


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        a	(_lowerCAmelCase   ):




							"""simple docstring"""


							def 					__snake_case      (							self :						Optional[Any]       )			->					Optional[Any]:
														__snake_case	:    Tuple											=     SMALL_MODEL_IDENTIFIER
														__snake_case	:    int											=     "pt"
														__snake_case	:    int											=     "tf"

							def 					__snake_case      (							self :						Any					,			lowerCamelCase :						str       )			->					int:
														__snake_case	:    List[str]											=     AutoModel.from_pretrained(self.test_model       )
														model_pt.save_pretrained(lowerCamelCase       )

							def 					__snake_case      (							self :						str					,			lowerCamelCase :						List[str]       )			->					Tuple:
														__snake_case	:    str											=     TFAutoModel.from_pretrained(self.test_model					,			from_pt=lowerCamelCase       )
														model_tf.save_pretrained(lowerCamelCase       )

							def 					__snake_case      (							self :						Union[str, Any]       )			->					Any:
														__snake_case	:    List[str]											=     "mock_framework"

														# Framework provided - return whatever the user provides
														__snake_case	:    List[str]											=     FeaturesManager.determine_framework(self.test_model					,			lowerCamelCase       )
														self.assertEqual(lowerCamelCase					,			lowerCamelCase       )

														# Local checkpoint and framework provided - return provided framework
														# PyTorch checkpoint
														with TemporaryDirectory() as local_pt_ckpt:
																					self._setup_pt_ckpt(lowerCamelCase       )
																					__snake_case	:    List[Any]											=     FeaturesManager.determine_framework(lowerCamelCase					,			lowerCamelCase       )
																					self.assertEqual(lowerCamelCase					,			lowerCamelCase       )

														# TensorFlow checkpoint
														with TemporaryDirectory() as local_tf_ckpt:
																					self._setup_tf_ckpt(lowerCamelCase       )
																					__snake_case	:    List[Any]											=     FeaturesManager.determine_framework(lowerCamelCase					,			lowerCamelCase       )
																					self.assertEqual(lowerCamelCase					,			lowerCamelCase       )

							def 					__snake_case      (							self :						Tuple       )			->					Union[str, Any]:
														# PyTorch checkpoint
														with TemporaryDirectory() as local_pt_ckpt:
																					self._setup_pt_ckpt(lowerCamelCase       )
																					__snake_case	:    Union[str, Any]											=     FeaturesManager.determine_framework(lowerCamelCase       )
																					self.assertEqual(lowerCamelCase					,			self.framework_pt       )

														# TensorFlow checkpoint
														with TemporaryDirectory() as local_tf_ckpt:
																					self._setup_tf_ckpt(lowerCamelCase       )
																					__snake_case	:    Optional[int]											=     FeaturesManager.determine_framework(lowerCamelCase       )
																					self.assertEqual(lowerCamelCase					,			self.framework_tf       )

														# Invalid local checkpoint
														with TemporaryDirectory() as local_invalid_ckpt:
																					with self.assertRaises(lowerCamelCase       ):
																												__snake_case	:    Optional[Any]											=     FeaturesManager.determine_framework(lowerCamelCase       )






							def 					__snake_case      (							self :						str       )			->					List[Any]:
														__snake_case	:    List[Any]											=     MagicMock(return_value=lowerCamelCase       )
														with patch("transformers.onnx.features.is_tf_available"					,			lowerCamelCase       ):
																					__snake_case	:    Any											=     FeaturesManager.determine_framework(self.test_model       )
																					self.assertEqual(lowerCamelCase					,			self.framework_pt       )

														# PyTorch not in environment -> use TensorFlow
														__snake_case	:    Union[str, Any]											=     MagicMock(return_value=lowerCamelCase       )
														with patch("transformers.onnx.features.is_torch_available"					,			lowerCamelCase       ):
																					__snake_case	:    Dict											=     FeaturesManager.determine_framework(self.test_model       )
																					self.assertEqual(lowerCamelCase					,			self.framework_tf       )

														# Both in environment -> use PyTorch
														__snake_case	:    Optional[int]											=     MagicMock(return_value=lowerCamelCase       )
														__snake_case	:    List[Any]											=     MagicMock(return_value=lowerCamelCase       )
														with patch("transformers.onnx.features.is_tf_available"					,			lowerCamelCase       ), patch(
														    "transformers.onnx.features.is_torch_available"					,			lowerCamelCase       ):
																					__snake_case	:    str											=     FeaturesManager.determine_framework(self.test_model       )
																					self.assertEqual(lowerCamelCase					,			self.framework_pt       )

														# Both not in environment -> raise error
														__snake_case	:    Tuple											=     MagicMock(return_value=lowerCamelCase       )
														__snake_case	:    str											=     MagicMock(return_value=lowerCamelCase       )
														with patch("transformers.onnx.features.is_tf_available"					,			lowerCamelCase       ), patch(
														    "transformers.onnx.features.is_torch_available"					,			lowerCamelCase       ):
																					with self.assertRaises(lowerCamelCase       ):
																												__snake_case	:    List[str]											=     FeaturesManager.determine_framework(self.test_model       )





import math







def        lowerCAmelCase_  (      __lowerCamelCase							,			__lowerCamelCase			):

							if initial_intensity < 0:
														raise ValueError("The value of intensity cannot be negative"			)
														# handling of negative values of initial intensity
							if angle < 0 or angle > 3_6_0:
														raise ValueError("In Malus Law, the angle is in the range 0-360 degrees"			)
														# handling of values out of allowed range
							return initial_intensity * (math.cos(math.radians(__lowerCamelCase			)			) ** 2)


if __name__ == "__main__":
			import doctest

			doctest.testmod(name="malus_law")

