

import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple, Union

import numpy as np
import regex as re

from ...utils import is_tf_available, is_torch_available, logging


if TYPE_CHECKING:
    if is_torch_available():
        import torch
    if is_tf_available():
        import tensorflow as tf

from ...tokenization_utils import AddedToken, PreTrainedTokenizer


lowerCamelCase_    =					logging.get_logger(__name__)

lowerCamelCase_    =					{
    '''vocab_file''': '''vocab.json''',
    '''merges_file''': '''merges.txt''',
}

lowerCamelCase_    =					{
    '''vocab_file''': {
        '''Salesforce/codegen-350M-mono''': '''https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/vocab.json''',
    },
    '''merges_file''': {
        '''Salesforce/codegen-350M-mono''': '''https://huggingface.co/Salesforce/codegen-350M-mono/resolve/main/merges.txt''',
    },
}

lowerCamelCase_    =					{
    '''Salesforce/codegen-350M-mono''': 2048,
}



@lru_cache()
def    UpperCamelCase(					)	->				str:





  '''simple docstring'''





  snake_case_       						=      (
      list(range(ord("""!"""							)			,					ord("""~"""							) + 1							)							) + list(range(ord("""¡"""							)			,					ord("""¬"""							) + 1							)							) + list(range(ord("""®"""							)			,					ord("""ÿ"""							) + 1							)							)
  )
  snake_case_       						=      bs[:]
  snake_case_       						=      0
  for b in range(2**8							):
    if b not in bs:
      bs.append(lowercase_							)
      cs.append(2**8 + n							)
      n += 1
  snake_case_       						=      [chr(lowercase_							) for n in cs]
  return dict(zip(lowercase_			,					lowercase_							)							)



def    UpperCamelCase(					lowercase_							)	->				Dict:





  '''simple docstring'''





  snake_case_       						=      set()
  snake_case_       						=      word[0]
  for char in word[1:]:
    pairs.add((prev_char, char)							)
    snake_case_       						=      char
  return pairs







class  __lowerCamelCase				(	__snake_case	):
      lowerCamelCase_	:      Any          =					VOCAB_FILES_NAMES
      lowerCamelCase_	:      Optional[Any]          =					PRETRAINED_VOCAB_FILES_MAP
      lowerCamelCase_	:      str          =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      lowerCamelCase_	:      List[str]          =					['input_ids', 'attention_mask']







      def __init__(     self							,  lowerCamelCase							,  lowerCamelCase							,  lowerCamelCase="replace"							,  lowerCamelCase="<|endoftext|>"							,  lowerCamelCase="<|endoftext|>"							,  lowerCamelCase="<|endoftext|>"							,  lowerCamelCase=None							,  lowerCamelCase=False							,  lowerCamelCase=False							,  **lowerCamelCase							,  )						->       str:
        snake_case_       						=      AddedToken(lowerCamelCase							,  lstrip=lowerCamelCase							,  rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase							,  lowerCamelCase   ) else bos_token
        snake_case_       						=      AddedToken(lowerCamelCase							,  lstrip=lowerCamelCase							,  rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase							,  lowerCamelCase   ) else eos_token
        snake_case_       						=      AddedToken(lowerCamelCase							,  lstrip=lowerCamelCase							,  rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase							,  lowerCamelCase   ) else unk_token
        snake_case_       						=      AddedToken(lowerCamelCase							,  lstrip=lowerCamelCase							,  rstrip=lowerCamelCase   ) if isinstance(lowerCamelCase							,  lowerCamelCase   ) else pad_token
        super().__init__(
            errors=lowerCamelCase							,  unk_token=lowerCamelCase							,  bos_token=lowerCamelCase							,  eos_token=lowerCamelCase							,  pad_token=lowerCamelCase							,  add_prefix_space=lowerCamelCase							,  add_bos_token=lowerCamelCase							,  **lowerCamelCase							,  )
        snake_case_       						=      add_bos_token

        with open(lowerCamelCase							,  encoding="""utf-8"""   ) as vocab_handle:
          snake_case_       						=      json.load(lowerCamelCase   )
        snake_case_       						=      {v: k for k, v in self.encoder.items()}
        snake_case_       						=      errors  # how to handle errors in decoding
        snake_case_       						=      bytes_to_unicode()
        snake_case_       						=      {v: k for k, v in self.byte_encoder.items()}
        with open(lowerCamelCase							,  encoding="""utf-8"""   ) as merges_handle:
          snake_case_       						=      merges_handle.read().split("""\n"""   )[1:-1]
        snake_case_       						=      [tuple(merge.split()   ) for merge in bpe_merges]
        snake_case_       						=      dict(zip(lowerCamelCase							,  range(len(lowerCamelCase   )   )   )   )
        snake_case_       						=      {}
        snake_case_       						=      add_prefix_space

        # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
        snake_case_       						=      re.compile(r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""   )







      @property
      def 	lowerCAmelCase_    (     self   )						->       Tuple:
        return len(self.encoder   )







      def 	lowerCAmelCase_    (     self   )						->       List[Any]:
        return dict(self.encoder							,  **self.added_tokens_encoder   )







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase   )						->       str:
        if token in self.cache:
          return self.cache[token]
        snake_case_       						=      tuple(lowerCamelCase   )
        snake_case_       						=      get_pairs(lowerCamelCase   )

        if not pairs:
          return token

        while True:
          snake_case_       						=      min(lowerCamelCase							,  key=lambda lowerCamelCase   : self.bpe_ranks.get(lowerCamelCase							,  float("""inf"""   )   )   )
          if bigram not in self.bpe_ranks:
            break
          snake_case_						,				snake_case_       						=      bigram
          snake_case_       						=      []
          snake_case_       						=      0
          while i < len(lowerCamelCase   ):
            try:
              snake_case_       						=      word.index(lowerCamelCase							,  lowerCamelCase   )
            except ValueError:
              new_word.extend(word[i:]   )
              break
            else:
              new_word.extend(word[i:j]   )
              snake_case_       						=      j

            if word[i] == first and i < len(lowerCamelCase   ) - 1 and word[i + 1] == second:
              new_word.append(first + second   )
              i += 2
            else:
              new_word.append(word[i]   )
              i += 1
          snake_case_       						=      tuple(lowerCamelCase   )
          snake_case_       						=      new_word
          if len(lowerCamelCase   ) == 1:
            break
          else:
            snake_case_       						=      get_pairs(lowerCamelCase   )
        snake_case_       						=      """ """.join(lowerCamelCase   )
        snake_case_       						=      word
        return word







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase							,  lowerCamelCase=None   )						->       Optional[int]:
        if self.add_bos_token:
          snake_case_       						=      [self.bos_token_id]
        else:
          snake_case_       						=      []

        snake_case_       						=      bos_token_ids + token_ids_a

        if token_ids_a is None:
          return output

        return output + bos_token_ids + token_ids_a







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase   )						->       Optional[int]:
        snake_case_       						=      []
        for token in re.findall(self.pat							,  lowerCamelCase   ):
          snake_case_       						=      """""".join(
              self.byte_encoder[b] for b in token.encode("""utf-8"""   )   )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
          bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCamelCase   ).split(""" """   )   )
        return bpe_tokens







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase   )						->       Optional[Any]:
        return self.encoder.get(lowerCamelCase							,  self.encoder.get(self.unk_token   )   )







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase   )						->       Dict:
        return self.decoder.get(lowerCamelCase   )







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase   )						->       str:
        snake_case_       						=      """""".join(lowerCamelCase   )
        snake_case_       						=      bytearray([self.byte_decoder[c] for c in text]   ).decode("""utf-8"""							,  errors=self.errors   )
        return text







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase							,  lowerCamelCase = None   )						->       Tuple[str]:
        if not os.path.isdir(lowerCamelCase   ):
          logger.error(f'''Vocabulary path ({save_directory}) should be a directory'''   )
          return
        snake_case_       						=      os.path.join(
            lowerCamelCase							,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]   )
        snake_case_       						=      os.path.join(
            lowerCamelCase							,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]   )

        with open(lowerCamelCase							,  """w"""							,  encoding="""utf-8"""   ) as f:
          f.write(json.dumps(self.encoder							,  indent=2							,  sort_keys=lowerCamelCase							,  ensure_ascii=lowerCamelCase   ) + """\n"""   )

