



'''simple docstring'''






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


UpperCamelCase__:   Optional[int]								=			logging.get_logger(__name__)

UpperCamelCase__:   int								=			{
    "google/vit-base-patch16-224": "https://huggingface.co/vit-base-patch16-224/resolve/main/config.json",
    # See all ViT models at https://huggingface.co/models?filter=vit
}

class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	lowerCamelCase__			 =       """vit"""







	def __init__(						self			:     Dict		,			__snake_case			:     int=768		,			__snake_case			:     Optional[int]=12		,			__snake_case			:     Any=12		,			__snake_case			:     Optional[Any]=3072		,			__snake_case			:     Any="gelu"		,			__snake_case			:     str=0.0		,			__snake_case			:     str=0.0		,			__snake_case			:     Dict=0.02		,			__snake_case			:     Optional[int]=1E-12		,			__snake_case			:     List[str]=224		,			__snake_case			:     Tuple=16		,			__snake_case			:     Dict=3		,			__snake_case			:     List[str]=True		,			__snake_case			:     Optional[int]=16		,			**__snake_case			:     Dict		,			)			->		Optional[Any]:
								super().__init__(**__snake_case		)

								UpperCAmelCase :       str 							=		hidden_size
								UpperCAmelCase :       int 							=		num_hidden_layers
								UpperCAmelCase :       List[Any] 							=		num_attention_heads
								UpperCAmelCase :       str 							=		intermediate_size
								UpperCAmelCase :       Union[str, Any] 							=		hidden_act
								UpperCAmelCase :       List[str] 							=		hidden_dropout_prob
								UpperCAmelCase :       Any 							=		attention_probs_dropout_prob
								UpperCAmelCase :       Optional[Any] 							=		initializer_range
								UpperCAmelCase :       Optional[int] 							=		layer_norm_eps
								UpperCAmelCase :       Union[str, Any] 							=		image_size
								UpperCAmelCase :       Any 							=		patch_size
								UpperCAmelCase :       Union[str, Any] 							=		num_channels
								UpperCAmelCase :       Any 							=		qkv_bias
								UpperCAmelCase :       Union[str, Any] 							=		encoder_stride

class 				SCREAMING_SNAKE_CASE(							A__			):







	"""simple docstring"""






	lowerCamelCase__			 =       version.parse("""1.11"""			)







	@property
	def      A	(						self			:     List[Any]		)			->		Mapping[str, Mapping[int, str]]:
								return OrderedDict(
								    [
								        ('''pixel_values''', {0: '''batch''', 1: '''num_channels''', 2: '''height''', 3: '''width'''}),
								    ]		)







	@property
	def      A	(						self			:     Union[str, Any]		)			->		float:
								return 1E-4









import platform
from argparse import ArgumentParser

import huggingface_hub

from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand



def 	lowerCAmelCase       (						lowerCAmelCase_       )->       Union[str, Any]:
				return EnvironmentCommand()







class  snake_case__(							UpperCAmelCase__							):







						'''simple docstring'''




						@staticmethod
						def   lowercase_       ( __lowercase							)    ->			List[Any]:
										lowerCAmelCase_       :					List[str]			 = parser.add_parser('''env'''							)
										download_parser.set_defaults(func=__lowercase							)




						def   lowercase_       ( self							)    ->			int:
										lowerCAmelCase_       :					Optional[Any]			 = huggingface_hub.__version__

										lowerCAmelCase_       :					str			 = '''not installed'''
										lowerCAmelCase_       :					str			 = '''NA'''
										if is_torch_available():
														import torch

														lowerCAmelCase_       :					Any			 = torch.__version__
														lowerCAmelCase_       :					str			 = torch.cuda.is_available()

										lowerCAmelCase_       :					List[str]			 = '''not installed'''
										if is_transformers_available():
														import transformers

														lowerCAmelCase_       :					Any			 = transformers.__version__

										lowerCAmelCase_       :					Optional[Any]			 = '''not installed'''
										if is_accelerate_available():
														import accelerate

														lowerCAmelCase_       :					List[Any]			 = accelerate.__version__

										lowerCAmelCase_       :					List[str]			 = '''not installed'''
										if is_xformers_available():
														import xformers

														lowerCAmelCase_       :					Optional[Any]			 = xformers.__version__

										lowerCAmelCase_       :					int			 = {
										    '''`diffusers` version''': version,
										    '''Platform''': platform.platform(),
										    '''Python version''': platform.python_version(),
										    '''PyTorch version (GPU?)''': f"""{pt_version} ({pt_cuda_available})""",
										    '''Huggingface_hub version''': hub_version,
										    '''Transformers version''': transformers_version,
										    '''Accelerate version''': accelerate_version,
										    '''xFormers version''': xformers_version,
										    '''Using GPU in script?''': '''<fill in>''',
										    '''Using distributed or parallel set-up in script?''': '''<fill in>''',
										}

										print('''\nCopy-and-paste the text below in your GitHub issue and FILL OUT the two last points.\n'''							)
										print(self.format_dict(__lowercase							)							)

										return info




						@staticmethod
						def   lowercase_       ( __lowercase							)    ->			str:
										return "\n".join([f"""- {prop}: {val}""" for prop, val in d.items()]							) + "\n"