




import importlib.metadata
import sys

from transformers.testing_utils import TestCasePlus
from transformers.utils.versions import require_version, require_version_core


a__		    =    importlib.metadata.version('''numpy''')
a__		    =    '''.'''.join([str(x) for x in sys.version_info[:3]])


class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



	"""simple docstring"""


	def 				lowerCamelCase__    (				self		:	Optional[Any]  )  ->					str:







						"""simple docstring"""







						require_version_core("""numpy<1000.4.5"""  )
						require_version_core("""numpy<1000.4"""  )
						require_version_core("""numpy<1000"""  )

						# le
						require_version_core("""numpy<=1000.4.5"""  )
						require_version_core(F'''numpy<={numpy_ver}'''  )

						# eq
						require_version_core(F'''numpy=={numpy_ver}'''  )

						# ne
						require_version_core("""numpy!=1000.4.5"""  )

						# ge
						require_version_core("""numpy>=1.0"""  )
						require_version_core("""numpy>=1.0.0"""  )
						require_version_core(F'''numpy>={numpy_ver}'''  )

						# gt
						require_version_core("""numpy>1.0.0"""  )

						# mix
						require_version_core("""numpy>1.0.0,<1000"""  )

						# requirement w/o version
						require_version_core("""numpy"""  )

						# unmet requirements due to version conflict
						for req in ["numpy==1.0.0", "numpy>=1000.0.0", F'''numpy<{numpy_ver}''']:
											try:
																require_version_core(lowerCAmelCase  )
											except ImportError as e:
																self.assertIn(F'''{req} is required'''				,    str(lowerCAmelCase  )  )
																self.assertIn("""but found"""				,    str(lowerCAmelCase  )  )

        # unmet requirements due to missing module
						for req in ["numpipypie>1", "numpipypie2"]:
											try:
																require_version_core(lowerCAmelCase  )
											except importlib.metadata.PackageNotFoundError as e:
																self.assertIn(F'''The \'{req}\' distribution was not found and is required by this application'''				,    str(lowerCAmelCase  )  )
																self.assertIn("""Try: pip install transformers -U"""				,    str(lowerCAmelCase  )  )

        # bogus requirements formats:
        # 1. whole thing
						for req in ["numpy??1.0.0", "numpy1.0.0"]:
											try:
																require_version_core(lowerCAmelCase  )
											except ValueError as e:
																self.assertIn("""requirement needs to be in the pip package format"""				,    str(lowerCAmelCase  )  )
        # 2. only operators
						for req in ["numpy=1.0.0", "numpy == 1.00", "numpy<>1.0.0", "numpy><1.00", "numpy>>1.0.0"]:
											try:
																require_version_core(lowerCAmelCase  )
											except ValueError as e:
																self.assertIn("""need one of """				,    str(lowerCAmelCase  )  )






	def 				lowerCamelCase__    (				self		:	Tuple  )  ->					str:







						"""simple docstring"""







						require_version("""python>=3.6.0"""  )

						# not matching requirements
						for req in ["python>9.9.9", "python<3.0.0"]:
											try:
																require_version_core(lowerCAmelCase  )
											except ImportError as e:
																self.assertIn(F'''{req} is required'''				,    str(lowerCAmelCase  )  )
																self.assertIn(F'''but found python=={python_ver}'''				,    str(lowerCAmelCase  )  )












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__		    =    logging.get_logger(__name__)

a__		    =    {
    '''apple/mobilevit-small''': '''https://huggingface.co/apple/mobilevit-small/resolve/main/config.json''',
    '''apple/mobilevit-x-small''': '''https://huggingface.co/apple/mobilevit-x-small/resolve/main/config.json''',
    '''apple/mobilevit-xx-small''': '''https://huggingface.co/apple/mobilevit-xx-small/resolve/main/config.json''',
    '''apple/deeplabv3-mobilevit-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-x-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-x-small/resolve/main/config.json'''
    ),
    '''apple/deeplabv3-mobilevit-xx-small''': (
        '''https://huggingface.co/apple/deeplabv3-mobilevit-xx-small/resolve/main/config.json'''
    ),
    # See all MobileViT models at https://huggingface.co/models?filter=mobilevit
}


class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



	"""simple docstring"""


