



'''simple docstring'''

import unittest

import numpy as np

from transformers.testing_utils import require_flax, require_tf, require_torch
from transformers.utils import (
    expand_dims,
    flatten_dict,
    is_flax_available,
    is_tf_available,
    is_torch_available,
    reshape,
    squeeze,
    transpose,
)


if is_flax_available():
						import jax.numpy as jnp

if is_tf_available():
						import tensorflow as tf

if is_torch_available():
						import torch

class __snake_case(				unittest.TestCase ):


						'''simple docstring'''



						def     __snake_case   ( self				)     ->     List[str]:
							lowerCAmelCase   =     {
							    "task_specific_params": {
							        "summarization": {"length_penalty": 1.0, "max_length": 128, "min_length": 12, "num_beams": 4},
							        "summarization_cnn": {"length_penalty": 2.0, "max_length": 142, "min_length": 56, "num_beams": 4},
							        "summarization_xsum": {"length_penalty": 1.0, "max_length": 62, "min_length": 11, "num_beams": 6},
							    }
							}
							lowerCAmelCase   =     {
							    "task_specific_params.summarization.length_penalty": 1.0,
							    "task_specific_params.summarization.max_length": 128,
							    "task_specific_params.summarization.min_length": 12,
							    "task_specific_params.summarization.num_beams": 4,
							    "task_specific_params.summarization_cnn.length_penalty": 2.0,
							    "task_specific_params.summarization_cnn.max_length": 142,
							    "task_specific_params.summarization_cnn.min_length": 56,
							    "task_specific_params.summarization_cnn.num_beams": 4,
							    "task_specific_params.summarization_xsum.length_penalty": 1.0,
							    "task_specific_params.summarization_xsum.max_length": 62,
							    "task_specific_params.summarization_xsum.min_length": 11,
							    "task_specific_params.summarization_xsum.num_beams": 6,
							}

							self.assertEqual(flatten_dict(_SCREAMING_SNAKE_CASE				)     ,	_SCREAMING_SNAKE_CASE				)


						def     __snake_case   ( self				)     ->     int:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE				)     ,	x.transpose()				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE     ,	axes=(1, 2, 0)				)     ,	x.transpose((1, 2, 0)				)				)				)


						@require_torch
						def     __snake_case   ( self				)     ->     Optional[Any]:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     torch.tensor(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE				)     ,	transpose(_SCREAMING_SNAKE_CASE				).numpy()				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							lowerCAmelCase   =     torch.tensor(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE     ,	axes=(1, 2, 0)				)     ,	transpose(_SCREAMING_SNAKE_CASE     ,	axes=(1, 2, 0)				).numpy()				)				)


						@require_tf
						def     __snake_case   ( self				)     ->     List[Any]:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     tf.constant(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE				)     ,	transpose(_SCREAMING_SNAKE_CASE				).numpy()				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							lowerCAmelCase   =     tf.constant(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE     ,	axes=(1, 2, 0)				)     ,	transpose(_SCREAMING_SNAKE_CASE     ,	axes=(1, 2, 0)				).numpy()				)				)


						@require_flax
						def     __snake_case   ( self				)     ->     Optional[Any]:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     jnp.array(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE				)     ,	np.asarray(transpose(_SCREAMING_SNAKE_CASE				)				)				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							lowerCAmelCase   =     jnp.array(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(transpose(_SCREAMING_SNAKE_CASE     ,	axes=(1, 2, 0)				)     ,	np.asarray(transpose(_SCREAMING_SNAKE_CASE     ,	axes=(1, 2, 0)				)				)				)				)


						def     __snake_case   ( self				)     ->     Any:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				)     ,	np.reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				)				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				)     ,	np.reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				)				)				)


						@require_torch
						def     __snake_case   ( self				)     ->     Any:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     torch.tensor(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				)     ,	reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				).numpy()				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							lowerCAmelCase   =     torch.tensor(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				)     ,	reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				).numpy()				)				)


						@require_tf
						def     __snake_case   ( self				)     ->     Optional[int]:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     tf.constant(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				)     ,	reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				).numpy()				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							lowerCAmelCase   =     tf.constant(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				)     ,	reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				).numpy()				)				)


