



import os
from argparse import ArgumentParser
from pathlib import Path
from shutil import copyfile
from typing import List

from datasets import config
from datasets.builder import DatasetBuilder
from datasets.commands import BaseDatasetsCLICommand
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadMode
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.info_utils import VerificationMode
def   UpperCAmelCase							(		A__				,  **A__     )							->					Tuple:
	return RunBeamCommand(
	    args.dataset				,  args.name				,  args.cache_dir				,  args.beam_pipeline_options				,  args.data_dir				,  args.all_configs				,  args.save_info or args.save_infos				,  args.ignore_verifications				,  args.force_redownload				,  **A__				,  )





class 		__SCREAMING_SNAKE_CASE      (				lowercase__      ):






				"""simple docstring"""

				@staticmethod
				def 		__lowerCamelCase(				SCREAMING_SNAKE_CASE__      ):






					"""simple docstring"""

					_snake_case					:							Optional[Any]					     =   parser.add_parser("""run_beam"""						,	help="""Run a Beam dataset processing pipeline"""      )
					run_beam_parser.add_argument("""dataset"""						,	type=SCREAMING_SNAKE_CASE__						,	help="""Name of the dataset to download"""      )
					run_beam_parser.add_argument("""--name"""						,	type=SCREAMING_SNAKE_CASE__						,	default=SCREAMING_SNAKE_CASE__						,	help="""Dataset config name"""      )
					run_beam_parser.add_argument(
					    """--cache_dir"""						,	type=SCREAMING_SNAKE_CASE__						,	default=SCREAMING_SNAKE_CASE__						,	help="""Cache directory where the datasets are stored"""						,	)
					run_beam_parser.add_argument(
					    """--beam_pipeline_options"""						,	type=SCREAMING_SNAKE_CASE__						,	default=""""""						,	help="""Beam pipeline options, separated by commas. Example:: `--beam_pipeline_options=job_name=my-job,project=my-project`"""						,	)
					run_beam_parser.add_argument(
					    """--data_dir"""						,	type=SCREAMING_SNAKE_CASE__						,	default=SCREAMING_SNAKE_CASE__						,	help="""Can be used to specify a manual directory to get the files from"""						,	)
					run_beam_parser.add_argument("""--all_configs"""						,	action="""store_true"""						,	help="""Test all dataset configurations"""      )
					run_beam_parser.add_argument("""--save_info"""						,	action="""store_true"""						,	help="""Save the dataset infos file"""      )
					run_beam_parser.add_argument(
					    """--ignore_verifications"""						,	action="""store_true"""						,	help="""Run the test without checksums and splits checks"""      )
					run_beam_parser.add_argument("""--force_redownload"""						,	action="""store_true"""						,	help="""Force dataset redownload"""      )
					# aliases
					run_beam_parser.add_argument("""--save_infos"""						,	action="""store_true"""						,	help="""alias for save_info"""      )
					run_beam_parser.set_defaults(func=SCREAMING_SNAKE_CASE__      )







				def __init__(				self						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__						,	**SCREAMING_SNAKE_CASE__						,	):






					"""simple docstring"""

					_snake_case					:							List[Any]					     =   dataset
					_snake_case					:							Any					     =   name
					_snake_case					:							str					     =   cache_dir
					_snake_case					:							Tuple					     =   beam_pipeline_options
					_snake_case					:							List[Any]					     =   data_dir
					_snake_case					:							List[Any]					     =   all_configs
					_snake_case					:							Optional[int]					     =   save_infos
					_snake_case					:							Tuple					     =   ignore_verifications
					_snake_case					:							Tuple					     =   force_redownload
					_snake_case					:							List[str]					     =   config_kwargs







				def 		__lowerCamelCase(				self      ):






					"""simple docstring"""

					import apache_beam as beam

					if self._name is not None and self._all_configs:
						print("""Both parameters `name` and `all_configs` can't be used at once."""      )
						exit(1      )
					_snake_case     , _snake_case					:							Tuple					     =   self._dataset, self._name
					_snake_case					:							str					     =   dataset_module_factory(SCREAMING_SNAKE_CASE__      )
					_snake_case					:							Dict					     =   import_main_class(dataset_module.module_path      )
					_snake_case					:							List[DatasetBuilder]					     =   []
					if self._beam_pipeline_options:
						_snake_case					:							Union[str, Any]					     =   beam.options.pipeline_options.PipelineOptions(
						    flags=[f'''--{opt.strip()}''' for opt in self._beam_pipeline_options.split(""","""      ) if opt]      )
					else:
						_snake_case					:							Optional[int]					     =   None
					if self._all_configs and len(builder_cls.BUILDER_CONFIGS      ) > 0:
						for builder_config in builder_cls.BUILDER_CONFIGS:
							builders.append(
							    builder_cls(
							        config_name=builder_config.name						,	data_dir=self._data_dir						,	hash=dataset_module.hash						,	beam_options=SCREAMING_SNAKE_CASE__						,	cache_dir=self._cache_dir						,	base_path=dataset_module.builder_kwargs.get("""base_path"""      )						,	)      )
					else:
						builders.append(
						    builder_cls(
						        config_name=SCREAMING_SNAKE_CASE__						,	data_dir=self._data_dir						,	beam_options=SCREAMING_SNAKE_CASE__						,	cache_dir=self._cache_dir						,	base_path=dataset_module.builder_kwargs.get("""base_path"""      )						,	**self._config_kwargs						,	)      )

					for builder in builders:
						builder.download_and_prepare(
						    download_mode=DownloadMode.REUSE_CACHE_IF_EXISTS
						    if not self._force_redownload
						    else DownloadMode.FORCE_REDOWNLOAD						,	download_config=DownloadConfig(cache_dir=config.DOWNLOADED_DATASETS_PATH      )						,	verification_mode=VerificationMode.NO_CHECKS
						    if self._ignore_verifications
						    else VerificationMode.ALL_CHECKS						,	try_from_hf_gcs=SCREAMING_SNAKE_CASE__						,	)
						if self._save_infos:
							builder._save_infos()

					print("""Apache beam run successful."""      )

