mirror of
https://github.com/huggingface/lerobot.git
synced 2026-07-30 21:19:40 +00:00
Steven Palma
7e0fd0d653
* refactor(types): change module name Co-authored-by: saiteja6006 <saiteja6006@gmail.com> * chore(test): remove package import test * chore: remove ruff exception --------- Co-authored-by: saiteja6006 <saiteja6006@gmail.com>
98 lines
3.1 KiB
Python
98 lines
3.1 KiB
Python
# Copyright 2026 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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from __future__ import annotations
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import abc
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from lerobot.lerobot_types import BatchType
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from ..buffer import ReplayBuffer, concatenate_batch_transitions
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class DataMixer(abc.ABC):
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"""Abstract interface for all data mixing strategies."""
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@abc.abstractmethod
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def sample(self, batch_size: int) -> BatchType:
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"""Draw one batch of ``batch_size`` transitions."""
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raise NotImplementedError
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def get_iterator(
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self,
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batch_size: int,
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async_prefetch: bool = True,
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queue_size: int = 2,
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):
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"""Infinite iterator that yields batches."""
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while True:
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yield self.sample(batch_size)
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class OnlineOfflineMixer(DataMixer):
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"""Mixes transitions from an online and an offline replay buffer."""
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def __init__(
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self,
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online_buffer: ReplayBuffer,
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offline_buffer: ReplayBuffer | None = None,
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online_ratio: float = 1.0,
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):
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if not 0.0 <= online_ratio <= 1.0:
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raise ValueError(f"online_ratio must be in [0, 1], got {online_ratio}")
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self.online_buffer = online_buffer
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self.offline_buffer = offline_buffer
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self.online_ratio = online_ratio
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def sample(self, batch_size: int) -> BatchType:
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if self.offline_buffer is None:
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return self.online_buffer.sample(batch_size)
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n_online = max(1, int(batch_size * self.online_ratio))
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n_offline = batch_size - n_online
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online_batch = self.online_buffer.sample(n_online)
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offline_batch = self.offline_buffer.sample(n_offline)
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return concatenate_batch_transitions(online_batch, offline_batch)
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def get_iterator(
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self,
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batch_size: int,
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async_prefetch: bool = True,
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queue_size: int = 2,
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):
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"""Yield batches by composing buffer async iterators."""
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n_online = max(1, int(batch_size * self.online_ratio))
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online_iter = self.online_buffer.get_iterator(
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batch_size=n_online,
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async_prefetch=async_prefetch,
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queue_size=queue_size,
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)
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if self.offline_buffer is None:
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yield from online_iter
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return
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n_offline = batch_size - n_online
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offline_iter = self.offline_buffer.get_iterator(
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batch_size=n_offline,
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async_prefetch=async_prefetch,
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queue_size=queue_size,
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)
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while True:
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yield concatenate_batch_transitions(next(online_iter), next(offline_iter))
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