"""simple docstring"""




from __future__ import annotations

import unittest

from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow


if is_tf_available():
				import numpy as np
				import tensorflow as tf

				from transformers import TFXLMRobertaModel
@require_tf
@require_sentencepiece
@require_tokenizers
class     UpperCamelCase__(			unittest.TestCase ):





						@slow
						def 				snake_case__	(       self     )					->				Optional[Any]:
													A__	     =							TFXLMRobertaModel.from_pretrained('jplu/tf-xlm-roberta-base'     )

													A__	     =							{
													    'input_ids': tf.convert_to_tensor([[0, 26_46, 1_02_69, 83, 9_99_42, 2]]		,dtype=tf.intaa     ),  # "My dog is cute"
													    'attention_mask': tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]		,dtype=tf.intaa     ),
													}

													A__	     =							model(__UpperCAmelCase     )['last_hidden_state']
													A__	     =							tf.TensorShape((1, 6, 7_68)     )
													self.assertEqual(output.shape		,__UpperCAmelCase     )
													# compare the actual values for a slice.
													A__	     =							tf.convert_to_tensor(
													    [
													        [
													            [0.0_6_8_1_7_6_2, 0.1_0_8_9_4_4_5_1, 0.0_6_7_7_2_5_0_4],
													            [-0.0_6_4_2_3_6_6_8, 0.0_2_3_6_6_6_1_5, 0.0_4_3_2_9_3_4_4],
													            [-0.0_6_0_5_7_2_9_5, 0.0_9_9_7_4_1_3_5, -0.0_0_0_7_0_5_8_4],
													        ]
													    ]		,dtype=tf.floataa		,)

													self.assertTrue(np.allclose(output[:, :3, :3].numpy()		,expected_slice.numpy()		,atol=1e-4     )     )






"""simple docstring"""




from __future__ import annotations

from math import pi
from typing import Protocol

import matplotlib.pyplot as plt
import numpy as np
class     UpperCamelCase__(			__A ):





						def 				snake_case__	(       self		,__UpperCAmelCase     )					->				float:
													return 0.0






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							min([-20, np.min(fft_results[1 : samplerate // 2 - 1]				)]				)
							A__	     =							max([20, np.max(fft_results[1 : samplerate // 2 - 1]				)]				)
							return lowest, highest






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							512
							A__	     =							[1] + [0] * (size - 1)
							A__	     =							[filter_type.process(UpperCamelCase__				) for item in inputs]

							A__	     =							[0] * (samplerate - size)  # zero-padding
							outputs += filler
							A__	     =							np.abs(np.fft.fft(UpperCamelCase__				)				)
							A__	     =							20 * np.logaa(UpperCamelCase__				)

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24       ,    samplerate / 2 - 1				)
							plt.xlabel('Frequency (Hz)'				)
							plt.xscale('log'				)

							# Display within reasonable bounds
							A__	     =							get_bounds(UpperCamelCase__       ,    UpperCamelCase__				)
							plt.ylim(max([-80, bounds[0]]				)       ,    min([80, bounds[1]]				)				)
							plt.ylabel('Gain (dB)'				)

							plt.plot(UpperCamelCase__				)
							plt.show()






def   UpperCAmelCase					(	UpperCamelCase__       ,    UpperCamelCase__				):






							"""simple docstring"""





							A__	     =							512
							A__	     =							[1] + [0] * (size - 1)
							A__	     =							[filter_type.process(UpperCamelCase__				) for item in inputs]

							A__	     =							[0] * (samplerate - size)  # zero-padding
							outputs += filler
							A__	     =							np.angle(np.fft.fft(UpperCamelCase__				)				)

							# Frequencies on log scale from 24 to nyquist frequency
							plt.xlim(24       ,    samplerate / 2 - 1				)
							plt.xlabel('Frequency (Hz)'				)
							plt.xscale('log'				)

							plt.ylim(-2 * pi       ,    2 * pi				)
							plt.ylabel('Phase shift (Radians)'				)
							plt.plot(np.unwrap(UpperCamelCase__       ,    -2 * pi				)				)
							plt.show()





