





from __future__ import annotations

import unittest

from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow

from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin import PipelineTesterMixin


if is_tf_available():
					import tensorflow as tf

					from transformers import (
					    TF_MODEL_FOR_PRETRAINING_MAPPING,
					    TFMobileBertForMaskedLM,
					    TFMobileBertForMultipleChoice,
					    TFMobileBertForNextSentencePrediction,
					    TFMobileBertForPreTraining,
					    TFMobileBertForQuestionAnswering,
					    TFMobileBertForSequenceClassification,
					    TFMobileBertForTokenClassification,
					    TFMobileBertModel,
					)

@require_tf
class        __SCREAMING_SNAKE_CASE					(     _a   ,		_a   ,		unittest.TestCase       ):
							snake_case     :      List[Any]						     =       (
							    (
							        TFMobileBertModel,
							        TFMobileBertForMaskedLM,
							        TFMobileBertForNextSentencePrediction,
							        TFMobileBertForPreTraining,
							        TFMobileBertForQuestionAnswering,
							        TFMobileBertForSequenceClassification,
							        TFMobileBertForTokenClassification,
							        TFMobileBertForMultipleChoice,
							    )
							    if is_tf_available()
							    else ()
							)
							snake_case     :      Dict						     =       (
							    {
							        """feature-extraction""": TFMobileBertModel,
							        """fill-mask""": TFMobileBertForMaskedLM,
							        """question-answering""": TFMobileBertForQuestionAnswering,
							        """text-classification""": TFMobileBertForSequenceClassification,
							        """token-classification""": TFMobileBertForTokenClassification,
							        """zero-shot""": TFMobileBertForSequenceClassification,
							    }
							    if is_tf_available()
							    else {}
							)
							snake_case     :      Any						     =       False
							snake_case     :      int						     =       False






							def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase=False  ):
														UpperCamelCase__				     =			super()._prepare_for_class(__lowerCAmelCase  , __lowerCAmelCase  , return_labels=__lowerCAmelCase  )

														if return_labels:
																					if model_class in get_values(__lowerCAmelCase  ):
																												UpperCamelCase__				     =			tf.zeros(self.model_tester.batch_size  , dtype=tf.intaa  )

														return inputs_dict

							class        __SCREAMING_SNAKE_CASE					(     _a       ):






														def __init__(						self  , __lowerCAmelCase  , __lowerCAmelCase=13  , __lowerCAmelCase=7  , __lowerCAmelCase=True  , __lowerCAmelCase=True  , __lowerCAmelCase=True  , __lowerCAmelCase=True  , __lowerCAmelCase=99  , __lowerCAmelCase=32  , __lowerCAmelCase=32  , __lowerCAmelCase=2  , __lowerCAmelCase=4  , __lowerCAmelCase=37  , __lowerCAmelCase="gelu"  , __lowerCAmelCase=0.1  , __lowerCAmelCase=0.1  , __lowerCAmelCase=512  , __lowerCAmelCase=16  , __lowerCAmelCase=2  , __lowerCAmelCase=0.02  , __lowerCAmelCase=3  , __lowerCAmelCase=4  , __lowerCAmelCase=None  , ):
																					UpperCamelCase__				     =			parent
																					UpperCamelCase__				     =			batch_size
																					UpperCamelCase__				     =			seq_length
																					UpperCamelCase__				     =			is_training
																					UpperCamelCase__				     =			use_input_mask
																					UpperCamelCase__				     =			use_token_type_ids
																					UpperCamelCase__				     =			use_labels
																					UpperCamelCase__				     =			vocab_size
																					UpperCamelCase__				     =			hidden_size
																					UpperCamelCase__				     =			num_hidden_layers
																					UpperCamelCase__				     =			num_attention_heads
																					UpperCamelCase__				     =			intermediate_size
																					UpperCamelCase__				     =			hidden_act
																					UpperCamelCase__				     =			hidden_dropout_prob
																					UpperCamelCase__				     =			attention_probs_dropout_prob
																					UpperCamelCase__				     =			max_position_embeddings
																					UpperCamelCase__				     =			type_vocab_size
																					UpperCamelCase__				     =			type_sequence_label_size
																					UpperCamelCase__				     =			initializer_range
																					UpperCamelCase__				     =			num_labels
																					UpperCamelCase__				     =			num_choices
																					UpperCamelCase__				     =			scope
																					UpperCamelCase__				     =			embedding_size






														def 				_lowerCamelCase		(						self  ):
																					UpperCamelCase__				     =			ids_tensor([self.batch_size, self.seq_length]  , self.vocab_size  )

