mask_max_dtc_value: ${grasped_normals_mask_max_dtc_value}
+      env_normals_mask_max_dtc_value: ${env_normals_mask_max_dtc_value}
+      clamp_dtc: ${clamp_dtc}
+      max_contact_prob: ${max_contact_prob}
+      mask_normals_within_sdf: ${mask_normals_within_sdf}
+      dtc_adaptive_normalization: ${dtc_adaptive_normalization}
+      adaptive_normals_mask: ${adaptive_normals_mask}
+      max_depth: ${max_depth}
+      image_shape: ${agent.desired_image_shape}
+      learnable_contact_preprocess_params: ${learnable_contact_preprocess_params}
+      learning_rate: ${agent.config.train_cfg.lr}
+      weight_decay: 0.0
+      contact_model_name: ${contact_model_name}
+      zero_centered: false
+suite:
+  suite: frankagym
+  name: frankagym
+  frame_stack: ${agent.n_obs_steps}
+  action_repeat: 1
+  discount: 0.99
+  hidden_dim: 1024
+  num_train_frames: 2010
+  num_seed_frames: 260
+  num_train_epochs: 5000
+  validate_every_epochs: 100
+  validate_diffusion_on_action_loss_every_epochs: 500
+  train_eval_diffusion_on_action_loss_every_epochs: 500
+  check_topk_every_epochs: 10
+  save_snapshot_every_epochs: 5000
+  eval_every_frames: 2000
+  num_eval_episodes: 5
+  save_snapshot: true
+  wait_for_user_to_start_episode: true
+  task_make_fn:
+    _target_: suite.frankagym.make
+    name: ${task_name}
+    height: 240
+    width: 320
+    frame_stack: ${suite.frame_stack}
+    action_repeat: ${suite.action_repeat}
+    seed: ${seed}
+    enable_arm: ${agent.enable_arm}
+    enable_gripper: ${enable_gripper}
+    start_with_gripper_open: ${start_with_gripper_open}
+    enable_camera: ${agent.enable_camera}
+    path_to_depth_extrinsics: ${path_to_depth_extrinsics}
+    contact_estimation_model_ckpt_path: ${contact_estimation_model_ckpt_path}
+    x_limit: ${x_limit}
+    y_limit: ${y_limit}
+    z_limit: ${z_limit}
+    device: ${device}
+    interpolation_frequency: ${interpolation_frequency}
+    policy_frequency: ${policy_frequency}
+    debug_timestamps: ${debug_timestamps}
+    stop_after_action: ${stop_after_action}
+    open_loop: ${open_loop}
+    wait_for_new_camera_frames: ${wait_for_new_camera_frames}
+    action_key: ${action_key}
+    action_trajectory_horizon: ${agent.config.policy_cfg.horizon}
+    action_trajectories: ${action_trajectories}
+    path_to_zarr_dataset: ${expert_dataset}
+    agent_policy_cfg: ???
+    true_action_history: ${true_action_history}
+num_train_frames_bc: 50000
+num_train_frames_drq: 1100000
+stddev_schedule_drq: linear(1.0,0.1,100000)
+task_name: FrankaInsertion-v1
+num_train_frames_vinn: 25000
+num_train_frames_diffusion: 1000000
+num_train_epochs_bc: 5000
+num_train_epochs_diffusion: 5000
+validate_every_epochs_bc: 5
+validate_every_epochs_diffusion: 25
+validate_diffusion_on_action_loss_every_epochs: 50
+train_eval_diffusion_on_action_loss_every_epochs: 500
+check_topk_every_epochs: 5
+check_topk_every_epochs_diffusion: ${validate_diffusion_on_action_loss_every_epochs}
+save_snapshot_every_epochs_diffusion: 5000
+x_limit:
+- 0.2
+- 0.7
+y_limit:
+- -0.4
+- 0.4
+z_limit:
+- -0.05
+- 0.55
+home_displacement:
+- 0.55
+- 0.0
+- 0.55
+- 180.0
+- 0.0
+- 0.0
+enable_gripper: true
+start_with_gripper_open: true
+offset_mask:
+- 1
+- 1
+- 1
+- 1
+- 1
+- 1
+path_to_depth_extrinsics: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy

2inskug9/.hydra/hydra.yaml

@@ -0,0 +1,169 @@
+hydra:
+  run:
+    dir: ${final_experiment_dir}
+  sweep:
+    dir: ${final_experiment_dir}
+    subdir: ${hydra.job.num}
+  launcher:
+    submitit_folder: ${final_experiment_dir}/.slurm
+    timeout_min: 60
+    cpus_per_task: null
+    gpus_per_node: null
+    tasks_per_node: 1
+    mem_gb: null
+    nodes: 1
+    name: ${hydra.job.name}
+    stderr_to_stdout: false
+    _target_: hydra_plugins.hydra_submitit_launcher.submitit_launcher.LocalLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - agent=diffusion
+    - suite=frankagym
+    - suite/frankagym_task@_global_=insertion
+  job:
+    name: eval_policy
+    chdir: true
+    override_dirname: agent=diffusion,suite/frankagym_task@_global_=insertion,suite=frankagym
+    id: ???
+    num: ???
+    config_name: config_eval
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.1'
+    cwd: /home/leonmkim/fish_leon/FISH
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /home/leonmkim/fish_leon/FISH/cfgs
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/2inskug9
+    choices:
+      suite: frankagym
+      suite/frankagym_task@_global_: insertion
+      agent: diffusion
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: submitit_local
+      hydra/output: default
+  verbose: false

2inskug9/.hydra/overrides.yaml

@@ -0,0 +1,3 @@
+- agent=diffusion
+- suite=frankagym
+- suite/frankagym_task@_global_=insertion

2inskug9/eval_policy.log

@@ -0,0 +1,15 @@
+[2025-01-06 20:40:45,800][py.warnings][WARNING] - /home/leonmkim/fish_leon/FISH/eval_policy.py:428: UserWarning: 
+The version_base parameter is not specified.
+Please specify a compatability version level, or None.
+Will assume defaults for version 1.1
+  @hydra.main(config_path='cfgs', config_name='config_eval')
+
+[2025-01-06 20:40:45,803][py.warnings][WARNING] - /home/leonmkim/fish_leon/FISH/eval_policy.py:365: UserWarning: 
+The version_base parameter is not specified.
+Please specify a compatability version level, or None.
+Will assume defaults for version 1.1
+  hydra.initialize(
+
+[2025-01-06 20:40:49,726][py.warnings][WARNING] - /home/leonmkim/fish_leon/FISH/eval_policy.py:414: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
+  payload = torch.load(f)
+

5qmtbx9d/episode_rosbags/episode_0_2025-01-07-20-45-18.bag

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:fe23231707dc8cd039df6798393bb32a7fdb2b5269f0d7491643a090c40e820c
+size 1406423449

5qmtbx9d/episode_rosbags/episode_2_2025-01-07-20-46-48.bag

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:2059801822bb12b3c7ec5ce54a24944d9f97192cc5e05bc9e28bef29b24b0fa5
+size 1412262733

5qmtbx9d/episode_rosbags/episode_3_2025-01-07-20-47-34.bag

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:9ed878bad62a79fc9dea7f7e774e1abd90b0816780c39be281c5de5c644ed698
+size 1410566127

5qmtbx9d/episode_rosbags/episode_4_2025-01-07-20-48-21.bag

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:07195c6d41a9d448314956089995708a527c9c4e8e962f85d9c31900aa54af47
+size 1410737371

6qq3p71c/.hydra/config.yaml

@@ -0,0 +1,350 @@
+root_dir: /home/${oc.env:USER}/fish_leon
+nstep: 3
+seed: 41
+dataset_shuffle_seed: ${seed}
+device: cuda
+save_video: true
+save_buffer: true
+use_tb: true
+baseline: false
+use_wandb: true
+eval: true
+process_contact_features: ${eval}
+obs_type: pixels
+use_color: true
+use_depth: true
+use_masks: false
+mask_list:
+- EE_obj_mask
+mask_representation: channels
+crop_hw:
+- 144
+- 144
+crop_down_offset: 48
+color_crop_type: null
+depth_crop_type: null
+segmask_crop_type: null
+add_crop_binary_mask: false
+add_coord_conv_map: false
+use_context_color: false
+use_context_depth: false
+use_context_segmask: false
+context_color_crop_type: null
+context_depth_crop_type: null
+context_segmask_crop_type: null
+context_add_crop_binary_mask: false
+context_add_coord_conv_map: false
+use_contact_map: false
+use_sdf_maps: false
+use_normals_maps: false
+which_objects: both
+max_contact_prob: 0.1
+max_depth: 2.0
+grasped_dtc_max_value: 0.105
+env_dtc_max_value: 0.425
+grasped_normals_mask_max_dtc_value: 0.105
+env_normals_mask_max_dtc_value: 0.425
+clamp_dtc: true
+dtc_adaptive_normalization: false
+mask_normals_within_sdf: true
+adaptive_normals_mask: true
+learnable_contact_preprocess_params: false
+contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_ctxt_seed_183386_epoch_9
+contact_estimation_model_ckpt_path: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
+num_eval: 5
+debug_timestamps: false
+open_loop: false
+action_trajectories: true
+stop_after_action: false
+interpolation_frequency: 25
+policy_frequency: 5
+wait_for_new_camera_frames: true
+random_start: false
+eval_starts: ${root_dir}/FISH/eval_starts/${suite.name}_${obs_type}/${task_name}
+train_demo_idxs_list_or_num: null
+num_valid_demos: null
+val_num_groups: 3
+name_of_expert_demo: 112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
+expert_dataset_dirpath: ${root_dir}/FISH/expert_demos/${suite.name}/${task_name}/${name_of_expert_demo}
+expert_dataset: ${expert_dataset_dirpath}/demos.zarr
+action_key: ${oc.if_else:${action_trajectories}, 'action_trajectory_${interpolation_frequency}hz',
+  'action'}
+semantic_demo_grouping_name: semantic_demo_grouping.yaml
+semantic_demo_grouping: ${expert_dataset_dirpath}/${semantic_demo_grouping_name}
+expert_dataset_config: ${expert_dataset_dirpath}/demo_config.yaml
+bc_regularize: false
+bc_weight_type: qfilter
+load_checkpoint: ${agent.load_checkpoint}
+wandb_run_id: '1009_1'
+true_action_history: false
+wandb_notes: null
+checkpoint_epoch: 12000
+load_residual_weight: false
+checkpoint_root_dir: /home/${oc.env:USER}/fish_leon/FISH
+checkpoint_weight_dir: ${checkpoint_root_dir}/exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
+residual_weight: ${root_dir}/FISH/weights/${suite.name}_${obs_type}/${task_name}/weight.pt
+experiment_dir: ./exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
+final_experiment_dir: ${experiment_dir}/${oc.generate_run_id:}
+agent:
+  _target_: agent.diffusion_policy.DiffusionPolicyAgent
+  name: diffusion_policy
+  load_checkpoint: ${eval}
+  device: ${device}
+  n_obs_steps: ${.config.policy_cfg.n_obs_steps}
+  suite_name: ${suite.name}
+  obs_type: ${obs_type}
+  enable_arm: ${eval}
+  enable_camera: ${eval}
+  use_tb: ${use_tb}
+  desired_image_shape:
+  - 13
+  - 180
+  - 240
+  orig_cam_shape:
+  - 3
+  - 240
+  - 320
+  config:
+    _target_: agent.diffusion_policy.DiffusionPolicyAgentConfig
+    compile: false
+    device: ${device}
+    cam_resize_shape: ${agent.desired_image_shape}
+    orig_cam_shape: ${agent.orig_cam_shape}
+    policy_frequency: ${policy_frequency}
+    interpolation_frequency: ${interpolation_frequency}
+    policy_cfg:
+      _target_: lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig
+      n_obs_steps: 1
+      horizon: 36
+      n_action_steps: ${agent.config.policy_cfg.horizon}
+      input_shapes:
+        observation.image: ${agent.config.cam_resize_shape}
+        context_observation.image: ${agent.config.cam_resize_shape}
+        observation.state:
+        - 8
+        observation.action_history:
+        - 7
+      output_shapes:
+        action:
+        - 7
+      input_normalization_modes:
+        observation.image: mean_std
+        observation.state: min_max
+        observation.action_history: min_max
+      output_normalization_modes:
+        action: min_max
+      vision_backbone: resnet18
+      pretrained_backbone_weights: null
+      transforms:
+      - _target_: torchaug.transforms.RandomAffine
+        degrees:
+        - -5
+        - 5
+        translate:
+        - 0.05
+        - 0.05
+        batch_transform: true
+        num_chunks: -1
+        batch_inplace: true
+      - _target_: torchaug.transforms.RandomColorJitter
+        brightness: 0.3
+        contrast: 0.4
+        saturation: 0.5
+        hue: 0.08
+        batch_transform: true
+        num_chunks: -1
+        batch_inplace: true
+      use_group_norm: true
+      spatial_softmax_num_keypoints: 32
+      action_history_encoder_config:
+        _target_: lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig
+        in_channels: 7
+        out_channels: 32
+        history_length: ${agent.config.policy_cfg.n_action_steps}
+        kernel_size: ${agent.config.policy_cfg.kernel_size}
+        downsample_kernel_size: 3
+        downsample_stride: 2
+        downsample_padding: 1
+      down_dims:
+      - 256
+      - 512
+      - 1024
+      kernel_size: 5
+      n_groups: 8
+      diffusion_step_embed_dim: 128
+      use_film_scale_modulation: true
+      noise_scheduler_type: DDIM
+      beta_schedule: squaredcos_cap_v2
+      beta_start: 0.0001
+      beta_end: 0.02
+      prediction_type: epsilon
+      clip_sample: true
+      clip_sample_range: 1.0
+      num_train_timesteps: 50
+      num_inference_steps: 10
+      do_mask_loss_for_padding: false
+    train_cfg:
+      _target_: utils.TrainConfig
+      lr: 0.0001
+      lr_scheduler: cosine
+      lr_warmup_steps: 500
+      adam_betas:
+      - 0.95
+      - 0.999
+      adam_eps: 1.0e-08
+      adam_weight_decay: 1.0e-06
+      grad_clip_norm: 10
+      offline_steps: ${num_train_frames_diffusion}
+      use_amp: true
+    observation_cfg:
+      _target_: agent.encoder.VisualFeatureSet
+      use_depth: ${use_depth}
+      use_color: ${use_color}
+      mask_input_dict:
+        _target_: agent.encoder.MaskInputDict
+        enable: ${use_masks}
+        representation: ${mask_representation}
+        mask_list: ${mask_list}
+      crop_input_config:
+        _target_: agent.encoder.CropInputConfig
+        color_crop_type: ${color_crop_type}
+        depth_crop_type: ${depth_crop_type}
+        segmask_crop_type: ${segmask_crop_type}
+        crop_hw: ${crop_hw}
+        crop_down_offset: ${crop_down_offset}
+        add_crop_binary_mask: ${add_crop_binary_mask}
+        add_coord_conv_map: ${add_coord_conv_map}
+      context_input_config:
+        _target_: agent.encoder.ContextInputConfig
+        use_color: ${use_context_color}
+        use_depth: ${use_context_depth}
+        mask_input_dict:
+          _target_: agent.encoder.MaskInputDict
+          enable: ${use_context_segmask}
+          representation: ${mask_representation}
+          mask_list: ${mask_list}
+        crop_input_config:
+          _target_: agent.encoder.CropInputConfig
+          color_crop_type: ${context_color_crop_type}
+          depth_crop_type: ${context_depth_crop_type}
+          segmask_crop_type: ${context_segmask_crop_type}
+          crop_hw: ${crop_hw}
+          crop_down_offset: ${crop_down_offset}
+          add_crop_binary_mask: ${context_add_crop_binary_mask}
+          add_coord_conv_map: ${context_add_coord_conv_map}
+      mask_soft_approx_scheduler_config:
+        _target_: agent.encoder.MaskSoftApproxSchedulerConfig
+        num_steps: 40000
+        initial_value: 10.0
+        final_value: 1000.0
+        interpolation_scheme: constant
+      use_contact_map: ${use_contact_map}
+      use_sdf_maps: ${use_sdf_maps}
+      use_normals_maps: ${use_normals_maps}
+      which_objects: ${which_objects}
+      grasped_dtc_max_value: ${grasped_dtc_max_value}
+      env_dtc_max_value: ${env_dtc_max_value}
+      grasped_normals_mask_max_dtc_value: ${grasped_normals_mask_max_dtc_value}
+      env_normals_mask_max_dtc_value: ${env_normals_mask_max_dtc_value}
+      clamp_dtc: ${clamp_dtc}
+      max_contact_prob: ${max_contact_prob}
+      mask_normals_within_sdf: ${mask_normals_within_sdf}
+      dtc_adaptive_normalization: ${dtc_adaptive_normalization}
+      adaptive_normals_mask: ${adaptive_normals_mask}
+      max_depth: ${max_depth}
+      image_shape: ${agent.desired_image_shape}
+      learnable_contact_preprocess_params: ${learnable_contact_preprocess_params}
+      learning_rate: ${agent.config.train_cfg.lr}
+      weight_decay: 0.0
+      contact_model_name: ${contact_model_name}
+      zero_centered: false
+suite:
+  suite: frankagym
+  name: frankagym
+  frame_stack: ${agent.n_obs_steps}
+  action_repeat: 1
+  discount: 0.99
+  hidden_dim: 1024
+  num_train_frames: 2010
+  num_seed_frames: 260
+  num_train_epochs: 5000
+  validate_every_epochs: 100
+  validate_diffusion_on_action_loss_every_epochs: 500
+  train_eval_diffusion_on_action_loss_every_epochs: 500
+  check_topk_every_epochs: 10
+  save_snapshot_every_epochs: 5000
+  eval_every_frames: 2000
+  num_eval_episodes: 5
+  save_snapshot: true
+  wait_for_user_to_start_episode: true
+  task_make_fn:
+    _target_: suite.frankagym.make
+    name: ${task_name}
+    height: 240
+    width: 320
+    frame_stack: ${suite.frame_stack}
+    action_repeat: ${suite.action_repeat}
+    seed: ${seed}
+    enable_arm: ${agent.enable_arm}
+    enable_gripper: ${enable_gripper}
+    start_with_gripper_open: ${start_with_gripper_open}
+    enable_camera: ${agent.enable_camera}
+    path_to_depth_extrinsics: ${path_to_depth_extrinsics}
+    contact_estimation_model_ckpt_path: ${contact_estimation_model_ckpt_path}
+    x_limit: ${x_limit}
+    y_limit: ${y_limit}
+    z_limit: ${z_limit}
+    device: ${device}
+    interpolation_frequency: ${interpolation_frequency}
+    policy_frequency: ${policy_frequency}
+    debug_timestamps: ${debug_timestamps}
+    stop_after_action: ${stop_after_action}
+    open_loop: ${open_loop}
+    wait_for_new_camera_frames: ${wait_for_new_camera_frames}
+    action_key: ${action_key}
+    action_trajectory_horizon: ${agent.config.policy_cfg.horizon}
+    action_trajectories: ${action_trajectories}
+    path_to_zarr_dataset: ${expert_dataset}
+    agent_policy_cfg: ???
+    true_action_history: ${true_action_history}
+num_train_frames_bc: 50000
+num_train_frames_drq: 1100000
+stddev_schedule_drq: linear(1.0,0.1,100000)
+task_name: FrankaInsertion-v1
+num_train_frames_vinn: 25000
+num_train_frames_diffusion: 1000000
+num_train_epochs_bc: 5000
+num_train_epochs_diffusion: 5000
+validate_every_epochs_bc: 5
+validate_every_epochs_diffusion: 25
+validate_diffusion_on_action_loss_every_epochs: 50
+train_eval_diffusion_on_action_loss_every_epochs: 500
+check_topk_every_epochs: 5
+check_topk_every_epochs_diffusion: ${validate_diffusion_on_action_loss_every_epochs}
+save_snapshot_every_epochs_diffusion: 5000
+x_limit:
+- 0.2
+- 0.7
+y_limit:
+- -0.4
+- 0.4
+z_limit:
+- -0.05
+- 0.55
+home_displacement:
+- 0.55
+- 0.0
+- 0.55
+- 180.0
+- 0.0
+- 0.0
+enable_gripper: true
+start_with_gripper_open: true
+offset_mask:
+- 1
+- 1
+- 1
+- 1
+- 1
+- 1
+path_to_depth_extrinsics: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy

