




import unittest

from transformers import ErnieMTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


UpperCamelCase__       				=	get_tests_dir('''fixtures/spiece.model''')
@require_sentencepiece
@require_tokenizers
class 							__lowercase   (			a__	,		unittest.TestCase    ):
     _lowerCAmelCase		       =						ErnieMTokenizer
     _lowerCAmelCase		       =						False
     _lowerCAmelCase		       =						True
     _lowerCAmelCase		       =						False
     _lowerCAmelCase		       =						False



     def 				__magic_name__		(  self   :							Any       ):
       super().setUp()

       # We have a SentencePiece fixture for testing
       a_		    =  ErnieMTokenizer(lowercase__      ,		unk_token='''<unk>'''      ,		pad_token='''<pad>'''       )
       tokenizer.save_pretrained(self.tmpdirname       )



     def 				__magic_name__		(  self   :							Union[str, Any]      ,		lowercase__   :							List[Any]       ):
       a_		    =  '''this is a test'''
       a_		    =  '''this is a test'''
       return input_text, output_text



     def 				__magic_name__		(  self   :							Union[str, Any]       ):
       a_		    =  '''<pad>'''
       a_		    =  0

       self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowercase__       )      ,		lowercase__       )
       self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowercase__       )      ,		lowercase__       )



     def 				__magic_name__		(  self   :							Optional[int]       ):
       a_		    =  list(self.get_tokenizer().get_vocab().keys()       )

       self.assertEqual(vocab_keys[0]      ,		'''<pad>'''       )
       self.assertEqual(vocab_keys[1]      ,		'''<unk>'''       )
       self.assertEqual(vocab_keys[-1]      ,		'''▁eloquent'''       )
       self.assertEqual(len(lowercase__       )      ,		3_0_0_0_0       )



     def 				__magic_name__		(  self   :							List[Any]       ):
       self.assertEqual(self.get_tokenizer().vocab_size      ,		3_0_0_0_0       )



     def 				__magic_name__		(  self   :							List[Any]       ):
       if not self.test_rust_tokenizer:
         return

       a_		    =  self.get_tokenizer()
       a_		    =  self.get_rust_tokenizer()

       a_		    =  '''I was born in 92000, and this is falsé.'''

       a_		    =  tokenizer.tokenize(lowercase__       )
       a_		    =  rust_tokenizer.tokenize(lowercase__       )
       self.assertListEqual(lowercase__      ,		lowercase__       )

       a_		    =  tokenizer.encode(lowercase__      ,		add_special_tokens=lowercase__       )
       a_		    =  rust_tokenizer.encode(lowercase__      ,		add_special_tokens=lowercase__       )
       self.assertListEqual(lowercase__      ,		lowercase__       )

       a_		    =  self.get_rust_tokenizer()
       a_		    =  tokenizer.encode(lowercase__       )
       a_		    =  rust_tokenizer.encode(lowercase__       )
       self.assertListEqual(lowercase__      ,		lowercase__       )



     def 				__magic_name__		(  self   :							List[str]       ):
       a_		    =  ErnieMTokenizer(lowercase__      ,		do_lower_case=lowercase__      ,		unk_token='''<unk>'''      ,		pad_token='''<pad>'''       )

       a_		    =  tokenizer.tokenize('''This is a test'''       )
       self.assertListEqual(lowercase__      ,		['''▁this''', '''▁is''', '''▁a''', '''▁test''']       )

       self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__       )      ,		[4_8, 2_5, 2_1, 1_2_8_9]       )

       a_		    =  tokenizer.tokenize('''I was born in 92000, and this is falsé.'''       )
       # ErnieMTokenizer(paddlenlp implementation) outputs '9' instead of '_9' so to mimic that '_9' is changed to '9'
       self.assertListEqual(
           lowercase__      ,		['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''é''', '''.''']       )
       a_		    =  tokenizer.convert_tokens_to_ids(lowercase__       )
       self.assertListEqual(lowercase__      ,		[3_1, 2_3, 3_8_6, 1_9, 5_1_8, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]       )

       a_		    =  tokenizer.convert_ids_to_tokens(lowercase__       )
       self.assertListEqual(
           lowercase__      ,		['''▁i''', '''▁was''', '''▁born''', '''▁in''', '''9''', '''2000''', ''',''', '''▁and''', '''▁this''', '''▁is''', '''▁fal''', '''s''', '''<unk>''', '''.''']      ,		)



