






# 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 argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


__UpperCamelCase					:		int	  =						"""Run commands across TPU VMs for initial setup before running `accelerate launch`."""
def      a_ (      _A=None  )			->			List[str]:







				"""simple docstring"""
				if subparsers is not None:
								snake_case__									=     subparsers.add_parser('tpu-config'      ,   description=_description  )
				else:
								snake_case__									=     argparse.ArgumentParser('Accelerate tpu-config command'      ,   description=_description  )
				# Core arguments
				snake_case__									=     parser.add_argument_group(
				    'Config Arguments'      ,   'Arguments that can be configured through `accelerate config`.'  )
				config_args.add_argument(
				    '--config_file'      ,   type=_A      ,   default=_A      ,   help='Path to the config file to use for accelerate.'      ,   )
				config_args.add_argument(
				    '--tpu_name'      ,   default=_A      ,   help='The name of the TPU to use. If not specified, will use the TPU specified in the config file.'      ,   )
				config_args.add_argument(
				    '--tpu_zone'      ,   default=_A      ,   help='The zone of the TPU to use. If not specified, will use the zone specified in the config file.'      ,   )
				snake_case__									=     parser.add_argument_group('TPU Arguments'      ,   'Arguments for options ran inside the TPU.'  )
				pod_args.add_argument(
				    '--use_alpha'      ,   action='store_true'      ,   help='Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`.'      ,   )
				pod_args.add_argument(
				    '--command_file'      ,   default=_A      ,   help='The path to the file containing the commands to run on the pod on startup.'      ,   )
				pod_args.add_argument(
				    '--command'      ,   action='append'      ,   nargs='+'      ,   help='A command to run on the pod. Can be passed multiple times.'      ,   )
				pod_args.add_argument(
				    '--install_accelerate'      ,   action='store_true'      ,   help='Whether to install accelerate on the pod. Defaults to False.'      ,   )
				pod_args.add_argument(
				    '--accelerate_version'      ,   default='latest'      ,   help='The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify \'dev\' to install from GitHub.'      ,   )
				pod_args.add_argument(
				    '--debug'      ,   action='store_true'      ,   help='If set, will print the command that would be run instead of running it.'  )

				if subparsers is not None:
								parser.set_defaults(func=_A  )
				return parser
def      a_ (      _A  )			->			Optional[int]:







				"""simple docstring"""
				snake_case__									=     None

				# Get the default from the config file if it exists.
				if args.config_file is not None or os.path.isfile(_A  ):
								snake_case__									=     load_config_from_file(args.config_file  )
								if not args.command_file and defaults.command_file is not None and not args.command:
												snake_case__									=     defaults.command_file
								if not args.command and defaults.commands is not None:
												snake_case__									=     defaults.commands
								if not args.tpu_name:
												snake_case__									=     defaults.tpu_name
								if not args.tpu_zone:
												snake_case__									=     defaults.tpu_zone
				if args.accelerate_version == "dev":
								snake_case__									=     'git+https://github.com/huggingface/accelerate.git'
				elif args.accelerate_version == "latest":
								snake_case__									=     'accelerate -U'
				elif isinstance(parse(args.accelerate_version  )      ,   _A  ):
								snake_case__									=     f'''accelerate=={args.accelerate_version}'''

				if not args.command_file and not args.command:
								raise ValueError('You must specify either a command file or a command to run on the pod.'  )

				if args.command_file:
								with open(args.command_file      ,   'r'  ) as f:
												snake_case__									=     [f.read().splitlines()]

    # To turn list of lists into list of strings
				if isinstance(args.command[0]      ,   _A  ):
								snake_case__									=     [line for cmd in args.command for line in cmd]
				# Default to the shared folder and install accelerate
				snake_case__									=     ['cd /usr/share']
				if args.install_accelerate:
								new_cmd += [f'''pip install {args.accelerate_version}''']
				new_cmd += args.command
				snake_case__									=     '; '.join(_A  )

				# Then send it to gcloud
				# Eventually try to use google-api-core to do this instead of subprocess
				snake_case__									=     ['gcloud']
				if args.use_alpha:
								cmd += ["alpha"]
				cmd += [
				    "compute",
				    "tpus",
				    "tpu-vm",
				    "ssh",
				    args.tpu_name,
				    "--zone",
				    args.tpu_zone,
				    "--command",
				    args.command,
				    "--worker",
				    "all",
				]
				if args.debug:
								print(f'''Running {' '.join(_A  )}'''  )
								return
				subprocess.run(_A  )
				print('Successfully setup pod.'  )


def      a_ (      )			->			Optional[Any]:







				"""simple docstring"""
				snake_case__									=     tpu_command_parser()
				snake_case__									=     parser.parse_args()

				tpu_command_launcher(_A  )












import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union

import pandas as pd
import pyarrow as pa

import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_utils import Literal


__UpperCamelCase					:		Any	  =						datasets.utils.logging.get_logger(__name__)

__UpperCamelCase					:		Union[str, Any]	  =						["""names""", """prefix"""]
__UpperCamelCase					:		List[str]	  =						["""warn_bad_lines""", """error_bad_lines""", """mangle_dupe_cols"""]
__UpperCamelCase					:		Dict	  =						["""encoding_errors""", """on_bad_lines"""]
__UpperCamelCase					:		Any	  =						["""date_format"""]


@dataclass
class   __SCREAMING_SNAKE_CASE(	datasets.BuilderConfig	):
							_UpperCAmelCase     =       ","
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       "infer"
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       True
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       False
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       True
							_UpperCAmelCase     =       True
							_UpperCAmelCase     =       False
							_UpperCAmelCase     =       True
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       "."
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       '"'
							_UpperCAmelCase     =       0
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       True
							_UpperCAmelCase     =       True
							_UpperCAmelCase     =       0
							_UpperCAmelCase     =       True
							_UpperCAmelCase     =       False
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       1_0_0_0_0
							_UpperCAmelCase     =       None
							_UpperCAmelCase     =       "strict"
							_UpperCAmelCase     =       "error"
							_UpperCAmelCase     =       None
							def lowerCAmelCase_ (     self:      Tuple						)		->		int:
											if self.delimiter is not None:
															snake_case__									=     self.delimiter
											if self.column_names is not None:
															snake_case__									=     self.column_names


							@property
							def lowerCAmelCase_ (     self:      Optional[int]						)		->		List[str]:
											snake_case__									=     {
											    'sep': self.sep,
											    'header': self.header,
											    'names': self.names,
											    'index_col': self.index_col,
											    'usecols': self.usecols,
											    'prefix': self.prefix,
											    'mangle_dupe_cols': self.mangle_dupe_cols,
											    'engine': self.engine,
											    'converters': self.converters,
											    'true_values': self.true_values,
											    'false_values': self.false_values,
											    'skipinitialspace': self.skipinitialspace,
											    'skiprows': self.skiprows,
											    'nrows': self.nrows,
											    'na_values': self.na_values,
											    'keep_default_na': self.keep_default_na,
											    'na_filter': self.na_filter,
											    'verbose': self.verbose,
											    'skip_blank_lines': self.skip_blank_lines,
											    'thousands': self.thousands,
											    'decimal': self.decimal,
											    'lineterminator': self.lineterminator,
											    'quotechar': self.quotechar,
											    'quoting': self.quoting,
											    'escapechar': self.escapechar,
											    'comment': self.comment,
											    'encoding': self.encoding,
											    'dialect': self.dialect,
											    'error_bad_lines': self.error_bad_lines,
											    'warn_bad_lines': self.warn_bad_lines,
											    'skipfooter': self.skipfooter,
											    'doublequote': self.doublequote,
											    'memory_map': self.memory_map,
											    'float_precision': self.float_precision,
											    'chunksize': self.chunksize,
											    'encoding_errors': self.encoding_errors,
											    'on_bad_lines': self.on_bad_lines,
											    'date_format': self.date_format,
											}

											# some kwargs must not be passed if they don't have a default value
											# some others are deprecated and we can also not pass them if they are the default value
											for pd_read_csv_parameter in _PANDAS_READ_CSV_NO_DEFAULT_PARAMETERS + _PANDAS_READ_CSV_DEPRECATED_PARAMETERS:
															if pd_read_csv_kwargs[pd_read_csv_parameter] == getattr(CsvConfig()       ,	UpperCamelCase						):
																			del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 2.0 new arguments
											if not (datasets.config.PANDAS_VERSION.major >= 2):
															for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_2_0_0_PARAMETERS:
																			del pd_read_csv_kwargs[pd_read_csv_parameter]

