File size: 2,428 Bytes
aa048fe | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 | # Copyright 2025 Optuna, HuggingFace Inc. and the LlamaFactory team.
#
# This code is inspired by the HuggingFace's transformers library.
# https://github.com/huggingface/transformers/blob/v5.0.0rc0/src/transformers/utils/logging.py
#
# 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 .types import ModelInput
class StatefulBuffer:
"""A buffer that stores model inputs."""
def __init__(self, max_buffer_size: int = 1_000_000_000) -> None:
self._buffer: list[ModelInput] = []
self._buffer_size: int = 0
self._max_buffer_size: int = max_buffer_size
def __len__(self) -> int:
return len(self._buffer)
@property
def size(self) -> int:
return self._buffer_size
def put(self, samples: list[ModelInput]) -> None:
"""Add samples to the buffer."""
num_tokens = sum(len(sample["input_ids"]) for sample in samples)
if self._buffer_size + num_tokens > self._max_buffer_size:
raise ValueError(f"Buffer size exceeds max buffer size {self._max_buffer_size}.")
self._buffer.extend(samples)
self._buffer_size += num_tokens
def get(self, value: int) -> list[ModelInput]:
"""Get samples from the buffer and remove them."""
samples = self._buffer[:value]
self._buffer_size -= sum(len(sample["input_ids"]) for sample in samples)
del self._buffer[:value]
return samples
def clear(self) -> None:
"""Clear the buffer."""
self._buffer = []
self._buffer_size = 0
def state_dict(self) -> dict:
"""Returns the state of the buffer."""
return {
"buffer": self._buffer,
"buffer_size": self._buffer_size,
}
def load_state_dict(self, state_dict: dict) -> None:
"""Loads the state into the buffer."""
self._buffer = state_dict["buffer"]
self._buffer_size = state_dict["buffer_size"]
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