





from __future__ import annotations

from typing import Any

class 		SCREAMING_SNAKE_CASE__				:


      def __init__(self       :      int				,			a__       :      int				,			a__       :      int				,			a__       :      float = 0      ):





         """simple docstring"""



         __snake_case       ,	__snake_case							       =   row, column
         __snake_case							       =   [[default_value for c in range(a__      )] for r in range(a__      )]


      def __str__(self       :      Any      ):





         """simple docstring"""



         __snake_case							       =   f"""Matrix consist of {self.row} rows and {self.column} columns\n"""

         # Make string identifier
         __snake_case							       =   0
         for row_vector in self.array:
            for obj in row_vector:
               __snake_case							       =   max(a__				,			len(str(a__      )      )      )
         __snake_case							       =   f"""%{max_element_length}s"""

         # Make string and return
         def single_line(a__       :      list[float]      ) -> str:
            nonlocal string_format_identifier
            __snake_case							       =   '''['''
            line += ", ".join(string_format_identifier % (obj,) for obj in row_vector      )
            line += "]"
            return line

         s += "\n".join(single_line(a__      ) for row_vector in self.array      )
         return s


      def __repr__(self       :      List[Any]      ):





         """simple docstring"""



         return str(self      )


      def    a (self       :      Union[str, Any]				,			a__       :      tuple[int, int]      ):





         """simple docstring"""



         if not (isinstance(a__				,			(list, tuple)      ) and len(a__      ) == 2):
            return False
         elif not (0 <= loc[0] < self.row and 0 <= loc[1] < self.column):
            return False
         else:
            return True


      def __getitem__(self       :      Tuple				,			a__       :      tuple[int, int]      ):





         """simple docstring"""



         assert self.validate_indicies(a__      )
         return self.array[loc[0]][loc[1]]


      def __setitem__(self       :      Optional[int]				,			a__       :      tuple[int, int]				,			a__       :      float      ):





         """simple docstring"""



         assert self.validate_indicies(a__      )
         __snake_case							       =   value


      def __add__(self       :      Optional[Any]				,			a__       :      Matrix      ):





         """simple docstring"""



         assert isinstance(a__				,			a__      )
         assert self.row == another.row and self.column == another.column

         # Add
         __snake_case							       =   Matrix(self.row				,			self.column      )
         for r in range(self.row      ):
            for c in range(self.column      ):
               __snake_case							       =   self[r, c] + another[r, c]
         return result


      def __neg__(self       :      str      ):





         """simple docstring"""



         __snake_case							       =   Matrix(self.row				,			self.column      )
         for r in range(self.row      ):
            for c in range(self.column      ):
               __snake_case							       =   -self[r, c]
         return result


      def __sub__(self       :      Union[str, Any]				,			a__       :      Matrix      ):





         """simple docstring"""



         return self + (-another)


      def __mul__(self       :      List[str]				,			a__       :      int | float | Matrix      ):





         """simple docstring"""



         if isinstance(a__				,			(int, float)      ):  # Scalar multiplication
            __snake_case							       =   Matrix(self.row				,			self.column      )
            for r in range(self.row      ):
               for c in range(self.column      ):
                  __snake_case							       =   self[r, c] * another
            return result
         elif isinstance(a__				,			a__      ):  # Matrix multiplication
            assert self.column == another.row
            __snake_case							       =   Matrix(self.row				,			another.column      )
            for r in range(self.row      ):
               for c in range(another.column      ):
                  for i in range(self.column      ):
                     result[r, c] += self[r, i] * another[i, c]
            return result
         else:
            __snake_case							       =   f"""Unsupported type given for another ({type(a__      )})"""
            raise TypeError(a__      )


      def    a (self       :      List[Any]      ):





         """simple docstring"""



         __snake_case							       =   Matrix(self.column				,			self.row      )
         for r in range(self.row      ):
            for c in range(self.column      ):
               __snake_case							       =   self[r, c]
         return result


      def    a (self       :      List[str]				,			a__       :      Matrix				,			a__       :      Matrix      ):





         """simple docstring"""



         assert isinstance(a__				,			a__      ) and isinstance(a__				,			a__      )
         assert self.row == self.column == u.row == v.row  # u, v should be column vector
         assert u.column == v.column == 1  # u, v should be column vector

         # Calculate
         __snake_case							       =   v.transpose()
         __snake_case							       =   (v_t * self * u)[0, 0] + 1
         if numerator_factor == 0:
            return None  # It's not invertable
         return self - ((self * u) * (v_t * self) * (1.0 / numerator_factor))


