






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:     List[Any]   					=					logging.get_logger(__name__)

__a:     Optional[Any]   					=					{
    '''sail/poolformer_s12''': '''https://huggingface.co/sail/poolformer_s12/resolve/main/config.json''',
    # See all PoolFormer models at https://huggingface.co/models?filter=poolformer
}
class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  '''poolformer'''


  def __init__(      self		:			Union[str, Any]       ,				lowerCamelCase		:			List[Any]=3       ,				lowerCamelCase		:			Any=16       ,				lowerCamelCase		:			Tuple=16       ,				lowerCamelCase		:			Union[str, Any]=3       ,				lowerCamelCase		:			Optional[Any]=4.0       ,				lowerCamelCase		:			Union[str, Any]=[2, 2, 6, 2]       ,				lowerCamelCase		:			str=[64, 128, 320, 512]       ,				lowerCamelCase		:			int=[7, 3, 3, 3]       ,				lowerCamelCase		:			Dict=[4, 2, 2, 2]       ,				lowerCamelCase		:			Optional[int]=[2, 1, 1, 1]       ,				lowerCamelCase		:			Optional[int]=4       ,				lowerCamelCase		:			Tuple=0.0       ,				lowerCamelCase		:			int="gelu"       ,				lowerCamelCase		:			Optional[int]=True       ,				lowerCamelCase		:			List[Any]=1E-5       ,				lowerCamelCase		:			Any=0.02       ,				**lowerCamelCase		:			List[str]       ,				)						->	Tuple:


         """simple docstring"""
         _UpperCAmelCase							=    num_channels
         _UpperCAmelCase							=    patch_size
         _UpperCAmelCase							=    stride
         _UpperCAmelCase							=    padding
         _UpperCAmelCase							=    pool_size
         _UpperCAmelCase							=    hidden_sizes
         _UpperCAmelCase							=    mlp_ratio
         _UpperCAmelCase							=    depths
         _UpperCAmelCase							=    patch_sizes
         _UpperCAmelCase							=    strides
         _UpperCAmelCase							=    num_encoder_blocks
         _UpperCAmelCase							=    drop_path_rate
         _UpperCAmelCase							=    hidden_act
         _UpperCAmelCase							=    use_layer_scale
         _UpperCAmelCase							=    layer_scale_init_value
         _UpperCAmelCase							=    initializer_range
         super().__init__(**lowerCamelCase							)



class 		SCREAMING_SNAKE_CASE__	(  UpperCAmelCase     ):

  '''simple docstring'''







  _lowerCamelCase    =  version.parse('''1.11'''     )


  @property
  def  lowerCamelCase       (      self		:			Union[str, 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		:			Union[str, Any]							)						->	float:


         """simple docstring"""
         return 2E-3







import os
import sys
import unittest


__a:     Tuple   					=					os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))

import check_dummies  # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, read_init  # noqa: E402


# Align TRANSFORMERS_PATH in check_dummies with the current path
__a:     Tuple   					=					os.path.join(git_repo_path, '''src''', '''transformers''')

__a:     Optional[Any]   					=					'''
{0} = None
'''

__a:     List[Any]   					=					'''
class {0}(metaclass=DummyObject):
    _backends = {1}

    def __init__(self, *args, **kwargs):
        requires_backends(self, {1})
'''


__a:     int   					=					'''
def {0}(*args, **kwargs):
    requires_backends({0}, {1})
'''
class 		SCREAMING_SNAKE_CASE__	(  unittest.TestCase     ):

  '''simple docstring'''







  def  lowerCamelCase       (      self		:			Tuple							)						->	List[str]:


         """simple docstring"""
         _UpperCAmelCase							=    find_backend("""    _import_structure[\"models.albert\"].append(\"AlbertTokenizerFast\")"""							)
         self.assertIsNone(lowerCamelCase							)

         _UpperCAmelCase							=    find_backend("""    if not is_tokenizers_available():"""							)
         self.assertEqual(lowerCamelCase       ,				"""tokenizers"""							)

         _UpperCAmelCase							=    find_backend("""    if not is_tensorflow_text_available():"""							)
         self.assertEqual(lowerCamelCase       ,				"""tensorflow_text"""							)

         _UpperCAmelCase							=    find_backend("""    if not (is_sentencepiece_available() and is_tokenizers_available()):"""							)
         self.assertEqual(lowerCamelCase       ,				"""sentencepiece_and_tokenizers"""							)

         _UpperCAmelCase							=    find_backend(
             """    if not (is_sentencepiece_available() and is_tensorflow_text_available()):"""							)
         self.assertEqual(lowerCamelCase       ,				"""sentencepiece_and_tensorflow_text"""							)

         _UpperCAmelCase							=    find_backend(
             """    if not (is_sentencepiece_available() and is_tokenizers_available() and is_vision_available()):"""							)
         self.assertEqual(lowerCamelCase       ,				"""sentencepiece_and_tokenizers_and_vision"""							)


  def  lowerCamelCase       (      self		:			int							)						->	List[str]:


         """simple docstring"""
         _UpperCAmelCase							=    read_init()
         # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
         self.assertIn("""torch"""       ,				lowerCamelCase							)
         self.assertIn("""tensorflow_text"""       ,				lowerCamelCase							)
         self.assertIn("""sentencepiece_and_tokenizers"""       ,				lowerCamelCase							)

         # Likewise, we can't assert on the exact content of a key
         self.assertIn("""BertModel"""       ,				objects["""torch"""]							)
         self.assertIn("""TFBertModel"""       ,				objects["""tf"""]							)
         self.assertIn("""FlaxBertModel"""       ,				objects["""flax"""]							)
         self.assertIn("""BertModel"""       ,				objects["""torch"""]							)
         self.assertIn("""TFBertTokenizer"""       ,				objects["""tensorflow_text"""]							)
         self.assertIn("""convert_slow_tokenizer"""       ,				objects["""sentencepiece_and_tokenizers"""]							)


  def  lowerCamelCase       (      self		:			int							)						->	Any:


         """simple docstring"""
         _UpperCAmelCase							=    create_dummy_object("""CONSTANT"""       ,				"""'torch'"""							)
         self.assertEqual(lowerCamelCase       ,				"""\nCONSTANT = None\n"""							)

         _UpperCAmelCase							=    create_dummy_object("""function"""       ,				"""'torch'"""							)
         self.assertEqual(
             lowerCamelCase       ,				"""\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"""							)

         _UpperCAmelCase							=    """
class FakeClass(metaclass=DummyObject):
    _backends = 'torch'

    def __init__(self, *args, **kwargs):
        requires_backends(self, 'torch')
"""
         _UpperCAmelCase							=    create_dummy_object("""FakeClass"""       ,				"""'torch'"""							)
         self.assertEqual(lowerCamelCase       ,				lowerCamelCase							)





  def  lowerCamelCase       (      self		:			Dict							)						->	List[str]:


         """simple docstring"""
         _UpperCAmelCase							=    """# This file is autogenerated by the command `make fix-copies`, do not edit.
from ..utils import DummyObject, requires_backends


CONSTANT = None


def function(*args, **kwargs):
    requires_backends(function, [\"torch\"])


class FakeClass(metaclass=DummyObject):
    _backends = [\"torch\"]

    def __init__(self, *args, **kwargs):
        requires_backends(self, [\"torch\"])
"""
         _UpperCAmelCase							=    create_dummy_files({"""torch""": ["""CONSTANT""", """function""", """FakeClass"""]}							)
         self.assertEqual(dummy_files["""torch"""]       ,				lowerCamelCase							)