66 lines
2.6 KiB
Python
66 lines
2.6 KiB
Python
# Copyright 2024 The HuggingFace Inc. team. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import datetime as dt
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import logging
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from dataclasses import dataclass, field
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from pathlib import Path
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from lerobot.common import envs, policies # noqa: F401
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from lerobot.configs import parser
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from lerobot.configs.default import EvalConfig
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from lerobot.configs.policies import PreTrainedConfig
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@dataclass
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class EvalPipelineConfig:
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# Either the repo ID of a model hosted on the Hub or a path to a directory containing weights
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# saved using `Policy.save_pretrained`. If not provided, the policy is initialized from scratch
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# (useful for debugging). This argument is mutually exclusive with `--config`.
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env: envs.EnvConfig
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eval: EvalConfig = field(default_factory=EvalConfig)
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policy: PreTrainedConfig | None = None
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output_dir: Path | None = None
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job_name: str | None = None
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seed: int | None = 1000
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def __post_init__(self):
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# HACK: We parse again the cli args here to get the pretrained path if there was one.
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policy_path = parser.get_path_arg("policy")
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if policy_path:
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cli_overrides = parser.get_cli_overrides("policy")
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self.policy = PreTrainedConfig.from_pretrained(policy_path, cli_overrides=cli_overrides)
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self.policy.pretrained_path = policy_path
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else:
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logging.warning(
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"No pretrained path was provided, evaluated policy will be built from scratch (random weights)."
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)
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if not self.job_name:
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if self.env is None:
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self.job_name = f"{self.policy.type}"
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else:
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self.job_name = f"{self.env.type}_{self.policy.type}"
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if not self.output_dir:
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now = dt.datetime.now()
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eval_dir = f"{now:%Y-%m-%d}/{now:%H-%M-%S}_{self.job_name}"
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self.output_dir = Path("outputs/eval") / eval_dir
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@classmethod
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def __get_path_fields__(cls) -> list[str]:
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"""This enables the parser to load config from the policy using `--policy.path=local/dir`"""
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return ["policy"]
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