# Testing
if __name__ == "__main__":






    def lowerCamelCase__    (							)      ->				None:
       # a^(-1)
       __snake_case							       =   Matrix(3       ,      3       ,      0       )
       for i in range(3       ):
          __snake_case							       =   1
       print(f"""a^(-1) is {ainv}"""       )
       # u, v
       __snake_case							       =   Matrix(3       ,      1       ,      0       )
       __snake_case       ,	__snake_case       ,	__snake_case							       =   1, 2, -3
       __snake_case							       =   Matrix(3       ,      1       ,      0       )
       __snake_case       ,	__snake_case       ,	__snake_case							       =   4, -2, 5
       print(f"""u is {u}"""       )
       print(f"""v is {v}"""       )
       print(f"""uv^T is {u * v.transpose()}"""       )
       # Sherman Morrison
       print(f"""(a + uv^T)^(-1) is {ainv.sherman_morrison(snake_case_       ,      snake_case_       )}"""       )






    def lowerCamelCase__    (							)      ->				None:
       import doctest

       doctest.testmod()







    testa()








"""simple docstring"""





from __future__ import annotations

import unittest

from transformers import DistilBertConfig, 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.distilbert.modeling_tf_distilbert import (
           TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
           TFDistilBertForMaskedLM,
           TFDistilBertForMultipleChoice,
           TFDistilBertForQuestionAnswering,
           TFDistilBertForSequenceClassification,
           TFDistilBertForTokenClassification,
           TFDistilBertModel,
       )

class 		lowercase					:





      def __init__(       self      ,						lowercase      ,						)		->     Optional[int]:
            lowerCAmelCase  						=       parent
            lowerCAmelCase  						=       13
            lowerCAmelCase  						=       7
            lowerCAmelCase  						=       True
            lowerCAmelCase  						=       True
            lowerCAmelCase  						=       False
            lowerCAmelCase  						=       True
            lowerCAmelCase  						=       99
            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





      def     _snake_case			(       self )		->     str:
            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  						=       DistilBertConfig(
                vocab_size=self.vocab_size      ,						dim=self.hidden_size      ,						n_layers=self.num_hidden_layers      ,						n_heads=self.num_attention_heads      ,						hidden_dim=self.intermediate_size      ,						hidden_act=self.hidden_act      ,						dropout=self.hidden_dropout_prob      ,						attention_dropout=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     _snake_case			(       self      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase )		->     List[Any]:
            lowerCAmelCase  						=       TFDistilBertModel(config=lowercase )
            lowerCAmelCase  						=       {"""input_ids""": input_ids, """attention_mask""": input_mask}

            lowerCAmelCase  						=       model(lowercase )

            lowerCAmelCase  						=       [input_ids, input_mask]

            lowerCAmelCase  						=       model(lowercase )

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





      def     _snake_case			(       self      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase )		->     Optional[int]:
            lowerCAmelCase  						=       TFDistilBertForMaskedLM(config=lowercase )
            lowerCAmelCase  						=       {"""input_ids""": input_ids, """attention_mask""": input_mask}
            lowerCAmelCase  						=       model(lowercase )
            self.parent.assertEqual(result.logits.shape      ,						(self.batch_size, self.seq_length, self.vocab_size) )





      def     _snake_case			(       self      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase )		->     List[Any]:
            lowerCAmelCase  						=       TFDistilBertForQuestionAnswering(config=lowercase )
            lowerCAmelCase  						=       {
                """input_ids""": input_ids,
                """attention_mask""": input_mask,
            }
            lowerCAmelCase  						=       model(lowercase )
            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     _snake_case			(       self      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase )		->     List[Any]:
            lowerCAmelCase  						=       self.num_labels
            lowerCAmelCase  						=       TFDistilBertForSequenceClassification(lowercase )
            lowerCAmelCase  						=       {"""input_ids""": input_ids, """attention_mask""": input_mask}
            lowerCAmelCase  						=       model(lowercase )
            self.parent.assertEqual(result.logits.shape      ,						(self.batch_size, self.num_labels) )





      def     _snake_case			(       self      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase )		->     Any:
            lowerCAmelCase  						=       self.num_choices
            lowerCAmelCase  						=       TFDistilBertForMultipleChoice(lowercase )
            lowerCAmelCase  						=       tf.tile(tf.expand_dims(lowercase      ,						1 )      ,						(1, self.num_choices, 1) )
            lowerCAmelCase  						=       tf.tile(tf.expand_dims(lowercase      ,						1 )      ,						(1, self.num_choices, 1) )
            lowerCAmelCase  						=       {
                """input_ids""": multiple_choice_inputs_ids,
                """attention_mask""": multiple_choice_input_mask,
            }
            lowerCAmelCase  						=       model(lowercase )
            self.parent.assertEqual(result.logits.shape      ,						(self.batch_size, self.num_choices) )





