

import numpy

# List of input, output pairs
lowercase_             =     (
    ((5, 2, 3), 1_5),
    ((6, 5, 9), 2_5),
    ((1_1, 1_2, 1_3), 4_1),
    ((1, 1, 1), 8),
    ((1_1, 1_2, 1_3), 4_1),
)
lowercase_             =     (((5_1_5, 2_2, 1_3), 5_5_5), ((6_1, 3_5, 4_9), 1_5_0))
lowercase_             =     [2, 4, 1, 5]
lowercase_             =     len(train_data)
lowercase_             =     0.0_0_9
def   a   (    A__			:     Optional[Any]   ,     A__			:     str="train"  )					->   Tuple:





      """simple docstring"""



      return calculate_hypothesis_value(snake_case__   ,     snake_case__  ) - output(
          snake_case__   ,     snake_case__  )
def   a   (    A__			:     Optional[int]  )					->   List[str]:





      """simple docstring"""



      _lowercase			 =0
      for i in range(len(snake_case__  ) - 1  ):
            hyp_val += data_input_tuple[i] * parameter_vector[i + 1]
      hyp_val += parameter_vector[0]
      return hyp_val
def   a   (    A__			:     Optional[int]   ,     A__			:     List[str]  )					->   Tuple:





      """simple docstring"""



      if data_set == "train":
            return train_data[example_no][1]
      elif data_set == "test":
            return test_data[example_no][1]
      return None
def   a   (    A__			:     Any   ,     A__			:     List[str]  )					->   Union[str, Any]:





      """simple docstring"""



      if data_set == "train":
            return _hypothesis_value(train_data[example_no][0]  )
      elif data_set == "test":
            return _hypothesis_value(test_data[example_no][0]  )
      return None
def   a   (    A__			:     Tuple   ,     A__			:     Any=m  )					->   List[str]:





      """simple docstring"""



      _lowercase			 =0
      for i in range(snake_case__  ):
            if index == -1:
                  summation_value += _error(snake_case__  )
            else:
                  summation_value += _error(snake_case__  ) * train_data[i][0][index]
      return summation_value
def   a   (    A__			:     Optional[int]  )					->   Optional[int]:





      """simple docstring"""



      _lowercase			 =summation_of_cost_derivative(snake_case__   ,     snake_case__  ) / m
      return cost_derivative_value
def   a   (    )					->   List[Any]:





      """simple docstring"""



      global parameter_vector
      # Tune these values to set a tolerance value for predicted output
      _lowercase			 =0.000002
      _lowercase			 =0
      _lowercase			 =0
      while True:
            j += 1
            _lowercase			 =[0, 0, 0, 0]
            for i in range(0   ,     len(snake_case__  )  ):
                  _lowercase			 =get_cost_derivative(i - 1  )
                  _lowercase			 =(
                      parameter_vector[i] - LEARNING_RATE * cost_derivative
                  )
            if numpy.allclose(
                snake_case__   ,     snake_case__   ,     atol=snake_case__   ,     rtol=snake_case__   ,     ):
                  break
            _lowercase			 =temp_parameter_vector
      print(('Number of iterations:', j)  )
def   a   (    )					->   Tuple:





      """simple docstring"""



      for i in range(len(snake_case__  )  ):
            print(('Actual output value:', output(snake_case__   ,     'test'  ))  )
            print(('Hypothesis output:', calculate_hypothesis_value(snake_case__   ,     'test'  ))  )


if __name__ == "__main__":
  run_gradient_descent()
  print('\nTesting gradient descent for a linear hypothesis function.\n')
  test_gradient_descent()





import json
import os
import unittest

from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 				__lowerCAmelCase  (      SCREAMING_SNAKE_CASE    ,    unittest.TestCase							):
  _a		    =						OpenAIGPTTokenizer
  _a		    =						OpenAIGPTTokenizerFast
  _a		    =						True
  _a		    =						False




  def 						A__  (       self      )						->				Tuple:
        '''simple docstring'''






        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        _lowercase			 =[
            'l',
            'o',
            'w',
            'e',
            'r',
            's',
            't',
            'i',
            'd',
            'n',
            'w</w>',
            'r</w>',
            't</w>',
            'lo',
            'low',
            'er</w>',
            'low</w>',
            'lowest</w>',
            'newer</w>',
            'wider</w>',
            '<unk>',
        ]
        _lowercase			 =dict(zip(lowerCAmelCase							,     range(len(lowerCAmelCase      )      )      )      )
        _lowercase			 =['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

        _lowercase			 =os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES['vocab_file']      )
        _lowercase			 =os.path.join(self.tmpdirname							,     VOCAB_FILES_NAMES['merges_file']      )
        with open(self.vocab_file							,     'w'      ) as fp:
              fp.write(json.dumps(lowerCAmelCase      )      )
        with open(self.merges_file							,     'w'      ) as fp:
              fp.write('\n'.join(lowerCAmelCase      )      )




  def 						A__  (       self							,     lowerCAmelCase      )						->				str:
        '''simple docstring'''






        return "lower newer", "lower newer"




  def 						A__  (       self      )						->				Tuple:
        '''simple docstring'''






        _lowercase			 =OpenAIGPTTokenizer(self.vocab_file							,     self.merges_file      )

        _lowercase			 ='lower'
        _lowercase			 =['low', 'er</w>']
        _lowercase			 =tokenizer.tokenize(lowerCAmelCase      )
        self.assertListEqual(lowerCAmelCase							,     lowerCAmelCase      )

        _lowercase			 =tokens + ['<unk>']
        _lowercase			 =[14, 15, 20]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase      )							,     lowerCAmelCase      )




  def 						A__  (       self							,     lowerCAmelCase=15      )						->				Union[str, Any]:
        '''simple docstring'''






        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''      ):
                    _lowercase			 =self.rust_tokenizer_class.from_pretrained(lowerCAmelCase							,     **lowerCAmelCase      )

                    # Simple input
                    _lowercase			 ='This is a simple input'
                    _lowercase			 =['This is a simple input 1', 'This is a simple input 2']
                    _lowercase			 =('This is a simple input', 'This is a pair')
                    _lowercase			 =[
                        ('This is a simple input 1', 'This is a simple input 2'),
                        ('This is a simple pair 1', 'This is a simple pair 2'),
                    ]

                    # Simple input tests
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Simple input
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Simple input
                    self.assertRaises(
                        lowerCAmelCase							,     tokenizer_r.batch_encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'							,     )

                    # Pair input
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Pair input
                    self.assertRaises(lowerCAmelCase							,     tokenizer_r.encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'      )

                    # Pair input
                    self.assertRaises(
                        lowerCAmelCase							,     tokenizer_r.batch_encode_plus							,     lowerCAmelCase							,     max_length=lowerCAmelCase							,     padding='max_length'							,     )




  def 						A__  (       self      )						->				Dict:
        '''simple docstring'''






        pass





@require_ftfy
@require_spacy
@require_tokenizers
class 				__lowerCAmelCase  (      SCREAMING_SNAKE_CASE							):
  pass


