

import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile, rmtree
from typing import Generator

import datasets.config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.filelock import logger as fl_logger
from datasets.utils.info_utils import VerificationMode
from datasets.utils.logging import ERROR, get_logger


_UpperCamelCase			      =		get_logger(__name__)







def 		_lowercase			(					lowercase__						):
      return TestCommand(
          args.dataset       ,     args.name       ,     args.cache_dir       ,     args.data_dir       ,     args.all_configs       ,     args.save_info or args.save_infos       ,     args.ignore_verifications       ,     args.force_redownload       ,     args.clear_cache       ,     )







class   __lowercase				(_UpperCAmelCase			):
 _UpperCamelCase        =  False  # to tell pytest it's not a test class
 @staticmethod
 def      UpperCamelCase__  (							A_ ) ->str:



       '''simple docstring'''





       __lowerCAmelCase :						int = parser.add_parser('''test'''				,							help='''Test dataset implementation.''' )
       test_parser.add_argument('''--name'''				,							type=A_				,							default=A_				,							help='''Dataset processing name''' )
       test_parser.add_argument(
           '''--cache_dir'''				,							type=A_				,							default=A_				,							help='''Cache directory where the datasets are stored.'''				,							)
       test_parser.add_argument(
           '''--data_dir'''				,							type=A_				,							default=A_				,							help='''Can be used to specify a manual directory to get the files from.'''				,							)
       test_parser.add_argument('''--all_configs'''				,							action='''store_true'''				,							help='''Test all dataset configurations''' )
       test_parser.add_argument(
           '''--save_info'''				,							action='''store_true'''				,							help='''Save the dataset infos in the dataset card (README.md)''' )
       test_parser.add_argument(
           '''--ignore_verifications'''				,							action='''store_true'''				,							help='''Run the test without checksums and splits checks.'''				,							)
       test_parser.add_argument('''--force_redownload'''				,							action='''store_true'''				,							help='''Force dataset redownload''' )
       test_parser.add_argument(
           '''--clear_cache'''				,							action='''store_true'''				,							help='''Remove downloaded files and cached datasets after each config test'''				,							)
       # aliases
       test_parser.add_argument('''--save_infos'''				,							action='''store_true'''				,							help='''alias to save_info''' )
       test_parser.add_argument('''dataset'''				,							type=A_				,							help='''Name of the dataset to download''' )
       test_parser.set_defaults(func=_test_command_factory )
 def __init__(							self				,							A_				,							A_				,							A_				,							A_				,							A_				,							A_				,							A_				,							A_				,							A_				,							) ->List[str]:



       '''simple docstring'''





       __lowerCAmelCase :						Dict = dataset
       __lowerCAmelCase :						Dict = name
       __lowerCAmelCase :						str = cache_dir
       __lowerCAmelCase :						Optional[Any] = data_dir
       __lowerCAmelCase :						int = all_configs
       __lowerCAmelCase :						Optional[int] = save_infos
       __lowerCAmelCase :						Optional[Any] = ignore_verifications
       __lowerCAmelCase :						Optional[Any] = force_redownload
       __lowerCAmelCase :						Optional[int] = clear_cache
       if clear_cache and not cache_dir:
             print(
                 '''When --clear_cache is used, specifying a cache directory is mandatory.\n'''
                 '''The \'download\' folder of the cache directory and the dataset builder cache will be deleted after each configuration test.\n'''
                 '''Please provide a --cache_dir that will be used to test the dataset script.''' )
             exit(1 )
       if save_infos:
             __lowerCAmelCase :						Tuple = True





 def      UpperCamelCase__  (							self ) ->str:



       '''simple docstring'''





       fl_logger().setLevel(A_ )
       if self._name is not None and self._all_configs:
             print('''Both parameters `config` and `all_configs` can\'t be used at once.''' )
             exit(1 )
       __lowerCAmelCase,							__lowerCAmelCase :						Optional[int] = self._dataset, self._name
       __lowerCAmelCase :						Tuple = dataset_module_factory(A_ )
       __lowerCAmelCase :						Dict = import_main_class(module.module_path )
       __lowerCAmelCase :						Dict = len(builder_cls.BUILDER_CONFIGS ) if self._all_configs and builder_cls.BUILDER_CONFIGS else 1

