"""simple docstring"""






# Copyright 2021 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 argparse

from ...utils.dataclasses import (
    ComputeEnvironment,
    DistributedType,
    DynamoBackend,
    PrecisionType,
    SageMakerDistributedType,
)
from ..menu import BulletMenu


lowerCAmelCase__  :  Tuple						     =	[
    'EAGER',
    'AOT_EAGER',
    'INDUCTOR',
    'NVFUSER',
    'AOT_NVFUSER',
    'AOT_CUDAGRAPHS',
    'OFI',
    'FX2TRT',
    'ONNXRT',
    'IPEX',
]



def   a_						(					lowerCamelCase					,			lowerCamelCase=None					,			lowerCamelCase=None					,			lowerCamelCase=None       ):
				UpperCAmelCase__             =							True
				while ask_again:
								UpperCAmelCase__             =							input(lowerCamelCase       )
								try:
												if default is not None and len(lowerCamelCase       ) == 0:
																return default
												return convert_value(lowerCamelCase       ) if convert_value is not None else result
								except Exception:
												if error_message is not None:
																print(lowerCamelCase       )



def   a_						(					lowerCamelCase					,			lowerCamelCase=[]					,			lowerCamelCase=None					,			lowerCamelCase=0       ):
				UpperCAmelCase__             =							BulletMenu(lowerCamelCase					,			lowerCamelCase       )
				UpperCAmelCase__             =							menu.run(default_choice=lowerCamelCase       )
				return convert_value(lowerCamelCase       ) if convert_value is not None else result



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							int(lowerCamelCase       )
				return ComputeEnvironment(['LOCAL_MACHINE', 'AMAZON_SAGEMAKER'][value]       )



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							int(lowerCamelCase       )
				return DistributedType(['NO', 'MULTI_CPU', 'MULTI_XPU', 'MULTI_GPU', 'MULTI_NPU', 'TPU'][value]       )



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							int(lowerCamelCase       )
				return DynamoBackend(DYNAMO_BACKENDS[value]       ).value



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							int(lowerCamelCase       )
				return PrecisionType(['no', 'fp16', 'bf16', 'fp8'][value]       )



def   a_						(					lowerCamelCase       ):
				UpperCAmelCase__             =							int(lowerCamelCase       )
				return SageMakerDistributedType(['NO', 'DATA_PARALLEL', 'MODEL_PARALLEL'][value]       )



def   a_						(					lowerCamelCase       ):
				return {"yes": True, "no": False}[value.lower()]







class 				snake_case       ( argparse.RawDescriptionHelpFormatter				):




					"""simple docstring"""

					def 		__lowerCAmelCase						(				self   :	Tuple    ,lowerCamelCase__   :	List[Any]    ,lowerCamelCase__   :	Dict    ,lowerCamelCase__   :	List[str]    ,lowerCamelCase__   :	Optional[int]			):
									UpperCAmelCase__             =							super()._format_usage(lowerCamelCase__    ,lowerCamelCase__    ,lowerCamelCase__    ,lowerCamelCase__			)
									UpperCAmelCase__             =							usage.replace('<command> [<args>] '    ,''			)
									return usage








from collections import OrderedDict
from typing import Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A__  :  int								=					logging.get_logger(__name__)

A__  :  Optional[int]								=					{
    '''facebook/data2vec-vision-base-ft''': (
        '''https://huggingface.co/facebook/data2vec-vision-base-ft/resolve/main/config.json'''
    ),
}



class 				__snake_case						(     UpperCamelCase_						):
							_a			      = '''data2vec-vision'''




							def __init__(       self     :       Tuple				,				A_     :       List[Any]=7_6_8				,				A_     :       Union[str, Any]=1_2				,				A_     :       Dict=1_2				,				A_     :       List[Any]=3_0_7_2				,				A_     :       Dict="gelu"				,				A_     :       Tuple=0.0				,				A_     :       Dict=0.0				,				A_     :       List[str]=0.02				,				A_     :       List[str]=1e-12				,				A_     :       Tuple=2_2_4				,				A_     :       Dict=1_6				,				A_     :       Optional[int]=3				,				A_     :       Optional[int]=False				,				A_     :       Any=False				,				A_     :       Tuple=False				,				A_     :       Optional[int]=False				,				A_     :       int=0.1				,				A_     :       Union[str, Any]=0.1				,				A_     :       List[Any]=True				,				A_     :       List[Any]=[3, 5, 7, 1_1]				,				A_     :       Union[str, Any]=[1, 2, 3, 6]				,				A_     :       Optional[int]=True				,				A_     :       Any=0.4				,				A_     :       str=2_5_6				,				A_     :       Optional[int]=1				,				A_     :       str=False				,				A_     :       Optional[int]=2_5_5				,				**A_     :       Optional[int]				,				):
									super().__init__(**A_)

									lowerCAmelCase_			:     str									= hidden_size
									lowerCAmelCase_			:     List[str]									= num_hidden_layers
									lowerCAmelCase_			:     Optional[Any]									= num_attention_heads
									lowerCAmelCase_			:     int									= intermediate_size
									lowerCAmelCase_			:     Union[str, Any]									= hidden_act
									lowerCAmelCase_			:     List[Any]									= hidden_dropout_prob
									lowerCAmelCase_			:     Tuple									= attention_probs_dropout_prob
									lowerCAmelCase_			:     str									= initializer_range
									lowerCAmelCase_			:     Tuple									= layer_norm_eps

									lowerCAmelCase_			:     List[Any]									= image_size
									lowerCAmelCase_			:     List[Any]									= patch_size
									lowerCAmelCase_			:     Any									= num_channels
									lowerCAmelCase_			:     Any									= use_mask_token
									lowerCAmelCase_			:     Optional[int]									= use_absolute_position_embeddings
									lowerCAmelCase_			:     str									= use_relative_position_bias
									lowerCAmelCase_			:     Optional[Any]									= use_shared_relative_position_bias
									lowerCAmelCase_			:     Dict									= layer_scale_init_value
									lowerCAmelCase_			:     Tuple									= drop_path_rate
									lowerCAmelCase_			:     Optional[int]									= use_mean_pooling
									# decode head attributes (semantic segmentation)
									lowerCAmelCase_			:     Any									= out_indices
									lowerCAmelCase_			:     int									= pool_scales
									# auxiliary head attributes (semantic segmentation)
									lowerCAmelCase_			:     Dict									= use_auxiliary_head
									lowerCAmelCase_			:     str									= auxiliary_loss_weight
									lowerCAmelCase_			:     Optional[Any]									= auxiliary_channels
									lowerCAmelCase_			:     str									= auxiliary_num_convs
									lowerCAmelCase_			:     str									= auxiliary_concat_input
									lowerCAmelCase_			:     str									= semantic_loss_ignore_index





class 				__snake_case						(     UpperCamelCase_						):
							_a			      = version.parse('''1.11'''						)




							@property
							def    UpperCAmelCase__			(       self     :       Tuple):
									return OrderedDict(
									    [
									        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
									    ])







							@property
							def    UpperCAmelCase__			(       self     :       Dict):
									return 1e-4





