

'''simple docstring'''




import pytest

from datasets import inspect_metric, list_metrics, load_metric




@pytest.fixture
def 						UpperCamelCase	(			a			)				->     Optional[int]:






     '''simple docstring'''
     monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecation_warnings'''		,						set()			)




@pytest.fixture
def 						UpperCamelCase	(			a			)				->     Union[str, Any]:






     '''simple docstring'''






     class   _SCREAMING_SNAKE_CASE   :



      def __init__(   self		:   Any			,				a__		:   Any      ):
           __magic_name__						       =    metric_id






     class   _SCREAMING_SNAKE_CASE   :
      __SCREAMING_SNAKE_CASE					:List[Any]      	=					[MetricMock(__a     ) for metric_id in ["""accuracy""", """mse""", """precision""", """codeparrot/apps_metric"""]]



      def 			snake_case__  (   self		:   int      ):
           return self._metrics


     monkeypatch.setattr('''datasets.inspect.huggingface_hub'''		,						HfhMock()			)




@pytest.mark.parametrize(
    '''func, args'''		,						[(load_metric, ('''metrics/mse''',)), (list_metrics, ()), (inspect_metric, ('''metrics/mse''', '''tmp_path'''))]			)
def 						UpperCamelCase	(			a		,						a		,						a		,						a		,						a			)				->     Optional[Any]:






     '''simple docstring'''
     if "tmp_path" in args:
          __magic_name__						       =    tuple(arg if arg != '''tmp_path''' else tmp_path for arg in args			)
     with pytest.warns(a		,						match='''https://huggingface.co/docs/evaluate'''			):
          func(*a			)









'''simple docstring'''




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowerCAmelCase         =						{"configuration_glpn": ["GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP", "GLPNConfig"]}

try:
      if not is_vision_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						["GLPNFeatureExtractor"]
      _lowerCAmelCase         =						["GLPNImageProcessor"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      _lowerCAmelCase         =						[
          "GLPN_PRETRAINED_MODEL_ARCHIVE_LIST",
          "GLPNForDepthEstimation",
          "GLPNLayer",
          "GLPNModel",
          "GLPNPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_glpn import GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP, GLPNConfig

      try:
            if not is_vision_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .feature_extraction_glpn import GLPNFeatureExtractor
            from .image_processing_glpn import GLPNImageProcessor

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_glpn import (
                GLPN_PRETRAINED_MODEL_ARCHIVE_LIST,
                GLPNForDepthEstimation,
                GLPNLayer,
                GLPNModel,
                GLPNPreTrainedModel,
            )


else:
      import sys

      _lowerCAmelCase         =						_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)






