
'''simple docstring'''






import os
import sys
import unittest


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






class  __magic_name__							(		unittest.TestCase    ):






       def       lowerCAmelCase		(      self)						->  List[str]:




          '''simple docstring'''
          _UpperCAmelCase       :       Dict							   =find_backend('    if not is_torch_available():')
          self.assertEqual(__a  ,							'torch')

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

          _UpperCAmelCase       :       Optional[int]							   =find_backend('    if not (is_torch_available() and is_transformers_available()):')
          self.assertEqual(__a  ,							'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")

          _UpperCAmelCase       :       str							   =find_backend(
              '    if not (is_torch_available() and is_transformers_available() and is_onnx_available()):')
          self.assertEqual(__a  ,							'torch_and_transformers_and_onnx')






       def       lowerCAmelCase		(      self)						->  str:




          '''simple docstring'''
          _UpperCAmelCase       :       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'  ,							__a)
          self.assertIn('torch_and_transformers'  ,							__a)
          self.assertIn('flax_and_transformers'  ,							__a)
          self.assertIn('torch_and_transformers_and_onnx'  ,							__a)

          # 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)						->  Union[str, Any]:




          '''simple docstring'''
          _UpperCAmelCase       :       Optional[int]							   =create_dummy_object('CONSTANT'  ,							'\'torch\'')
          self.assertEqual(__a  ,							'\nCONSTANT = None\n')

          _UpperCAmelCase       :       Optional[Any]							   =create_dummy_object('function'  ,							'\'torch\'')
          self.assertEqual(
              __a  ,							'\ndef function(*args, **kwargs):\n    requires_backends(function, \'torch\')\n')

          _UpperCAmelCase       :       List[str]							   ='\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'
          _UpperCAmelCase       :       List[Any]							   =create_dummy_object('FakeClass'  ,							'\'torch\'')
          self.assertEqual(__a  ,							__a)






       def       lowerCAmelCase		(      self)						->  List[str]:




          '''simple docstring'''
          _UpperCAmelCase       :       List[Any]							   ='# 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'
          _UpperCAmelCase       :       Union[str, Any]							   =create_dummy_files({'torch': ['CONSTANT', 'function', 'FakeClass']})
          self.assertEqual(dummy_files['torch']  ,							__a)





'''simple docstring'''






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


lowercase							=logging.get_logger(__name__)

lowercase							={
    'vinvino02/glpn-kitti': 'https://huggingface.co/vinvino02/glpn-kitti/resolve/main/config.json',
    # See all GLPN models at https://huggingface.co/models?filter=glpn
}






class  __magic_name__							(		lowerCAmelCase    ):
       UpperCAmelCase										="glpn"






       def __init__(      self  ,							snake_case=3  ,							snake_case=4  ,							snake_case=[2, 2, 2, 2]  ,							snake_case=[8, 4, 2, 1]  ,							snake_case=[3_2, 6_4, 1_6_0, 2_5_6]  ,							snake_case=[7, 3, 3, 3]  ,							snake_case=[4, 2, 2, 2]  ,							snake_case=[1, 2, 5, 8]  ,							snake_case=[4, 4, 4, 4]  ,							snake_case="gelu"  ,							snake_case=0.0  ,							snake_case=0.0  ,							snake_case=0.02  ,							snake_case=0.1  ,							snake_case=1E-6  ,							snake_case=6_4  ,							snake_case=1_0  ,							snake_case=-1  ,							**snake_case  ,							)						->  Tuple:




          '''simple docstring'''
          super().__init__(**snake_case)

          _UpperCAmelCase       :       Any							   =num_channels
          _UpperCAmelCase       :       List[str]							   =num_encoder_blocks
          _UpperCAmelCase       :       Optional[Any]							   =depths
          _UpperCAmelCase       :       str							   =sr_ratios
          _UpperCAmelCase       :       Dict							   =hidden_sizes
          _UpperCAmelCase       :       List[str]							   =patch_sizes
          _UpperCAmelCase       :       Any							   =strides
          _UpperCAmelCase       :       List[str]							   =mlp_ratios
          _UpperCAmelCase       :       Dict							   =num_attention_heads
          _UpperCAmelCase       :       List[str]							   =hidden_act
          _UpperCAmelCase       :       int							   =hidden_dropout_prob
          _UpperCAmelCase       :       List[Any]							   =attention_probs_dropout_prob
          _UpperCAmelCase       :       Union[str, Any]							   =initializer_range
          _UpperCAmelCase       :       Tuple							   =drop_path_rate
          _UpperCAmelCase       :       str							   =layer_norm_eps
          _UpperCAmelCase       :       Optional[int]							   =decoder_hidden_size
          _UpperCAmelCase       :       List[str]							   =max_depth
          _UpperCAmelCase       :       Dict							   =head_in_index

