
"""simple docstring"""




import unittest

import numpy as np

from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow

from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask


if is_flax_available():
					import jax.numpy as jnp

					from transformers.models.roformer.modeling_flax_roformer import (
					    FlaxRoFormerForMaskedLM,
					    FlaxRoFormerForMultipleChoice,
					    FlaxRoFormerForQuestionAnswering,
					    FlaxRoFormerForSequenceClassification,
					    FlaxRoFormerForTokenClassification,
					    FlaxRoFormerModel,
					)





class 							UpperCAmelCase				(  unittest.TestCase  ):




	'''simple docstring'''





	def __init__(	self :			Dict							,A :			Optional[Any]							,A :			List[Any]=13							,A :			str=7							,A :			List[str]=True							,A :			Optional[int]=True							,A :			str=True							,A :			Any=True							,A :			Optional[Any]=99							,A :			int=32							,A :			List[Any]=5							,A :			int=4							,A :			str=37							,A :			Any="gelu"							,A :			List[str]=0.1							,A :			List[str]=0.1							,A :			Optional[int]=5_12							,A :			Optional[int]=16							,A :			int=2							,A :			Any=0.02							,A :			List[Any]=4							,):
					__A             =			parent
					__A             =			batch_size
					__A             =			seq_length
					__A             =			is_training
					__A             =			use_attention_mask
					__A             =			use_token_type_ids
					__A             =			use_labels
					__A             =			vocab_size
					__A             =			hidden_size
					__A             =			num_hidden_layers
					__A             =			num_attention_heads
					__A             =			intermediate_size
					__A             =			hidden_act
					__A             =			hidden_dropout_prob
					__A             =			attention_probs_dropout_prob
					__A             =			max_position_embeddings
					__A             =			type_vocab_size
					__A             =			type_sequence_label_size
					__A             =			initializer_range
					__A             =			num_choices






	def     UpperCamelCase_  (	self :			Optional[Any]			):
					__A             =			ids_tensor([self.batch_size, self.seq_length]							,self.vocab_size			)

					__A             =			None
					if self.use_attention_mask:
									__A             =			random_attention_mask([self.batch_size, self.seq_length]			)

					__A             =			None
					if self.use_token_type_ids:
									__A             =			ids_tensor([self.batch_size, self.seq_length]							,self.type_vocab_size			)

					__A             =			RoFormerConfig(
					    vocab_size=self.vocab_size							,hidden_size=self.hidden_size							,num_hidden_layers=self.num_hidden_layers							,num_attention_heads=self.num_attention_heads							,intermediate_size=self.intermediate_size							,hidden_act=self.hidden_act							,hidden_dropout_prob=self.hidden_dropout_prob							,attention_probs_dropout_prob=self.attention_probs_dropout_prob							,max_position_embeddings=self.max_position_embeddings							,type_vocab_size=self.type_vocab_size							,is_decoder=A							,initializer_range=self.initializer_range							,)

					return config, input_ids, token_type_ids, attention_mask







	def     UpperCamelCase_  (	self :			Any			):
					__A             =			self.prepare_config_and_inputs()
					__A      ,							__A      ,							__A      ,							__A             =			config_and_inputs
					__A             =			{"input_ids": input_ids, "token_type_ids": token_type_ids, "attention_mask": attention_mask}
					return config, inputs_dict





@require_flax
class 							UpperCAmelCase				(  __SCREAMING_SNAKE_CASE      ,      unittest.TestCase  ):




	'''simple docstring'''





	snake_case_    =					True

	snake_case_    =					(
	    (
	        FlaxRoFormerModel,
	        FlaxRoFormerForMaskedLM,
	        FlaxRoFormerForSequenceClassification,
	        FlaxRoFormerForTokenClassification,
	        FlaxRoFormerForMultipleChoice,
	        FlaxRoFormerForQuestionAnswering,
	    )
	    if is_flax_available()
	    else ()
	)






	def     UpperCamelCase_  (	self :			List[str]			):
					__A             =			FlaxRoFormerModelTester(self			)







	@slow
	def     UpperCamelCase_  (	self :			Optional[int]			):
					for model_class_name in self.all_model_classes:
									__A             =			model_class_name.from_pretrained("junnyu/roformer_chinese_small"							,from_pt=A			)
									__A             =			model(np.ones((1, 1)			)			)
									self.assertIsNotNone(A			)





@require_flax
class 							UpperCAmelCase				(  unittest.TestCase  ):




	'''simple docstring'''





	@slow
	def     UpperCamelCase_  (	self :			Dict			):
					__A             =			FlaxRoFormerForMaskedLM.from_pretrained("junnyu/roformer_chinese_base"			)
					__A             =			jnp.array([[0, 1, 2, 3, 4, 5]]			)
					__A             =			model(A			)[0]

					__A             =			5_00_00

					__A             =			(1, 6, vocab_size)
					self.assertEqual(output.shape							,A			)

					__A             =			jnp.array(
					    [[[-0.12_05, -1.02_65, 0.29_22], [-1.51_34, 0.19_74, 0.15_19], [-5.01_35, -3.90_03, -0.84_04]]]			)

					self.assertTrue(jnp.allclose(output[:, :3, :3]							,A							,atol=1E-4			)			)


from __future__ import annotations


def 						UpperCAmelCase      (     a_ = 4						)		->     list[list[int]]:







				"""simple docstring"""



				__A             =			abs(a_						) or 4
				return [[1 + x + y * row_size for x in range(a_						)] for y in range(a_						)]


def 						UpperCAmelCase      (     a_						)		->     list[list[int]]:







				"""simple docstring"""



				return reverse_row(transpose(a_						)						)
				# OR.. transpose(reverse_column(matrix))


def 						UpperCAmelCase      (     a_						)		->     list[list[int]]:







				"""simple docstring"""



				return reverse_row(reverse_column(a_						)						)
				# OR.. reverse_column(reverse_row(matrix))


def 						UpperCAmelCase      (     a_						)		->     list[list[int]]:







				"""simple docstring"""



				return reverse_column(transpose(a_						)						)
				# OR.. transpose(reverse_row(matrix))


def 						UpperCAmelCase      (     a_						)		->     list[list[int]]:







				"""simple docstring"""



				__A             =			[list(a_						) for x in zip(*a_						)]
				return matrix


def 						UpperCAmelCase      (     a_						)		->     list[list[int]]:







				"""simple docstring"""



				__A             =			matrix[::-1]
				return matrix


def 						UpperCAmelCase      (     a_						)		->     list[list[int]]:







				"""simple docstring"""



				__A             =			[x[::-1] for x in matrix]
				return matrix


def 						UpperCAmelCase      (     a_						)		->     None:







				"""simple docstring"""



				for i in matrix:
								print(*a_						)


if __name__ == "__main__":
					SCREAMING_SNAKE_CASE							:Union[str, Any]										=    make_matrix()
					print('\norigin:\n')
					print_matrix(matrix)
					print('\nrotate 90 counterclockwise:\n')
					print_matrix(rotate_aa(matrix))

					SCREAMING_SNAKE_CASE							:Tuple										=    make_matrix()
					print('\norigin:\n')
					print_matrix(matrix)
					print('\nrotate 180:\n')
					print_matrix(rotate_aaa(matrix))

					SCREAMING_SNAKE_CASE							:Union[str, Any]										=    make_matrix()
					print('\norigin:\n')
					print_matrix(matrix)
					print('\nrotate 270 counterclockwise:\n')
					print_matrix(rotate_aaa(matrix))
