





from __future__ import annotations

import unittest

from transformers import MPNetConfig, is_tf_available
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.models.mpnet.modeling_tf_mpnet import (
			    TFMPNetForMaskedLM,
			    TFMPNetForMultipleChoice,
			    TFMPNetForQuestionAnswering,
			    TFMPNetForSequenceClassification,
			    TFMPNetForTokenClassification,
			    TFMPNetModel,
			)






class  __A   :

							'''simple docstring'''







							def __init__(   self	,  __lowerCAmelCase	,  __lowerCAmelCase=1_3	,  __lowerCAmelCase=7	,  __lowerCAmelCase=True	,  __lowerCAmelCase=True	,  __lowerCAmelCase=False	,  __lowerCAmelCase=True	,  __lowerCAmelCase=9_9	,  __lowerCAmelCase=6_4	,  __lowerCAmelCase=2	,  __lowerCAmelCase=4	,  __lowerCAmelCase=6_4	,  __lowerCAmelCase="gelu"	,  __lowerCAmelCase=0.1	,  __lowerCAmelCase=0.1	,  __lowerCAmelCase=5_1_2	,  __lowerCAmelCase=1_6	,  __lowerCAmelCase=2	,  __lowerCAmelCase=0.02	,  __lowerCAmelCase=3	,  __lowerCAmelCase=4	,  __lowerCAmelCase=None	,  ):



								'''simple docstring'''







								lowerCamelCase__        =		parent
								lowerCamelCase__        =		batch_size
								lowerCamelCase__        =		seq_length
								lowerCamelCase__        =		is_training
								lowerCamelCase__        =		use_input_mask
								lowerCamelCase__        =		use_token_type_ids
								lowerCamelCase__        =		use_labels
								lowerCamelCase__        =		vocab_size
								lowerCamelCase__        =		hidden_size
								lowerCamelCase__        =		num_hidden_layers
								lowerCamelCase__        =		num_attention_heads
								lowerCamelCase__        =		intermediate_size
								lowerCamelCase__        =		hidden_act
								lowerCamelCase__        =		hidden_dropout_prob
								lowerCamelCase__        =		attention_probs_dropout_prob
								lowerCamelCase__        =		max_position_embeddings
								lowerCamelCase__        =		type_vocab_size
								lowerCamelCase__        =		type_sequence_label_size
								lowerCamelCase__        =		initializer_range
								lowerCamelCase__        =		num_labels
								lowerCamelCase__        =		num_choices
								lowerCamelCase__        =		scope





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		ids_tensor([self.batch_size, self.seq_length]	,  self.vocab_size							)

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

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

								lowerCamelCase__        =		MPNetConfig(
								    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	,  initializer_range=self.initializer_range	,  )
								return config, input_ids, input_mask, sequence_labels, token_labels, choice_labels





							def 		__lowerCamelCase    (   self	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase							):



								'''simple docstring'''







								lowerCamelCase__        =		TFMPNetModel(config=__lowerCAmelCase							)
								lowerCamelCase__        =		{'''input_ids''': input_ids, '''attention_mask''': input_mask}
								lowerCamelCase__        =		model(__lowerCAmelCase							)
								lowerCamelCase__        =		[input_ids, input_mask]
								lowerCamelCase__        =		model(__lowerCAmelCase							)
								self.parent.assertEqual(result.last_hidden_state.shape	,  (self.batch_size, self.seq_length, self.hidden_size)							)





							def 		__lowerCamelCase    (   self	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase							):



								'''simple docstring'''







								lowerCamelCase__        =		TFMPNetForMaskedLM(config=__lowerCAmelCase							)
								lowerCamelCase__        =		{'''input_ids''': input_ids, '''attention_mask''': input_mask}
								lowerCamelCase__        =		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							):



								'''simple docstring'''







								lowerCamelCase__        =		TFMPNetForQuestionAnswering(config=__lowerCAmelCase							)
								lowerCamelCase__        =		{
								    '''input_ids''': input_ids,
								    '''attention_mask''': input_mask,
								}
								lowerCamelCase__        =		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	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase							):



								'''simple docstring'''







								lowerCamelCase__        =		self.num_labels
								lowerCamelCase__        =		TFMPNetForSequenceClassification(__lowerCAmelCase							)
								lowerCamelCase__        =		{'''input_ids''': input_ids, '''attention_mask''': input_mask}
								lowerCamelCase__        =		model(__lowerCAmelCase							)
								self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.num_labels)							)





							def 		__lowerCamelCase    (   self	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase							):



								'''simple docstring'''







								lowerCamelCase__        =		self.num_choices
								lowerCamelCase__        =		TFMPNetForMultipleChoice(__lowerCAmelCase							)
								lowerCamelCase__        =		tf.tile(tf.expand_dims(__lowerCAmelCase	,  1							)	,  (1, self.num_choices, 1)							)
								lowerCamelCase__        =		tf.tile(tf.expand_dims(__lowerCAmelCase	,  1							)	,  (1, self.num_choices, 1)							)
								lowerCamelCase__        =		{
								    '''input_ids''': multiple_choice_inputs_ids,
								    '''attention_mask''': multiple_choice_input_mask,
								}
								lowerCamelCase__        =		model(__lowerCAmelCase							)
								self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.num_choices)							)





							def 		__lowerCamelCase    (   self	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase	,  __lowerCAmelCase							):