					# If save_infos=True, the dataset infos file is created next to the loaded module file.
					# 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:
						_snake_case					:							Tuple					     =   os.path.join(builder_cls.get_imported_module_dir()						,	config.DATASETDICT_INFOS_FILENAME      )

						_snake_case					:							List[str]					     =   Path(SCREAMING_SNAKE_CASE__      ).name + """.py"""

						_snake_case					:							str					     =   os.path.join(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__      )
						if os.path.isfile(SCREAMING_SNAKE_CASE__      ):
							_snake_case					:							int					     =   os.path.dirname(SCREAMING_SNAKE_CASE__      )
						elif os.path.isfile(SCREAMING_SNAKE_CASE__      ):
							_snake_case					:							Union[str, Any]					     =   path
						else:  # in case of a remote dataset
							print(f'''Dataset Infos file saved at {dataset_infos_path}'''      )
							exit(1      )

						# Move datasetinfo back to the user
						_snake_case					:							Dict					     =   os.path.join(SCREAMING_SNAKE_CASE__						,	config.DATASETDICT_INFOS_FILENAME      )
						copyfile(SCREAMING_SNAKE_CASE__						,	SCREAMING_SNAKE_CASE__      )
						print(f'''Dataset Infos file saved at {user_dataset_infos_path}'''      )










# 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   UpperCAmelCase							(		A__				,  A__     )							->					Any:
	if name != "training_function" and name != "main":
		raise ValueError(f'''Incorrect function name passed: {name}, choose either \'main\' or \'training_function\''''     )
	_snake_case     , _snake_case					:							Union[str, Any]					     =   [], False
	for line in lines:
		if not found_start and f'''def {name}''' in line:
			_snake_case					:							Tuple					     =   True
			good_lines.append(A__     )
			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(A__     )
def   UpperCAmelCase							(		A__     )							->					Dict:
	return [line for line in lines if not line.lstrip().startswith("""#"""     ) and line != "\n"]


def   UpperCAmelCase							(		A__				,  A__				,  A__				,  A__ = None     )							->					str:
	with open(A__				,  """r"""     ) as f:
		_snake_case					:							Tuple					     =   f.readlines()
	with open(os.path.abspath(os.path.join("""examples"""				,  """nlp_example.py"""     )     )				,  """r"""     ) as f:
		_snake_case					:							Optional[Any]					     =   f.readlines()
	with open(A__				,  """r"""     ) as f:
		_snake_case					:							Optional[Any]					     =   f.readlines()
	if secondary_filename is not None:
		with open(A__				,  """r"""     ) as f:
			_snake_case					:							List[str]					     =   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:
		_snake_case					:							Dict					     =   clean_lines(get_function_contents_by_name(A__				,  """main"""     )     )
		_snake_case					:							int					     =   clean_lines(get_function_contents_by_name(A__				,  """main"""     )     )
		_snake_case					:							Optional[Any]					     =   clean_lines(get_function_contents_by_name(A__				,  """main"""     )     )
		if secondary_filename is not None:
			_snake_case					:							Optional[Any]					     =   clean_lines(get_function_contents_by_name(A__				,  """main"""     )     )
	else:
		_snake_case					:							str					     =   clean_lines(get_function_contents_by_name(A__				,  """training_function"""     )     )
		_snake_case					:							List[Any]					     =   clean_lines(get_function_contents_by_name(A__				,  """training_function"""     )     )
		_snake_case					:							Union[str, Any]					     =   clean_lines(get_function_contents_by_name(A__				,  """training_function"""     )     )
		if secondary_filename is not None:
			_snake_case					:							List[Any]					     =   clean_lines(
			    get_function_contents_by_name(A__				,  """training_function"""     )     )

	_snake_case					:							str					     =   """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
	_snake_case					:							Dict					     =   []
	_snake_case					:							str					     =   []  # We keep track of the idxs just in case it's a repeated statement
	_snake_case					:							Optional[Any]					     =   iter(A__     )
	for i in range(len(A__     ) - 1     ):
		if i not in passed_idxs:
			_snake_case					:							Any					     =   next(A__     )
			if (line not in full_file_func) and (line.lstrip() != _dl_line):
				if "TESTING_MOCKED_DATALOADERS" not in line:
					new_feature_code.append(A__     )
					passed_idxs.append(A__     )
				else:
					# Skip over the `config['num_epochs'] = 2` statement
					_snake_case					:							Optional[int]					     =   next(A__     )

    # Extract out just the new parts from the full_file_training_func
	_snake_case					:							Any					     =   []
	_snake_case					:							Tuple					     =   []  # We keep track of the idxs just in case it's a repeated statement
	for i, line in enumerate(A__     ):
		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(A__     )
					passed_idxs.append(A__     )

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

	return diff_from_example





