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# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved. | |
# SPDX-License-Identifier: Apache-2.0 | |
# | |
# 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 cosmos_predict1.diffusion.training.utils.checkpointer import MultiRankCheckpointer | |
from cosmos_predict1.utils.fsdp_checkpointer import FSDPCheckpointer | |
from cosmos_predict1.utils.trainer import Trainer as BaseTrainer | |
class Trainer(BaseTrainer): | |
def __init__(self, config): | |
super(Trainer, self).__init__(config) | |
if config.trainer.distributed_parallelism == "ddp": | |
self.checkpointer = MultiRankCheckpointer(config.checkpoint, config.job, callbacks=self.callbacks) | |
elif config.trainer.distributed_parallelism == "fsdp": | |
self.checkpointer = FSDPCheckpointer(config.checkpoint, config.job, callbacks=self.callbacks) | |
else: | |
raise ValueError(f"Unsupported distributed parallelism: {config.trainer.distributed_parallelism}") | |