


import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format



class   _a      :
    a_    :				Dict             =    None
    def      _UpperCamelCase       ( self							:					Union[str, Any]				):
          lowerCamelCase__           =		self.feature_extraction_class(**self.feat_extract_dict				)
          lowerCamelCase__           =		json.loads(feat_extract.to_json_string()				)
          for key, value in self.feat_extract_dict.items():
                self.assertEqual(obj[key]							,					UpperCamelCase__				)
    def      _UpperCamelCase       ( self							:					Tuple				):
          lowerCamelCase__           =		self.feature_extraction_class(**self.feat_extract_dict				)

          with tempfile.TemporaryDirectory() as tmpdirname:
                lowerCamelCase__           =		os.path.join(UpperCamelCase__							,					'feat_extract.json'				)
                feat_extract_first.to_json_file(UpperCamelCase__				)
                lowerCamelCase__           =		self.feature_extraction_class.from_json_file(UpperCamelCase__				)

          self.assertEqual(feat_extract_second.to_dict()							,					feat_extract_first.to_dict()				)
    def      _UpperCamelCase       ( self							:					List[str]				):
          lowerCamelCase__           =		self.feature_extraction_class(**self.feat_extract_dict				)

          with tempfile.TemporaryDirectory() as tmpdirname:
                lowerCamelCase__           =		feat_extract_first.save_pretrained(UpperCamelCase__				)[0]
                check_json_file_has_correct_format(UpperCamelCase__				)
                lowerCamelCase__           =		self.feature_extraction_class.from_pretrained(UpperCamelCase__				)

          self.assertEqual(feat_extract_second.to_dict()							,					feat_extract_first.to_dict()				)


    def      _UpperCamelCase       ( self							:					Optional[int]				):
          lowerCamelCase__           =		self.feature_extraction_class()
          self.assertIsNotNone(UpperCamelCase__				)







"""simple docstring"""


from ...configuration_utils import PretrainedConfig
from ...utils import logging


_snake_case          =							logging.get_logger(__name__)

_snake_case          =							{
    "microsoft/swinv2-tiny-patch4-window8-256": (
        "https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json"
    ),
}



class   _a      (      SCREAMING_SNAKE_CASE_ ):
    a_    :				Union[str, Any]             =    'swinv2'

    a_    :				Optional[int]             =    {
        'num_attention_heads': 'num_heads',
        'num_hidden_layers': 'num_layers',
    }
    def __init__( self							:					List[str]							,					SCREAMING_SNAKE_CASE__							:					int=2_24							,					SCREAMING_SNAKE_CASE__							:					str=4							,					SCREAMING_SNAKE_CASE__							:					List[Any]=3							,					SCREAMING_SNAKE_CASE__							:					str=96							,					SCREAMING_SNAKE_CASE__							:					Dict=[2, 2, 6, 2]							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=[3, 6, 12, 24]							,					SCREAMING_SNAKE_CASE__							:					Tuple=7							,					SCREAMING_SNAKE_CASE__							:					Union[str, Any]=4.0							,					SCREAMING_SNAKE_CASE__							:					List[str]=True							,					SCREAMING_SNAKE_CASE__							:					List[Any]=0.0							,					SCREAMING_SNAKE_CASE__							:					Optional[int]=0.0							,					SCREAMING_SNAKE_CASE__							:					Dict=0.1							,					SCREAMING_SNAKE_CASE__							:					Tuple="gelu"							,					SCREAMING_SNAKE_CASE__							:					Tuple=False							,					SCREAMING_SNAKE_CASE__							:					Any=0.02							,					SCREAMING_SNAKE_CASE__							:					List[Any]=1e-5							,					SCREAMING_SNAKE_CASE__							:					int=32							,					**SCREAMING_SNAKE_CASE__							:					List[str]							,					):
          super().__init__(**SCREAMING_SNAKE_CASE__				)

          lowerCamelCase__           =		image_size
          lowerCamelCase__           =		patch_size
          lowerCamelCase__           =		num_channels
          lowerCamelCase__           =		embed_dim
          lowerCamelCase__           =		depths
          lowerCamelCase__           =		len(SCREAMING_SNAKE_CASE__				)
          lowerCamelCase__           =		num_heads
          lowerCamelCase__           =		window_size
          lowerCamelCase__           =		mlp_ratio
          lowerCamelCase__           =		qkv_bias
          lowerCamelCase__           =		hidden_dropout_prob
          lowerCamelCase__           =		attention_probs_dropout_prob
          lowerCamelCase__           =		drop_path_rate
          lowerCamelCase__           =		hidden_act
          lowerCamelCase__           =		use_absolute_embeddings
          lowerCamelCase__           =		layer_norm_eps
          lowerCamelCase__           =		initializer_range
          lowerCamelCase__           =		encoder_stride
          # we set the hidden_size attribute in order to make Swinv2 work with VisionEncoderDecoderModel
          # this indicates the channel dimension after the last stage of the model
          lowerCamelCase__           =		int(embed_dim * 2 ** (len(SCREAMING_SNAKE_CASE__				) - 1)				)
          lowerCamelCase__           =		(0, 0, 0, 0)



