from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


_lowercase							:      Optional[Any]      							=logging.get_logger(__name__)


_lowercase							:      Union[str, Any]      							=TypeVar('''DatasetType''', Dataset, IterableDataset)



def A__  (			lowercase:     Tuple,		lowercase:     Dict = None,		lowercase:     str = None,		lowercase:     Optional[int] = None,		lowercase:     int = None,		lowercase:     List[str] = "first_exhausted",		)				->		Optional[int]:
       from .arrow_dataset import Dataset
       from .iterable_dataset import IterableDataset

       if not datasets:
              raise ValueError('Unable to interleave an empty list of datasets.'					)
       for i, dataset in enumerate(lowercase					):
              if not isinstance(lowercase,		(Dataset, IterableDataset)					):
                     if isinstance(lowercase,		(DatasetDict, IterableDatasetDict)					):
                            if not dataset:
                                   raise ValueError(
                                       F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
                                       'is an empty dataset dictionary.'					)
                            raise ValueError(
                                F'Dataset at position {i} has at least one split: {list(lowercase					)}\n'
                                F'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(lowercase					)					)}\']'					)
                     raise ValueError(
                         F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(lowercase					).__name__}.'					)
              if i == 0:
                     A  ,  A						:     List[str]         =(
                         (Dataset, IterableDataset) if isinstance(lowercase,		lowercase					) else (IterableDataset, Dataset)
                     )
              elif not isinstance(lowercase,		lowercase					):
                     raise ValueError(
                         F'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'					)
       if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
              raise ValueError(F'{stopping_strategy} is not supported. Please enter a valid stopping_strategy.'					)
       if dataset_type is Dataset:
              return _interleave_map_style_datasets(
                  lowercase,		lowercase,		lowercase,		info=lowercase,		split=lowercase,		stopping_strategy=lowercase					)
       else:
              return _interleave_iterable_datasets(
                  lowercase,		lowercase,		lowercase,		info=lowercase,		split=lowercase,		stopping_strategy=lowercase					)



def A__  (			lowercase:     Tuple,		lowercase:     Union[str, Any] = None,		lowercase:     Tuple = None,		lowercase:     Any = 0,		)				->		Union[str, Any]:







       if not dsets:
              raise ValueError('Unable to concatenate an empty list of datasets.'					)
       for i, dataset in enumerate(lowercase					):
              if not isinstance(lowercase,		(Dataset, IterableDataset)					):
                     if isinstance(lowercase,		(DatasetDict, IterableDatasetDict)					):
                            if not dataset:
                                   raise ValueError(
                                       F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} '
                                       'is an empty dataset dictionary.'					)
                            raise ValueError(
                                F'Dataset at position {i} has at least one split: {list(lowercase					)}\n'
                                F'Please pick one to interleave with the other datasets, for example: dataset[\'{next(iter(lowercase					)					)}\']'					)
                     raise ValueError(
                         F'Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(lowercase					).__name__}.'					)
              if i == 0:
                     A  ,  A						:     str         =(
                         (Dataset, IterableDataset) if isinstance(lowercase,		lowercase					) else (IterableDataset, Dataset)
                     )
              elif not isinstance(lowercase,		lowercase					):
                     raise ValueError(
                         F'Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects.'					)
       if dataset_type is Dataset:
              return _concatenate_map_style_datasets(lowercase,		info=lowercase,		split=lowercase,		axis=lowercase					)
       else:
              return _concatenate_iterable_datasets(lowercase,		info=lowercase,		split=lowercase,		axis=lowercase					)







# Copyright 2021 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

from accelerate.utils import ComputeEnvironment

from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file  # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environment  # noqa: F401
from .sagemaker import get_sagemaker_input


_lowercase							:      List[str]      							='''Launches a series of prompts to create and save a `default_config.yaml` configuration file for your training system. Should always be ran first on your machine'''



def A__  (			)				->		List[Any]:
       A						:     Any         =_ask_options(
           'In which compute environment are you running?',		['This machine', 'AWS (Amazon SageMaker)'],		_convert_compute_environment,		)
       if compute_environment == ComputeEnvironment.AMAZON_SAGEMAKER:
              A						:     Tuple         =get_sagemaker_input()
       else:
              A						:     str         =get_cluster_input()
       return config



def A__  (			lowercase:     int=None					)				->		str:
       if subparsers is not None:
              A						:     List[str]         =subparsers.add_parser('config',		description=lowercase					)
       else:
              A						:     Union[str, Any]         =argparse.ArgumentParser('Accelerate config command',		description=lowercase					)

       parser.add_argument(
           '--config_file',		default=lowercase,		help=(
               'The path to use to store the config file. Will default to a file named default_config.yaml in the cache '
               'location, which is the content of the environment `HF_HOME` suffixed with \'accelerate\', or if you don\'t have '
               'such an environment variable, your cache directory (\'~/.cache\' or the content of `XDG_CACHE_HOME`) suffixed '
               'with \'huggingface\'.'
           ),		)

       if subparsers is not None:
              parser.set_defaults(func=lowercase					)
       return parser



def A__  (			lowercase:     Tuple					)				->		List[Any]:
       A						:     Union[str, Any]         =get_user_input()
       if args.config_file is not None:
              A						:     Optional[Any]         =args.config_file
       else:
              if not os.path.isdir(lowercase					):
                     os.makedirs(lowercase					)
              A						:     Union[str, Any]         =default_yaml_config_file

       if config_file.endswith('.json'					):
              config.to_json_file(lowercase					)
       else:
              config.to_yaml_file(lowercase					)
       print(F'accelerate configuration saved at {config_file}'					)



def A__  (			)				->		Optional[int]:
       A						:     Any         =config_command_parser()
       A						:     int         =parser.parse_args()
       config_command(lowercase					)


if __name__ == "__main__":
    main()






