make config changes

egomimic/hydra_configs/data/eva_bc_s3.yaml

@@ -8,7 +8,7 @@ train_datasets:
     embodiment: "eva_bimanual"
     cache_root: "/coc/flash7/scratch/.cache/"
     filters: 
-      task: "fold clothes"
+      task: "object in container"
     local_files_only: True
     debug: False
 
@@ -20,16 +20,16 @@ valid_datasets:
     embodiment: "eva_bimanual"
     cache_root: "/coc/flash7/scratch/.cache/"
     filters: 
-      task: "fold clothes"
+      task: "object in container"
     local_files_only: True
     debug: False
 
 train_dataloader_params:
   dataset1:
     batch_size: 32
-    num_workers: 10
+    num_workers: 6
 
 valid_dataloader_params:
   dataset1:
     batch_size: 32
-    num_workers: 10
+    num_workers: 6

egomimic/hydra_configs/data/mecka_test.yaml

@@ -2,25 +2,27 @@ _target_: egomimic.pl_utils.pl_data_utils.MultiDataModuleWrapper
 
 train_datasets:
   dataset1:
+    _target_: rldb.utils.S3RLDBDataset
     _target_: rldb.utils.S3RLDBDataset
     bucket_name: "rldb"
     mode: train
     local_mode: True
     embodiment: "mecka_bimanual"
     filters:
-      task: "fold_clothes"
+      task: "organizing_tools"
     local_files_only: True
 
 
 valid_datasets:
   dataset1:
+    _target_: rldb.utils.S3RLDBDataset
     _target_: rldb.utils.S3RLDBDataset
     bucket_name: "rldb"
     mode: valid
     local_mode: True
     embodiment: "mecka_bimanual"
     filters:
-      task: "fold_clothes"
+      task: "organizing_tools"
     local_files_only: True
 
 

egomimic/hydra_configs/data/obj_cont_cotrain.yaml

@@ -0,0 +1,54 @@
+_target_: egomimic.pl_utils.pl_data_utils.MultiDataModuleWrapper
+train_datasets:
+  dataset1:
+    _target_: egomimic.rldb.utils.S3RLDBDataset
+    bucket_name: rldb
+    mode: train
+    embodiment: eva_right_arm
+    filters:
+      task: object in container
+    local_files_only: true
+
+  dataset2:
+    _target_: egomimic.rldb.utils.S3RLDBDataset
+    bucket_name: rldb
+    mode: train
+    embodiment: aria_right_arm
+    filters:
+      task: object in container
+    local_files_only: true
+
+
+valid_datasets:
+  dataset1:
+    _target_: egomimic.rldb.utils.S3RLDBDataset
+    bucket_name: rldb
+    mode: valid
+    embodiment: eva_right_arm
+    filters:
+      task: object in container
+    local_files_only: true
+
+  dataset2:
+    _target_: egomimic.rldb.utils.S3RLDBDataset
+    bucket_name: rldb
+    mode: valid
+    embodiment: aria_right_arm
+    filters:
+      task: object in container
+    local_files_only: true
+
+train_dataloader_params:
+  dataset1:
+    batch_size: 32
+    num_workers: 8
+  dataset2:
+    batch_size: 32
+    num_workers: 8
+valid_dataloader_params:
+  dataset1:
+    batch_size: 32
+    num_workers: 8
+  dataset2:
+    batch_size: 32
+    num_workers: 8

egomimic/hydra_configs/model/pi0.5.yaml

@@ -3,24 +3,32 @@ robomimic_model:
   _target_: egomimic.algo.pi.PI
   data_schematic: _${data.dataset.data_schematic}
   camera_transforms:
-    _target_: egomimic.utils.egomimicUtils.CameraTransforms
-    intrinsics_key: "base" # change to base_half if using half res 
-    extrinsics_key: "ariaJun7"
+    eva_right_arm:
+      _target_: egomimic.utils.egomimicUtils.CameraTransforms
+      intrinsics_key: "base" # change to base_half if using half res 
+      extrinsics_key: "x5Dec13_2"
+    aria_right_arm:
+      _target_: egomimic.utils.egomimicUtils.CameraTransforms
+      intrinsics_key: "base" # change to base_half if using half res 
+      extrinsics_key: "ariaJun7"
   ac_keys:
-    aria_bimanual: "actions_cartesian"
-  domains: ["aria_bimanual"]
+    eva_right_arm: "actions_cartesian"
+    aria_right_arm: "actions_cartesian"
+  domains: ["eva_right_arm", "aria_right_arm"]
 
   action_converters:
     rules:
-      ARIA_BIMANUAL:
-        _target_: egomimic.utils.action_utils.HumanBimanualCartesianEuler
+      EVA_RIGHT_ARM:
+        _target_: egomimic.utils.action_utils.RobotRightCartesianEuler
+      ARIA_RIGHT_ARM:
+        _target_: egomimic.utils.action_utils.HumanRightCartesianEuler
     # optional fallback if no match is found
     fallback:
       _target_: egomimic.utils.action_utils.BaseActionConverter
 
   config:      
     pytorch_training_precision: bfloat16
-    pytorch_weight_path: /storage/home/hcoda1/5/rpunamiya6/cedar-dx/rpunamiya6/Projects/EgoVerse/egomimic/algo/pi_checkpoints/pi05_base_pytorch
+    pytorch_weight_path: /storage/home/hcoda1/5/acheluva3/jcedar/EgoVerse/egomimic/algo/pi_checkpoints/pi05_base_pytorch
     model:
       pi05: true
       action_dim: 32

egomimic/hydra_configs/model/pi0.5_mecka.yaml

@@ -0,0 +1,57 @@
+_target_: egomimic.pl_utils.pl_model.ModelWrapper
+robomimic_model:
+  _target_: egomimic.algo.pi.PI
+  data_schematic: _${data.dataset.data_schematic}
+  camera_transforms:
+    mecka_bimanual:
+      _target_: egomimic.utils.egomimicUtils.CameraTransforms
+      intrinsics_key: "mecka" # change to base_half if using half res 
+      extrinsics_key: "mecka"
+  ac_keys:
+    mecka_bimanual: "actions_cartesian"
+  domains: ["mecka_bimanual"]
+
+  action_converters:
+    rules:
+      MECKA_BIMANUAL:
+        _target_: egomimic.utils.action_utils.HumanBimanualCartesianEuler
+    # optional fallback if no match is found
+    fallback:
+      _target_: egomimic.utils.action_utils.BaseActionConverter
+
+  config:      
+    pytorch_training_precision: bfloat16
+    pytorch_weight_path: /storage/home/hcoda1/5/acheluva3/jcedar/EgoVerse/egomimic/algo/pi_checkpoints/pi05_base_pytorch
+    model:
+      pi05: true
+      action_dim: 32
+      action_horizon: 100
+      max_token_len: 180
+
+  train_image_augs:
+    _target_: torchvision.transforms.Compose
+    transforms:
+      - _target_: torchvision.transforms.Resize
+        size: 224
+        interpolation: 3
+  eval_image_augs:
+    _target_: torchvision.transforms.Compose
+    transforms:
+      - _target_: torchvision.transforms.Resize
+        size: 224
+        interpolation: 3
+
+optimizer:
+  _target_: torch.optim.AdamW
+  _partial_: true
+  lr: 5e-4
+  betas: [0.9, 0.999]
+  eps: 1e-8
+  weight_decay: 0.0
+
+scheduler:
+  _target_: transformers.get_cosine_schedule_with_warmup
+  _partial_: true
+  num_warmup_steps: 1000
+  num_training_steps: 100000
+  num_cycles: 0.5