


'''simple docstring'''



def 			_UpperCamelCase					(						UpperCamelCase__    ):
			UpperCAmelCase__     :    int         =   set()
			# edges = list of graph's edges
			UpperCAmelCase__     :    List[str]         =   get_edges(A__    )

			# While there are still elements in edges list, take an arbitrary edge
			# (from_node, to_node) and add his extremity to chosen_vertices and then
			# remove all arcs adjacent to the from_node and to_node
			while edges:
						UpperCAmelCase__      ,				UpperCAmelCase__     :    List[str]         =   edges.pop()
						chosen_vertices.add(A__    )
						chosen_vertices.add(A__    )
						for edge in edges.copy():
									if from_node in edge or to_node in edge:
												edges.discard(A__    )
			return chosen_vertices







def 			_UpperCamelCase					(						UpperCamelCase__    ):
			UpperCAmelCase__     :    int         =   set()
			for from_node, to_nodes in graph.items():
						for to_node in to_nodes:
									edges.add((from_node, to_node)    )
			return edges


if __name__ == "__main__":
		import doctest

		doctest.testmod()

		# graph = {0: [1, 3], 1: [0, 3], 2: [0, 3, 4], 3: [0, 1, 2], 4: [2, 3]}
		# print(f"Matching vertex cover:\n{matching_min_vertex_cover(graph)}")





from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch

from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch





@require_torch
@require_tf
class     lowerCamelCase__(					__lowerCamelCase):
      def 			lowerCAmelCase__						(				self: List[Any]   ):
             __lowerCamelCase   =						SMALL_MODEL_IDENTIFIER
             __lowerCamelCase   =						"""pt"""
             __lowerCamelCase   =						"""tf"""
      def 			lowerCAmelCase__						(				self: Optional[Any]    ,       UpperCamelCase_: Optional[Any]   ):
             __lowerCamelCase   =						AutoModel.from_pretrained(self.test_model   )
             model_pt.save_pretrained(UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: Tuple    ,       UpperCamelCase_: Union[str, Any]   ):
             __lowerCamelCase   =						TFAutoModel.from_pretrained(self.test_model    ,       from_pt=UpperCamelCase_   )
             model_tf.save_pretrained(UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: Union[str, Any]   ):
             __lowerCamelCase   =						"""mock_framework"""

             # Framework provided - return whatever the user provides
             __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model    ,       UpperCamelCase_   )
             self.assertEqual(UpperCamelCase_    ,       UpperCamelCase_   )

             # Local checkpoint and framework provided - return provided framework
             # PyTorch checkpoint
             with TemporaryDirectory() as local_pt_ckpt:
                    self._setup_pt_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_    ,       UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       UpperCamelCase_   )

             # TensorFlow checkpoint
             with TemporaryDirectory() as local_tf_ckpt:
                    self._setup_tf_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_    ,       UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: int   ):
             # PyTorch checkpoint
             with TemporaryDirectory() as local_pt_ckpt:
                    self._setup_pt_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_pt   )

             # TensorFlow checkpoint
             with TemporaryDirectory() as local_tf_ckpt:
                    self._setup_tf_ckpt(UpperCamelCase_   )
                    __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_tf   )

             # Invalid local checkpoint
             with TemporaryDirectory() as local_invalid_ckpt:
                    with self.assertRaises(UpperCamelCase_   ):
                           __lowerCamelCase   =						FeaturesManager.determine_framework(UpperCamelCase_   )




      def 			lowerCAmelCase__						(				self: Optional[int]   ):
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_tf_available"""    ,       UpperCamelCase_   ):
                    __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_pt   )

             # PyTorch not in environment -> use TensorFlow
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_torch_available"""    ,       UpperCamelCase_   ):
                    __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_tf   )

             # Both in environment -> use PyTorch
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_tf_available"""    ,       UpperCamelCase_   ), patch(
                 """transformers.onnx.features.is_torch_available"""    ,       UpperCamelCase_   ):
                    __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )
                    self.assertEqual(UpperCamelCase_    ,       self.framework_pt   )

             # Both not in environment -> raise error
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             __lowerCamelCase   =						MagicMock(return_value=UpperCamelCase_   )
             with patch("""transformers.onnx.features.is_tf_available"""    ,       UpperCamelCase_   ), patch(
                 """transformers.onnx.features.is_torch_available"""    ,       UpperCamelCase_   ):
                    with self.assertRaises(UpperCamelCase_   ):
                           __lowerCamelCase   =						FeaturesManager.determine_framework(self.test_model   )