6qq3p71c/.hydra/hydra.yaml

@@ -0,0 +1,169 @@
+hydra:
+  run:
+    dir: ${final_experiment_dir}
+  sweep:
+    dir: ${final_experiment_dir}
+    subdir: ${hydra.job.num}
+  launcher:
+    submitit_folder: ${final_experiment_dir}/.slurm
+    timeout_min: 60
+    cpus_per_task: null
+    gpus_per_node: null
+    tasks_per_node: 1
+    mem_gb: null
+    nodes: 1
+    name: ${hydra.job.name}
+    stderr_to_stdout: false
+    _target_: hydra_plugins.hydra_submitit_launcher.submitit_launcher.LocalLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
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+    override_dirname: agent=diffusion,suite/frankagym_task@_global_=insertion,suite=frankagym
+    id: ???
+    num: ???
+    config_name: config_eval
+    env_set: {}
+    env_copy: []
+    config:
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+        item_sep: ','
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+    version_base: '1.1'
+    cwd: /home/leonmkim/fish_leon/FISH
+    config_sources:
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+      schema: pkg
+      provider: hydra
+    - path: /home/leonmkim/fish_leon/FISH/cfgs
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c
+    choices:
+      suite: frankagym
+      suite/frankagym_task@_global_: insertion
+      agent: diffusion
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: submitit_local
+      hydra/output: default
+  verbose: false

6qq3p71c/.hydra/overrides.yaml

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+The version_base parameter is not specified.
+Please specify a compatability version level, or None.
+Will assume defaults for version 1.1
+  @hydra.main(config_path='cfgs', config_name='config_eval')
+
+[2025-01-07 17:13:58,665][py.warnings][WARNING] - /home/leonmkim/fish_leon/FISH/eval_robot.py:532: UserWarning: 
+The version_base parameter is not specified.
+Please specify a compatability version level, or None.
+Will assume defaults for version 1.1
+  hydra.initialize(
+

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+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_setup.py:_flush():76] Configure stats pid to 2196057
+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_setup.py:_flush():76] Loading settings from /home/leonmkim/.config/wandb/settings
+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_setup.py:_flush():76] Loading settings from /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/wandb/settings
+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_setup.py:_flush():76] Loading settings from environment variables: {}
+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_setup.py:_flush():76] Applying setup settings: {'_disable_service': False}
+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_setup.py:_flush():76] Inferring run settings from compute environment: {'program_relpath': 'FISH/eval_robot.py', 'program_abspath': '/home/leonmkim/fish_leon/FISH/eval_robot.py', 'program': '/home/leonmkim/fish_leon/FISH/eval_robot.py'}
+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_setup.py:_flush():76] Applying login settings: {}
+2025-01-07 17:14:04,425 INFO    MainThread:2196057 [wandb_init.py:_log_setup():529] Logging user logs to /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/wandb/run-20250107_171404-6qq3p71c/logs/debug.log
+2025-01-07 17:14:04,426 INFO    MainThread:2196057 [wandb_init.py:_log_setup():530] Logging internal logs to /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/wandb/run-20250107_171404-6qq3p71c/logs/debug-internal.log
+2025-01-07 17:14:04,426 INFO    MainThread:2196057 [wandb_init.py:init():569] calling init triggers
+2025-01-07 17:14:04,426 INFO    MainThread:2196057 [wandb_init.py:init():576] wandb.init called with sweep_config: {}
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'translate': [0.05, 0.05], 'batch_transform': True, 'num_chunks': -1, 'batch_inplace': True}, {'_target_': 'torchaug.transforms.RandomColorJitter', 'brightness': 0.3, 'contrast': 0.4, 'saturation': 0.5, 'hue': 0.08, 'batch_transform': True, 'num_chunks': -1, 'batch_inplace': True}], 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'action_history_encoder_config': {'_target_': 'lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig', 'in_channels': 7, 'out_channels': 32, 'history_length': 6, 'kernel_size': 5, 'downsample_kernel_size': 3, 'downsample_stride': 2, 'downsample_padding': 1}, 'down_dims': [256, 512, 1024], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDIM', 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_train_timesteps': 50, 'num_inference_steps': 10, 'do_mask_loss_for_padding': False, 'input_shapes': {'observation.image': [13, 180, 240], 'context_observation.image': [13, 180, 240], 'observation.state': [8], 'observation.action_history': [7]}}, 'train_cfg': {'_target_': 'utils.TrainConfig', 'lr': 0.0001, 'lr_scheduler': 'cosine', 'lr_warmup_steps': 500, 'adam_betas': [0.95, 0.999], 'adam_eps': 1e-08, 'adam_weight_decay': 1e-06, 'grad_clip_norm': 10, 'offline_steps': 1000000, 'use_amp': True}, 'observation_cfg': {'_target_': 'agent.encoder.VisualFeatureSet', 'use_depth': True, 'use_color': True, 'mask_input_dict': {'_target_': 'agent.encoder.MaskInputDict', 'enable': True, 'representation': 'channels', 'mask_list': ['EE_obj_mask']}, 'crop_input_config': {'_target_': 'agent.encoder.CropInputConfig', 'color_crop_type': None, 'depth_crop_type': None, 'segmask_crop_type': None, 'crop_hw': [144, 144], 'crop_down_offset': 48, 'add_crop_binary_mask': False, 'add_coord_conv_map': False}, 'context_input_config': {'_target_': 'agent.encoder.ContextInputConfig', 'use_color': False, 'use_depth': False, 'mask_input_dict': {'_target_': 'agent.encoder.MaskInputDict', 'enable': False, 'representation': 'channels', 'mask_list': ['EE_obj_mask']}, 'crop_input_config': {'_target_': 'agent.encoder.CropInputConfig', 'color_crop_type': None, 'depth_crop_type': None, 'segmask_crop_type': None, 'crop_hw': [144, 144], 'crop_down_offset': 48, 'add_crop_binary_mask': False, 'add_coord_conv_map': False}}, 'mask_soft_approx_scheduler_config': {'_target_': 'agent.encoder.MaskSoftApproxSchedulerConfig', 'num_steps': 40000, 'initial_value': 10.0, 'final_value': 1000.0, 'interpolation_scheme': 'cosine'}, 'use_contact_map': False, 'use_sdf_maps': False, 'use_normals_maps': False, 'which_objects': 'both', 'grasped_dtc_max_value': 0.2, 'env_dtc_max_value': 0.4, 'grasped_normals_mask_max_dtc_value': 0.2, 'env_normals_mask_max_dtc_value': 0.4, 'clamp_dtc': True, 'max_contact_prob': 0.1, 'mask_normals_within_sdf': True, 'dtc_adaptive_normalization': False, 'adaptive_normals_mask': True, 'max_depth': 2.0, 'image_shape': [13, 180, 240], 'learnable_contact_preprocess_params': True, 'learning_rate': 0.0001, 'weight_decay': 0.0, 'contact_model_name': 'local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9', 'zero_centered': False}}, 'true_action_history': False}}, 'num_train_frames_bc': 50000, 'num_train_frames_drq': 1100000, 'stddev_schedule_drq': 'linear(1.0,0.1,100000)', 'task_name': 'FrankaInsertion-v1', 'num_train_frames_vinn': 25000, 'num_train_frames_diffusion': 1000000, 'num_train_epochs_bc': 5000, 'num_train_epochs_diffusion': 15000, 'validate_every_epochs_bc': 5, 'validate_every_epochs_diffusion': 250, 'validate_diffusion_on_action_loss_every_epochs': 250, 'train_eval_diffusion_on_action_loss_every_epochs': 250, 'check_topk_every_epochs': 5, 'check_topk_every_epochs_diffusion': 250, 'save_snapshot_every_epochs_diffusion': 1500, 'x_limit': [0.2, 0.7], 'y_limit': [-0.4, 0.4], 'z_limit': [-0.05, 0.55], 'home_displacement': [0.55, 0.0, 0.55, 180.0, 0.0, 0.0], 'enable_gripper': True, 'start_with_gripper_open': True, 'offset_mask': [1, 1, 1, 1, 1, 1], 'path_to_depth_extrinsics': '~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy', 'feature_type': '180x240_1_RGB_D_2.0_msk_channels_EE_obj_mask_acthst_hst6_out32_dwnkrnl3_dwnstrd2_dwnpd1', 'save_buffer': True, 'num_eval': 5, 'random_start': False, 'eval_starts': '/home/leonmkim/fish_leon/FISH/eval_starts/frankagym_pixels/FrankaInsertion-v1', 'num_valid_demos': None, 'load_checkpoint': True, 'checkpoint_epoch': 12000, 'load_residual_weight': False, 'checkpoint_root_dir': '/home/leonmkim/fish_leon/FISH', 'checkpoint_weight_dir': '/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1', 'residual_weight': '/home/leonmkim/fish_leon/FISH/weights/frankagym_pixels/FrankaInsertion-v1/weight.pt', 'final_experiment_dir': './exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c'}
+2025-01-07 17:14:04,426 INFO    MainThread:2196057 [wandb_init.py:init():619] starting backend
+2025-01-07 17:14:04,426 INFO    MainThread:2196057 [wandb_init.py:init():623] setting up manager
+2025-01-07 17:14:04,430 INFO    MainThread:2196057 [backend.py:_multiprocessing_setup():105] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-01-07 17:14:04,431 INFO    MainThread:2196057 [wandb_init.py:init():631] backend started and connected
+2025-01-07 17:14:04,443 INFO    MainThread:2196057 [wandb_init.py:init():720] updated telemetry
+2025-01-07 17:14:04,453 INFO    MainThread:2196057 [wandb_init.py:init():753] communicating run to backend with 90.0 second timeout
+2025-01-07 17:14:04,702 INFO    MainThread:2196057 [wandb_run.py:_on_init():2435] communicating current version
+2025-01-07 17:14:04,770 INFO    MainThread:2196057 [wandb_run.py:_on_init():2444] got version response upgrade_message: "wandb version 0.19.2 is available!  To upgrade, please run:\n $ pip install wandb --upgrade"
+
+2025-01-07 17:14:04,770 INFO    MainThread:2196057 [wandb_init.py:init():804] starting run threads in backend
+2025-01-07 17:14:05,123 INFO    MainThread:2196057 [wandb_run.py:_console_start():2413] atexit reg
+2025-01-07 17:14:05,123 INFO    MainThread:2196057 [wandb_run.py:_redirect():2255] redirect: wrap_raw
+2025-01-07 17:14:05,123 INFO    MainThread:2196057 [wandb_run.py:_redirect():2320] Wrapping output streams.
+2025-01-07 17:14:05,124 INFO    MainThread:2196057 [wandb_run.py:_redirect():2345] Redirects installed.
+2025-01-07 17:14:05,125 INFO    MainThread:2196057 [wandb_init.py:init():847] run started, returning control to user process
+2025-01-07 17:14:05,125 INFO    MainThread:2196057 [wandb_run.py:_tensorboard_callback():1544] tensorboard callback: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/tb, True
+2025-01-07 17:14:07,444 INFO    MainThread:2196057 [wandb_run.py:_config_callback():1382] config_cb None None {'grasped_obj_name': 'hbm', 'left_book_slot': 'twodim'}
+2025-01-07 17:18:08,590 WARNING MsgRouterThr:2196057 [router.py:message_loop():77] message_loop has been closed