																					UpperCamelCase__				     =			None
																					if self.use_input_mask:
																												UpperCamelCase__				     =			random_attention_mask([self.batch_size, self.seq_length]  )

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

																					UpperCamelCase__				     =			None
																					UpperCamelCase__				     =			None
																					UpperCamelCase__				     =			None
																					if self.use_labels:
																												UpperCamelCase__				     =			ids_tensor([self.batch_size]  , self.type_sequence_label_size  )
																												UpperCamelCase__				     =			ids_tensor([self.batch_size, self.seq_length]  , self.num_labels  )
																												UpperCamelCase__				     =			ids_tensor([self.batch_size]  , self.num_choices  )

																					UpperCamelCase__				     =			MobileBertConfig(
																					    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  , initializer_range=self.initializer_range  , embedding_size=self.embedding_size  , )

																					return config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			TFMobileBertModel(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )

																					UpperCamelCase__				     =			[input_ids, input_mask]
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )

																					UpperCamelCase__				     =			model(__lowerCAmelCase  )

																					self.parent.assertEqual(
																					    result.last_hidden_state.shape  , (self.batch_size, self.seq_length, self.hidden_size)  )
																					self.parent.assertEqual(result.pooler_output.shape  , (self.batch_size, self.hidden_size)  )






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			TFMobileBertForMaskedLM(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )
																					self.parent.assertEqual(result.logits.shape  , (self.batch_size, self.seq_length, self.vocab_size)  )






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			TFMobileBertForNextSentencePrediction(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )
																					self.parent.assertEqual(result.logits.shape  , (self.batch_size, 2)  )






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			TFMobileBertForPreTraining(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )
																					self.parent.assertEqual(
																					    result.prediction_logits.shape  , (self.batch_size, self.seq_length, self.vocab_size)  )
																					self.parent.assertEqual(result.seq_relationship_logits.shape  , (self.batch_size, 2)  )






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			self.num_labels
																					UpperCamelCase__				     =			TFMobileBertForSequenceClassification(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )
																					self.parent.assertEqual(result.logits.shape  , (self.batch_size, self.num_labels)  )






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			self.num_choices
																					UpperCamelCase__				     =			TFMobileBertForMultipleChoice(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			tf.tile(tf.expand_dims(__lowerCAmelCase  , 1  )  , (1, self.num_choices, 1)  )
																					UpperCamelCase__				     =			tf.tile(tf.expand_dims(__lowerCAmelCase  , 1  )  , (1, self.num_choices, 1)  )
																					UpperCamelCase__				     =			tf.tile(tf.expand_dims(__lowerCAmelCase  , 1  )  , (1, self.num_choices, 1)  )
																					UpperCamelCase__				     =			{
																					    """input_ids""": multiple_choice_inputs_ids,
																					    """attention_mask""": multiple_choice_input_mask,
																					    """token_type_ids""": multiple_choice_token_type_ids,
																					}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )
																					self.parent.assertEqual(result.logits.shape  , (self.batch_size, self.num_choices)  )






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			self.num_labels
																					UpperCamelCase__				     =			TFMobileBertForTokenClassification(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )
																					self.parent.assertEqual(result.logits.shape  , (self.batch_size, self.seq_length, self.num_labels)  )






														def 				_lowerCamelCase		(						self  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  , __lowerCAmelCase  ):
																					UpperCamelCase__				     =			TFMobileBertForQuestionAnswering(config=__lowerCAmelCase  )
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """attention_mask""": input_mask, """token_type_ids""": token_type_ids}
																					UpperCamelCase__				     =			model(__lowerCAmelCase  )
																					self.parent.assertEqual(result.start_logits.shape  , (self.batch_size, self.seq_length)  )
																					self.parent.assertEqual(result.end_logits.shape  , (self.batch_size, self.seq_length)  )







														def 				_lowerCamelCase		(						self  ):
																					UpperCamelCase__				     =			self.prepare_config_and_inputs()
																					(
																					    (
																					    UpperCamelCase__
																					)     ,     (
																					    UpperCamelCase__
																					)     ,     (
																					    UpperCamelCase__
																					)     ,     (
																					    UpperCamelCase__
																					)     ,     (
																					    UpperCamelCase__
																					)     ,     (
																					    UpperCamelCase__
																					)     ,     (
																					    UpperCamelCase__
																					)     ,     
																					)				     =			config_and_inputs
																					UpperCamelCase__				     =			{"""input_ids""": input_ids, """token_type_ids""": token_type_ids, """attention_mask""": input_mask}
																					return config, inputs_dict






