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Zero
| # Copyright (c) 2025 Bytedance Ltd. and/or its affiliates | |
| # 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 functools import partial | |
| import torch | |
| from torch.distributed.fsdp import FullyShardedDataParallel as FSDP | |
| from torch.distributed.fsdp import MixedPrecision, ShardingStrategy | |
| from torch.distributed.fsdp.wrap import lambda_auto_wrap_policy | |
| def shard_model( | |
| model, | |
| device_id, | |
| param_dtype=torch.bfloat16, | |
| reduce_dtype=torch.float32, | |
| buffer_dtype=torch.float32, | |
| process_group=None, | |
| sharding_strategy=ShardingStrategy.FULL_SHARD, | |
| sync_module_states=True, | |
| ): | |
| model = FSDP( | |
| module=model, | |
| process_group=process_group, | |
| sharding_strategy=sharding_strategy, | |
| auto_wrap_policy=partial( | |
| lambda_auto_wrap_policy, lambda_fn=lambda m: m in model.blocks), | |
| mixed_precision=MixedPrecision( | |
| param_dtype=param_dtype, | |
| reduce_dtype=reduce_dtype, | |
| buffer_dtype=buffer_dtype), | |
| device_id=device_id, | |
| sync_module_states=sync_module_states) | |
| return model | |