6qq3p71c/wandb/run-20250107_171404-6qq3p71c/files/code/FISH/eval_robot.py

@@ -0,0 +1,605 @@
+#%%
+import warnings
+import os
+
+os.environ['MKL_SERVICE_FORCE_INTEL'] = '1'
+os.environ['MUJOCO_GL'] = 'egl'
+from pathlib import Path
+#%%
+import hydra
+import numpy as np
+import torch
+
+import utils
+from utils import get_feature_dirname_from_configs
+
+from video import VideoRecorder
+import pickle
+import time
+import threading
+import shutil
+from logger import Logger
+
+import wandb 
+from omegaconf import OmegaConf, open_dict
+
+from replay_buffer_robot import RosbagEvalReplayBufferStorage
+from lerobot.common.utils.utils import _relative_path_between
+
+torch.backends.cudnn.benchmark = True
+warnings.filterwarnings('ignore', category=DeprecationWarning)
+
+# import specs for replay buffer
+from dm_env import specs
+
+import sys, signal
+import yaml
+
+import binomial_cis as bc
+
+# get path of current file
+current_path = os.path.dirname(os.path.realpath(__file__))
+sys.path.append(os.path.join(current_path, os.pardir))
+# from contact_estimation.src.utils.viz_utils import normalized_surface_normal_to_rgb, depth_map_to_im, grasped_env_dtc_map_to_im, contact_prob_map_to_im, desaturate_color_image, masked_overlay_im_list
+
+def make_agent(obs_spec, action_spec, cfg):
+	cfg.obs_shape = obs_spec['pixels'].shape
+	dataset_statistics = None # this will be loaded from the checkpoint
+	try:
+		cfg.action_shape = action_spec.shape
+	except:
+		pass
+	return hydra.utils.instantiate(cfg, dataset_statistics)
+
+class Workspace:
+	def __init__(self, cfg):
+		self.work_dir = Path.cwd()
+		print(f'workspace: {self.work_dir}')
+		
+		signal.signal(signal.SIGINT, self.signal_handler)
+		
+		self.cfg = cfg
+		self.loading_uncompiled_checkpoint_with_compile = False
+		self.loading_compiled_checkpoint_with_no_compile = False
+
+		snapshot_path = Path(self.cfg.checkpoint_weight_dir) / f'snapshot_{self.cfg.checkpoint_epoch}.pt' 
+		self.load_checkpoint_conf(snapshot_path=snapshot_path)
+
+		# load config for action trajectories
+		utils.set_seed_everywhere(self.cfg.seed)
+		self.device = torch.device(self.cfg.device)
+		self.setup()
+
+		# self.agent = make_agent(self.eval_env.observation_spec(),
+		# 						self.eval_env.action_spec(), self.cfg.agent)
+		self.timer = utils.Timer()
+		# self._global_step = 0
+		self._global_episode = 0
+		self._global_epoch = 0
+		self.num_episode_successes = 0
+
+		self.alpha_range = [.01, .025, .05, .1]
+
+		# Need to convert hydra config to primitive container for wandb https://docs.wandb.ai/guides/integrations/hydra
+		with open_dict(self.cfg):
+			self.cfg.feature_type = get_feature_dirname_from_configs(
+				hydra.utils.instantiate(self.cfg.agent.config.observation_cfg), 
+				self.cfg.agent.config.policy_cfg.input_shapes,
+				hydra.utils.instantiate(self.cfg.agent.config.policy_cfg.action_history_encoder_config) if 'observation.action_history' in self.cfg.agent.config.policy_cfg.input_shapes else None,
+			)
+
+		wandb_config = OmegaConf.to_container(
+			self.cfg, resolve=True, throw_on_missing=True
+		)
+		# must be called before any tf summary writer is created
+		if self.cfg.use_wandb:
+			# get the run id from the final_experiment_dir directory
+			run_id = os.path.basename(os.path.normpath(self.cfg.final_experiment_dir))
+			wandb.init(project='extrinsic_contact_downstream', entity='serialexperimentsleon', job_type='eval', sync_tensorboard=self.cfg.use_tb, config=wandb_config, id=run_id)
+
+		self.logger = Logger(self.work_dir, use_tb=self.cfg.use_tb, use_wandb=self.cfg.use_wandb)
+
+		# if not self.loading_uncompiled_checkpoint_with_compile and self.cfg.agent.config.compile:
+		# 	self.agent.compile_modules()
+			
+		# self.load_checkpoint(snapshot_path=snapshot_path)
+
+		# if self.loading_uncompiled_checkpoint_with_compile: # need to call compile after loading the checkpoint
+		# 	self.agent.compile_modules()
+
+		print(f"loaded agent with feature_type: {self.cfg.feature_type}")
+
+	def check_for_key_press(self):
+		while self.continue_keypress_thread:
+			inp = input("Press 'r' to restart current episode, 'n' to stop current episode and skip to next, 'q' to break entire eval\n")
+			if inp == 'n':
+				self.preempt_episode = True
+				print("preempting episode")
+			elif inp in ['', '0', '1']: # enter key
+				if inp in ['0', '1']:
+					self.num_episode_successes += int(inp)
+				self.proceed_after_env_reset_event.set()
+				print("proceeding to start episode!")
+			elif inp == 'q':
+				self.proceed_after_env_reset_event.set()
+				self.preempt_episode = True
+				self.exit_eval = True
+				self.continue_keypress_thread = False # will stop the keypress thread
+				print("quitting eval")
+				break
+			elif inp == 'r':
+				print('restarting episode')
+				self.preempt_episode = True
+				self.restart_episode = True
+			else:
+				print("Invalid key press, try again")
+		
+		# self.keypress_input_thread.join() # wait for the keypress thread to finish
+
+	def signal_handler(self, signal, frame):
+		print("\nprogram exiting gracefully")
+		self.proceed_after_env_reset_event.set()
+		self.preempt_episode = True
+		self.exit_eval = True
+		self.continue_keypress_thread = False # will stop the keypress thread
+		self.keypress_input_thread.join() # wait for the keypress thread to finish
+		video_filepath = self.video_recorder.save()
+		# get the video file and convert to video tensor to log 
+		self.logger.log_video('eval/video', video_filepath, self.global_step)
+		wandb.finish()
+		sys.exit(0)
+		
+	def setup(self):
+		# create envs
+		self.eval_env = hydra.utils.call(self.cfg.suite.task_make_fn)
+		# expert_demo_config_path = os.path.join(os.path.dirname(self.cfg.expert_dataset), 'demo_config.yaml')
+		# self.expert_demo_config = yaml.load(open(expert_demo_config_path, 'r'), Loader=yaml.FullLoader)
+		# self.eval_env._env.action_trans_norm = expert_demo_config['max_translation_action_norm']
+		# self.eval_env._env.action_rot_norm = expert_demo_config['max_rotation_action_norm']
+		# self.eval_env._env.action_period = expert_demo_config['sample_period']
+		# print(f"setting max_translation_action_norm to {expert_demo_config['max_translation_action_norm']} and sample_period to {expert_demo_config['sample_period']}")
+		# print(f"setting max_rotation_action_norm to {expert_demo_config['max_rotation_action_norm']}")
+
+		# self.eval_env.set_demo_params(self.cfg.expert_dataset)
+
+		# Turn off random start
+		self.eval_env.random_start = False
+
+		# create replay buffer
+		# data_specs = [
+		# 	{
+		# 		'observation': self.eval_env.observation_spec(),
+		# 	},
+		# 	# self.eval_env.observation_spec()['features'],
+		# 	self.eval_env.action_spec(),
+		# 	specs.Array(self.eval_env.action_spec().shape, self.eval_env.action_spec().dtype, 'vinn_action'), 
+		# 	specs.Array((1, ), np.float32, 'reward'),
+		# 	specs.Array((1, ), np.float32, 'discount'),
+		# ]
+
+		# self.eval_replay_storage = ZarrEvalReplayBufferStorage(data_specs, self.work_dir / 'eval_buffer', debug_timestamps=self.cfg.debug_timestamps, save_buffer=self.cfg.save_buffer, debug_info_data_specs=self.eval_env.debug_info_data_specs, camera_info_dict=self.eval_env.get_camera_info_dict())
+		self.eval_replay_storage = RosbagEvalReplayBufferStorage(self.work_dir)
+
+		self.video_recorder = VideoRecorder(
+			self.work_dir if self.cfg.save_video else None,
+			ros_enabled=True,
+			fps=self.cfg.agent.config.policy_frequency,
+			)
+		
+		print('workspace setup complete')
+		
+	@property
+	def global_step(self):
+		# return self._global_step
+		return self.eval_env.get_global_step()
+
+	@property
+	def global_episode(self):
+		return self._global_episode
+
+	@property
+	def global_frame(self):
+		return self.global_step * self.cfg.action_repeat
+
+	@property
+	def global_epoch(self):
+		return self._global_epoch
+	
+	def reset(self, eval_idx):
+		if not self.eval_env.enable_arm:
+			return np.array([0,0,0], dtype=np.float32)
+		self.eval_env.arm_refresh(reset=False)
+		# Set start position
+		try:
+			self.eval_env.set_position(self.start_pos[eval_idx])
+		except:
+			self.eval_env.arm.set_position(self.start_pos[eval_idx])
+			if self.eval_env.arm.keep_gripper_closed:
+				self.eval_env.arm.close_gripper_fully()
+			else:
+				self.eval_env.arm.open_gripper_fully()
+		time.sleep(0.1)
+		time_step = self.eval_env.step(np.zeros(self.eval_env.action_spec().shape[0], dtype=np.float32),
+									   np.zeros(self.eval_env.action_spec().shape[0], dtype=np.float32))	
+		return time_step
+
+	def eval(self):
+		# before evals start, prompt user for name of grasped object and the left book of the slot location
+		grasped_obj_name = input("Enter the name of the grasped object: ")
+		left_book_slot = input("Enter the left book slot location: ")
+		# update wandb config
+		if self.cfg.use_wandb:
+			wandb.config.update({'grasped_obj_name': grasped_obj_name, 'left_book_slot': left_book_slot})
+
+		self.preempt_episode = False
+		self.exit_eval = False
+		self.restart_episode = False
+
+		self.continue_keypress_thread = True
+		self.proceed_after_env_reset_event = threading.Event()
+		self.keypress_input_thread = threading.Thread(target=self.check_for_key_press)
+		self.keypress_input_thread.start()
+
+		# # Set model to eval mode
+		# self.agent.train(False)
+		
+		eval_until_episode = utils.Until(self.cfg.num_eval)
+
+		self.use_action_history = False
+		# if "dp" in repr(self.agent) and "observation.action_history" in self.cfg.agent.config.policy_cfg.input_shapes:
+		if "observation.action_history" in self.cfg.agent.config.policy_cfg.input_shapes:
+			self.use_action_history = True
+
+		# self.eval_replay_storage._new_eval_step(0)
+
+		# if 'vinn' in repr(self.agent) or 'openloop' in repr(self.agent):
+		# 	with open(self.cfg.expert_dataset, 'rb') as f:
+		# 		if self.cfg.obs_type == 'pixels':
+		# 			self.expert_demo, _, self.expert_action, self.expert_reward = pickle.load(f)
+		# 		elif self.cfg.obs_type == 'features':
+		# 			_, self.expert_demo, self.expert_action, self.expert_reward = pickle.load(f)
+				
+		# 		if self.cfg.action_trajectories:
+		# 			with open(self.cfg.expert_action_trajectories, 'rb') as f:
+		# 				self.expert_action = pickle.load(f)
+
+		# 		if isinstance(self.cfg.train_demo_idxs_list_or_num, int):
+		# 			if self.cfg.train_demo_idxs_list_or_num == -1:
+		# 				self.cfg.train_demo_idxs_list_or_num = len(self.expert_demo)
+		# 			train_demo_idxs_list_or_num = list(range(self.cfg.train_demo_idxs_list_or_num))
+				
+		# 		self.expert_demo = self.expert_demo[train_demo_idxs_list_or_num]
+		# 		self.expert_action = self.expert_action[train_demo_idxs_list_or_num]
+		# 		self.expert_reward = self.expert_reward[train_demo_idxs_list_or_num]
+		# 		# if self.cfg.action_plans:
+		# 		# 	self.expert_action_plans = self.expert_action_plans[self.cfg.train_demo_idxs_list_or_num]
+		# 		# self.expert_demo = self.expert_demo[:self.cfg.num_demos]
+		# 		# self.expert_action = self.expert_action[:self.cfg.num_demos]
+		# 		# self.expert_reward = self.expert_reward[:self.cfg.num_demos]
+
+		# 		self.expert_demo = np.concatenate(self.expert_demo, axis=0)
+		# 		self.expert_rgb_obs = np.ascontiguousarray(np.transpose(self.expert_demo, (0,2,3,1))[:, :,:,:3].astype(np.uint8))
+		# 		self.expert_action = np.concatenate(self.expert_action, axis=0)
+				
+		# 		self.agent.save_representations(self.expert_demo, self.expert_action, 128, config=self.expert_demo_config)
+		
+		# Get start points
+		if self.cfg.random_start:
+			eval_starts = Path(self.cfg.eval_starts) / 'starts.pkl'
+			if eval_starts.exists():
+				with eval_starts.open('rb') as f:
+					self.start_pos = pickle.load(f)
+			else:
+				eval_starts = Path(self.cfg.eval_starts)
+				eval_starts.mkdir(parents=True, exist_ok=True)
+				
+				# Generate start points
+				self.start_pos = []
+				try:
+					for _ in range(self.cfg.num_eval):
+						self.start_pos.append(self.eval_env.get_random_pos())
+				except:
+					for _ in range(self.cfg.num_eval):
+						self.start_pos.append(self.eval_env.arm.get_random_pos())
+
+				# Save start points for the task
+				eval_starts = eval_starts / 'starts.pkl'
+				with eval_starts.open('wb') as f:
+					pickle.dump(self.start_pos, f)
+
+		time_step = self.eval_env.reset()
+		# replay_thread = None
+		while eval_until_episode(self.global_episode) and not self.exit_eval:
+			# self.video_recorder.init(self.eval_env, video_filename=f'{self.global_episode}_eval.mp4')
+			print(f"Starting episode {self.global_episode}")
+			time_step = self.eval_env.reset() #Leon: need to call reset twice in case objects are trapped
+			self.video_recorder.init(self.eval_env, video_filename=f'{self.global_episode}_eval.mp4')
+			# x = input("Press Enter to continue... after reseting env")
+			print("Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success")
+			self.proceed_after_env_reset_event.clear() # clear the event flag
+			self.proceed_after_env_reset_event.wait() # blocking wait for the event flag to be set
+			if self.global_episode > 0:
+				self.logger.log_metrics({'num_success': self.num_episode_successes}, self.global_step, 'eval', episode=self.global_episode)
+				self.logger.log_metrics({'success_rate': self.num_episode_successes/self.global_episode}, self.global_step, 'eval', episode=self.global_episode)
+
+				# log confidence intervals for success rate
