






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


__a :    Any								=				get_logger(__name__)



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     List[Any]      )  -> List[str]:





    """simple docstring"""

    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 (		lowercase_					):







     '''simple docstring'''
     SCREAMING_SNAKE_CASE				  =			False  # to tell pytest it's not a test class




     @staticmethod
     def 						lowerCAmelCase_       (			UpperCamelCase_    :     ArgumentParser			):


         """simple docstring"""



         __A             =		parser.add_parser("""test"""	,		help="""Test dataset implementation."""			)
         test_parser.add_argument("""--name"""	,		type=UpperCamelCase_	,		default=UpperCamelCase_	,		help="""Dataset processing name"""			)
         test_parser.add_argument(
             """--cache_dir"""	,		type=UpperCamelCase_	,		default=UpperCamelCase_	,		help="""Cache directory where the datasets are stored."""	,		)
         test_parser.add_argument(
             """--data_dir"""	,		type=UpperCamelCase_	,		default=UpperCamelCase_	,		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=UpperCamelCase_	,		help="""Name of the dataset to download"""			)
         test_parser.set_defaults(func=_test_command_factory			)




     def __init__(			self    :     str	,		UpperCamelCase_    :     str	,		UpperCamelCase_    :     str	,		UpperCamelCase_    :     str	,		UpperCamelCase_    :     str	,		UpperCamelCase_    :     bool	,		UpperCamelCase_    :     bool	,		UpperCamelCase_    :     bool	,		UpperCamelCase_    :     bool	,		UpperCamelCase_    :     bool	,		):


         """simple docstring"""



         __A             =		dataset
         __A             =		name
         __A             =		cache_dir
         __A             =		data_dir
         __A             =		all_configs
         __A             =		save_infos
         __A             =		ignore_verifications
         __A             =		force_redownload
         __A             =		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:
             __A             =		True





     def 						lowerCAmelCase_       (			self    :     Dict			):


         """simple docstring"""



         fl_logger().setLevel(UpperCamelCase_			)
         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			)
         __A      ,		__A             =		self._dataset, self._name
         __A             =		dataset_module_factory(UpperCamelCase_			)
         __A             =		import_main_class(module.module_path			)
         __A             =		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=UpperCamelCase_	,		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})"			)
             __A             =		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=UpperCamelCase_	,		)
             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:
                 __A             =		os.path.join(builder_cls.get_imported_module_dir()	,		"""README.md"""			)
                 __A             =		Path(UpperCamelCase_			).name + """.py"""
                 __A             =		os.path.join(UpperCamelCase_	,		UpperCamelCase_			)
                 if os.path.isfile(UpperCamelCase_			):
                     __A             =		os.path.dirname(UpperCamelCase_			)
                 elif os.path.isfile(UpperCamelCase_			):
                     __A             =		path
                 elif os.path.isdir(UpperCamelCase_			):  # for local directories containing only data files
                     __A             =		path
                 else:  # in case of a remote dataset
                     __A             =		None
                     print(F"Dataset card saved at {dataset_readme_path}"			)

                 # Move dataset_info back to the user
                 if dataset_dir is not None:
                     __A             =		os.path.join(UpperCamelCase_	,		"""README.md"""			)
                     copyfile(UpperCamelCase_	,		UpperCamelCase_			)
                     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			)
                 __A             =		os.path.join(self._cache_dir	,		datasets.config.DOWNLOADED_DATASETS_DIR			)
                 if os.path.isdir(UpperCamelCase_			):
                     logger.warning(F"Clearing cache at {download_dir}"			)
                     rmtree(UpperCamelCase_			)

         print("""Test successful."""			)












# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from typing import List



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     List[str]     ,			__lowercase				:     str      )  -> Optional[int]:





    """simple docstring"""

    if name != "training_function" and name != "main":
        raise ValueError(f"Incorrect function name passed: {name}, choose either 'main' or 'training_function'"      )
    __A      ,		__A             =		[], False
    for line in lines:
        if not found_start and f"def {name}" in line:
            __A             =		True
            good_lines.append(__lowercase      )
            continue
        if found_start:
            if name == "training_function" and "def main" in line:
                return good_lines
            if name == "main" and "if __name__" in line:
                return good_lines
            good_lines.append(__lowercase      )



def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     List[str]      )  -> Optional[int]:





    """simple docstring"""

    return [line for line in lines if not line.lstrip().startswith("""#"""      ) and line != "\n"]






def      _SCREAMING_SNAKE_CASE  (	__lowercase				:     str     ,			__lowercase				:     str     ,			__lowercase				:     bool     ,			__lowercase				:     str = None      )  -> List[Any]:





    """simple docstring"""

    with open(__lowercase     ,			"""r"""      ) as f:
        __A             =		f.readlines()
    with open(os.path.abspath(os.path.join("""examples"""     ,			"""nlp_example.py"""      )      )     ,			"""r"""      ) as f:
        __A             =		f.readlines()
    with open(__lowercase     ,			"""r"""      ) as f:
        __A             =		f.readlines()
    if secondary_filename is not None:
        with open(__lowercase     ,			"""r"""      ) as f:
            __A             =		f.readlines()

    # This is our base, we remove all the code from here in our `full_filename` and `feature_filename` to find the new content
    if parser_only:
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
        if secondary_filename is not None:
            __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""main"""      )      )
    else:
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )
        __A             =		clean_lines(get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )
        if secondary_filename is not None:
            __A             =		clean_lines(
                get_function_contents_by_name(__lowercase     ,			"""training_function"""      )      )

    __A             =		"""train_dataloader, eval_dataloader = get_dataloaders(accelerator, batch_size)\n"""

    # Specific code in our script that differs from the full version, aka what is new
    __A             =		[]
    __A             =		[]  # We keep track of the idxs just in case it's a repeated statement
    __A             =		iter(__lowercase      )
    for i in range(len(__lowercase      ) - 1      ):
        if i not in passed_idxs:
            __A             =		next(__lowercase      )
            if (line not in full_file_func) and (line.lstrip() != _dl_line):
                if "TESTING_MOCKED_DATALOADERS" not in line:
                    new_feature_code.append(__lowercase      )
                    passed_idxs.append(__lowercase      )
                else:
                    # Skip over the `config['num_epochs'] = 2` statement
                    __A             =		next(__lowercase      )

    # Extract out just the new parts from the full_file_training_func
    __A             =		[]
    __A             =		[]  # We keep track of the idxs just in case it's a repeated statement
    for i, line in enumerate(__lowercase      ):
        if i not in passed_idxs:
            if (line not in full_file_func) and (line.lstrip() != _dl_line):
                if "TESTING_MOCKED_DATALOADERS" not in line:
                    new_full_example_parts.append(__lowercase      )
                    passed_idxs.append(__lowercase      )

    # Finally, get the overall diff
    __A             =		[line for line in new_feature_code if line not in new_full_example_parts]
    if secondary_filename is not None:
        __A             =		[line for line in full_file_contents if line not in secondary_file_func]
        __A             =		[line for line in diff_from_example if line not in diff_from_two]

    return diff_from_example