       def get_builders() -> Generator[DatasetBuilder, None, None]:
             if self._all_configs and builder_cls.BUILDER_CONFIGS:
                   for i, config in enumerate(builder_cls.BUILDER_CONFIGS ):
                         if "config_name" in module.builder_kwargs:
                               yield builder_cls(
                                   cache_dir=self._cache_dir				,							data_dir=self._data_dir				,							**module.builder_kwargs				,							)
                         else:
                               yield builder_cls(
                                   config_name=config.name				,							cache_dir=self._cache_dir				,							data_dir=self._data_dir				,							**module.builder_kwargs				,							)
             else:
                   if "config_name" in module.builder_kwargs:
                         yield builder_cls(cache_dir=self._cache_dir				,							data_dir=self._data_dir				,							**module.builder_kwargs )
                   else:
                         yield builder_cls(
                             config_name=A_				,							cache_dir=self._cache_dir				,							data_dir=self._data_dir				,							**module.builder_kwargs				,							)

       for j, builder in enumerate(get_builders() ):
             print(f"""Testing builder '{builder.config.name}' ({j + 1}/{n_builders})""" )
             __lowerCAmelCase :						int = os.path.exists(
                 os.path.join(builder.get_imported_module_dir()				,							datasets.config.DATASETDICT_INFOS_FILENAME ) )  # record checksums only if we need to update a (deprecated) dataset_infos.json
             builder.download_and_prepare(
                 download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
                 if not self._force_redownload
                 else DownloadMode.FORCE_REDOWNLOAD				,							verification_mode=VerificationMode.NO_CHECKS
                 if self._ignore_verifications
                 else VerificationMode.ALL_CHECKS				,							try_from_hf_gcs=A_				,							)
             builder.as_dataset()
             if self._save_infos:
                   builder._save_infos()

             # If save_infos=True, the dataset card (README.md) is created next to the loaded module file.
             # The dataset_infos are saved in the YAML part of the README.md

             # Let's move it to the original directory of the dataset script, to allow the user to
             # upload them on S3 at the same time afterwards.
             if self._save_infos:
                   __lowerCAmelCase :						str = os.path.join(builder_cls.get_imported_module_dir()				,							'''README.md''' )
                   __lowerCAmelCase :						Dict = Path(A_ ).name + '''.py'''
                   __lowerCAmelCase :						Optional[int] = os.path.join(A_				,							A_ )
                   if os.path.isfile(A_ ):
                         __lowerCAmelCase :						Union[str, Any] = os.path.dirname(A_ )
                   elif os.path.isfile(A_ ):
                         __lowerCAmelCase :						int = path
                   elif os.path.isdir(A_ ):  # for local directories containing only data files
                         __lowerCAmelCase :						List[Any] = path
                   else:  # in case of a remote dataset
                         __lowerCAmelCase :						List[str] = None
                         print(f"""Dataset card saved at {dataset_readme_path}""" )

                   # Move dataset_info back to the user
                   if dataset_dir is not None:
                         __lowerCAmelCase :						Optional[int] = os.path.join(A_				,							'''README.md''' )
                         copyfile(A_				,							A_ )
                         print(f"""Dataset card saved at {user_dataset_readme_path}""" )

            # If clear_cache=True, the download folder and the dataset builder cache directory are deleted
             if self._clear_cache:
                   if os.path.isdir(builder._cache_dir ):
                         logger.warning(f"""Clearing cache at {builder._cache_dir}""" )
                         rmtree(builder._cache_dir )
                   __lowerCAmelCase :						int = os.path.join(self._cache_dir				,							datasets.config.DOWNLOADED_DATASETS_DIR )
                   if os.path.isdir(A_ ):
                         logger.warning(f"""Clearing cache at {download_dir}""" )
                         rmtree(A_ )

       print('''Test successful.''' )





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


_UpperCamelCase			      =		logging.get_logger(__name__)

_UpperCamelCase			      =		{
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

_UpperCamelCase			      =		{
    "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",
    },
}

