File size: 8,679 Bytes
bceceb3 7a76c8f bceceb3 7a76c8f bceceb3 7a76c8f bceceb3 7a76c8f bceceb3 7a76c8f bceceb3 7a76c8f bceceb3 7a76c8f bceceb3 |
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 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 |
#!/usr/bin/env python
hf_cache_home = os.path.expanduser(
os.getenv("HF_HOME", os.path.join(os.getenv("XDG_CACHE_HOME", "~/.cache"), "huggingface"))
)
cache_dir = os.path.join(hf_cache_home, "accelerate")
default_json_config_file = os.path.join(cache_dir, "default_config.yaml")
default_yaml_config_file = os.path.join(cache_dir, "default_config.yaml")
# For backward compatibility: the default config is the json one if it's the only existing file.
if os.path.isfile(default_yaml_config_file) or not os.path.isfile(default_json_config_file):
default_config_file = default_yaml_config_file
else:
default_config_file = default_json_config_file
def load_config_from_file(config_file):
if config_file is not None:
if not os.path.isfile(config_file):
raise FileNotFoundError(
f"The passed configuration file `{config_file}` does not exist. "
"Please pass an existing file to `accelerate launch`, or use the the default one "
"created through `accelerate config` and run `accelerate launch` "
"without the `--config_file` argument."
)
else:
config_file = default_config_file
with open(config_file, "r", encoding="utf-8") as f:
if config_file.endswith(".json"):
if (
json.load(f).get("compute_environment", ComputeEnvironment.LOCAL_MACHINE)
== ComputeEnvironment.LOCAL_MACHINE
):
config_class = ClusterConfig
else:
config_class = SageMakerConfig
return config_class.from_json_file(json_file=config_file)
else:
if (
yaml.safe_load(f).get("compute_environment", ComputeEnvironment.LOCAL_MACHINE)
== ComputeEnvironment.LOCAL_MACHINE
):
config_class = ClusterConfig
else:
config_class = SageMakerConfig
return config_class.from_yaml_file(yaml_file=config_file)
@dataclass
class BaseConfig:
compute_environment: ComputeEnvironment
distributed_type: Union[DistributedType, SageMakerDistributedType]
mixed_precision: str
use_cpu: bool
debug: bool
def to_dict(self):
result = self.__dict__
# For serialization, it's best to convert Enums to strings (or their underlying value type).
for key, value in result.items():
if isinstance(value, Enum):
result[key] = value.value
if isinstance(value, dict) and not bool(value):
result[key] = None
result = {k: v for k, v in result.items() if v is not None}
return result
@classmethod
def from_json_file(cls, json_file=None):
json_file = default_json_config_file if json_file is None else json_file
with open(json_file, "r", encoding="utf-8") as f:
config_dict = json.load(f)
if "compute_environment" not in config_dict:
config_dict["compute_environment"] = ComputeEnvironment.LOCAL_MACHINE
if "mixed_precision" not in config_dict:
config_dict["mixed_precision"] = "fp16" if ("fp16" in config_dict and config_dict["fp16"]) else None
if "fp16" in config_dict: # Convert the config to the new format.
del config_dict["fp16"]
if "dynamo_backend" in config_dict: # Convert the config to the new format.
dynamo_backend = config_dict.pop("dynamo_backend")
config_dict["dynamo_config"] = {} if dynamo_backend == "NO" else {"dynamo_backend": dynamo_backend}
if "use_cpu" not in config_dict:
config_dict["use_cpu"] = False
if "debug" not in config_dict:
config_dict["debug"] = False
extra_keys = sorted(set(config_dict.keys()) - set(cls.__dataclass_fields__.keys()))
if len(extra_keys) > 0:
raise ValueError(
f"The config file at {json_file} had unknown keys ({extra_keys}), please try upgrading your `accelerate`"
" version or fix (and potentially remove) these keys from your config file."