								'''simple docstring'''







								lowerCamelCase__        =		self.num_labels
								lowerCamelCase__        =		TFMPNetForTokenClassification(__lowerCAmelCase							)
								lowerCamelCase__        =		{'''input_ids''': input_ids, '''attention_mask''': input_mask}
								lowerCamelCase__        =		model(__lowerCAmelCase							)
								self.parent.assertEqual(result.logits.shape	,  (self.batch_size, self.seq_length, self.num_labels)							)





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		self.prepare_config_and_inputs()
								((lowerCamelCase__)    ,     (lowerCamelCase__)    ,     (lowerCamelCase__)    ,     (lowerCamelCase__)    ,     (lowerCamelCase__)    ,     (lowerCamelCase__))        =		config_and_inputs
								lowerCamelCase__        =		{'''input_ids''': input_ids, '''attention_mask''': input_mask}
								return config, inputs_dict






@require_tf
class  __A   (   lowerCAmelCase      ,    lowerCAmelCase      ,    unittest.TestCase			):

							'''simple docstring'''







							lowerCAmelCase_												=						(
							    (
							        TFMPNetForMaskedLM,
							        TFMPNetForMultipleChoice,
							        TFMPNetForQuestionAnswering,
							        TFMPNetForSequenceClassification,
							        TFMPNetForTokenClassification,
							        TFMPNetModel,
							    )
							    if is_tf_available()
							    else ()
							)
							lowerCAmelCase_												=						(
							    {
							        """feature-extraction""": TFMPNetModel,
							        """fill-mask""": TFMPNetForMaskedLM,
							        """question-answering""": TFMPNetForQuestionAnswering,
							        """text-classification""": TFMPNetForSequenceClassification,
							        """token-classification""": TFMPNetForTokenClassification,
							        """zero-shot""": TFMPNetForSequenceClassification,
							    }
							    if is_tf_available()
							    else {}
							)
							lowerCAmelCase_												=						False
							lowerCAmelCase_												=						False





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		TFMPNetModelTester(self							)
								lowerCamelCase__        =		ConfigTester(self	,  config_class=__lowerCAmelCase	,  hidden_size=3_7							)





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								self.config_tester.run_common_tests()





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_mpnet_model(*__lowerCAmelCase							)





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_mpnet_for_masked_lm(*__lowerCAmelCase							)





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_mpnet_for_question_answering(*__lowerCAmelCase							)





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_mpnet_for_sequence_classification(*__lowerCAmelCase							)





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_mpnet_for_multiple_choice(*__lowerCAmelCase							)





							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		self.model_tester.prepare_config_and_inputs()
								self.model_tester.create_and_check_mpnet_for_token_classification(*__lowerCAmelCase							)





							@slow
							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								for model_name in ["microsoft/mpnet-base"]:
									lowerCamelCase__        =		TFMPNetModel.from_pretrained(__lowerCAmelCase							)
									self.assertIsNotNone(__lowerCAmelCase							)






@require_tf
class  __A   (   unittest.TestCase			):

							'''simple docstring'''







							@slow
							def 		__lowerCamelCase    (   self							):



								'''simple docstring'''







								lowerCamelCase__        =		TFMPNetModel.from_pretrained('''microsoft/mpnet-base'''							)
								lowerCamelCase__        =		tf.constant([[0, 1, 2, 3, 4, 5]]							)
								lowerCamelCase__        =		model(__lowerCAmelCase							)[0]

								lowerCamelCase__        =		[1, 6, 7_6_8]
								self.assertEqual(output.shape	,  __lowerCAmelCase							)

								lowerCamelCase__        =		tf.constant(
								    [
								        [
								            [-0.106_7172, 0.0821_6473, 0.002_4543],
								            [-0.0346_5879, 0.835_4118, -0.0325_2288],
								            [-0.0656_9476, -0.1242_4111, -0.049_4436],
								        ]
								    ]							)
								tf.debugging.assert_near(output[:, :3, :3]	,  __lowerCAmelCase	,  atol=1E-4							)










import os





def lowerCAmelCase__()    ->				int:







	'''simple docstring'''







	lowerCamelCase__        =		os.path.dirname(os.path.realpath(__snake_case							)							)
	lowerCamelCase__        =		os.path.join(__snake_case	,'''triangle.txt'''							)

	with open(__snake_case							) as in_file:
		lowerCamelCase__        =		[[int(__snake_case							) for i in line.split()] for line in in_file]

	while len(__snake_case							) != 1:
		lowerCamelCase__        =		triangle.pop()
		lowerCamelCase__        =		triangle[-1]
		for j in range(len(__snake_case							) - 1							):
			curr_row[j] += max(last_row[j]	,last_row[j + 1]							)
	return triangle[0][0]


if __name__ == "__main__":
			print(solution())