+				k = self.num_episode_successes # number of successes
+				n = self.global_episode # number of trials
+
+				table_columns = []
+				table_data = []
+				for alpha in self.alpha_range:
+					lb = bc.binom_ci(k, n, alpha, 'lb')
+					ub = bc.binom_ci(k, n, alpha, 'ub')
+
+					self.logger.log_metrics({f'success_rate_lb_{alpha}': lb}, self.global_step, 'eval', episode=self.global_episode)
+					self.logger.log_metrics({f'success_rate_ub_{alpha}': ub}, self.global_step, 'eval', episode=self.global_episode)
+
+			time_step = self.eval_env.reset()
+			# debug_info_dict = self.eval_env.debug_info_dict
+			# if replay_thread is not None:
+			# 	# wait for the last replay thread to finish
+			# 	replay_thread.join()
+
+			# self.eval_replay_storage.add(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict)
+			# replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict))
+			# replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step, debug_info_dict))
+
+			# replay_thread.start()
+			if self.cfg.random_start:
+				time_step = self.reset(self.global_episode)
+				time.sleep(2) #5)
+			# if 'vinn' in repr(self.agent):
+			# 	self.agent.reset()
+			# 	# self.agent.buffer.reset()
+			# 	# if self.cfg.open_loop:
+			# 	# 	self.agent.current_step = 0
+			# if 'openloop' in repr(self.agent):
+			# 	self.agent.curr_step = 0
+			# at start of each episode, provide zero action for policies that use action history
+			# shape should be (T_o, T_a, action_dim)
+
+			# while not time_step.last() and not self.preempt_episode:
+			self.video_recorder.ros_start_recording()
+			self.eval_replay_storage.start_episode()
+			self.eval_env.start_policy_timer()
+			while not self.eval_env.episode_done() and not self.preempt_episode:
+				# with torch.no_grad(), utils.eval_mode(self.agent):
+				# 	# if self.cfg.agent.provide_topk:
+				# 	# 	action, vinn_action, topk = self.agent.act(
+				# 	# 		time_step.observation['pixels'],
+				# 	# 		self.global_step,
+				# 	# 		eval_mode=True)
+				# 	# elif self.cfg.agent.provide_obs:
+				# 	# 	action, vinn_action, obs = self.agent.act(
+				# 	# 		time_step.observation['pixels'],
+				# 	# 		self.global_step,
+				# 	# 		eval_mode=True)
+				# 	# else:
+				# 	action, vinn_action = self.agent.act(
+				# 		time_step.observation,
+				# 		self.global_step,
+				# 		eval_mode=True,
+				# 		obs_timestamp=time_step.observation['timestamp'],
+				# 		obs_seq=time_step.observation['seq'],
+				# 		action_history=action_history,
+				# 		action_history_start_timestamp=action_history_start_timestamp,
+				# 		)
+					# DONT WAIT FOR POLICY TO GET AN ACTION 
+					# we dont want to slow down grabbing obs and passing to sam/contact features
+
+				self.eval_env.run_policy_threads() # this just does a rospy sleep
+					
+				# if self.use_action_history:
+				# 	action_history_start_timestamp = time_step.observation['timestamp']
+				# 	# action_history = action[:self.cfg.agent.config.policy_cfg.action_history_encoder_config.history_length, ...]		
+				# 	# add n_obs_steps dimension to action_history, for now we assume n_obs_steps = 1
+				# 	# TODO: handle n_obs_steps > 1
+				# 	action_history = action[np.newaxis, ...]
+
+				# time_step = self.eval_env.step(action, vinn_action) # obs, reward after action has been taken
+				# debug_info_dict = self.eval_env.debug_info_dict
+				
+				# time_step = self.eval_env.ros_step()
+				
+				# replay_thread.join()
+
+				# time how long it takes to execute the step
+				# time_before_add = time.perf_counter()
+				# self.eval_replay_storage.add(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict)
+				# use thread to call the add function in a separate thread
+				# replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step._replace(observation=time_step.observation[self.cfg.obs_type]), debug_info_dict))
+
+				# replay_thread = threading.Thread(target=self.eval_replay_storage.add, args=(time_step, debug_info_dict))
+				# replay_thread.start()
+				
+				# print(f"Time to add to replay buffer: {time.perf_counter() - time_before_add}")
+
+				# self.video_recorder.record(self.eval_env)
+				# self._global_step += 1
+			
+			self.eval_env.stop_policy_timer()
+			
+			if self.restart_episode:
+				# means we should delete the current episode and start again
+				self.restart_episode = False
+				self.eval_replay_storage.reset_current_episode()
+				self.video_recorder.reset_current_episode()
+
+			else:
+				self.eval_replay_storage.store_current_episode()
+				video_filepath = self.video_recorder.save()
+				self.logger.log_video(f"eval/{video_filepath.name.rstrip('.mp4')}", video_filepath, self.global_step)
+				self._global_episode += 1
+			
+			self.preempt_episode = False # reset preempt_episode flag
+		
+		# self.video_recorder.save(f'{episode}_eval.mp4')
+		# get the video file and convert to video tensor to log 
+
+		self.eval_env.reset()
+		
+		print("Evaluation finished. To wrap up, rate prev episode, press 0 for failure and 1 for success")
+		self.proceed_after_env_reset_event.clear() # clear the event flag
+		self.proceed_after_env_reset_event.wait() # blocking wait for the event flag to be set
+		if self.global_episode > 0:
+			# self.logger.log_metrics({'num_success': self.num_episode_successes}, self.global_step, 'eval', episode=self.global_episode)
+			self.logger.log_metrics({'num_success': self.num_episode_successes}, self.global_step, 'eval', episode=self.global_episode)
+			self.logger.log_metrics({'success_rate': self.num_episode_successes/self.global_episode}, self.global_step, 'eval', episode=self.global_episode)
+			
+			# log confidence intervals for success rate
+			k = self.num_episode_successes # number of successes
+			n = self.global_episode # number of trials
+
+			table_columns = ['success_rate']
+			table_data = [self.num_episode_successes/self.global_episode]
+			for alpha in self.alpha_range:
+				lb = bc.binom_ci(k, n, alpha, 'lb')
+				ub = bc.binom_ci(k, n, alpha, 'ub')
+
+				self.logger.log_metrics({f'success_rate_lb_{alpha}': lb}, self.global_step, 'eval', episode=self.global_episode)
+				self.logger.log_metrics({f'success_rate_ub_{alpha}': ub}, self.global_step, 'eval', episode=self.global_episode)
+
+				table_columns.extend([f'success_rate_lb_{alpha}', f'success_rate_ub_{alpha}'])
+				table_data.extend([lb, ub])
+
+			table_data = [table_data]
+
+			# seperately log as a table
+			wandb.log({
+				"eval/success_rate_ci": wandb.Table(data=table_data, columns=table_columns)
+			})
+
+			# also accumulate eval metrics across previous eval runs 
+			# TODO: change wandb init to resume from an existing run!!!
+			run_filter={
+				"jobType": "eval",
+				"config.wandb_run_id": self.cfg.wandb_run_id, 
+				"summary_metrics.episode": {"$gte": 5},
+				"config.checkpoint_epoch": self.cfg.checkpoint_epoch,
+				"state": "finished",
+				# "config.grasped_obj_name": grasped_obj_name,
+				# "config.left_book_slot": left_book_slot,
+			}
+
+			api = wandb.Api()
+			filtered_runs = api.runs("serialexperimentsleon/extrinsic_contact_downstream", filters=run_filter)
+			total_num_successes = self.num_episode_successes
+			total_num_episodes = self.global_episode
+			list_of_historical_run_ids = []
+			if len(filtered_runs) > 0:
+				for filtered_run in filtered_runs:
+					total_num_successes += filtered_run.summary_metrics['eval/num_success']
+					# total_num_episodes += filtered_run.summary_metrics['episode']
+					total_num_episodes += filtered_run.config['num_eval']
+					list_of_historical_run_ids.append(filtered_run.id)
+
+			wandb.summary['total_num_successes'] = total_num_successes
+			wandb.summary['total_num_episodes'] = total_num_episodes
+			wandb.summary['total_success_rate'] = total_num_successes/total_num_episodes
+				
+			# log the accumulated metrics as a table
+			total_table_columns = ['total_num_successes', 'total_num_episodes', 'total_success_rate']
+			total_table_data = [total_num_successes, total_num_episodes, total_num_successes/total_num_episodes]
+			self.logger.log_metrics({'total_success_rate': total_num_successes/total_num_episodes}, self.global_step, 'eval', episode=total_num_episodes)
+			
+			for alpha in self.alpha_range:
+				lb = bc.binom_ci(total_num_successes, total_num_episodes, alpha, 'lb')
+				ub = bc.binom_ci(total_num_successes, total_num_episodes, alpha, 'ub')
+				total_table_columns.extend([f'total_success_rate_lb_{alpha}', f'total_success_rate_ub_{alpha}'])
+				total_table_data.extend([lb, ub])
+				wandb.summary[f'total_success_rate_lb_{alpha}'] = lb
+				wandb.summary[f'total_success_rate_ub_{alpha}'] = ub
+
+				self.logger.log_metrics({f'total_success_rate_lb_{alpha}': lb}, self.global_step, 'eval', episode=total_num_episodes)
+				self.logger.log_metrics({f'total_success_rate_ub_{alpha}': ub}, self.global_step, 'eval', episode=total_num_episodes)
+
+			total_table_data = [total_table_data]
+			wandb.log({
+				'eval/total_success_rate_ci': wandb.Table(data=total_table_data, columns=total_table_columns)
+			})
+
+		self.continue_keypress_thread = False # will stop the keypress thread
+		self.keypress_input_thread.join() # wait for the keypress thread to finish
+
+	def load_checkpoint_conf(self, snapshot_path):
+		config_path = snapshot_path.parent / 'config.yaml'
+		if not config_path.exists():
+			raise FileNotFoundError(f'No snapshot conf found at {config_path}')
+		else:
+			# load the omegaconf config
+			hydra.core.global_hydra.GlobalHydra.instance().clear()
+			hydra.initialize(
+				str(_relative_path_between(Path(config_path).absolute().parent, Path(__file__).absolute().parent)),
+			)
+			cfg = hydra.compose(Path(config_path).stem)
+			from deepdiff import DeepDiff
+			from omegaconf import open_dict
+			diff = DeepDiff(OmegaConf.to_container(cfg), OmegaConf.to_container(self.cfg)) # old, new
+			# import re
+			overwriteable_keys = [f"root{overwritable_key}" for overwritable_key in ["['use_wandb']", "['path_to_depth_extrinsics']", "['eval']", "['root_dir']", "['wandb_notes']", "['agent']['config']['train_cfg']['use_amp']", "['agent']['config']['compile']", "['agent']['config']['policy_cfg']['num_inference_steps']"]]
+			if "values_changed" in diff:
+				# top_k_checkpoints, wandb_notes, agent.config.train_cfg.use_amp, save_snapshot_every_epochs_diffusion, check_topk_every_epochs_diffusion, validate_diffusion_on_action_loss_every_epochs, train_eval_diffusion_on_action_loss_every_epochs, validate_every_epochs_diffusion
+				# for keys above, overwrite the old config with the new config
+				for k, v in diff['values_changed'].items():
+					# replace any keys that are under "root['suite']"
+					if k in overwriteable_keys or k.startswith("root['suite']"):
+						print(f"Found changed key {k} with value {v}. Overwriting old checkpoint config")
+						if k == "root['agent']['config']['compile']":
+							if diff['values_changed'][k]['new_value']:
+								self.loading_uncompiled_checkpoint_with_compile = True
+							elif not diff['values_changed'][k]['new_value']:
+								# raise ValueError("Cannot load a compiled checkpoint without compile")
+								self.loading_compiled_checkpoint_with_no_compile = True
+						exec(f"{k.replace('root[', 'cfg[')} = {k.replace('root[', 'self.cfg[')}")
+			# for any new values, update the old checkpoint config
+			if "dictionary_item_added" in diff:
+				for new_key in diff['dictionary_item_added']: # this is a list
+					# if new_key == "root['suite']['task_make_fn']['observation_cfg']":
+					if new_key == "root['suite']['task_make_fn']['agent_policy_cfg']":
+						# pass the agents observation_cfg to the suite task_make_fn
+						with open_dict(cfg): # to allow addition of non-existing keys
+							# cfg.suite.task_make_fn.observation_cfg = cfg.agent.config.observation_cfg
+							cfg.suite.task_make_fn.agent_policy_cfg = cfg.agent.config
+						continue
+					elif "['agent']['config']['policy_cfg']['input_shapes']" in new_key:
+						# skip adding the new key if it is the input_shapes of the policy_cfg
+						continue
+					else:
+						print(f"Found new key {new_key} with value {eval(new_key.replace('root[', 'self.cfg['))}. Adding to checkpoint config")
+					# eval(new_key.replace('root', 'cfg')) = eval(new_key.replace('root', 'self.cfg'))
+					if new_key == "root['agent']['config']['compile']":
+						if self.cfg.agent.config.compile:
+							self.loading_uncompiled_checkpoint_with_compile = True
+					
+					with open_dict(cfg):
+						exec(f"{new_key.replace('root[', 'cfg[')}={new_key.replace('root[', 'self.cfg[')}")
+			self.cfg = cfg
+
+	def load_checkpoint(self, snapshot_path, bc=False):
+		print(f'resuming {repr(self.agent)}: {snapshot_path}')
+		with snapshot_path.open('rb') as f:
+			payload = torch.load(f)
+		agent_payload = {}
+		for k, v in payload.items():
+			if k not in self.__dict__:
+				agent_payload[k] = v
+			elif k == '_global_epoch':
+				self._global_epoch = v
+				print(f'loaded epoch: {v}')
+				if self.cfg.use_wandb:
+					# add to config of wandb
+					wandb.config.update({'epoch': v})
+
+		# self.agent.load_snapshot_eval(agent_payload, bc)
+
+@hydra.main(config_path='cfgs', config_name='config_eval')
+def main(cfg):
+	from eval_robot import Workspace as W
+	root_dir = Path.cwd()
+	workspace = W(cfg)
+
+	workspace.eval()
+
+if __name__ == '__main__':
+	main()

