

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 SCREAMING_SNAKE_CASE  (		__snake_case							,						unittest.TestCase							):






			"""simple docstring"""




			__A						  =  OpenAIGPTTokenizer
			__A						  =  OpenAIGPTTokenizerFast
			__A						  =  True
			__A						  =  False


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				super().setUp()

				# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
				snake_case_      		= [
				    '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>',
				]
				snake_case_      		= dict(zip(__UpperCamelCase ,				range(len(__UpperCamelCase							)							)							)							)
				snake_case_      		= ['#version: 0.2', 'l o', 'lo w', 'e r</w>', '']

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


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase							):

				"""simple docstring"""


				return "lower newer", "lower newer"


			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


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

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

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


			def 			__lowerCAmelCase (    self ,				__UpperCamelCase=15							):

				"""simple docstring"""


				for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
					with self.subTest(f"""{tokenizer.__class__.__name__} ({pretrained_name})"""							):
						snake_case_      		= self.rust_tokenizer_class.from_pretrained(__UpperCamelCase ,				**__UpperCamelCase							)

						# Simple input
						snake_case_      		= 'This is a simple input'
						snake_case_      		= ['This is a simple input 1', 'This is a simple input 2']
						snake_case_      		= ('This is a simple input', 'This is a pair')
						snake_case_      		= [
						    ('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(__UpperCamelCase ,				tokenizer_r.encode ,				__UpperCamelCase ,				max_length=__UpperCamelCase ,				padding='max_length'							)

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

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

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

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

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







			def 			__lowerCAmelCase (    self							):

				"""simple docstring"""


				pass







@require_ftfy
@require_spacy
@require_tokenizers
class SCREAMING_SNAKE_CASE  (		__snake_case							):






			"""simple docstring"""




			pass



from collections import defaultdict





def a(lowercase__			, lowercase__	):





	'''simple docstring'''
	snake_case_      		= first_str.lower().strip()
	snake_case_      		= second_str.lower().strip()

	# Remove whitespace
	snake_case_      		= first_str.replace(' '			, ''	)
	snake_case_      		= second_str.replace(' '			, ''	)

	# Strings of different lengths are not anagrams
	if len(lowercase__	) != len(lowercase__	):
		return False

	# Default values for count should be 0
	snake_case_      		= defaultdict(lowercase__	)

	# For each character in input strings,
	# increment count in the corresponding
	for i in range(len(lowercase__	)	):
		count[first_str[i]] += 1
		count[second_str[i]] -= 1

	return all(_count == 0 for _count in count.values()	)


if __name__ == "__main__":
		from doctest import testmod

		testmod()
		A											=     input('Enter the first string ').strip()
		A											=     input('Enter the second string ').strip()

		A											=     check_anagrams(input_a, input_b)
		print(f"""{input_a} and {input_b} are {"" if status else "not "}anagrams.""")