     def 				__magic_name__		(  self   :							Dict       ):
       a_		    =  ErnieMTokenizer(lowercase__      ,		unk_token='''<unk>'''      ,		pad_token='''<pad>'''       )

       a_		    =  tokenizer.encode('''sequence builders'''       )
       a_		    =  tokenizer.encode('''multi-sequence build'''       )

       a_		    =  tokenizer.build_inputs_with_special_tokens(lowercase__       )
       a_		    =  tokenizer.build_inputs_with_special_tokens(lowercase__      ,		lowercase__       )

       assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
       assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + [
           tokenizer.sep_token_id
       ] + text_a + [tokenizer.sep_token_id]



     @slow
     def 				__magic_name__		(  self   :							Optional[int]       ):
       # fmt: off
       a_		    =  {'''input_ids''': [[0, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 9, 3_0_4, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 5, 5, 5, 1_6, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 6_4_6_0, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 3_5_5_9, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [0, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 7, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [0, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 5, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}
       # fmt: on

       self.tokenizer_integration_test_util(
           expected_encoding=lowercase__      ,		model_name='''susnato/ernie-m-base_pytorch'''      ,		sequences=[
               '''Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '''
               '''general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural '''
               '''Language Understanding (NLU) and Natural Language Generation (NLG) with over32+ pretrained '''
               '''models in100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.''',
               '''BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '''
               '''conditioning on both left and right context in all layers.''',
               '''The quick brown fox jumps over the lazy dog.''',
           ]      ,		)






from __future__ import annotations

import sys
class 							__lowercase   :



     def __init__(  self   :							Any      ,		lowercase__   :							str      ,		lowercase__   :							int       ):
       a_		    =  letter
       a_		    =  freq
       a_		    =  {}



     def __repr__(  self   :							List[Any]       ):
       return f"{self.letter}:{self.freq}"



class 							__lowercase   :



     def __init__(  self   :							Optional[int]      ,		lowercase__   :							int      ,		lowercase__   :							Letter | TreeNode      ,		lowercase__   :							Letter | TreeNode       ):
       a_		    =  freq
       a_		    =  left
       a_		    =  right






def 				UpperCAmelCase__  (							_A			):






  """simple docstring"""


  a_		    =  {}
  with open(_A			) as f:
    while True:
      a_		    =  f.read(1			)
      if not c:
        break
      a_		    =  chars[c] + 1 if c in chars else 1
  return sorted((Letter(_A      ,      _A			) for c, f in chars.items())      ,      key=lambda _A			: x.freq			)






def 				UpperCAmelCase__  (							_A			):






  """simple docstring"""


  a_		    =  letters  # type: ignore
  while len(_A			) > 1:
    a_		    =  response.pop(0			)
    a_		    =  response.pop(0			)
    a_		    =  left.freq + right.freq
    a_		    =  TreeNode(_A      ,      _A      ,      _A			)
    response.append(_A			)
    response.sort(key=lambda _A			: x.freq			)
  return response[0]






def 				UpperCAmelCase__  (							_A      ,      _A			):






  """simple docstring"""


  if isinstance(_A      ,      _A			):
    a_		    =  bitstring
    return [root]
  a_		    =  root  # type: ignore
  a_		    =  []
  letters += traverse_tree(treenode.left      ,      bitstring + '''0'''			)
  letters += traverse_tree(treenode.right      ,      bitstring + '''1'''			)
  return letters






def 				UpperCAmelCase__  (							_A			):






  """simple docstring"""


  a_		    =  parse_file(_A			)
  a_		    =  build_tree(_A			)
  a_		    =  {
      k: v for letter in traverse_tree(_A      ,      ''''''			) for k, v in letter.bitstring.items()
  }
  print(f"Huffman Coding  of {file_path}: "			)
  with open(_A			) as f:
    while True:
      a_		    =  f.read(1			)
      if not c:
        break
      print(letters[c]      ,      end=''' '''			)
  print()


if __name__ == "__main__":
  # pass the file path to the huffman function
  huffman(sys.argv[1])