6qq3p71c/wandb/run-20250107_171404-6qq3p71c/files/config.yaml

@@ -0,0 +1,895 @@
+wandb_version: 1
+
+root_dir:
+  desc: null
+  value: /home/leonmkim/fish_leon
+replay_buffer_size:
+  desc: null
+  value: 150000
+replay_buffer_num_workers:
+  desc: null
+  value: 2
+nstep:
+  desc: null
+  value: 3
+batch_size:
+  desc: null
+  value: 128
+seed:
+  desc: null
+  value: 1
+dataset_shuffle_seed:
+  desc: null
+  value: 0
+device:
+  desc: null
+  value: cuda
+save_video:
+  desc: null
+  value: true
+save_train_video:
+  desc: null
+  value: true
+use_tb:
+  desc: null
+  value: true
+use_wandb:
+  desc: null
+  value: true
+wandb_run_id:
+  desc: null
+  value: '1009_1'
+wandb_notes:
+  desc: null
+  value: 1009_1_restarted_3
+eval:
+  desc: null
+  value: true
+true_action_history:
+  desc: null
+  value: false
+train_pad_after:
+  desc: null
+  value: 4
+process_contact_features:
+  desc: null
+  value: true
+obs_type:
+  desc: null
+  value: pixels
+use_color:
+  desc: null
+  value: true
+use_depth:
+  desc: null
+  value: true
+use_masks:
+  desc: null
+  value: true
+mask_list:
+  desc: null
+  value:
+  - EE_obj_mask
+mask_representation:
+  desc: null
+  value: channels
+crop_hw:
+  desc: null
+  value:
+  - 144
+  - 144
+crop_down_offset:
+  desc: null
+  value: 48
+color_crop_type:
+  desc: null
+  value: null
+depth_crop_type:
+  desc: null
+  value: null
+segmask_crop_type:
+  desc: null
+  value: null
+add_crop_binary_mask:
+  desc: null
+  value: false
+add_coord_conv_map:
+  desc: null
+  value: false
+use_context_color:
+  desc: null
+  value: false
+use_context_depth:
+  desc: null
+  value: false
+use_context_segmask:
+  desc: null
+  value: false
+context_color_crop_type:
+  desc: null
+  value: null
+context_depth_crop_type:
+  desc: null
+  value: null
+context_segmask_crop_type:
+  desc: null
+  value: null
+context_add_crop_binary_mask:
+  desc: null
+  value: false
+context_add_coord_conv_map:
+  desc: null
+  value: false
+use_contact_map:
+  desc: null
+  value: false
+use_sdf_maps:
+  desc: null
+  value: false
+use_normals_maps:
+  desc: null
+  value: false
+which_objects:
+  desc: null
+  value: both
+max_contact_prob:
+  desc: null
+  value: 0.1
+max_depth:
+  desc: null
+  value: 2.0
+grasped_dtc_max_value:
+  desc: null
+  value: 0.2
+env_dtc_max_value:
+  desc: null
+  value: 0.4
+grasped_normals_mask_max_dtc_value:
+  desc: null
+  value: 0.2
+env_normals_mask_max_dtc_value:
+  desc: null
+  value: 0.4
+clamp_dtc:
+  desc: null
+  value: true
+dtc_adaptive_normalization:
+  desc: null
+  value: false
+mask_normals_within_sdf:
+  desc: null
+  value: true
+adaptive_normals_mask:
+  desc: null
+  value: true
+learnable_contact_preprocess_params:
+  desc: null
+  value: true
+contact_model_name:
+  desc: null
+  value: local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9
+contact_estimation_model_ckpt_path:
+  desc: null
+  value: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
+encoder_type:
+  desc: null
+  value: small
+debug_timestamps:
+  desc: null
+  value: false
+open_loop:
+  desc: null
+  value: false
+action_trajectories:
+  desc: null
+  value: true
+stop_after_action:
+  desc: null
+  value: false
+interpolation_frequency:
+  desc: null
+  value: 25
+policy_frequency:
+  desc: null
+  value: 5
+wait_for_new_camera_frames:
+  desc: null
+  value: true
+baseline:
+  desc: null
+  value: false
+train_demo_idxs_list_or_num:
+  desc: null
+  value: -1
+log_train_every_steps:
+  desc: null
+  value: 25
+name_of_expert_demo:
+  desc: null
+  value: 120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
+expert_dataset_dirpath:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
+store_dataset_in_memory:
+  desc: null
+  value: false
+expert_dataset:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demos.zarr
+action_key:
+  desc: null
+  value: action_trajectory_25hz
+semantic_demo_grouping_name:
+  desc: null
+  value: semantic_demo_grouping.yaml
+semantic_demo_grouping:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/semantic_demo_grouping.yaml
+include_groups_list:
+  desc: null
+  value: all
+expert_dataset_config:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demo_config.yaml
+name_of_valid_demo:
+  desc: null
+  value: 120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
+valid_dataset_dir:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demos.zarr
+valid_demo_idxs_list_or_num:
+  desc: null
+  value: null
+val_num_groups:
+  desc: null
+  value: 5
+load_bc:
+  desc: null
+  value: true
+checkpoint_epoch_list:
+  desc: null
+  value:
+  - 99
+  - 199
+  - 299
+  - 399
+  - 499
+  - 599
+  - 699
+  - 799
+  - 899
+  - 999
+  - 1249
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+  - 1749
+  - 1999
+  - 2999
+  - 3999
+  - 4999
+  - 5999
+  - 6999
+  - 7999
+  - 8999
+  - 9999
+snapshot_root_dir:
+  desc: null
+  value: /mnt/grasp_high_usage/leonmkim/contact_estimation/FISH
+save_snapshot:
+  desc: null
+  value: true
+save_last_snapshot:
+  desc: null
+  value: true
+save_snapshot_when_done:
+  desc: null
+  value: true
+top_k_checkpoints:
+  desc: null
+  value: 5
+save_snapshot_link_to_weights_dir:
+  desc: null
+  value: deprecated
+bc_regularize:
+  desc: null
+  value: false
+bc_weight_type:
+  desc: null
+  value: qfilter
+experiment_dir:
+  desc: null
+  value: ./exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1
+agent:
+  desc: null
+  value:
+    _target_: agent.diffusion_policy.DiffusionPolicyAgent
+    name: diffusion_policy
+    load_checkpoint: true
+    device: cuda
+    n_obs_steps: 1
+    suite_name: frankagym
+    obs_type: pixels
+    enable_arm: true
+    enable_camera: true
+    use_tb: true
+    desired_image_shape:
+    - 13
+    - 180
+    - 240
+    orig_cam_shape:
+    - 3
+    - 240
+    - 320
+    config:
+      _target_: agent.diffusion_policy.DiffusionPolicyAgentConfig
+      compile: false
+      device: cuda
+      cam_resize_shape:
+      - 13
+      - 180
+      - 240
+      orig_cam_shape:
+      - 3
+      - 240
+      - 320
+      policy_frequency: 5
+      interpolation_frequency: 25
+      policy_cfg:
+        _target_: lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig
+        n_obs_steps: 1
+        horizon: 36
+        n_action_steps: 36
+        output_shapes:
+          action:
+          - 7
+        input_normalization_modes:
+          observation.image: mean_std
+          observation.state: min_max
+          observation.action_history: min_max
+        output_normalization_modes:
+          action: min_max
+        vision_backbone: resnet18
+        pretrained_backbone_weights: null
+        transforms:
+        - _target_: torchaug.transforms.RandomAffine
+          degrees:
+          - -5
+          - 5
+          translate:
+          - 0.05
+          - 0.05
+          batch_transform: true
+          num_chunks: -1
+          batch_inplace: true
+        - _target_: torchaug.transforms.RandomColorJitter
+          brightness: 0.3
+          contrast: 0.4
+          saturation: 0.5
+          hue: 0.08
+          batch_transform: true
+          num_chunks: -1
+          batch_inplace: true
+        use_group_norm: true
+        spatial_softmax_num_keypoints: 32
+        action_history_encoder_config:
+          _target_: lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig
+          in_channels: 7
+          out_channels: 32
+          history_length: 6
+          kernel_size: 5
+          downsample_kernel_size: 3
+          downsample_stride: 2
+          downsample_padding: 1
+        down_dims:
+        - 256
+        - 512
+        - 1024
+        kernel_size: 5
+        n_groups: 8
+        diffusion_step_embed_dim: 128
+        use_film_scale_modulation: true
+        noise_scheduler_type: DDIM
+        beta_schedule: squaredcos_cap_v2
+        beta_start: 0.0001
+        beta_end: 0.02
+        prediction_type: epsilon
+        clip_sample: true
+        clip_sample_range: 1.0
+        num_train_timesteps: 50
+        num_inference_steps: 10
+        do_mask_loss_for_padding: false
+        input_shapes:
+          observation.image:
+          - 13
+          - 180
+          - 240
+          context_observation.image:
+          - 13
+          - 180
+          - 240
+          observation.state:
+          - 8
+          observation.action_history:
+          - 7
+      train_cfg:
+        _target_: utils.TrainConfig
+        lr: 0.0001
+        lr_scheduler: cosine
+        lr_warmup_steps: 500
+        adam_betas:
+        - 0.95
+        - 0.999
+        adam_eps: 1.0e-08
+        adam_weight_decay: 1.0e-06
+        grad_clip_norm: 10
+        offline_steps: 1000000
+        use_amp: true
+      observation_cfg:
+        _target_: agent.encoder.VisualFeatureSet
+        use_depth: true
+        use_color: true
+        mask_input_dict:
+          _target_: agent.encoder.MaskInputDict
+          enable: true
+          representation: channels
+          mask_list:
+          - EE_obj_mask
+        crop_input_config:
+          _target_: agent.encoder.CropInputConfig
+          color_crop_type: null
+          depth_crop_type: null
+          segmask_crop_type: null
+          crop_hw:
+          - 144
+          - 144
+          crop_down_offset: 48
+          add_crop_binary_mask: false
+          add_coord_conv_map: false
+        context_input_config:
+          _target_: agent.encoder.ContextInputConfig
+          use_color: false
+          use_depth: false
+          mask_input_dict:
+            _target_: agent.encoder.MaskInputDict
+            enable: false
+            representation: channels
+            mask_list:
+            - EE_obj_mask
+          crop_input_config:
+            _target_: agent.encoder.CropInputConfig
+            color_crop_type: null
+            depth_crop_type: null
+            segmask_crop_type: null
+            crop_hw:
+            - 144
+            - 144
+            crop_down_offset: 48
+            add_crop_binary_mask: false
+            add_coord_conv_map: false
+        mask_soft_approx_scheduler_config:
+          _target_: agent.encoder.MaskSoftApproxSchedulerConfig
+          num_steps: 40000
+          initial_value: 10.0
+          final_value: 1000.0
+          interpolation_scheme: cosine
+        use_contact_map: false
+        use_sdf_maps: false
+        use_normals_maps: false
+        which_objects: both
+        grasped_dtc_max_value: 0.2
+        env_dtc_max_value: 0.4
+        grasped_normals_mask_max_dtc_value: 0.2
+        env_normals_mask_max_dtc_value: 0.4
+        clamp_dtc: true
+        max_contact_prob: 0.1
+        mask_normals_within_sdf: true
+        dtc_adaptive_normalization: false
+        adaptive_normals_mask: true
+        max_depth: 2.0
+        image_shape:
+        - 13
+        - 180
+        - 240
+        learnable_contact_preprocess_params: true
+        learning_rate: 0.0001
+        weight_decay: 0.0
+        contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9
+        zero_centered: false
+suite:
+  desc: null
+  value:
+    suite: frankagym
+    name: frankagym
+    frame_stack: 1
+    action_repeat: 1
+    discount: 0.99
+    hidden_dim: 1024
+    num_train_frames: 2010
+    num_seed_frames: 260
+    num_train_epochs: 5000
+    validate_every_epochs: 100
+    validate_diffusion_on_action_loss_every_epochs: 500
+    train_eval_diffusion_on_action_loss_every_epochs: 500
+    check_topk_every_epochs: 10
+    save_snapshot_every_epochs: 5000
+    eval_every_frames: 2000
+    num_eval_episodes: 5
+    save_snapshot: true
+    wait_for_user_to_start_episode: true
+    task_make_fn:
+      _target_: suite.frankagym.make
+      name: FrankaInsertion-v1
+      height: 240
+      width: 320
+      frame_stack: 1
+      action_repeat: 1
+      seed: 1
+      enable_arm: true
+      enable_gripper: true
+      start_with_gripper_open: true
+      enable_camera: true
+      path_to_depth_extrinsics: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy
+      contact_estimation_model_ckpt_path: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
+      x_limit:
+      - 0.2
+      - 0.7
+      y_limit:
+      - -0.4
+      - 0.4
+      z_limit:
+      - -0.05
+      - 0.55
+      device: cuda
+      interpolation_frequency: 25
+      policy_frequency: 5
+      debug_timestamps: false
+      stop_after_action: false
+      open_loop: false
+      wait_for_new_camera_frames: true
+      action_key: action_trajectory_25hz
+      action_trajectory_horizon: 36
+      action_trajectories: true
+      path_to_zarr_dataset: /home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demos.zarr
+      agent_policy_cfg:
+        _target_: agent.diffusion_policy.DiffusionPolicyAgentConfig
+        compile: false
+        device: cuda
+        cam_resize_shape:
+        - 13
+        - 180
+        - 240
+        orig_cam_shape:
+        - 3
+        - 240
+        - 320
+        policy_frequency: 5
+        interpolation_frequency: 25
+        policy_cfg:
+          _target_: lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig
+          n_obs_steps: 1
+          horizon: 36
+          n_action_steps: 36
+          output_shapes:
+            action:
+            - 7
+          input_normalization_modes:
+            observation.image: mean_std
+            observation.state: min_max
+            observation.action_history: min_max
+          output_normalization_modes:
+            action: min_max
+          vision_backbone: resnet18
+          pretrained_backbone_weights: null
+          transforms:
+          - _target_: torchaug.transforms.RandomAffine
+            degrees:
+            - -5
+            - 5
+            translate:
+            - 0.05
+            - 0.05
+            batch_transform: true
+            num_chunks: -1
+            batch_inplace: true
+          - _target_: torchaug.transforms.RandomColorJitter
+            brightness: 0.3
+            contrast: 0.4
+            saturation: 0.5
+            hue: 0.08
+            batch_transform: true
+            num_chunks: -1
+            batch_inplace: true
+          use_group_norm: true
+          spatial_softmax_num_keypoints: 32
+          action_history_encoder_config:
+            _target_: lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig
+            in_channels: 7
+            out_channels: 32
+            history_length: 6
+            kernel_size: 5
+            downsample_kernel_size: 3
+            downsample_stride: 2
+            downsample_padding: 1
+          down_dims:
+          - 256
+          - 512
+          - 1024
+          kernel_size: 5
+          n_groups: 8
+          diffusion_step_embed_dim: 128
+          use_film_scale_modulation: true
+          noise_scheduler_type: DDIM
+          beta_schedule: squaredcos_cap_v2
+          beta_start: 0.0001
+          beta_end: 0.02
+          prediction_type: epsilon
+          clip_sample: true
+          clip_sample_range: 1.0
+          num_train_timesteps: 50
+          num_inference_steps: 10
+          do_mask_loss_for_padding: false
+          input_shapes:
+            observation.image:
+            - 13
+            - 180
+            - 240
+            context_observation.image:
+            - 13
+            - 180
+            - 240
+            observation.state:
+            - 8
+            observation.action_history:
+            - 7
+        train_cfg:
+          _target_: utils.TrainConfig
+          lr: 0.0001
+          lr_scheduler: cosine
+          lr_warmup_steps: 500
+          adam_betas:
+          - 0.95
+          - 0.999
+          adam_eps: 1.0e-08
+          adam_weight_decay: 1.0e-06
+          grad_clip_norm: 10
+          offline_steps: 1000000
+          use_amp: true
+        observation_cfg:
+          _target_: agent.encoder.VisualFeatureSet
+          use_depth: true
+          use_color: true
+          mask_input_dict:
+            _target_: agent.encoder.MaskInputDict
+            enable: true
+            representation: channels
+            mask_list:
+            - EE_obj_mask
+          crop_input_config:
+            _target_: agent.encoder.CropInputConfig
+            color_crop_type: null
+            depth_crop_type: null
+            segmask_crop_type: null
+            crop_hw:
+            - 144
+            - 144
+            crop_down_offset: 48
+            add_crop_binary_mask: false
+            add_coord_conv_map: false
+          context_input_config:
+            _target_: agent.encoder.ContextInputConfig
+            use_color: false
+            use_depth: false
+            mask_input_dict:
+              _target_: agent.encoder.MaskInputDict
+              enable: false
+              representation: channels
+              mask_list:
+              - EE_obj_mask
+            crop_input_config:
+              _target_: agent.encoder.CropInputConfig
+              color_crop_type: null
+              depth_crop_type: null
+              segmask_crop_type: null
+              crop_hw:
+              - 144
+              - 144
+              crop_down_offset: 48
+              add_crop_binary_mask: false
+              add_coord_conv_map: false
+          mask_soft_approx_scheduler_config:
+            _target_: agent.encoder.MaskSoftApproxSchedulerConfig
+            num_steps: 40000
+            initial_value: 10.0
+            final_value: 1000.0
+            interpolation_scheme: cosine
+          use_contact_map: false
+          use_sdf_maps: false
+          use_normals_maps: false
+          which_objects: both
+          grasped_dtc_max_value: 0.2
+          env_dtc_max_value: 0.4
+          grasped_normals_mask_max_dtc_value: 0.2
+          env_normals_mask_max_dtc_value: 0.4
+          clamp_dtc: true
+          max_contact_prob: 0.1
+          mask_normals_within_sdf: true
+          dtc_adaptive_normalization: false
+          adaptive_normals_mask: true
+          max_depth: 2.0
+          image_shape:
+          - 13
+          - 180
+          - 240
+          learnable_contact_preprocess_params: true
+          learning_rate: 0.0001
+          weight_decay: 0.0
+          contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9
+          zero_centered: false
+      true_action_history: false
+num_train_frames_bc:
+  desc: null
+  value: 50000
+num_train_frames_drq:
+  desc: null
+  value: 1100000
+stddev_schedule_drq:
+  desc: null
+  value: linear(1.0,0.1,100000)
+task_name:
+  desc: null
+  value: FrankaInsertion-v1
+num_train_frames_vinn:
+  desc: null
+  value: 25000
+num_train_frames_diffusion:
+  desc: null
+  value: 1000000
+num_train_epochs_bc:
+  desc: null
+  value: 5000
+num_train_epochs_diffusion:
+  desc: null
+  value: 15000
+validate_every_epochs_bc:
+  desc: null
+  value: 5
+validate_every_epochs_diffusion:
+  desc: null
+  value: 250
+validate_diffusion_on_action_loss_every_epochs:
+  desc: null
+  value: 250
+train_eval_diffusion_on_action_loss_every_epochs:
+  desc: null
+  value: 250
+check_topk_every_epochs:
+  desc: null
+  value: 5
+check_topk_every_epochs_diffusion:
+  desc: null
+  value: 250
+save_snapshot_every_epochs_diffusion:
+  desc: null
+  value: 1500
+x_limit:
+  desc: null
+  value:
+  - 0.2
+  - 0.7
+y_limit:
+  desc: null
+  value:
+  - -0.4
+  - 0.4
+z_limit:
+  desc: null
+  value:
+  - -0.05
+  - 0.55
+home_displacement:
+  desc: null
+  value:
+  - 0.55
+  - 0.0
+  - 0.55
+  - 180.0
+  - 0.0
+  - 0.0
+enable_gripper:
+  desc: null
+  value: true
+start_with_gripper_open:
+  desc: null
+  value: true
+offset_mask:
+  desc: null
+  value:
+  - 1
+  - 1
+  - 1
+  - 1
+  - 1
+  - 1
+path_to_depth_extrinsics:
+  desc: null
+  value: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy
+feature_type:
+  desc: null
+  value: 180x240_1_RGB_D_2.0_msk_channels_EE_obj_mask_acthst_hst6_out32_dwnkrnl3_dwnstrd2_dwnpd1
+save_buffer:
+  desc: null
+  value: true
+num_eval:
+  desc: null
+  value: 5
+random_start:
+  desc: null
+  value: false
+eval_starts:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/eval_starts/frankagym_pixels/FrankaInsertion-v1
+num_valid_demos:
+  desc: null
+  value: null
+load_checkpoint:
+  desc: null
+  value: true
+checkpoint_epoch:
+  desc: null
+  value: 12000
+load_residual_weight:
+  desc: null
+  value: false
+checkpoint_root_dir:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH
+checkpoint_weight_dir:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1
+residual_weight:
+  desc: null
+  value: /home/leonmkim/fish_leon/FISH/weights/frankagym_pixels/FrankaInsertion-v1/weight.pt
+final_experiment_dir:
+  desc: null
+  value: ./exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c
+_wandb:
+  desc: null
+  value:
+    code_path: code/FISH/eval_robot.py
+    python_version: 3.10.14
+    cli_version: 0.17.5
+    framework: torch
+    is_jupyter_run: false
+    is_kaggle_kernel: false
+    start_time: 1736288044
+    t:
+      1:
+      - 1
+      - 41
+      - 49
+      - 50
+      - 55
+      - 83
+      2:
+      - 1
+      - 41
+      - 49
+      - 50
+      - 55
+      - 83
+      3:
+      - 14
+      - 16
+      - 23
+      - 35
+      - 62
+      4: 3.10.14
+      5: 0.17.5
+      8:
+      - 5
+      13: linux-x86_64
+grasped_obj_name:
+  desc: null
+  value: hbm
+left_book_slot:
+  desc: null
+  value: twodim