						@require_flax
						def     __snake_case   ( self				)     ->     List[Any]:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     jnp.array(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				)     ,	np.asarray(reshape(_SCREAMING_SNAKE_CASE     ,	(4, 3)				)				)				)				)

							lowerCAmelCase   =     np.random.randn(3     ,	4     ,	5				)
							lowerCAmelCase   =     jnp.array(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				)     ,	np.asarray(reshape(_SCREAMING_SNAKE_CASE     ,	(12, 5)				)				)				)				)


						def     __snake_case   ( self				)     ->     int:
							lowerCAmelCase   =     np.random.randn(1     ,	3     ,	4				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE				)     ,	np.squeeze(_SCREAMING_SNAKE_CASE				)				)				)

							lowerCAmelCase   =     np.random.randn(1     ,	4     ,	1     ,	5				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				)     ,	np.squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				)				)				)


						@require_torch
						def     __snake_case   ( self				)     ->     str:
							lowerCAmelCase   =     np.random.randn(1     ,	3     ,	4				)
							lowerCAmelCase   =     torch.tensor(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE				)     ,	squeeze(_SCREAMING_SNAKE_CASE				).numpy()				)				)

							lowerCAmelCase   =     np.random.randn(1     ,	4     ,	1     ,	5				)
							lowerCAmelCase   =     torch.tensor(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				)     ,	squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				).numpy()				)				)


						@require_tf
						def     __snake_case   ( self				)     ->     Dict:
							lowerCAmelCase   =     np.random.randn(1     ,	3     ,	4				)
							lowerCAmelCase   =     tf.constant(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE				)     ,	squeeze(_SCREAMING_SNAKE_CASE				).numpy()				)				)

							lowerCAmelCase   =     np.random.randn(1     ,	4     ,	1     ,	5				)
							lowerCAmelCase   =     tf.constant(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				)     ,	squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				).numpy()				)				)


						@require_flax
						def     __snake_case   ( self				)     ->     List[str]:
							lowerCAmelCase   =     np.random.randn(1     ,	3     ,	4				)
							lowerCAmelCase   =     jnp.array(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE				)     ,	np.asarray(squeeze(_SCREAMING_SNAKE_CASE				)				)				)				)

							lowerCAmelCase   =     np.random.randn(1     ,	4     ,	1     ,	5				)
							lowerCAmelCase   =     jnp.array(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				)     ,	np.asarray(squeeze(_SCREAMING_SNAKE_CASE     ,	axis=2				)				)				)				)


						def     __snake_case   ( self				)     ->     Any:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							self.assertTrue(np.allclose(expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				)     ,	np.expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				)				)				)


						@require_torch
						def     __snake_case   ( self				)     ->     Any:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     torch.tensor(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				)     ,	expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				).numpy()				)				)


						@require_tf
						def     __snake_case   ( self				)     ->     str:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     tf.constant(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				)     ,	expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				).numpy()				)				)




						@require_flax
						def     __snake_case   ( self				)     ->     str:
							lowerCAmelCase   =     np.random.randn(3     ,	4				)
							lowerCAmelCase   =     jnp.array(_SCREAMING_SNAKE_CASE				)
							self.assertTrue(np.allclose(expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				)     ,	np.asarray(expand_dims(_SCREAMING_SNAKE_CASE     ,	axis=1				)				)				)				)




'''simple docstring'''

import cmath
import math






def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						float							,		_SCREAMING_SNAKE_CASE					:						float							,		_SCREAMING_SNAKE_CASE					:						float							,		_SCREAMING_SNAKE_CASE					:						float							)      ->						complex:







	"""simple docstring"""
	lowerCAmelCase   =     math.radians(_SCREAMING_SNAKE_CASE							)
	lowerCAmelCase   =     math.radians(_SCREAMING_SNAKE_CASE							)

	# Convert voltage and current to rectangular form
	lowerCAmelCase   =     cmath.rect(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)
	lowerCAmelCase   =     cmath.rect(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)

	# Calculate apparent power
	return voltage_rect * current_rect


if __name__ == "__main__":
				import doctest

				doctest.testmod()