






from collections import Counter
from functools import total_ordering

from data_structures.heap.heap import Heap





@total_ordering
class __lowerCamelCase			:





	"""simple docstring"""






	def __init__(							self	,   UpperCAmelCase	,   UpperCAmelCase   ):
							"""simple docstring"""







							_UpperCAmelCase     =      word
							_UpperCAmelCase     =      count

	def __eq__(							self	,   UpperCAmelCase   ):
							"""simple docstring"""







							if not isinstance(UpperCAmelCase	,   UpperCAmelCase   ):
													return NotImplemented
							return self.count == other.count

	def __lt__(							self	,   UpperCAmelCase   ):
							"""simple docstring"""







							if not isinstance(UpperCAmelCase	,   UpperCAmelCase   ):
													return NotImplemented
							return self.count < other.count



def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  list[str]:





						"""simple docstring"""



						_UpperCAmelCase     =      Heap()
						_UpperCAmelCase     =      Counter(__lowerCAmelCase     )
						heap.build_max_heap(
						    [WordCount(__lowerCAmelCase			,		__lowerCAmelCase     ) for word, count in count_by_word.items()]     )
						return [heap.extract_max().word for _ in range(min(__lowerCAmelCase			,		len(__lowerCAmelCase     )     )     )]


if __name__ == "__main__":
		import doctest

		doctest.testmod()








import unittest
import warnings
from dataclasses import dataclass

from transformers.convert_slow_tokenizer import SpmConverter
from transformers.testing_utils import get_tests_dir





@dataclass
class __lowerCamelCase			:





	"""simple docstring"""






	UpperCamelCase__								=				42





class __lowerCamelCase			(				unittest.TestCase):





	"""simple docstring"""






	def 	UpperCamelCase   (							self   ):
							"""simple docstring"""







							_UpperCAmelCase     =      get_tests_dir('fixtures/test_sentencepiece.model'   )
							_UpperCAmelCase     =      get_tests_dir('fixtures/test_sentencepiece_with_bytefallback.model'   )

							_UpperCAmelCase     =      FakeOriginalTokenizer(vocab_file=UpperCAmelCase   )

							with warnings.catch_warnings(record=UpperCAmelCase   ) as w:
													_UpperCAmelCase     =      SpmConverter(UpperCAmelCase   )
							self.assertEqual(len(UpperCAmelCase   )	,   0   )

							_UpperCAmelCase     =      FakeOriginalTokenizer(vocab_file=UpperCAmelCase   )

							with warnings.catch_warnings(record=UpperCAmelCase   ) as w:
													_UpperCAmelCase     =      SpmConverter(UpperCAmelCase   )
							self.assertEqual(len(UpperCAmelCase   )	,   1   )

							self.assertIn(
							    'The sentencepiece tokenizer that you are converting to a fast tokenizer uses the byte fallback option'
							    ' which is not implemented in the fast tokenizers.'	,   str(w[0].message   )	,   )