6qq3p71c/wandb/run-20250107_171404-6qq3p71c/files/diff.patch

@@ -0,0 +1,20 @@
+diff --git a/FISH/cfgs/config_eval.yaml b/FISH/cfgs/config_eval.yaml
+index a5e82a4..aa5b9b9 100644
+--- a/FISH/cfgs/config_eval.yaml
++++ b/FISH/cfgs/config_eval.yaml
+@@ -134,13 +134,13 @@ load_checkpoint: ${agent.load_checkpoint}
+ # all books, 10/20 demos per book
+ # RGBD+mask+act history
+ # wandb_run_id: '1002_0' 
+-# wandb_run_id: '1009_1' # seed 1
++wandb_run_id: '1009_1' # seed 1
+ # wandb_run_id: '1022_0' # dataset shuffle seed 1
+ 
+ # RGBD+mask+contact(all ftrs)+act history
+ # wandb_run_id: '1003_0'
+ # wandb_run_id: '1013_1' # seed 1
+-wandb_run_id: '1017_0' # dataset shuffle seed 1
++# wandb_run_id: '1017_0' # dataset shuffle seed 1
+ 
+ # all books, 6/20 demos per book
+ # RGBD+mask+act history

6qq3p71c/wandb/run-20250107_171404-6qq3p71c/files/media/table/eval/success_rate_ci_5_d8821c50291f0fbf979f.table.json

@@ -0,0 +1 @@
+{"columns": ["success_rate", "success_rate_lb_0.01", "success_rate_ub_0.01", "success_rate_lb_0.025", "success_rate_ub_0.025", "success_rate_lb_0.05", "success_rate_ub_0.05", "success_rate_lb_0.1", "success_rate_ub_0.1"], "data": [[1.0, 0.7501049041247838, 1, 0.6051223873881857, 1, 0.6927025019737123, 1, 0.6332908421488255, 1]]}

6qq3p71c/wandb/run-20250107_171404-6qq3p71c/files/media/table/eval/total_success_rate_ci_6_32f8ff8bc7debb3475b0.table.json

@@ -0,0 +1 @@
+{"columns": ["total_num_successes", "total_num_episodes", "total_success_rate", "total_success_rate_lb_0.01", "total_success_rate_ub_0.01", "total_success_rate_lb_0.025", "total_success_rate_ub_0.025", "total_success_rate_lb_0.05", "total_success_rate_ub_0.05", "total_success_rate_lb_0.1", "total_success_rate_ub_0.1"], "data": [[40, 40, 1.0, 0.9973071514565537, 1, 0.9194368123169305, 1, 0.9303731656703893, 1, 1, 1]]}

6qq3p71c/wandb/run-20250107_171404-6qq3p71c/files/media/videos/eval/0_eval_0_393b812fc042bd7e1762.mp4

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+
+loaded agent with feature_type: 180x240_1_RGB_D_2.0_msk_channels_EE_obj_mask_acthst_hst6_out32_dwnkrnl3_dwnstrd2_dwnpd1
+[INFO] [1736288047.446354]: resetting environment
+[INFO] [1736288047.453040]: cleared current plan
+[INFO] [1736288047.454401]: moving to home
+[INFO] [1736288048.456647]: reached home
+[INFO] [1736288048.457992]: reset action history
+[INFO] [1736288051.166052]: environment reset
+Starting episode 0
+[INFO] [1736288051.168266]: resetting environment
+[INFO] [1736288051.170970]: cleared current plan
+[INFO] [1736288051.171934]: moving to home
+[INFO] [1736288052.174192]: reached home
+[INFO] [1736288052.176315]: reset action history
+[INFO] [1736288054.884992]: environment reset
+Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
+proceeding to start episode!
+[INFO] [1736288058.772756]: resetting environment
+[INFO] [1736288058.775386]: cleared current plan
+[INFO] [1736288058.776317]: moving to home
+[INFO] [1736288059.778693]: reached home
+[INFO] [1736288059.780184]: reset action history
+[INFO] [1736288062.488178]: environment reset
+bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/episode_rosbags/episode_0_2025-01-07-17-14-22.bag
+... logging to /home/leonmkim/.ros/log/a8a09c64-c64e-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2196057.log
+started roslaunch server http://158.130.50.37:45693/
+SUMMARY
+========
+PARAMETERS
+ * /rosdistro: noetic
+ * /rosversion: 1.16.0
+NODES
+  /
+    print_text (rostopic/rostopic)
+    pub_text (rostopic/rostopic)
+    rosbag_record (rosbag/record)
+ROS_MASTER_URI=http://localhost:11311
+process[pub_text-1]: started with pid [2196323]
+process[print_text-2]: started with pid [2196324]
+process[rosbag_record-3]: started with pid [2196348]
+started bagging!
+[INFO] [1736288089.470625]: Storing episode...
+[rosbag_record-3] killing on exit
+[print_text-2] killing on exit
+[pub_text-1] killing on exit
+[INFO] [1736288090.213810]: Stored episode 1.
+[INFO] [1736288090.214220]: Saving video...
+[INFO] [1736288090.407353]: Video saved!
+Starting episode 1
+[INFO] [1736288090.424573]: resetting environment
+[INFO] [1736288090.429065]: cleared current plan
+[INFO] [1736288090.429331]: moving to home
+[INFO] [1736288093.932065]: reached home
+[INFO] [1736288093.932504]: reset action history
+[INFO] [1736288096.639688]: environment reset
+Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
+proceeding to start episode!Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+[INFO] [1736288101.545175]: resetting environment
+[INFO] [1736288101.547077]: cleared current plan
+[INFO] [1736288101.547243]: moving to home
+[INFO] [1736288102.548676]: reached home
+[INFO] [1736288102.549088]: reset action history
+[INFO] [1736288105.256199]: environment reset
+bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/episode_rosbags/episode_1_2025-01-07-17-15-05.bag
+... logging to /home/leonmkim/.ros/log/a8a09c64-c64e-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2196057.log
+started roslaunch server http://158.130.50.37:34905/
+SUMMARY
+========
+PARAMETERS
+ * /rosdistro: noetic
+ * /rosversion: 1.16.0
+NODES
+  /
+    print_text (rostopic/rostopic)
+    pub_text (rostopic/rostopic)
+    rosbag_record (rosbag/record)
+ROS_MASTER_URI=http://localhost:11311
+process[pub_text-4]: started with pid [2196456]
+process[print_text-5]: started with pid [2196457]
+process[rosbag_record-6]: started with pid [2196458]
+started bagging!
+For topic gripper_width: timestamp difference is -124921717 for nearest: 1736288108578846536 - target: 1736288108703768253 at idx 51
+For topic gripper_width: timestamp difference is -145909032 for nearest: 1736288123978846112 - target: 1736288124124755144 at idx 249
+[INFO] [1736288132.210189]: Storing episode...
+[rosbag_record-6] killing on exit
+[print_text-5] killing on exit
+[pub_text-4] killing on exit
+[INFO] [1736288132.990908]: Stored episode 2.
+[INFO] [1736288132.991155]: Saving video...
+[INFO] [1736288133.398446]: Video saved!
+Starting episode 2
+[INFO] [1736288133.436094]: resetting environment
+[INFO] [1736288133.446242]: cleared current plan
+[INFO] [1736288133.446503]: moving to home
+[INFO] [1736288136.948453]: reached home
+[INFO] [1736288136.951681]: reset action history
+[INFO] [1736288139.684073]: environment reset
+Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
+proceeding to start episode!Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+[INFO] [1736288143.883637]: resetting environment
+[INFO] [1736288143.892647]: cleared current plan
+[INFO] [1736288143.892892]: moving to home
+[INFO] [1736288144.897276]: reached home
+[INFO] [1736288144.897884]: reset action history
+[INFO] [1736288147.607549]: environment reset
+bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/episode_rosbags/episode_2_2025-01-07-17-15-47.bag
+... logging to /home/leonmkim/.ros/log/a8a09c64-c64e-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2196057.log
+started roslaunch server http://158.130.50.37:42555/
+SUMMARY
+========
+PARAMETERS
+ * /rosdistro: noetic
+ * /rosversion: 1.16.0
+NODES
+  /
+    print_text (rostopic/rostopic)
+    pub_text (rostopic/rostopic)
+    rosbag_record (rosbag/record)
+ROS_MASTER_URI=http://localhost:11311
+process[pub_text-7]: started with pid [2196627]
+process[print_text-8]: started with pid [2196628]
+process[rosbag_record-9]: started with pid [2196629]
+started bagging!
+For topic gripper_width: timestamp difference is -114301312 for nearest: 1736288163078846109 - target: 1736288163193147421 at idx 214
+[INFO] [1736288174.653705]: Storing episode...
+[rosbag_record-9] killing on exit
+[pub_text-7] killing on exit
+[print_text-8] killing on exit
+[INFO] [1736288175.483296]: Stored episode 3.
+[INFO] [1736288175.487671]: Saving video...
+[INFO] [1736288175.928281]: Video saved!
+Starting episode 3
+[INFO] [1736288175.963236]: resetting environment
+[INFO] [1736288175.979364]: cleared current plan
+[INFO] [1736288175.982054]: moving to home
+[WARN] [1736288175.816678]: Plan exhausted
+[WARN] [1736288175.855680]: Plan exhausted
+[WARN] [1736288175.895124]: Plan exhausted
+[WARN] [1736288175.936891]: Plan exhausted
+[WARN] [1736288175.975119]: Plan exhausted
+[INFO] [1736288179.488671]: reached home
+[INFO] [1736288179.490201]: reset action history
+[INFO] [1736288182.271283]: environment reset
+Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
+proceeding to start episode!Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+[INFO] [1736288189.497045]: resetting environment
+[INFO] [1736288189.511681]: cleared current plan
+[INFO] [1736288189.513828]: moving to home
+[INFO] [1736288190.518853]: reached home
+[INFO] [1736288190.521546]: reset action history
+[INFO] [1736288193.395998]: environment reset
+bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/episode_rosbags/episode_3_2025-01-07-17-16-33.bag
+... logging to /home/leonmkim/.ros/log/a8a09c64-c64e-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2196057.log
+started roslaunch server http://158.130.50.37:42313/
+SUMMARY
+========
+PARAMETERS
+ * /rosdistro: noetic
+ * /rosversion: 1.16.0
+NODES
+  /
+    print_text (rostopic/rostopic)
+    pub_text (rostopic/rostopic)
+    rosbag_record (rosbag/record)
+ROS_MASTER_URI=http://localhost:11311
+process[pub_text-10]: started with pid [2196763]
+process[print_text-11]: started with pid [2196764]
+process[rosbag_record-12]: started with pid [2196765]
+started bagging!
+[INFO] [1736288220.519458]: Storing episode...
+[rosbag_record-12] killing on exit
+[print_text-11] killing on exit[pub_text-10] killing on exit
+[INFO] [1736288221.315220]: Stored episode 4.
+[INFO] [1736288221.323039]: Saving video...
+[INFO] [1736288221.611912]: Video saved!
+Starting episode 4
+[INFO] [1736288221.667188]: resetting environment
+[INFO] [1736288221.679914]: cleared current plan
+[INFO] [1736288221.680210]: moving to home
+[INFO] [1736288225.185673]: reached home
+[INFO] [1736288225.192642]: reset action history
+[INFO] [1736288227.990526]: environment reset
+Press Enter to continue... after reseting env. To rate prev episode, press 0 for failure and 1 for success
+proceeding to start episode!Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+[INFO] [1736288229.514098]: resetting environment
+[INFO] [1736288229.529114]: cleared current plan
+[INFO] [1736288229.532282]: moving to home
+[INFO] [1736288230.540100]: reached home
+[INFO] [1736288230.546015]: reset action history
+[INFO] [1736288233.321995]: environment reset
+bag_path_name:=/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/episode_rosbags/episode_4_2025-01-07-17-17-13.bag
+... logging to /home/leonmkim/.ros/log/a8a09c64-c64e-11ef-96d2-5defea869005/roslaunch-leonmkim-ROG-Strix-G15CS-G15CS-2196057.log
+started roslaunch server http://158.130.50.37:44333/
+SUMMARY
+========
+PARAMETERS
+ * /rosdistro: noetic
+ * /rosversion: 1.16.0
+NODES
+  /
+    print_text (rostopic/rostopic)
+    pub_text (rostopic/rostopic)
+    rosbag_record (rosbag/record)
+ROS_MASTER_URI=http://localhost:11311
+process[pub_text-13]: started with pid [2196891]
+process[print_text-14]: started with pid [2196892]
+process[rosbag_record-15]: started with pid [2196893]
+started bagging!
+[INFO] [1736288260.270188]: Storing episode...
+[print_text-14] killing on exit[rosbag_record-15] killing on exit[pub_text-13] killing on exit
+[INFO] [1736288261.100069]: Stored episode 5.
+[INFO] [1736288261.101015]: Saving video...
+[INFO] [1736288261.769383]: Video saved!
+[INFO] [1736288261.833899]: resetting environment
+[INFO] [1736288261.849791]: cleared current plan
+[INFO] [1736288261.851942]: moving to home
+[WARN] [1736288261.625256]: Plan exhausted
+[WARN] [1736288261.671281]: Plan exhausted
+[WARN] [1736288261.706568]: Plan exhausted
+[WARN] [1736288261.747101]: Plan exhausted
+[WARN] [1736288261.786364]: Plan exhausted
+[WARN] [1736288261.827991]: Plan exhausted
+[INFO] [1736288265.354731]: reached home
+[INFO] [1736288265.360890]: reset action history
+[INFO] [1736288268.198443]: environment reset
+Evaluation finished. To wrap up, rate prev episode, press 0 for failure and 1 for success
+proceeding to start episode!Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+Comuting lower confidence bound
+Comuting upper confidence bound
+proceeding to start episode!