        snake_case_       						=      0
        with open(lowerCamelCase							,  """w"""							,  encoding="""utf-8"""   ) as writer:
          writer.write("""#version: 0.2\n"""   )
          for bpe_tokens, token_index in sorted(self.bpe_ranks.items()							,  key=lambda lowerCamelCase   : kv[1]   ):
            if index != token_index:
              logger.warning(
                  f'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                  """ Please check that the tokenizer is not corrupted!"""   )
              snake_case_       						=      token_index
            writer.write(""" """.join(lowerCamelCase   ) + """\n"""   )
            index += 1

        return vocab_file, merge_file







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase							,  lowerCamelCase=False							,  **lowerCamelCase   )						->       Dict:
        snake_case_       						=      kwargs.pop("""add_prefix_space"""							,  self.add_prefix_space   )
        if is_split_into_words or add_prefix_space:
          snake_case_       						=      """ """ + text
        return (text, kwargs)







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase							,  lowerCamelCase = False							,  lowerCamelCase = None							,  lowerCamelCase = None							,  **lowerCamelCase							,  )						->       str:
        snake_case_       						=      super()._decode(
            token_ids=lowerCamelCase							,  skip_special_tokens=lowerCamelCase							,  clean_up_tokenization_spaces=lowerCamelCase							,  **lowerCamelCase							,  )

        if truncate_before_pattern is not None and len(lowerCamelCase   ) > 0:
          snake_case_       						=      self.truncate(lowerCamelCase							,  lowerCamelCase   )

        return decoded_text







      def 	lowerCAmelCase_    (     self							,  lowerCamelCase							,  lowerCamelCase   )						->       Optional[int]:
        def find_re(lowerCamelCase							,  lowerCamelCase							,  lowerCamelCase   ):
          snake_case_       						=      pattern.search(lowerCamelCase							,  lowerCamelCase   )
          return m.start() if m else -1

        snake_case_       						=      [re.compile(lowerCamelCase							,  re.MULTILINE   ) for pattern in truncate_before_pattern]

        snake_case_       						=      list(re.finditer("""^print"""							,  lowerCamelCase							,  re.MULTILINE   )   )

        if len(lowerCamelCase   ) > 1:
          snake_case_       						=      completion[: prints[1].start()]

        snake_case_       						=      list(re.finditer("""^def"""							,  lowerCamelCase							,  re.MULTILINE   )   )

        if len(lowerCamelCase   ) > 1:
          snake_case_       						=      completion[: defs[1].start()]

        snake_case_       						=      0

        snake_case_       						=      [
            pos for pos in [find_re(lowerCamelCase							,  lowerCamelCase							,  lowerCamelCase   ) for terminal in terminals] if pos != -1
        ]

        if len(lowerCamelCase   ) > 0:
          return completion[: min(lowerCamelCase   )]
        else:
          return completion
# as due to their complexity multi-gpu tests could impact other tests, and to aid debug we have those in a separate module.

import os
import sys

from transformers.testing_utils import TestCasePlus, execute_subprocess_async, get_gpu_count, require_torch_gpu, slow

from .utils import load_json


class 						a__							(   __snake_case		):



			@classmethod
			def __SCREAMING_SNAKE_CASE							(						cls    ) ->    Optional[int]:
								return cls







			@slow
			@require_torch_gpu
			def __SCREAMING_SNAKE_CASE							(						self    ) ->    Dict:
								__a							=   self.get_auto_remove_tmp_dir()
								__a							=   f'''
            --model_name Helsinki-NLP/opus-mt-en-ro
            --save_dir {output_dir}
            --data_dir {self.test_file_dir_str}/test_data/wmt_en_ro
            --num_beams 2
            --task translation
        '''.split()

								# we want this test to run even if there is only one GPU, but if there are more we use them all
								__a							=   get_gpu_count()
								__a							=   f'''
            -m torch.distributed.launch
            --nproc_per_node={n_gpu}
            {self.test_file_dir}/run_distributed_eval.py
        '''.split()
								__a							=   [sys.executable] + distributed_args + args
								execute_subprocess_async(UpperCAmelCase      ,						env=self.get_env()    )

								__a							=   os.path.join(UpperCAmelCase      ,						'test_bleu.json'    )
								__a							=   load_json(UpperCAmelCase    )
								# print(metrics)
								self.assertGreaterEqual(metrics['bleu']      ,						2_5    )




