


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        _a							(			unittest.TestCase			):

							def       lowerCamelCase_ (							self:	Union[str, Any]							)			->   List[Any]:





									"""simple docstring"""







									lowercase__            =      find_backend('''    if not is_torch_available():'''							)
									self.assertEqual(UpperCamelCase_    ,						'''torch'''							)

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

									lowercase__            =      find_backend('''    if not (is_torch_available() and is_transformers_available()):'''							)
									self.assertEqual(UpperCamelCase_    ,						'''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")

									lowercase__            =      find_backend(
									    '''    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):'''							)
									self.assertEqual(UpperCamelCase_    ,						'''torch_and_transformers_and_onnx'''							)

							def       lowerCamelCase_ (							self:	Any							)			->   Optional[Any]:





									"""simple docstring"""







									lowercase__            =      read_init()
									# We don't assert on the exact list of keys to allow for smooth grow of backend-specific objects
									self.assertIn('''torch'''    ,						UpperCamelCase_							)
									self.assertIn('''torch_and_transformers'''    ,						UpperCamelCase_							)
									self.assertIn('''flax_and_transformers'''    ,						UpperCamelCase_							)
									self.assertIn('''torch_and_transformers_and_onnx'''    ,						UpperCamelCase_							)

									# 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       lowerCamelCase_ (							self:	Optional[Any]							)			->   Optional[int]:





									"""simple docstring"""







									lowercase__            =      create_dummy_object('''CONSTANT'''    ,						'''\'torch\''''							)
									self.assertEqual(UpperCamelCase_    ,						'''\nCONSTANT = None\n'''							)

									lowercase__            =      create_dummy_object('''function'''    ,						'''\'torch\''''							)
									self.assertEqual(
									    UpperCamelCase_    ,						'''\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n'''							)

									lowercase__            =      '''
class FakeClass(metaclass=DummyObject):
    _backends = \'torch\'

    def __init__(self, *args, **kwargs):
        requires_backends(self, \'torch\')

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, \'torch\')

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, \'torch\')
'''
									lowercase__            =      create_dummy_object('''FakeClass'''    ,						'''\'torch\''''							)
									self.assertEqual(UpperCamelCase_    ,						UpperCamelCase_							)


							def       lowerCamelCase_ (							self:	Any							)			->   List[Any]:





									"""simple docstring"""







									lowercase__            =      '''# 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"])

    @classmethod
    def from_config(cls, *args, **kwargs):
        requires_backends(cls, ["torch"])

    @classmethod
    def from_pretrained(cls, *args, **kwargs):
        requires_backends(cls, ["torch"])
'''
									lowercase__            =      create_dummy_files({'''torch''': ['''CONSTANT''', '''function''', '''FakeClass''']}							)
									self.assertEqual(dummy_files['''torch''']    ,						UpperCamelCase_							)








from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowerCamelCase	:		List[str]							       =   {"""configuration_vit_msn""": ["""VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMSNConfig"""]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _lowerCamelCase	:		List[Any]							       =   [
      """VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """ViTMSNModel""",
      """ViTMSNForImageClassification""",
      """ViTMSNPreTrainedModel""",
  ]

if TYPE_CHECKING:
  from .configuration_vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_vit_msn import (
        VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST,
        ViTMSNForImageClassification,
        ViTMSNModel,
        ViTMSNPreTrainedModel,
    )

else:
  import sys

  _lowerCamelCase	:		Tuple							       =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)