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6qq3p71c/wandb/run-20250107_171404-6qq3p71c/logs/debug.log

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'agent.encoder.CropInputConfig', 'color_crop_type': None, 'depth_crop_type': None, 'segmask_crop_type': None, 'crop_hw': [144, 144], 'crop_down_offset': 48, 'add_crop_binary_mask': False, 'add_coord_conv_map': False}, 'context_input_config': {'_target_': 'agent.encoder.ContextInputConfig', 'use_color': False, 'use_depth': False, 'mask_input_dict': {'_target_': 'agent.encoder.MaskInputDict', 'enable': False, 'representation': 'channels', 'mask_list': ['EE_obj_mask']}, 'crop_input_config': {'_target_': 'agent.encoder.CropInputConfig', 'color_crop_type': None, 'depth_crop_type': None, 'segmask_crop_type': None, 'crop_hw': [144, 144], 'crop_down_offset': 48, 'add_crop_binary_mask': False, 'add_coord_conv_map': False}}, 'mask_soft_approx_scheduler_config': {'_target_': 'agent.encoder.MaskSoftApproxSchedulerConfig', 'num_steps': 40000, 'initial_value': 10.0, 'final_value': 1000.0, 'interpolation_scheme': 'cosine'}, 'use_contact_map': False, 'use_sdf_maps': False, 'use_normals_maps': False, 'which_objects': 'both', 'grasped_dtc_max_value': 0.2, 'env_dtc_max_value': 0.4, 'grasped_normals_mask_max_dtc_value': 0.2, 'env_normals_mask_max_dtc_value': 0.4, 'clamp_dtc': True, 'max_contact_prob': 0.1, 'mask_normals_within_sdf': True, 'dtc_adaptive_normalization': False, 'adaptive_normals_mask': True, 'max_depth': 2.0, 'image_shape': [13, 180, 240], 'learnable_contact_preprocess_params': True, 'learning_rate': 0.0001, 'weight_decay': 0.0, 'contact_model_name': 'local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9', 'zero_centered': False}}}, 'suite': {'suite': 'frankagym', 'name': 'frankagym', 'frame_stack': 1, 'action_repeat': 1, 'discount': 0.99, 'hidden_dim': 1024, 'num_train_frames': 2010, 'num_seed_frames': 260, 'num_train_epochs': 5000, 'validate_every_epochs': 100, 'validate_diffusion_on_action_loss_every_epochs': 500, 'train_eval_diffusion_on_action_loss_every_epochs': 500, 'check_topk_every_epochs': 10, 'save_snapshot_every_epochs': 5000, 'eval_every_frames': 2000, 'num_eval_episodes': 5, 'save_snapshot': True, 'wait_for_user_to_start_episode': True, 'task_make_fn': {'_target_': 'suite.frankagym.make', 'name': 'FrankaInsertion-v1', 'height': 240, 'width': 320, 'frame_stack': 1, 'action_repeat': 1, 'seed': 1, 'enable_arm': True, 'enable_gripper': True, 'start_with_gripper_open': True, 'enable_camera': True, 'path_to_depth_extrinsics': '~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy', 'contact_estimation_model_ckpt_path': '~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt', 'x_limit': [0.2, 0.7], 'y_limit': [-0.4, 0.4], 'z_limit': [-0.05, 0.55], 'device': 'cuda', 'interpolation_frequency': 25, 'policy_frequency': 5, 'debug_timestamps': False, 'stop_after_action': False, 'open_loop': False, 'wait_for_new_camera_frames': True, 'action_key': 'action_trajectory_25hz', 'action_trajectory_horizon': 36, 'action_trajectories': True, 'path_to_zarr_dataset': '/home/leonmkim/fish_leon/FISH/expert_demos/frankagym/FrankaInsertion-v1/120_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act/demos.zarr', 'agent_policy_cfg': {'_target_': 'agent.diffusion_policy.DiffusionPolicyAgentConfig', 'compile': False, 'device': 'cuda', 'cam_resize_shape': [13, 180, 240], 'orig_cam_shape': [3, 240, 320], 'policy_frequency': 5, 'interpolation_frequency': 25, 'policy_cfg': {'_target_': 'lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig', 'n_obs_steps': 1, 'horizon': 36, 'n_action_steps': 36, 'output_shapes': {'action': [7]}, 'input_normalization_modes': {'observation.image': 'mean_std', 'observation.state': 'min_max', 'observation.action_history': 'min_max'}, 'output_normalization_modes': {'action': 'min_max'}, 'vision_backbone': 'resnet18', 'pretrained_backbone_weights': None, 'transforms': [{'_target_': 'torchaug.transforms.RandomAffine', 'degrees': [-5, 5], 'translate': [0.05, 0.05], 'batch_transform': True, 'num_chunks': -1, 'batch_inplace': True}, {'_target_': 'torchaug.transforms.RandomColorJitter', 'brightness': 0.3, 'contrast': 0.4, 'saturation': 0.5, 'hue': 0.08, 'batch_transform': True, 'num_chunks': -1, 'batch_inplace': True}], 'use_group_norm': True, 'spatial_softmax_num_keypoints': 32, 'action_history_encoder_config': {'_target_': 'lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig', 'in_channels': 7, 'out_channels': 32, 'history_length': 6, 'kernel_size': 5, 'downsample_kernel_size': 3, 'downsample_stride': 2, 'downsample_padding': 1}, 'down_dims': [256, 512, 1024], 'kernel_size': 5, 'n_groups': 8, 'diffusion_step_embed_dim': 128, 'use_film_scale_modulation': True, 'noise_scheduler_type': 'DDIM', 'beta_schedule': 'squaredcos_cap_v2', 'beta_start': 0.0001, 'beta_end': 0.02, 'prediction_type': 'epsilon', 'clip_sample': True, 'clip_sample_range': 1.0, 'num_train_timesteps': 50, 'num_inference_steps': 10, 'do_mask_loss_for_padding': False, 'input_shapes': {'observation.image': [13, 180, 240], 'context_observation.image': [13, 180, 240], 'observation.state': [8], 'observation.action_history': [7]}}, 'train_cfg': {'_target_': 'utils.TrainConfig', 'lr': 0.0001, 'lr_scheduler': 'cosine', 'lr_warmup_steps': 500, 'adam_betas': [0.95, 0.999], 'adam_eps': 1e-08, 'adam_weight_decay': 1e-06, 'grad_clip_norm': 10, 'offline_steps': 1000000, 'use_amp': True}, 'observation_cfg': {'_target_': 'agent.encoder.VisualFeatureSet', 'use_depth': True, 'use_color': True, 'mask_input_dict': {'_target_': 'agent.encoder.MaskInputDict', 'enable': True, 'representation': 'channels', 'mask_list': ['EE_obj_mask']}, 'crop_input_config': {'_target_': 'agent.encoder.CropInputConfig', 'color_crop_type': None, 'depth_crop_type': None, 'segmask_crop_type': None, 'crop_hw': [144, 144], 'crop_down_offset': 48, 'add_crop_binary_mask': False, 'add_coord_conv_map': False}, 'context_input_config': {'_target_': 'agent.encoder.ContextInputConfig', 'use_color': False, 'use_depth': False, 'mask_input_dict': {'_target_': 'agent.encoder.MaskInputDict', 'enable': False, 'representation': 'channels', 'mask_list': ['EE_obj_mask']}, 'crop_input_config': {'_target_': 'agent.encoder.CropInputConfig', 'color_crop_type': None, 'depth_crop_type': None, 'segmask_crop_type': None, 'crop_hw': [144, 144], 'crop_down_offset': 48, 'add_crop_binary_mask': False, 'add_coord_conv_map': False}}, 'mask_soft_approx_scheduler_config': {'_target_': 'agent.encoder.MaskSoftApproxSchedulerConfig', 'num_steps': 40000, 'initial_value': 10.0, 'final_value': 1000.0, 'interpolation_scheme': 'cosine'}, 'use_contact_map': False, 'use_sdf_maps': False, 'use_normals_maps': False, 'which_objects': 'both', 'grasped_dtc_max_value': 0.2, 'env_dtc_max_value': 0.4, 'grasped_normals_mask_max_dtc_value': 0.2, 'env_normals_mask_max_dtc_value': 0.4, 'clamp_dtc': True, 'max_contact_prob': 0.1, 'mask_normals_within_sdf': True, 'dtc_adaptive_normalization': False, 'adaptive_normals_mask': True, 'max_depth': 2.0, 'image_shape': [13, 180, 240], 'learnable_contact_preprocess_params': True, 'learning_rate': 0.0001, 'weight_decay': 0.0, 'contact_model_name': 'local_multitask_outhd64all_home_crop_h144w144d48_mask_ctxtmask_seed_220979_epoch_9', 'zero_centered': False}}, 'true_action_history': False}}, 'num_train_frames_bc': 50000, 'num_train_frames_drq': 1100000, 'stddev_schedule_drq': 'linear(1.0,0.1,100000)', 'task_name': 'FrankaInsertion-v1', 'num_train_frames_vinn': 25000, 'num_train_frames_diffusion': 1000000, 'num_train_epochs_bc': 5000, 'num_train_epochs_diffusion': 15000, 'validate_every_epochs_bc': 5, 'validate_every_epochs_diffusion': 250, 'validate_diffusion_on_action_loss_every_epochs': 250, 'train_eval_diffusion_on_action_loss_every_epochs': 250, 'check_topk_every_epochs': 5, 'check_topk_every_epochs_diffusion': 250, 'save_snapshot_every_epochs_diffusion': 1500, 'x_limit': [0.2, 0.7], 'y_limit': [-0.4, 0.4], 'z_limit': [-0.05, 0.55], 'home_displacement': [0.55, 0.0, 0.55, 180.0, 0.0, 0.0], 'enable_gripper': True, 'start_with_gripper_open': True, 'offset_mask': [1, 1, 1, 1, 1, 1], 'path_to_depth_extrinsics': '~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy', 'feature_type': '180x240_1_RGB_D_2.0_msk_channels_EE_obj_mask_acthst_hst6_out32_dwnkrnl3_dwnstrd2_dwnpd1', 'save_buffer': True, 'num_eval': 5, 'random_start': False, 'eval_starts': '/home/leonmkim/fish_leon/FISH/eval_starts/frankagym_pixels/FrankaInsertion-v1', 'num_valid_demos': None, 'load_checkpoint': True, 'checkpoint_epoch': 12000, 'load_residual_weight': False, 'checkpoint_root_dir': '/home/leonmkim/fish_leon/FISH', 'checkpoint_weight_dir': '/home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1', 'residual_weight': '/home/leonmkim/fish_leon/FISH/weights/frankagym_pixels/FrankaInsertion-v1/weight.pt', 'final_experiment_dir': './exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c'}
+2025-01-07 17:14:04,426 INFO    MainThread:2196057 [wandb_init.py:init():619] starting backend
+2025-01-07 17:14:04,426 INFO    MainThread:2196057 [wandb_init.py:init():623] setting up manager
+2025-01-07 17:14:04,430 INFO    MainThread:2196057 [backend.py:_multiprocessing_setup():105] multiprocessing start_methods=fork,spawn,forkserver, using: spawn
+2025-01-07 17:14:04,431 INFO    MainThread:2196057 [wandb_init.py:init():631] backend started and connected
+2025-01-07 17:14:04,443 INFO    MainThread:2196057 [wandb_init.py:init():720] updated telemetry
+2025-01-07 17:14:04,453 INFO    MainThread:2196057 [wandb_init.py:init():753] communicating run to backend with 90.0 second timeout
+2025-01-07 17:14:04,702 INFO    MainThread:2196057 [wandb_run.py:_on_init():2435] communicating current version
+2025-01-07 17:14:04,770 INFO    MainThread:2196057 [wandb_run.py:_on_init():2444] got version response upgrade_message: "wandb version 0.19.2 is available!  To upgrade, please run:\n $ pip install wandb --upgrade"
+
+2025-01-07 17:14:04,770 INFO    MainThread:2196057 [wandb_init.py:init():804] starting run threads in backend
+2025-01-07 17:14:05,123 INFO    MainThread:2196057 [wandb_run.py:_console_start():2413] atexit reg
+2025-01-07 17:14:05,123 INFO    MainThread:2196057 [wandb_run.py:_redirect():2255] redirect: wrap_raw
+2025-01-07 17:14:05,123 INFO    MainThread:2196057 [wandb_run.py:_redirect():2320] Wrapping output streams.
+2025-01-07 17:14:05,124 INFO    MainThread:2196057 [wandb_run.py:_redirect():2345] Redirects installed.
+2025-01-07 17:14:05,125 INFO    MainThread:2196057 [wandb_init.py:init():847] run started, returning control to user process
+2025-01-07 17:14:05,125 INFO    MainThread:2196057 [wandb_run.py:_tensorboard_callback():1544] tensorboard callback: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/6qq3p71c/tb, True
+2025-01-07 17:14:07,444 INFO    MainThread:2196057 [wandb_run.py:_config_callback():1382] config_cb None None {'grasped_obj_name': 'hbm', 'left_book_slot': 'twodim'}
+2025-01-07 17:18:08,590 WARNING MsgRouterThr:2196057 [router.py:message_loop():77] message_loop has been closed

