




'''simple docstring'''





import os
import sys
import unittest


_lowerCAmelCase										=     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
_lowerCAmelCase										=     os.path.join(git_repo_path, '''src''', '''diffusers''')






class 	lowerCAmelCase_(    unittest.TestCase					):
  '''simple docstring'''




  def 							UpperCAmelCase_     (   self				)   ->		int:
      lowerCAmelCase__			:  int											= find_backend("""    if not is_torch_available():"""				)
      self.assertEqual(lowercase_  ,"""torch"""				)

      # backend_with_underscore = find_backend("    if not is_tensorflow_text_available():")
      # self.assertEqual(backend_with_underscore, "tensorflow_text")

      lowerCAmelCase__			:  List[str]											= find_backend("""    if not (is_torch_available() and is_transformers_available()):"""				)
      self.assertEqual(lowercase_  ,"""torch_and_transformers"""				)

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

      lowerCAmelCase__			:  Any											= find_backend(
          """    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):"""				)
      self.assertEqual(lowercase_  ,"""torch_and_transformers_and_onnx"""				)




  def 							UpperCAmelCase_     (   self				)   ->		Optional[Any]:
      lowerCAmelCase__			:  Union[str, Any]											= read_init()
      # We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
      self.assertIn("""torch"""  ,lowercase_				)
      self.assertIn("""torch_and_transformers"""  ,lowercase_				)
      self.assertIn("""flax_and_transformers"""  ,lowercase_				)
      self.assertIn("""torch_and_transformers_and_onnx"""  ,lowercase_				)

      # Likewise, we can't assert on the exact content of a key
      self.assertIn("""UNet2DModel"""  ,objects["""torch"""]				)
      self.assertIn("""FlaxUNet2DConditionModel"""  ,objects["""flax"""]				)
      self.assertIn("""StableDiffusionPipeline"""  ,objects["""torch_and_transformers"""]				)
      self.assertIn("""FlaxStableDiffusionPipeline"""  ,objects["""flax_and_transformers"""]				)
      self.assertIn("""LMSDiscreteScheduler"""  ,objects["""torch_and_scipy"""]				)
      self.assertIn("""OnnxStableDiffusionPipeline"""  ,objects["""torch_and_transformers_and_onnx"""]				)




  def 							UpperCAmelCase_     (   self				)   ->		Any:
      lowerCAmelCase__			:  Dict											= create_dummy_object("""CONSTANT"""  ,"""'torch'"""				)
      self.assertEqual(lowercase_  ,"""\nCONSTANT = None\n"""				)

      lowerCAmelCase__			:  Union[str, Any]											= create_dummy_object("""function"""  ,"""'torch'"""				)
      self.assertEqual(
          lowercase_  ,"""\ndef function(*args, **kwargs):\n    requires_backends(function, 'torch')\n"""				)

      lowerCAmelCase__			:  List[Any]											= "\nclass FakeClass(metaclass=DummyObject):\n    _backends = 'torch'\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, 'torch')\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, 'torch')\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, 'torch')\n"
      lowerCAmelCase__			:  List[str]											= create_dummy_object("""FakeClass"""  ,"""'torch'"""				)
      self.assertEqual(lowercase_  ,lowercase_				)






  def 							UpperCAmelCase_     (   self				)   ->		Optional[int]:
      lowerCAmelCase__			:  List[str]											= "# This file is autogenerated by the command `make fix-copies`, do not edit.\nfrom ..utils import DummyObject, requires_backends\n\n\nCONSTANT = None\n\n\ndef function(*args, **kwargs):\n    requires_backends(function, [\"torch\"])\n\n\nclass FakeClass(metaclass=DummyObject):\n    _backends = [\"torch\"]\n\n    def __init__(self, *args, **kwargs):\n        requires_backends(self, [\"torch\"])\n\n    @classmethod\n    def from_config(cls, *args, **kwargs):\n        requires_backends(cls, [\"torch\"])\n\n    @classmethod\n    def from_pretrained(cls, *args, **kwargs):\n        requires_backends(cls, [\"torch\"])\n"
      lowerCAmelCase__			:  int											= create_dummy_files({"""torch""": ["""CONSTANT""", """function""", """FakeClass"""]}				)
      self.assertEqual(dummy_files["""torch"""]  ,lowercase_				)







'''simple docstring'''





from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices


_lowerCAmelCase										=     logging.get_logger(__name__)

_lowerCAmelCase										=     {
    '''facebook/convnextv2-tiny-1k-224''': '''https://huggingface.co/facebook/convnextv2-tiny-1k-224/resolve/main/config.json''',
}






class 	lowerCAmelCase_(    SCREAMING_SNAKE_CASE_						,			SCREAMING_SNAKE_CASE_					):
  '''simple docstring'''




  __lowercase							:				Tuple           =				'''convnextv2'''




  def __init__(   self  ,__UpperCAmelCase=3  ,__UpperCAmelCase=4  ,__UpperCAmelCase=4  ,__UpperCAmelCase=None  ,__UpperCAmelCase=None  ,__UpperCAmelCase="gelu"  ,__UpperCAmelCase=0.0_2  ,__UpperCAmelCase=1E-12  ,__UpperCAmelCase=0.0  ,__UpperCAmelCase=224  ,__UpperCAmelCase=None  ,__UpperCAmelCase=None  ,**__UpperCAmelCase  ,)   ->		Union[str, Any]:
      super().__init__(**__UpperCAmelCase				)

      lowerCAmelCase__			:  int											= num_channels
      lowerCAmelCase__			:  List[Any]											= patch_size
      lowerCAmelCase__			:  Union[str, Any]											= num_stages
      lowerCAmelCase__			:  Tuple											= [96, 192, 384, 768] if hidden_sizes is None else hidden_sizes
      lowerCAmelCase__			:  str											= [3, 3, 9, 3] if depths is None else depths
      lowerCAmelCase__			:  Optional[Any]											= hidden_act
      lowerCAmelCase__			:  str											= initializer_range
      lowerCAmelCase__			:  List[str]											= layer_norm_eps
      lowerCAmelCase__			:  Dict											= drop_path_rate
      lowerCAmelCase__			:  int											= image_size
      lowerCAmelCase__			:  int											= ["""stem"""] + [F"""stage{idx}""" for idx in range(1  ,len(self.depths				) + 1				)]
      lowerCAmelCase__				,       lowerCAmelCase__			:  Tuple											= get_aligned_output_features_output_indices(
          out_features=__UpperCAmelCase  ,out_indices=__UpperCAmelCase  ,stage_names=self.stage_names				)