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			TFMobileBertModelTest.TFMobileBertModelTester(self  )
														UpperCamelCase__				     =			ConfigTester(self  , config_class=__lowerCAmelCase  , hidden_size=37  )






							def 				_lowerCamelCase		(						self  ):
														self.config_tester.run_common_tests()






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_model(*__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_for_masked_lm(*__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_for_multiple_choice(*__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_for_next_sequence_prediction(*__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_for_pretraining(*__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_for_question_answering(*__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_for_sequence_classification(*__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.model_tester.prepare_config_and_inputs()
														self.model_tester.create_and_check_mobilebert_for_token_classification(*__lowerCAmelCase  )







							@slow
							def 				_lowerCamelCase		(						self  ):
														# for model_name in TF_MOBILEBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
														for model_name in ["google/mobilebert-uncased"]:
																					UpperCamelCase__				     =			TFMobileBertModel.from_pretrained(__lowerCAmelCase  )
																					self.assertIsNotNone(__lowerCAmelCase  )






@require_tf
class        __SCREAMING_SNAKE_CASE					(     unittest.TestCase       ):






							@slow
							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			TFMobileBertForPreTraining.from_pretrained("""google/mobilebert-uncased"""  )
														UpperCamelCase__				     =			tf.constant([[0, 1, 2, 3, 4, 5]]  )
														UpperCamelCase__				     =			model(__lowerCAmelCase  )[0]

														UpperCamelCase__				     =			[1, 6, 30522]
														self.assertEqual(output.shape  , __lowerCAmelCase  )

														UpperCamelCase__				     =			tf.constant(
														    [
														        [
														            [-4.591_9547, -9.24_8295, -9.64_5256],
														            [-6.730_6175, -6.44_0284, -6.605_2837],
														            [-7.274_3506, -6.784_7915, -6.02_4673],
														        ]
														    ]  )
														tf.debugging.assert_near(output[:, :3, :3]  , __lowerCAmelCase  , atol=1E-4  )











from sympy import diff, lambdify, symbols
from sympy.functions import *  # noqa: F403





def     _UpperCamelCase     (a__   :str   ,			a__   :complex   ,			a__   :str = "x"   ,			a__   :float = 10**-10   ,			a__   :int = 1   ,			):






							"""simple docstring"""





							UpperCamelCase__				     =			symbols(a__       )
							UpperCamelCase__				     =			lambdify(a__   ,			a__       )
							UpperCamelCase__				     =			lambdify(a__   ,			diff(a__   ,			a__       )       )

							UpperCamelCase__				     =			starting_point

							while True:
														if diff_function(a__       ) != 0:
																					UpperCamelCase__				     =			prev_guess - multiplicity * func(a__       ) / diff_function(
																					    a__       )
														else:
																					raise ZeroDivisionError("""Could not find root"""       ) from None

														# Precision is checked by comparing the difference of consecutive guesses
														if abs(next_guess - prev_guess       ) < precision:
																					return next_guess

														UpperCamelCase__				     =			next_guess


# Let's Execute
if __name__ == "__main__":
					# Find root of trigonometric function
					# Find value of pi
					print(f"""The root of sin(x) = 0 is {newton_raphson('sin(x)', 2)}""")

					# Find root of polynomial
					# Find fourth Root of 5
					print(f"""The root of x**4 - 5 = 0 is {newton_raphson('x**4 -5', 0.4 +5J)}""")

					# Find value of e
					print(
					    "The root of log(y) - 1 = 0 is ",
					    f"""{newton_raphson('log(y) - 1', 2, variable='y')}""",
					)

					# Exponential Roots
					print(
					    "The root of exp(x) - 1 = 0 is",
					    f"""{newton_raphson('exp(x) - 1', 10, precision=0.0_05)}""",
					)

					# Find root of cos(x)
					print(f"""The root of cos(x) = 0 is {newton_raphson('cos(x)', 0)}""")




