Simplify configs (#550)

Co-authored-by: Remi <remi.cadene@huggingface.co>
Co-authored-by: HUANG TZU-CHUN <137322177+tc-huang@users.noreply.github.com>

lerobot/configs/default.py

@@ -0,0 +1,66 @@
+#!/usr/bin/env python
+
+# 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.
+
+from dataclasses import dataclass, field
+
+from lerobot.common import (
+    policies,  # noqa: F401
+)
+from lerobot.common.datasets.transforms import ImageTransformsConfig
+
+
+@dataclass
+class DatasetConfig:
+    # You may provide a list of datasets here. `train.py` creates them all and concatenates them. Note: only data
+    # keys common between the datasets are kept. Each dataset gets and additional transform that inserts the
+    # "dataset_index" into the returned item. The index mapping is made according to the order in which the
+    # datsets are provided.
+    repo_id: str
+    episodes: list[int] | None = None
+    image_transforms: ImageTransformsConfig = field(default_factory=ImageTransformsConfig)
+    local_files_only: bool = False
+    use_imagenet_stats: bool = True
+    video_backend: str = "pyav"
+
+
+@dataclass
+class WandBConfig:
+    enable: bool = False
+    # Set to true to disable saving an artifact despite training.save_checkpoint=True
+    disable_artifact: bool = False
+    project: str = "lerobot"
+    entity: str | None = None
+    notes: str | None = None
+
+
+@dataclass
+class EvalConfig:
+    n_episodes: int = 50
+    # `batch_size` specifies the number of environments to use in a gym.vector.VectorEnv.
+    batch_size: int = 50
+    # `use_async_envs` specifies whether to use asynchronous environments (multiprocessing).
+    use_async_envs: bool = False
+
+    def __post_init__(self):
+        if self.batch_size > self.n_episodes:
+            raise ValueError(
+                "The eval batch size is greater than the number of eval episodes "
+                f"({self.batch_size} > {self.n_episodes}). As a result, {self.batch_size} "
+                f"eval environments will be instantiated, but only {self.n_episodes} will be used. "
+                "This might significantly slow down evaluation. To fix this, you should update your command "
+                f"to increase the number of episodes to match the batch size (e.g. `eval.n_episodes={self.batch_size}`), "
+                f"or lower the batch size (e.g. `eval.batch_size={self.n_episodes}`)."
+            )