)
return cls(**config_dict)
def to_json_file(self, json_file):
with open(json_file, "w", encoding="utf-8") as f:
content = json.dumps(self.to_dict(), indent=2, sort_keys=True) + "\n"
f.write(content)
@classmethod
def from_yaml_file(cls, yaml_file=None):
yaml_file = default_yaml_config_file if yaml_file is None else yaml_file
with open(yaml_file, "r", encoding="utf-8") as f:
config_dict = yaml.safe_load(f)
if "compute_environment" not in config_dict:
config_dict["compute_environment"] = ComputeEnvironment.LOCAL_MACHINE
if "mixed_precision" not in config_dict:
config_dict["mixed_precision"] = "fp16" if ("fp16" in config_dict and config_dict["fp16"]) else None
if isinstance(config_dict["mixed_precision"], bool) and not config_dict["mixed_precision"]:
config_dict["mixed_precision"] = "no"
if "fp16" in config_dict: # Convert the config to the new format.
del config_dict["fp16"]
if "dynamo_backend" in config_dict: # Convert the config to the new format.
dynamo_backend = config_dict.pop("dynamo_backend")
config_dict["dynamo_config"] = {} if dynamo_backend == "NO" else {"dynamo_backend": dynamo_backend}
if "use_cpu" not in config_dict:
config_dict["use_cpu"] = False
if "debug" not in config_dict:
config_dict["debug"] = False
extra_keys = sorted(set(config_dict.keys()) - set(cls.__dataclass_fields__.keys()))
if len(extra_keys) > 0:
raise ValueError(
f"The config file at {yaml_file} had unknown keys ({extra_keys}), please try upgrading your `accelerate`"
" version or fix (and potentially remove) these keys from your config file."
)
return cls(**config_dict)
def to_yaml_file(self, yaml_file):
with open(yaml_file, "w", encoding="utf-8") as f:
yaml.safe_dump(self.to_dict(), f)
def __post_init__(self):
if isinstance(self.compute_environment, str):
self.compute_environment = ComputeEnvironment(self.compute_environment)
if isinstance(self.distributed_type, str):
if self.compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
self.distributed_type = SageMakerDistributedType(self.distributed_type)
else:
self.distributed_type = DistributedType(self.distributed_type)
if self.dynamo_config is None:
self.dynamo_config = {}
@dataclass
class ClusterConfig(BaseConfig):
num_processes: int
machine_rank: int = 0
num_machines: int = 1
gpu_ids: Optional[str] = None
main_process_ip: Optional[str] = None
main_process_port: Optional[int] = None
rdzv_backend: Optional[str] = "static"
same_network: Optional[bool] = False
main_training_function: str = "main"
# args for deepspeed_plugin
deepspeed_config: dict = None
# args for fsdp
fsdp_config: dict = None
# args for megatron_lm
megatron_lm_config: dict = None
# args for ipex
ipex_config: dict = None
# args for TPU
downcast_bf16: bool = False
# args for TPU pods
tpu_name: str = None
tpu_zone: str = None
tpu_use_cluster: bool = False
tpu_use_sudo: bool = False
command_file: str = None
commands: List[str] = None
tpu_vm: List[str] = None
tpu_env: List[str] = None
# args for dynamo
dynamo_config: dict = None
def __post_init__(self):
if self.deepspeed_config is None:
self.deepspeed_config = {}
if self.fsdp_config is None:
self.fsdp_config = {}
if self.megatron_lm_config is None:
self.megatron_lm_config = {}
if self.ipex_config is None:
self.ipex_config = {}
return super().__post_init__()
@dataclass
class SageMakerConfig(BaseConfig):
ec2_instance_type: str
iam_role_name: str
image_uri: Optional[str] = None
profile: Optional[str] = None
region: str = "us-east-1"
num_machines: int = 1
gpu_ids: str = "all"
base_job_name: str = f"accelerate-sagemaker-{num_machines}"
pytorch_version: str = SAGEMAKER_PYTORCH_VERSION
transformers_version: str = SAGEMAKER_TRANSFORMERS_VERSION
py_version: str = SAGEMAKER_PYTHON_VERSION
sagemaker_inputs_file: str = None
sagemaker_metrics_file: str = None
additional_args: dict = None
dynamo_config: dict = None
|