9fviy2t8/.hydra/config.yaml

@@ -0,0 +1,350 @@
+root_dir: /home/${oc.env:USER}/fish_leon
+nstep: 3
+seed: 41
+dataset_shuffle_seed: ${seed}
+device: cuda
+save_video: true
+save_buffer: true
+use_tb: true
+baseline: false
+use_wandb: true
+eval: true
+process_contact_features: ${eval}
+obs_type: pixels
+use_color: true
+use_depth: true
+use_masks: false
+mask_list:
+- EE_obj_mask
+mask_representation: channels
+crop_hw:
+- 144
+- 144
+crop_down_offset: 48
+color_crop_type: null
+depth_crop_type: null
+segmask_crop_type: null
+add_crop_binary_mask: false
+add_coord_conv_map: false
+use_context_color: false
+use_context_depth: false
+use_context_segmask: false
+context_color_crop_type: null
+context_depth_crop_type: null
+context_segmask_crop_type: null
+context_add_crop_binary_mask: false
+context_add_coord_conv_map: false
+use_contact_map: false
+use_sdf_maps: false
+use_normals_maps: false
+which_objects: both
+max_contact_prob: 0.1
+max_depth: 2.0
+grasped_dtc_max_value: 0.105
+env_dtc_max_value: 0.425
+grasped_normals_mask_max_dtc_value: 0.105
+env_normals_mask_max_dtc_value: 0.425
+clamp_dtc: true
+dtc_adaptive_normalization: false
+mask_normals_within_sdf: true
+adaptive_normals_mask: true
+learnable_contact_preprocess_params: false
+contact_model_name: local_multitask_outhd64all_home_crop_h144w144d48_ctxt_seed_183386_epoch_9
+contact_estimation_model_ckpt_path: ~/fish_leon/contact_estimation/artifacts/175604_2/checkpoints/epoch=09-val_loss=0.00.ckpt
+num_eval: 5
+debug_timestamps: false
+open_loop: false
+action_trajectories: true
+stop_after_action: false
+interpolation_frequency: 25
+policy_frequency: 5
+wait_for_new_camera_frames: true
+random_start: false
+eval_starts: ${root_dir}/FISH/eval_starts/${suite.name}_${obs_type}/${task_name}
+train_demo_idxs_list_or_num: null
+num_valid_demos: null
+val_num_groups: 3
+name_of_expert_demo: 112_240x320_all_twodim_left_to_right_annotated_start_idx_5hz_zstd7_EE_pxl_coords_expert_demos_imp_act
+expert_dataset_dirpath: ${root_dir}/FISH/expert_demos/${suite.name}/${task_name}/${name_of_expert_demo}
+expert_dataset: ${expert_dataset_dirpath}/demos.zarr
+action_key: ${oc.if_else:${action_trajectories}, 'action_trajectory_${interpolation_frequency}hz',
+  'action'}
+semantic_demo_grouping_name: semantic_demo_grouping.yaml
+semantic_demo_grouping: ${expert_dataset_dirpath}/${semantic_demo_grouping_name}
+expert_dataset_config: ${expert_dataset_dirpath}/demo_config.yaml
+bc_regularize: false
+bc_weight_type: qfilter
+load_checkpoint: ${agent.load_checkpoint}
+wandb_run_id: '1009_1'
+true_action_history: false
+wandb_notes: null
+checkpoint_epoch: 12000
+load_residual_weight: false
+checkpoint_root_dir: /home/${oc.env:USER}/fish_leon/FISH
+checkpoint_weight_dir: ${checkpoint_root_dir}/exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
+residual_weight: ${root_dir}/FISH/weights/${suite.name}_${obs_type}/${task_name}/weight.pt
+experiment_dir: ./exp_local/${suite.name}_${obs_type}/${task_name}/${wandb_run_id}
+final_experiment_dir: ${experiment_dir}/${oc.generate_run_id:}
+agent:
+  _target_: agent.diffusion_policy.DiffusionPolicyAgent
+  name: diffusion_policy
+  load_checkpoint: ${eval}
+  device: ${device}
+  n_obs_steps: ${.config.policy_cfg.n_obs_steps}
+  suite_name: ${suite.name}
+  obs_type: ${obs_type}
+  enable_arm: ${eval}
+  enable_camera: ${eval}
+  use_tb: ${use_tb}
+  desired_image_shape:
+  - 13
+  - 180
+  - 240
+  orig_cam_shape:
+  - 3
+  - 240
+  - 320
+  config:
+    _target_: agent.diffusion_policy.DiffusionPolicyAgentConfig
+    compile: false
+    device: ${device}
+    cam_resize_shape: ${agent.desired_image_shape}
+    orig_cam_shape: ${agent.orig_cam_shape}
+    policy_frequency: ${policy_frequency}
+    interpolation_frequency: ${interpolation_frequency}
+    policy_cfg:
+      _target_: lerobot.common.policies.diffusion.configuration_diffusion.DiffusionConfig
+      n_obs_steps: 1
+      horizon: 36
+      n_action_steps: ${agent.config.policy_cfg.horizon}
+      input_shapes:
+        observation.image: ${agent.config.cam_resize_shape}
+        context_observation.image: ${agent.config.cam_resize_shape}
+        observation.state:
+        - 8
+        observation.action_history:
+        - 7
+      output_shapes:
+        action:
+        - 7
+      input_normalization_modes:
+        observation.image: mean_std
+        observation.state: min_max
+        observation.action_history: min_max
+      output_normalization_modes:
+        action: min_max
+      vision_backbone: resnet18
+      pretrained_backbone_weights: null
+      transforms:
+      - _target_: torchaug.transforms.RandomAffine
+        degrees:
+        - -5
+        - 5
+        translate:
+        - 0.05
+        - 0.05
+        batch_transform: true
+        num_chunks: -1
+        batch_inplace: true
+      - _target_: torchaug.transforms.RandomColorJitter
+        brightness: 0.3
+        contrast: 0.4
+        saturation: 0.5
+        hue: 0.08
+        batch_transform: true
+        num_chunks: -1
+        batch_inplace: true
+      use_group_norm: true
+      spatial_softmax_num_keypoints: 32
+      action_history_encoder_config:
+        _target_: lerobot.common.policies.diffusion.configuration_diffusion.Unet1dEncoderConfig
+        in_channels: 7
+        out_channels: 32
+        history_length: ${agent.config.policy_cfg.n_action_steps}
+        kernel_size: ${agent.config.policy_cfg.kernel_size}
+        downsample_kernel_size: 3
+        downsample_stride: 2
+        downsample_padding: 1
+      down_dims:
+      - 256
+      - 512
+      - 1024
+      kernel_size: 5
+      n_groups: 8
+      diffusion_step_embed_dim: 128
+      use_film_scale_modulation: true
+      noise_scheduler_type: DDIM
+      beta_schedule: squaredcos_cap_v2
+      beta_start: 0.0001
+      beta_end: 0.02
+      prediction_type: epsilon
+      clip_sample: true
+      clip_sample_range: 1.0
+      num_train_timesteps: 50
+      num_inference_steps: 10
+      do_mask_loss_for_padding: false
+    train_cfg:
+      _target_: utils.TrainConfig
+      lr: 0.0001
+      lr_scheduler: cosine
+      lr_warmup_steps: 500
+      adam_betas:
+      - 0.95
+      - 0.999
+      adam_eps: 1.0e-08
+      adam_weight_decay: 1.0e-06
+      grad_clip_norm: 10
+      offline_steps: ${num_train_frames_diffusion}
+      use_amp: true
+    observation_cfg:
+      _target_: agent.encoder.VisualFeatureSet
+      use_depth: ${use_depth}
+      use_color: ${use_color}
+      mask_input_dict:
+        _target_: agent.encoder.MaskInputDict
+        enable: ${use_masks}
+        representation: ${mask_representation}
+        mask_list: ${mask_list}
+      crop_input_config:
+        _target_: agent.encoder.CropInputConfig
+        color_crop_type: ${color_crop_type}
+        depth_crop_type: ${depth_crop_type}
+        segmask_crop_type: ${segmask_crop_type}
+        crop_hw: ${crop_hw}
+        crop_down_offset: ${crop_down_offset}
+        add_crop_binary_mask: ${add_crop_binary_mask}
+        add_coord_conv_map: ${add_coord_conv_map}
+      context_input_config:
+        _target_: agent.encoder.ContextInputConfig
+        use_color: ${use_context_color}
+        use_depth: ${use_context_depth}
+        mask_input_dict:
+          _target_: agent.encoder.MaskInputDict
+          enable: ${use_context_segmask}
+          representation: ${mask_representation}
+          mask_list: ${mask_list}
+        crop_input_config:
+          _target_: agent.encoder.CropInputConfig
+          color_crop_type: ${context_color_crop_type}
+          depth_crop_type: ${context_depth_crop_type}
+          segmask_crop_type: ${context_segmask_crop_type}
+          crop_hw: ${crop_hw}
+          crop_down_offset: ${crop_down_offset}
+          add_crop_binary_mask: ${context_add_crop_binary_mask}
+          add_coord_conv_map: ${context_add_coord_conv_map}
+      mask_soft_approx_scheduler_config:
+        _target_: agent.encoder.MaskSoftApproxSchedulerConfig
+        num_steps: 40000
+        initial_value: 10.0
+        final_value: 1000.0
+        interpolation_scheme: constant
+      use_contact_map: ${use_contact_map}
+      use_sdf_maps: ${use_sdf_maps}
+      use_normals_maps: ${use_normals_maps}
+      which_objects: ${which_objects}
+      grasped_dtc_max_value: ${grasped_dtc_max_value}
+      env_dtc_max_value: ${env_dtc_max_value}
+      grasped_normals_mask_max_dtc_value: ${grasped_normals_mask_max_dtc_value}
+      env_normals_mask_max_dtc_value: ${env_normals_mask_max_dtc_value}
+      clamp_dtc: ${clamp_dtc}
+      max_contact_prob: ${max_contact_prob}
+      mask_normals_within_sdf: ${mask_normals_within_sdf}
+      dtc_adaptive_normalization: ${dtc_adaptive_normalization}
+      adaptive_normals_mask: ${adaptive_normals_mask}
+      max_depth: ${max_depth}
+      image_shape: ${agent.desired_image_shape}
+      learnable_contact_preprocess_params: ${learnable_contact_preprocess_params}
+      learning_rate: ${agent.config.train_cfg.lr}
+      weight_decay: 0.0
+      contact_model_name: ${contact_model_name}
+      zero_centered: false
+suite:
+  suite: frankagym
+  name: frankagym
+  frame_stack: ${agent.n_obs_steps}
+  action_repeat: 1
+  discount: 0.99
+  hidden_dim: 1024
+  num_train_frames: 2010
+  num_seed_frames: 260
+  num_train_epochs: 5000
+  validate_every_epochs: 100
+  validate_diffusion_on_action_loss_every_epochs: 500
+  train_eval_diffusion_on_action_loss_every_epochs: 500
+  check_topk_every_epochs: 10
+  save_snapshot_every_epochs: 5000
+  eval_every_frames: 2000
+  num_eval_episodes: 5
+  save_snapshot: true
+  wait_for_user_to_start_episode: true
+  task_make_fn:
+    _target_: suite.frankagym.make
+    name: ${task_name}
+    height: 240
+    width: 320
+    frame_stack: ${suite.frame_stack}
+    action_repeat: ${suite.action_repeat}
+    seed: ${seed}
+    enable_arm: ${agent.enable_arm}
+    enable_gripper: ${enable_gripper}
+    start_with_gripper_open: ${start_with_gripper_open}
+    enable_camera: ${agent.enable_camera}
+    path_to_depth_extrinsics: ${path_to_depth_extrinsics}
+    contact_estimation_model_ckpt_path: ${contact_estimation_model_ckpt_path}
+    x_limit: ${x_limit}
+    y_limit: ${y_limit}
+    z_limit: ${z_limit}
+    device: ${device}
+    interpolation_frequency: ${interpolation_frequency}
+    policy_frequency: ${policy_frequency}
+    debug_timestamps: ${debug_timestamps}
+    stop_after_action: ${stop_after_action}
+    open_loop: ${open_loop}
+    wait_for_new_camera_frames: ${wait_for_new_camera_frames}
+    action_key: ${action_key}
+    action_trajectory_horizon: ${agent.config.policy_cfg.horizon}
+    action_trajectories: ${action_trajectories}
+    path_to_zarr_dataset: ${expert_dataset}
+    agent_policy_cfg: ???
+    true_action_history: ${true_action_history}
+num_train_frames_bc: 50000
+num_train_frames_drq: 1100000
+stddev_schedule_drq: linear(1.0,0.1,100000)
+task_name: FrankaInsertion-v1
+num_train_frames_vinn: 25000
+num_train_frames_diffusion: 1000000
+num_train_epochs_bc: 5000
+num_train_epochs_diffusion: 5000
+validate_every_epochs_bc: 5
+validate_every_epochs_diffusion: 25
+validate_diffusion_on_action_loss_every_epochs: 50
+train_eval_diffusion_on_action_loss_every_epochs: 500
+check_topk_every_epochs: 5
+check_topk_every_epochs_diffusion: ${validate_diffusion_on_action_loss_every_epochs}
+save_snapshot_every_epochs_diffusion: 5000
+x_limit:
+- 0.2
+- 0.7
+y_limit:
+- -0.4
+- 0.4
+z_limit:
+- -0.05
+- 0.55
+home_displacement:
+- 0.55
+- 0.0
+- 0.55
+- 180.0
+- 0.0
+- 0.0
+enable_gripper: true
+start_with_gripper_open: true
+offset_mask:
+- 1
+- 1
+- 1
+- 1
+- 1
+- 1
+path_to_depth_extrinsics: ~/fish_leon/FISH/cfgs/camera_poses/camera_poses_L515/20240904-122305/color_tf_world.npy

9fviy2t8/.hydra/hydra.yaml

@@ -0,0 +1,169 @@
+hydra:
+  run:
+    dir: ${final_experiment_dir}
+  sweep:
+    dir: ${final_experiment_dir}
+    subdir: ${hydra.job.num}
+  launcher:
+    submitit_folder: ${final_experiment_dir}/.slurm
+    timeout_min: 60
+    cpus_per_task: null
+    gpus_per_node: null
+    tasks_per_node: 1
+    mem_gb: null
+    nodes: 1
+    name: ${hydra.job.name}
+    stderr_to_stdout: false
+    _target_: hydra_plugins.hydra_submitit_launcher.submitit_launcher.LocalLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - agent=diffusion
+    - suite=frankagym
+    - suite/frankagym_task@_global_=insertion
+  job:
+    name: eval_robot
+    chdir: true
+    override_dirname: agent=diffusion,suite/frankagym_task@_global_=insertion,suite=frankagym
+    id: ???
+    num: ???
+    config_name: config_eval
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.1'
+    cwd: /home/leonmkim/fish_leon/FISH
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /home/leonmkim/fish_leon/FISH/cfgs
+      schema: file
+      provider: main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /home/leonmkim/fish_leon/FISH/exp_local/frankagym_pixels/FrankaInsertion-v1/1009_1/9fviy2t8
+    choices:
+      suite: frankagym
+      suite/frankagym_task@_global_: insertion
+      agent: diffusion
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: submitit_local
+      hydra/output: default
+  verbose: false

9fviy2t8/.hydra/overrides.yaml

@@ -0,0 +1,3 @@
+- agent=diffusion
+- suite=frankagym
+- suite/frankagym_task@_global_=insertion

9fviy2t8/episode_rosbags/aligned_depth_to_color_K.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4a962c703d20da282f5e009d432dff51df4ebd22f3386699b6754ea9cfc06a55
+size 200

9fviy2t8/episode_rosbags/cam_tf_world.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:29313ba240dd65ebbc79056d5582a97c9586cf2a1d4a1e0db13b87b49152cc9e
+size 256

9fviy2t8/episode_rosbags/color_K.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4a962c703d20da282f5e009d432dff51df4ebd22f3386699b6754ea9cfc06a55
+size 200

9fviy2t8/episode_rosbags/depth_K.npy

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:cc601d2fecd31c5513c76a88b5d4d8059adc1f92dad682e2d755d89a66d8fdf7
+size 200