





'''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 				UpperCAmelCase__   (self      :	str				)					-> Union[str, Any]:
						lowercase         = TFXLMRobertaModel.from_pretrained("jplu/tf-xlm-roberta-base"				)

						lowercase         = {
						    "input_ids": tf.convert_to_tensor([[0, 2_6_4_6, 1_0_2_6_9, 8_3, 9_9_9_4_2, 2]]							,			dtype=tf.intaa				),  # "My dog is cute"
						    "attention_mask": tf.convert_to_tensor([[1, 1, 1, 1, 1, 1]]							,			dtype=tf.intaa				),
						}

						lowercase         = model(A__				)["last_hidden_state"]
						lowercase         = tf.TensorShape((1, 6, 7_6_8)				)
						self.assertEqual(output.shape							,			A__				)
						# compare the actual values for a slice.
						lowercase         = 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

class       UpperCAmelCase :




		def __init__(self      :	Dict							,			A__      :	str							,			A__      :	str				)					-> str:
						lowercase   ,							lowercase         = text, pattern
						lowercase   ,							lowercase         = len(A__				), len(A__				)




		def 				UpperCAmelCase__   (self      :	Any							,			A__      :	str				)					-> int:

						for i in range(self.patLen - 1							,			-1							,			-1				):
										if char == self.pattern[i]:
														return i
						return -1




		def 				UpperCAmelCase__   (self      :	List[Any]							,			A__      :	int				)					-> int:

						for i in range(self.patLen - 1							,			-1							,			-1				):
										if self.pattern[i] != self.text[current_pos + i]:
														return current_pos + i
						return -1





		def 				UpperCAmelCase__   (self      :	Optional[Any]				)					-> list[int]:
						# searches pattern in text and returns index positions
						lowercase         = []
						for i in range(self.textLen - self.patLen + 1				):
										lowercase         = self.mismatch_in_text(A__				)
										if mismatch_index == -1:
														positions.append(A__				)
										else:
														lowercase         = self.match_in_pattern(self.text[mismatch_index]				)
														lowercase         = (
														    mismatch_index - match_index
														)  # shifting index lgtm [py/multiple-definition]
						return positions




__lowerCamelCase : List[str]											=			"ABAABA"
__lowerCamelCase : List[str]											=			"AB"
__lowerCamelCase : Union[str, Any]											=			BoyerMooreSearch(text, pattern)
__lowerCamelCase : List[str]											=			bms.bad_character_heuristic()

if len(positions) == 0:
			print("No match found")
else:
			print("Pattern found in following positions: ")
			print(positions)




