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#!/usr/bin/env python
# Copyright 2025 The HuggingFace Team. All rights reserved.
#
# 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.
import enum
import logging
from pathlib import Path
import yaml
from accelerate.commands.utils import CustomArgumentParser
class ConversionStatus(enum.Enum):
NOT_YET_IMPLEMENTED = 0
REMOVED = -1
ARGUMENT_KEY_MAPPING = {
# New keys in FSDP2
"fsdp_version": "fsdp_version",
"fsdp_reshard_after_forward": "fsdp_reshard_after_forward",
# https://github.com/pytorch/torchtitan/blob/main/docs/fsdp.md
# https://huggingface.co/docs/accelerate/en/usage_guides/fsdp
"fsdp_auto_wrap_policy": "fsdp_auto_wrap_policy",
"fsdp_backward_prefetch": ConversionStatus.REMOVED,
"fsdp_forward_prefetch": ConversionStatus.NOT_YET_IMPLEMENTED,
"fsdp_cpu_ram_efficient_loading": "fsdp_cpu_ram_efficient_loading",
"fsdp_offload_params": "fsdp_offload_params",
"fsdp_sharding_strategy": "fsdp_reshard_after_forward",
"fsdp_state_dict_type": "fsdp_state_dict_type",
"fsdp_sync_module_states": ConversionStatus.REMOVED,
"fsdp_transformer_layer_cls_to_wrap": "fsdp_transformer_layer_cls_to_wrap",
"fsdp_min_num_params": "fsdp_min_num_params",
"fsdp_use_orig_params": ConversionStatus.REMOVED,
"fsdp_activation_checkpointing": "fsdp_activation_checkpointing",
}
ARGUMENT_VALUE_MAPPING = {
"fsdp_sharding_strategy": {
"FULL_SHARD": True,
"SHARD_GRAD_OP": False,
"HYBRID_SHARD": True,
"HYBRID_SHARD_ZERO2": False,
"NO_SHARD": False,
},
"fsdp_reshard_after_forward": { # Needed to convert newly created configs using FSDP1 to FSDP2
"FULL_SHARD": True,
"SHARD_GRAD_OP": False,
"HYBRID_SHARD": True,
"HYBRID_SHARD_ZERO2": False,
"NO_SHARD": False,
},
}
logger = logging.getLogger(__name__)
def _validate_to_fsdp2_args(args):
if not Path(args.config_file).exists():
raise FileNotFoundError(f"Config file {args.config_file} not found")
if not args.overwrite and args.output_file is None:
raise ValueError("If --overwrite is not set, --output_file must be provided")
if not args.overwrite and Path(args.output_file).exists():
raise FileExistsError(f"Output file {args.output_file} already exists and --overwrite is not set")
def convert_config_to_fsdp2(config: dict) -> dict:
fsdp_config = config.get("fsdp_config", {})
if not fsdp_config:
logger.info("No FSDP config found in the config file, skipping conversion...")
return config
new_fsdp_config = {}
if fsdp_config.get("fsdp_version", 1) == 2:
logger.warning("Config already specfies FSDP2, skipping conversion...")
logger.warning(
"If the config doesn't use new argument names, change `fsdp_version` to `1` and rerun the command."
)
return config
for key, value in fsdp_config.items():
conversion_status = ARGUMENT_KEY_MAPPING.get(key, None)
if isinstance(conversion_status, ConversionStatus) or conversion_status is None:
conversion_status = key
new_fsdp_config[conversion_status] = value
continue
if conversion_status == ConversionStatus.REMOVED:
logger.warning(f"Argument {key} has been removed in FSDP2, skipping this key...")
continue
if conversion_status == ConversionStatus.NOT_YET_IMPLEMENTED:
logger.warning(f"Argument {key} is not yet implemented in FSDP2, skipping this key...")
continue
if conversion_status is None:
logger.warning(f"Argument {key} is not being converted, skipping this key...")
new_fsdp_config[key] = value
else:
if key in ARGUMENT_VALUE_MAPPING:
value = ARGUMENT_VALUE_MAPPING[key].get(value, value)
new_fsdp_config[ARGUMENT_KEY_MAPPING[key]] = value
new_fsdp_config["fsdp_version"] = 2
config["fsdp_config"] = new_fsdp_config
return config
def to_fsdp2_command_parser(subparsers=None):
description = "Convert an Accelerate config from FSDP1 to FSDP2"
if subparsers is not None:
parser = subparsers.add_parser("to-fsdp2", description=description)
else:
parser = CustomArgumentParser(description=description)
parser.add_argument("--config_file", type=str, help="The config file to convert to FSDP2", required=True)
parser.add_argument(
"--overwrite",
action="store_true",
help="Overwrite the config file if it exists",
default=False,
)
parser.add_argument(
"--output_file",
type=str,
help="The path to the output file to write the converted config to. If not provided, the input file will be overwritten (if --overwrite is set)",
default=None,
)
if subparsers is not None:
parser.set_defaults(func=to_fsdp2_command)
return parser
def load_config(config_file: str) -> dict:
with open(config_file) as f:
config = yaml.safe_load(f)
if not config:
raise ValueError("Config file is empty")
return config
def to_fsdp2_command(args):
_validate_to_fsdp2_args(args)
config = load_config(args.config_file)
if args.overwrite and args.output_file is None:
args.output_file = args.config_file
new_config = convert_config_to_fsdp2(config)
with open(args.output_file, "w") as f:
yaml.dump(new_config, f)
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