# Copyright 2022 Cerebras Systems.
#
# 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.
"""
This module contains the implementation of the DataLoader callback class.
"""
from contextlib import contextmanager
from cerebras.modelzoo.trainer.callbacks import Callback
from cerebras.pytorch.utils.nest import visit_torch_tensors
[docs]class DataLoaderCallback(Callback):
"""
Callback class that handles saving and loading dataloader state
to the checkpoint.
"""
def __init__(self):
"""
Attributes:
dataloader: The training dataloader object to save to the checkpoint.
"""
self.dataloader = None
def on_enter_fit(
self, trainer, stack, train_dataloader, val_dataloader, loop
):
@contextmanager
def store_dataloader():
# pylint: disable=attribute-defined-outside-init
try:
self.dataloader = train_dataloader
yield
finally:
self.dataloader = None
stack.enter_context(store_dataloader())
def on_save_checkpoint(self, trainer, state_dict):
if self.dataloader is not None and self.dataloader.is_restartable:
state_dict["dataloader"] = self.dataloader.state_dict()
def on_load_checkpoint(self, trainer, state_dict):
if self.dataloader is not None and self.dataloader.is_restartable:
if "dataloader" in state_dict:
self.dataloader.load_state_dict(state_dict["dataloader"])
trainer.logger.info(
f"Dataloader state found in checkpoint and loaded successfully."
)
else:
trainer.logger.info(
"Dataloader state not found in the checkpoint. "
"DataLoaders will yield samples from the beginning."
)