chore: move constants to utils (#2016)

src/lerobot/utils/constants.py

@@ -0,0 +1,68 @@
+# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# keys
+import os
+from pathlib import Path
+
+from huggingface_hub.constants import HF_HOME
+
+OBS_ENV_STATE = "observation.environment_state"
+OBS_STATE = "observation.state"
+OBS_IMAGE = "observation.image"
+OBS_IMAGES = "observation.images"
+OBS_LANGUAGE = "observation.language"
+ACTION = "action"
+REWARD = "next.reward"
+TRUNCATED = "next.truncated"
+DONE = "next.done"
+
+OBS_LANGUAGE_TOKENS = OBS_LANGUAGE + ".tokens"
+OBS_LANGUAGE_ATTENTION_MASK = OBS_LANGUAGE + ".attention_mask"
+
+ROBOTS = "robots"
+ROBOT_TYPE = "robot_type"
+TELEOPERATORS = "teleoperators"
+
+# files & directories
+CHECKPOINTS_DIR = "checkpoints"
+LAST_CHECKPOINT_LINK = "last"
+PRETRAINED_MODEL_DIR = "pretrained_model"
+TRAINING_STATE_DIR = "training_state"
+RNG_STATE = "rng_state.safetensors"
+TRAINING_STEP = "training_step.json"
+OPTIMIZER_STATE = "optimizer_state.safetensors"
+OPTIMIZER_PARAM_GROUPS = "optimizer_param_groups.json"
+SCHEDULER_STATE = "scheduler_state.json"
+
+POLICY_PREPROCESSOR_DEFAULT_NAME = "policy_preprocessor"
+POLICY_POSTPROCESSOR_DEFAULT_NAME = "policy_postprocessor"
+
+if "LEROBOT_HOME" in os.environ:
+    raise ValueError(
+        f"You have a 'LEROBOT_HOME' environment variable set to '{os.getenv('LEROBOT_HOME')}'.\n"
+        "'LEROBOT_HOME' is deprecated, please use 'HF_LEROBOT_HOME' instead."
+    )
+
+# cache dir
+default_cache_path = Path(HF_HOME) / "lerobot"
+HF_LEROBOT_HOME = Path(os.getenv("HF_LEROBOT_HOME", default_cache_path)).expanduser()
+
+# calibration dir
+default_calibration_path = HF_LEROBOT_HOME / "calibration"
+HF_LEROBOT_CALIBRATION = Path(os.getenv("HF_LEROBOT_CALIBRATION", default_calibration_path)).expanduser()
+
+
+# streaming datasets
+LOOKBACK_BACKTRACKTABLE = 100
+LOOKAHEAD_BACKTRACKTABLE = 100

src/lerobot/utils/random_utils.py

@@ -23,8 +23,8 @@ import numpy as np
 import torch
 from safetensors.torch import load_file, save_file
 
-from lerobot.constants import RNG_STATE
 from lerobot.datasets.utils import flatten_dict, unflatten_dict
+from lerobot.utils.constants import RNG_STATE
 
 
 def serialize_python_rng_state() -> dict[str, torch.Tensor]:

src/lerobot/utils/train_utils.py

@@ -21,18 +21,18 @@ from torch.optim import Optimizer
 from torch.optim.lr_scheduler import LRScheduler
 
 from lerobot.configs.train import TrainPipelineConfig
-from lerobot.constants import (
+from lerobot.datasets.utils import load_json, write_json
+from lerobot.optim.optimizers import load_optimizer_state, save_optimizer_state
+from lerobot.optim.schedulers import load_scheduler_state, save_scheduler_state
+from lerobot.policies.pretrained import PreTrainedPolicy
+from lerobot.processor import PolicyProcessorPipeline
+from lerobot.utils.constants import (
     CHECKPOINTS_DIR,
     LAST_CHECKPOINT_LINK,
     PRETRAINED_MODEL_DIR,
     TRAINING_STATE_DIR,
     TRAINING_STEP,
 )
-from lerobot.datasets.utils import load_json, write_json
-from lerobot.optim.optimizers import load_optimizer_state, save_optimizer_state
-from lerobot.optim.schedulers import load_scheduler_state, save_scheduler_state
-from lerobot.policies.pretrained import PreTrainedPolicy
-from lerobot.processor import PolicyProcessorPipeline
 from lerobot.utils.random_utils import load_rng_state, save_rng_state
 
 

src/lerobot/utils/wandb_utils.py

@@ -23,7 +23,7 @@ from huggingface_hub.constants import SAFETENSORS_SINGLE_FILE
 from termcolor import colored
 
 from lerobot.configs.train import TrainPipelineConfig
-from lerobot.constants import PRETRAINED_MODEL_DIR
+from lerobot.utils.constants import PRETRAINED_MODEL_DIR
 
 
 def cfg_to_group(cfg: TrainPipelineConfig, return_list: bool = False) -> list[str] | str: