






import pandas as pd
from matplotlib import pyplot as plt
from sklearn.linear_model import LinearRegression

# Splitting the dataset into the Training set and Test set
from sklearn.model_selection import train_test_split

# Fitting Polynomial Regression to the dataset
from sklearn.preprocessing import PolynomialFeatures

# Importing the dataset
UpperCAmelCase__				   =		pd.read_csv(
    "https://s3.us-west-2.amazonaws.com/public.gamelab.fun/dataset/"
    "position_salaries.csv"
)
UpperCAmelCase__				   =		dataset.iloc[:, 1:2].values
UpperCAmelCase__				   =		dataset.iloc[:, 2].values


UpperCAmelCase__   ,      UpperCAmelCase__   ,      UpperCAmelCase__   ,      UpperCAmelCase__				   =		train_test_split(X, y, test_size=0.2, random_state=0)


UpperCAmelCase__				   =		PolynomialFeatures(degree=4)
UpperCAmelCase__				   =		poly_reg.fit_transform(X)
UpperCAmelCase__				   =		LinearRegression()
pol_reg.fit(X_poly, y)
def 						_a    (      )							->			Optional[Any]:
 plt.scatter(a	,							a	,							color='''red''' )
 plt.plot(a	,							pol_reg.predict(poly_reg.fit_transform(a ) )	,							color='''blue''' )
 plt.title('''Truth or Bluff (Linear Regression)''' )
 plt.xlabel('''Position level''' )
 plt.ylabel('''Salary''' )
 plt.show()


if __name__ == "__main__":
     viz_polymonial()

     # Predicting a new result with Polymonial Regression
     pol_reg.predict(poly_reg.fit_transform([[5.5]]))
     # output should be 132148.43750003







import os
import unittest

from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer

from ...test_tokenization_common import TokenizerTesterMixin




class 					snake_case__						(       lowerCAmelCase_				,     unittest.TestCase     ):






     """simple docstring"""


     _SCREAMING_SNAKE_CASE						=	TransfoXLTokenizer
     _SCREAMING_SNAKE_CASE						=	False
     _SCREAMING_SNAKE_CASE						=	False






     def    lowercase_   (       self  :  Optional[int]					)   ->Any:
            super().setUp()

            snake_case__							:	Tuple   	=	[
                '<unk>',
                '[CLS]',
                '[SEP]',
                'want',
                'unwanted',
                'wa',
                'un',
                'running',
                ',',
                'low',
                'l',
            ]
            snake_case__							:	Any   	=	os.path.join(self.tmpdirname, VOCAB_FILES_NAMES['vocab_file']					)
            with open(self.vocab_file, 'w', encoding='utf-8'					) as vocab_writer:
                   vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]					)					)






     def    lowercase_   (       self  :  Union[str, Any], **_snake_case  :  List[Any]					)   ->Dict:
            snake_case__							:	str   	=	True
            return TransfoXLTokenizer.from_pretrained(self.tmpdirname, **_snake_case					)






     def    lowercase_   (       self  :  Optional[Any], _snake_case  :  str					)   ->Dict:
            snake_case__							:	List[Any]   	=	'<unk> UNwanted , running'
            snake_case__							:	List[Any]   	=	'<unk> unwanted, running'
            return input_text, output_text






     def    lowercase_   (       self  :  List[Any]					)   ->Tuple:
            snake_case__							:	Dict   	=	TransfoXLTokenizer(vocab_file=self.vocab_file, lower_case=_snake_case					)

            snake_case__							:	str   	=	tokenizer.tokenize('<unk> UNwanted , running'					)
            self.assertListEqual(_snake_case, ['<unk>', 'unwanted', ',', 'running']					)

            self.assertListEqual(tokenizer.convert_tokens_to_ids(_snake_case					), [0, 4, 8, 7]					)






     def    lowercase_   (       self  :  List[str]					)   ->List[Any]:
            snake_case__							:	str   	=	TransfoXLTokenizer(lower_case=_snake_case					)

            self.assertListEqual(
                tokenizer.tokenize(' \tHeLLo ! how  \n Are yoU ?  '					), ['hello', '!', 'how', 'are', 'you', '?']					)






     def    lowercase_   (       self  :  Optional[int]					)   ->Optional[Any]:
            snake_case__							:	Optional[int]   	=	TransfoXLTokenizer(lower_case=_snake_case					)

            self.assertListEqual(
                tokenizer.tokenize(' \tHeLLo ! how  \n Are yoU ?  '					), ['HeLLo', '!', 'how', 'Are', 'yoU', '?']					)






     def    lowercase_   (       self  :  Optional[int]					)   ->Union[str, Any]:
            snake_case__							:	List[Any]   	=	TransfoXLTokenizer(lower_case=_snake_case					)
            snake_case__							:	Dict   	=	'Hello (bracket) and side-scrolled [and] Henry\'s $5,000 with 3.34 m. What\'s up!?'
            snake_case__							:	List[Any]   	=	[
                'Hello',
                '(',
                'bracket',
                ')',
                'and',
                'side',
                '@-@',
                'scrolled',
                '[',
                'and',
                ']',
                'Henry',
                '\'s',
                '$',
                '5',
                '@,@',
                '000',
                'with',
                '3',
                '@.@',
                '34',
                'm',
                '.',
                'What',
                '\'s',
                'up',
                '!',
                '?',
            ]

            self.assertListEqual(tokenizer.tokenize(_snake_case					), _snake_case					)

            self.assertEqual(tokenizer.convert_tokens_to_string(_snake_case					), _snake_case					)






     def    lowercase_   (       self  :  Dict					)   ->Any:
            snake_case__							:	Dict   	=	self.get_tokenizer()
            snake_case__							:	Optional[Any]   	=	len(_snake_case					)

            tokenizer.add_tokens(['new1', 'new2']					)
            tokenizer.move_added_token('new1', 1					)

            # Check that moved token is not copied (duplicate)
            self.assertEqual(len(_snake_case					), original_len + 2					)
            # Check that token is moved to specified id
            self.assertEqual(tokenizer.encode('new1'					), [1]					)
            self.assertEqual(tokenizer.decode([1]					), 'new1'					)