      def     _snake_case			(       self      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase      ,						lowercase )		->     int:
            lowerCAmelCase  						=       self.num_labels
            lowerCAmelCase  						=       TFDistilBertForTokenClassification(lowercase )
            lowerCAmelCase  						=       {"""input_ids""": input_ids, """attention_mask""": input_mask}
            lowerCAmelCase  						=       model(lowercase )
            self.parent.assertEqual(result.logits.shape      ,						(self.batch_size, self.seq_length, self.num_labels) )





      def     _snake_case			(       self )		->     Optional[Any]:
            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 		lowercase					(					_UpperCAmelCase     ,  _UpperCAmelCase     ,  unittest.TestCase					):
      _SCREAMING_SNAKE_CASE					=      (
          (
              TFDistilBertModel,
              TFDistilBertForMaskedLM,
              TFDistilBertForQuestionAnswering,
              TFDistilBertForSequenceClassification,
              TFDistilBertForTokenClassification,
              TFDistilBertForMultipleChoice,
          )
          if is_tf_available()
          else None
      )
      _SCREAMING_SNAKE_CASE					=      (
          {
              'feature-extraction': TFDistilBertModel,
              'fill-mask': TFDistilBertForMaskedLM,
              'question-answering': TFDistilBertForQuestionAnswering,
              'text-classification': TFDistilBertForSequenceClassification,
              'token-classification': TFDistilBertForTokenClassification,
              'zero-shot': TFDistilBertForSequenceClassification,
          }
          if is_tf_available()
          else {}
      )
      _SCREAMING_SNAKE_CASE					=      False
      _SCREAMING_SNAKE_CASE					=      False





      def     _snake_case			(       self )		->     Dict:
            lowerCAmelCase  						=       TFDistilBertModelTester(self )
            lowerCAmelCase  						=       ConfigTester(self      ,						config_class=lowercase      ,						dim=37 )





      def     _snake_case			(       self )		->     str:
            self.config_tester.run_common_tests()





      def     _snake_case			(       self )		->     int:
            lowerCAmelCase  						=       self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_distilbert_model(*lowercase )





      def     _snake_case			(       self )		->     Any:
            lowerCAmelCase  						=       self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_distilbert_for_masked_lm(*lowercase )





      def     _snake_case			(       self )		->     Optional[Any]:
            lowerCAmelCase  						=       self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_distilbert_for_question_answering(*lowercase )





      def     _snake_case			(       self )		->     Union[str, Any]:
            lowerCAmelCase  						=       self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_distilbert_for_sequence_classification(*lowercase )





      def     _snake_case			(       self )		->     List[Any]:
            lowerCAmelCase  						=       self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_distilbert_for_multiple_choice(*lowercase )





      def     _snake_case			(       self )		->     str:
            lowerCAmelCase  						=       self.model_tester.prepare_config_and_inputs()
            self.model_tester.create_and_check_distilbert_for_token_classification(*lowercase )





      @slow
      def     _snake_case			(       self )		->     List[str]:
            for model_name in list(TF_DISTILBERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1] ):
                  lowerCAmelCase  						=       TFDistilBertModel.from_pretrained(lowercase )
                  self.assertIsNotNone(lowercase )







@require_tf
class 		lowercase					(					unittest.TestCase					):





      @slow
      def     _snake_case			(       self )		->     Any:
            lowerCAmelCase  						=       TFDistilBertModel.from_pretrained("""distilbert-base-uncased""" )
            lowerCAmelCase  						=       tf.constant([[0, 1, 2, 3, 4, 5]] )
            lowerCAmelCase  						=       model(lowercase )[0]

            lowerCAmelCase  						=       [1, 6, 768]
            self.assertEqual(output.shape      ,						lowercase )

            lowerCAmelCase  						=       tf.constant(
                [
                    [
                        [0.19_261_885, -0.13_732_955, 0.4_119_799],
                        [0.22_150_156, -0.07_422_661, 0.39_037_204],
                        [0.22_756_018, -0.0_896_414, 0.3_701_467],
                    ]
                ] )
            tf.debugging.assert_near(output[:, :3, :3]      ,						lowercase      ,						atol=1e-4 )






