'''simple docstring'''




import operator as op


_lowercase		:				List[Any]	       =		"scaler.pt"
_lowercase		:				int	       =		"pytorch_model"
_lowercase		:				str	       =		"random_states"
_lowercase		:				int	       =		"optimizer"
_lowercase		:				List[Any]	       =		"scheduler"
_lowercase		:				Tuple	       =		"pytorch_model.bin"
_lowercase		:				Tuple	       =		"pytorch_model.bin.index.json"
_lowercase		:				Dict	       =		"model.safetensors"
_lowercase		:				List[Any]	       =		"model.safetensors.index.json"
_lowercase		:				List[Any]	       =		"1.10.2"
_lowercase		:				Optional[Any]	       =		"py38"
_lowercase		:				Optional[Any]	       =		"4.17.0"
_lowercase		:				List[str]	       =		["ml.p3.16xlarge", "ml.p3dn.24xlarge", "ml.p4dn.24xlarge"]
_lowercase		:				Any	       =		["FULL_SHARD", "SHARD_GRAD_OP", "NO_SHARD", "HYBRID_SHARD", "HYBRID_SHARD_ZERO2"]
_lowercase		:				Union[str, Any]	       =		["TRANSFORMER_BASED_WRAP", "SIZE_BASED_WRAP", "NO_WRAP"]
_lowercase		:				List[str]	       =		["BACKWARD_PRE", "BACKWARD_POST", "NO_PREFETCH"]
_lowercase		:				List[str]	       =		["FULL_STATE_DICT", "LOCAL_STATE_DICT", "SHARDED_STATE_DICT"]
_lowercase		:				Dict	       =		"2.0.1"
_lowercase		:				Tuple	       =		["pdsh", "standard", "openmpi", "mvapich"]
_lowercase		:				Dict	       =		["default", "reduce-overhead", "max-autotune"]

_lowercase		:				Optional[int]	       =		{">": op.gt, ">=": op.ge, "==": op.eq, "!=": op.ne, "<=": op.le, "<": op.lt}

# These are the args for `torch.distributed.launch` for pytorch < 1.9
_lowercase		:				Any	       =		[
    "nnodes",
    "nproc_per_node",
    "rdzv_backend",
    "rdzv_endpoint",
    "rdzv_id",
    "rdzv_conf",
    "standalone",
    "max_restarts",
    "monitor_interval",
    "start_method",
    "role",
    "module",
    "m",
    "no_python",
    "run_path",
    "log_dir",
    "r",
    "redirects",
    "t",
    "tee",
    "node_rank",
    "master_addr",
    "master_port",
]

_lowercase		:				Union[str, Any]	       =		["DEEPSPEED", "MULTI_GPU", "FSDP", "MEGATRON_LM"]
_lowercase		:				Any	       =		["DEEPSPEED", "MULTI_XPU", "FSDP"]






'''simple docstring'''




import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate





@dataclass(frozen=_UpperCAmelCase)
class 					__magic_name__		(					_UpperCAmelCase):
			UpperCamelCase__       = field(default='''image-classification''',  metadata={'''include_in_asdict_even_if_is_default''': True})
			UpperCamelCase__       = Features({'''image''': Image()})
			UpperCamelCase__       = Features({'''labels''': ClassLabel})
			UpperCamelCase__       = "image"
			UpperCamelCase__       = "labels"







			def 			SCREAMING_SNAKE_CASE_  (			self       :						Tuple       ,    lowercase_       :						str					):
										if self.label_column not in features:
																	raise ValueError(f'''Column {self.label_column} is not present in features.'''					)
										if not isinstance(features[self.label_column]       ,    lowercase_					):
																	raise ValueError(f'''Column {self.label_column} is not a ClassLabel.'''					)
										lowercase_      :    List[str]       		= copy.deepcopy(self					)
										lowercase_      :    List[str]       		= self.label_schema.copy()
										lowercase_      :    List[Any]       		= features[self.label_column]
										lowercase_      :    Optional[Any]       		= label_schema
										return task_template







			@property
			def 			SCREAMING_SNAKE_CASE_  (			self       :						int					):
										return {
										    self.image_column: "image",
										    self.label_column: "labels",
										}