_UpperCamelCase			      =		{
    "Salesforce/codegen-350M-mono": 2048,
}







@lru_cache()
def 		_lowercase			(					):
      __lowerCAmelCase :						Union[str, Any] = (
          list(range(ord('''!'''						)       ,     ord('''~'''						) + 1						)						) + list(range(ord('''¡'''						)       ,     ord('''¬'''						) + 1						)						) + list(range(ord('''®'''						)       ,     ord('''ÿ'''						) + 1						)						)
      )
      __lowerCAmelCase :						Optional[int] = bs[:]
      __lowerCAmelCase :						Union[str, Any] = 0
      for b in range(2**8						):
            if b not in bs:
                  bs.append(lowercase__						)
                  cs.append(2**8 + n						)
                  n += 1
      __lowerCAmelCase :						Optional[int] = [chr(lowercase__						) for n in cs]
      return dict(zip(lowercase__       ,     lowercase__						)						)







def 		_lowercase			(					lowercase__						):
      __lowerCAmelCase :						List[Any] = set()
      __lowerCAmelCase :						int = word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)						)
            __lowerCAmelCase :						int = char
      return pairs







class   __lowercase				(_UpperCAmelCase			):
 _UpperCamelCase        =  VOCAB_FILES_NAMES
 _UpperCamelCase        =  PRETRAINED_VOCAB_FILES_MAP
 _UpperCamelCase        =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _UpperCamelCase        =  ["""input_ids""", """attention_mask"""]
 def __init__(							self				,							A_				,							A_				,							A_="replace"				,							A_="<|endoftext|>"				,							A_="<|endoftext|>"				,							A_="<|endoftext|>"				,							A_=None				,							A_=False				,							A_=False				,							**A_				,							) ->Union[str, Any]:



       '''simple docstring'''





       __lowerCAmelCase :						Union[str, Any] = AddedToken(A_				,							lstrip=A_				,							rstrip=A_ ) if isinstance(A_				,							A_ ) else bos_token
       __lowerCAmelCase :						Tuple = AddedToken(A_				,							lstrip=A_				,							rstrip=A_ ) if isinstance(A_				,							A_ ) else eos_token
       __lowerCAmelCase :						Any = AddedToken(A_				,							lstrip=A_				,							rstrip=A_ ) if isinstance(A_				,							A_ ) else unk_token
       __lowerCAmelCase :						List[Any] = AddedToken(A_				,							lstrip=A_				,							rstrip=A_ ) if isinstance(A_				,							A_ ) else pad_token
       super().__init__(
           errors=A_				,							unk_token=A_				,							bos_token=A_				,							eos_token=A_				,							pad_token=A_				,							add_prefix_space=A_				,							add_bos_token=A_				,							**A_				,							)
       __lowerCAmelCase :						List[str] = add_bos_token

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

       # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
       __lowerCAmelCase :						Optional[Any] = re.compile(R'''\'s|\'t|\'re|\'ve|\'m|\'ll|\'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+''' )
 @property
 def      UpperCamelCase__  (							self ) ->Dict:



       '''simple docstring'''





       return len(self.encoder )
 def      UpperCamelCase__  (							self ) ->str:



       '''simple docstring'''





       return dict(self.encoder				,							**self.added_tokens_encoder )
 def      UpperCamelCase__  (							self				,							A_ ) ->Tuple:



       '''simple docstring'''





       if token in self.cache:
             return self.cache[token]
       __lowerCAmelCase :						Tuple = tuple(A_ )
       __lowerCAmelCase :						str = get_pairs(A_ )

       if not pairs:
             return token

       while True:
             __lowerCAmelCase :						int = min(A_				,							key=lambda A_ : self.bpe_ranks.get(A_				,							float('''inf''' ) ) )
             if bigram not in self.bpe_ranks:
                   break
             __lowerCAmelCase,							__lowerCAmelCase :						Dict = bigram
             __lowerCAmelCase :						Union[str, Any] = []
             __lowerCAmelCase :						Union[str, Any] = 0
             while i < len(A_ ):
                   try:
                         __lowerCAmelCase :						List[str] = word.index(A_				,							A_ )
                   except ValueError:
                         new_word.extend(word[i:] )
                         break
                   else:
                         new_word.extend(word[i:j] )
                         __lowerCAmelCase :						Optional[int] = j

                   if word[i] == first and i < len(A_ ) - 1 and word[i + 1] == second:
                         new_word.append(first + second )
                         i += 2
                   else:
                         new_word.append(word[i] )
                         i += 1
             __lowerCAmelCase :						Optional[int] = tuple(A_ )
             __lowerCAmelCase :						List[Any] = new_word
             if len(A_ ) == 1:
                   break
             else:
                   __lowerCAmelCase :						Optional[int] = get_pairs(A_ )
       __lowerCAmelCase :						List[str] = ''' '''.join(A_ )
       __lowerCAmelCase :						Any = word
       return word
 def      UpperCamelCase__  (							self				,							A_				,							A_=None ) ->Tuple:



       '''simple docstring'''





       if self.add_bos_token:
             __lowerCAmelCase :						Any = [self.bos_token_id]
       else:
             __lowerCAmelCase :						Union[str, Any] = []

       __lowerCAmelCase :						Union[str, Any] = bos_token_ids + token_ids_a

       if token_ids_a is None:
             return output

       return output + bos_token_ids + token_ids_a
 def      UpperCamelCase__  (							self				,							A_ ) ->List[str]:



       '''simple docstring'''





       __lowerCAmelCase :						str = []
       for token in re.findall(self.pat				,							A_ ):
             __lowerCAmelCase :						Any = ''''''.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(A_ ).split(''' ''' ) )
       return bpe_tokens
 def      UpperCamelCase__  (							self				,							A_ ) ->Dict:



       '''simple docstring'''





       return self.encoder.get(A_				,							self.encoder.get(self.unk_token ) )
 def      UpperCamelCase__  (							self				,							A_ ) ->Optional[int]:



       '''simple docstring'''





       return self.decoder.get(A_ )
 def      UpperCamelCase__  (							self				,							A_ ) ->Optional[Any]:



       '''simple docstring'''





       __lowerCAmelCase :						List[Any] = ''''''.join(A_ )
       __lowerCAmelCase :						Optional[Any] = bytearray([self.byte_decoder[c] for c in text] ).decode('''utf-8'''				,							errors=self.errors )
       return text
 def      UpperCamelCase__  (							self				,							A_				,							A_ = None ) ->Tuple[str]:



       '''simple docstring'''





       if not os.path.isdir(A_ ):
             logger.error(f"""Vocabulary path ({save_directory}) should be a directory""" )
             return
       __lowerCAmelCase :						List[str] = os.path.join(
           A_				,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file'''] )
       __lowerCAmelCase :						Tuple = os.path.join(
           A_				,							(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file'''] )

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

       __lowerCAmelCase :						Optional[int] = 0
       with open(A_				,							'''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 A_ : 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!''' )
                         __lowerCAmelCase :						List[Any] = token_index
                   writer.write(''' '''.join(A_ ) + '''\n''' )
                   index += 1

       return vocab_file, merge_file
 def      UpperCamelCase__  (							self				,							A_				,							A_=False				,							**A_ ) ->Union[str, Any]:



       '''simple docstring'''





       __lowerCAmelCase :						Tuple = kwargs.pop('''add_prefix_space'''				,							self.add_prefix_space )
       if is_split_into_words or add_prefix_space:
             __lowerCAmelCase :						List[str] = ''' ''' + text
       return (text, kwargs)
 def      UpperCamelCase__  (							self				,							A_				,							A_ = False				,							A_ = None				,							A_ = None				,							**A_				,							) ->str:



       '''simple docstring'''





       __lowerCAmelCase :						List[Any] = super()._decode(
           token_ids=A_				,							skip_special_tokens=A_				,							clean_up_tokenization_spaces=A_				,							**A_				,							)

       if truncate_before_pattern is not None and len(A_ ) > 0:
             __lowerCAmelCase :						str = self.truncate(A_				,							A_ )

       return decoded_text





 def      UpperCamelCase__  (							self				,							A_				,							A_ ) ->int:



       '''simple docstring'''





       def find_re(A_				,							A_				,							A_ ):
             __lowerCAmelCase :						Dict = pattern.search(A_				,							A_ )
             return m.start() if m else -1

       __lowerCAmelCase :						int = [re.compile(A_				,							re.MULTILINE ) for pattern in truncate_before_pattern]

       __lowerCAmelCase :						Tuple = list(re.finditer('''^print'''				,							A_				,							re.MULTILINE ) )

       if len(A_ ) > 1:
             __lowerCAmelCase :						int = completion[: prints[1].start()]

       __lowerCAmelCase :						Optional[Any] = list(re.finditer('''^def'''				,							A_				,							re.MULTILINE ) )

       if len(A_ ) > 1:
             __lowerCAmelCase :						List[str] = completion[: defs[1].start()]

       __lowerCAmelCase :						Optional[Any] = 0

       __lowerCAmelCase :						Optional[int] = [
           pos for pos in [find_re(A_				,							A_				,							A_ ) for terminal in terminals] if pos != -1
       ]

       if len(A_ ) > 0:
             return completion[: min(A_ )]
       else:
             return completion