        # Remove 1.3 new arguments
											if not (datasets.config.PANDAS_VERSION.major >= 1 and datasets.config.PANDAS_VERSION.minor >= 3):
															for pd_read_csv_parameter in _PANDAS_READ_CSV_NEW_1_3_0_PARAMETERS:
																			del pd_read_csv_kwargs[pd_read_csv_parameter]

											return pd_read_csv_kwargs


class   __SCREAMING_SNAKE_CASE(	datasets.ArrowBasedBuilder	):
							_UpperCAmelCase     =       CsvConfig
							def lowerCAmelCase_ (     self:      str						)		->		int:
											return datasets.DatasetInfo(features=self.config.features						)
							def lowerCAmelCase_ (     self:      Tuple       ,	UpperCamelCase:      Dict						)		->		int:
											if not self.config.data_files:
															raise ValueError(F'''At least one data file must be specified, but got data_files={self.config.data_files}'''						)
											snake_case__									=     dl_manager.download_and_extract(self.config.data_files						)
											if isinstance(UpperCamelCase       ,	(str, list, tuple)						):
															snake_case__									=     data_files
															if isinstance(UpperCamelCase       ,	UpperCamelCase						):
																			snake_case__									=     [files]
															snake_case__									=     [dl_manager.iter_files(UpperCamelCase						) for file in files]
															return [datasets.SplitGenerator(name=datasets.Split.TRAIN       ,	gen_kwargs={'files': files}						)]
											snake_case__									=     []
											for split_name, files in data_files.items():
															if isinstance(UpperCamelCase       ,	UpperCamelCase						):
																			snake_case__									=     [files]
															snake_case__									=     [dl_manager.iter_files(UpperCamelCase						) for file in files]
															splits.append(datasets.SplitGenerator(name=UpperCamelCase       ,	gen_kwargs={'files': files}						)						)
											return splits
							def lowerCAmelCase_ (     self:      int       ,	UpperCamelCase:      pa.Table						)		->		pa.Table:
											if self.config.features is not None:
															snake_case__									=     self.config.features.arrow_schema
															if all(not require_storage_cast(UpperCamelCase						) for feature in self.config.features.values()						):
																			# cheaper cast
																			snake_case__									=     pa.Table.from_arrays([pa_table[field.name] for field in schema]       ,	schema=UpperCamelCase						)
															else:
																			# more expensive cast; allows str <-> int/float or str to Audio for example
																			snake_case__									=     table_cast(UpperCamelCase       ,	UpperCamelCase						)
											return pa_table


							def lowerCAmelCase_ (     self:      str       ,	UpperCamelCase:      Tuple						)		->		Tuple:
											snake_case__									=     self.config.features.arrow_schema if self.config.features else None
											# dtype allows reading an int column as str
											snake_case__									=     (
											    {
											        name: dtype.to_pandas_dtype() if not require_storage_cast(UpperCamelCase						) else object
											        for name, dtype, feature in zip(schema.names       ,	schema.types       ,	self.config.features.values()						)
											    }
											    if schema is not None
											    else None
											)
											for file_idx, file in enumerate(itertools.chain.from_iterable(UpperCamelCase						)						):
															snake_case__									=     pd.read_csv(UpperCamelCase       ,	iterator=UpperCamelCase       ,	dtype=UpperCamelCase       ,	**self.config.pd_read_csv_kwargs						)
															try:
																			for batch_idx, df in enumerate(UpperCamelCase						):
																							snake_case__									=     pa.Table.from_pandas(UpperCamelCase						)
																							# Uncomment for debugging (will print the Arrow table size and elements)
																							# logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
																							# logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
																							yield (file_idx, batch_idx), self._cast_table(UpperCamelCase						)
															except ValueError as e:
																			logger.error(F'''Failed to read file \'{file}\' with error {type(UpperCamelCase						)}: {e}'''						)
																			raise