	__magic_name__      :					Any			  =		'mobilevit'






	def __init__(				self		:	int				,    lowerCAmelCase		:	Dict=3				,    lowerCAmelCase		:	Dict=256				,    lowerCAmelCase		:	Any=2				,    lowerCAmelCase		:	Any=[144, 192, 240]				,    lowerCAmelCase		:	int=[16, 32, 64, 96, 128, 160, 640]				,    lowerCAmelCase		:	List[Any]=4				,    lowerCAmelCase		:	Tuple=2.0				,    lowerCAmelCase		:	Tuple=4.0				,    lowerCAmelCase		:	List[str]="silu"				,    lowerCAmelCase		:	Tuple=3				,    lowerCAmelCase		:	Tuple=32				,    lowerCAmelCase		:	Any=0.1				,    lowerCAmelCase		:	List[str]=0.0				,    lowerCAmelCase		:	Union[str, Any]=0.1				,    lowerCAmelCase		:	List[str]=0.02				,    lowerCAmelCase		:	Optional[Any]=1E-5				,    lowerCAmelCase		:	Union[str, Any]=True				,    lowerCAmelCase		:	List[str]=256				,    lowerCAmelCase		:	List[Any]=[6, 12, 18]				,    lowerCAmelCase		:	Tuple=0.1				,    lowerCAmelCase		:	List[str]=255				,    **lowerCAmelCase		:	Union[str, Any]				,    )  ->					Optional[Any]:







						"""simple docstring"""







						super().__init__(**lowerCAmelCase  )

						__UpperCamelCase				:  Tuple								=			num_channels
						__UpperCamelCase				:  Union[str, Any]								=			image_size
						__UpperCamelCase				:  List[Any]								=			patch_size
						__UpperCamelCase				:  Optional[int]								=			hidden_sizes
						__UpperCamelCase				:  Union[str, Any]								=			neck_hidden_sizes
						__UpperCamelCase				:  List[str]								=			num_attention_heads
						__UpperCamelCase				:  Union[str, Any]								=			mlp_ratio
						__UpperCamelCase				:  Tuple								=			expand_ratio
						__UpperCamelCase				:  Optional[Any]								=			hidden_act
						__UpperCamelCase				:  int								=			conv_kernel_size
						__UpperCamelCase				:  Any								=			output_stride
						__UpperCamelCase				:  int								=			hidden_dropout_prob
						__UpperCamelCase				:  Union[str, Any]								=			attention_probs_dropout_prob
						__UpperCamelCase				:  Dict								=			classifier_dropout_prob
						__UpperCamelCase				:  Any								=			initializer_range
						__UpperCamelCase				:  List[str]								=			layer_norm_eps
						__UpperCamelCase				:  Union[str, Any]								=			qkv_bias

						# decode head attributes for semantic segmentation
						__UpperCamelCase				:  Any								=			aspp_out_channels
						__UpperCamelCase				:  Union[str, Any]								=			atrous_rates
						__UpperCamelCase				:  Union[str, Any]								=			aspp_dropout_prob
						__UpperCamelCase				:  List[str]								=			semantic_loss_ignore_index






class       SCREAMING_SNAKE_CASE_							(					_UpperCamelCase      ):



	"""simple docstring"""


	__magic_name__      :					Optional[Any]			  =		version.parse('1.11'      )






	@property
	def 				lowerCamelCase__    (				self		:	Any  )  ->					Mapping[str, Mapping[int, str]]:







						"""simple docstring"""







						return OrderedDict([("""pixel_values""", {0: """batch""", 1: """num_channels""", 2: """height""", 3: """width"""})]  )






	@property
	def 				lowerCamelCase__    (				self		:	List[Any]  )  ->					Mapping[str, Mapping[int, str]]:







						"""simple docstring"""







						if self.task == "image-classification":
											return OrderedDict([("""logits""", {0: """batch"""})]  )
						else:
											return OrderedDict([("""last_hidden_state""", {0: """batch"""}), ("""pooler_output""", {0: """batch"""})]  )






	@property
	def 				lowerCamelCase__    (				self		:	Optional[int]  )  ->					float:







						"""simple docstring"""







						return 1E-4






