



'''simple docstring'''





# 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


__a  			=						"Run commands across TPU VMs for initial setup before running `accelerate launch`."





def 		__snake_case(							_lowerCAmelCase=None						)						->					Tuple:
      if subparsers is not None:
            snake_case__    :       Union[str, Any]       		= subparsers.add_parser("""tpu-config"""	,  description=_description						)
      else:
            snake_case__    :       Dict       		= argparse.ArgumentParser("""Accelerate tpu-config command"""	,  description=_description						)
      # Core arguments
      snake_case__    :       List[Any]       		= parser.add_argument_group(
          """Config Arguments"""	,  """Arguments that can be configured through `accelerate config`."""						)
      config_args.add_argument(
          """--config_file"""	,  type=_lowerCAmelCase	,  default=_lowerCAmelCase	,  help="""Path to the config file to use for accelerate."""	,  )
      config_args.add_argument(
          """--tpu_name"""	,  default=_lowerCAmelCase	,  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=_lowerCAmelCase	,  help="""The zone of the TPU to use. If not specified, will use the zone specified in the config file."""	,  )
      snake_case__    :       int       		= 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=_lowerCAmelCase	,  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=_lowerCAmelCase						)
      return parser





def 		__snake_case(							_lowerCAmelCase						)						->					int:
      snake_case__    :       Dict       		= None

      # Get the default from the config file if it exists.
      if args.config_file is not None or os.path.isfile(_lowerCAmelCase						):
            snake_case__    :       Optional[Any]       		= 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__    :       Tuple       		= defaults.command_file
            if not args.command and defaults.commands is not None:
                  snake_case__    :       List[Any]       		= defaults.commands
            if not args.tpu_name:
                  snake_case__    :       Any       		= defaults.tpu_name
            if not args.tpu_zone:
                  snake_case__    :       Tuple       		= defaults.tpu_zone
      if args.accelerate_version == "dev":
            snake_case__    :       str       		= """git+https://github.com/huggingface/accelerate.git"""
      elif args.accelerate_version == "latest":
            snake_case__    :       int       		= """accelerate -U"""
      elif isinstance(parse(args.accelerate_version						)	,  _lowerCAmelCase						):
            snake_case__    :       Dict       		= 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__    :       List[str]       		= [f.read().splitlines()]

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

      # Then send it to gcloud
      # Eventually try to use google-api-core to do this instead of subprocess
      snake_case__    :       int       		= ["""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(_lowerCAmelCase						)}"						)
            return
      subprocess.run(_lowerCAmelCase						)
      print("""Successfully setup pod."""						)





def 		__snake_case(							)						->					Optional[int]:
      snake_case__    :       List[Any]       		= tpu_command_parser()
      snake_case__    :       Tuple       		= parser.parse_args()

      tpu_command_launcher(_lowerCAmelCase						)





'''simple docstring'''





import os
from tempfile import TemporaryDirectory
from unittest import TestCase

import pytest
from absl.testing import parameterized

from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict
from datasets.iterable_dataset import IterableDataset
from datasets.load import dataset_module_factory, import_main_class
from datasets.utils.file_utils import cached_path


__a  			=						[
    {"dataset": "wikipedia", "config_name": "20220301.de"},
    {"dataset": "wikipedia", "config_name": "20220301.en"},
    {"dataset": "wikipedia", "config_name": "20220301.fr"},
    {"dataset": "wikipedia", "config_name": "20220301.frr"},
    {"dataset": "wikipedia", "config_name": "20220301.it"},
    {"dataset": "wikipedia", "config_name": "20220301.simple"},
    {"dataset": "snli", "config_name": "plain_text"},
    {"dataset": "eli5", "config_name": "LFQA_reddit"},
    {"dataset": "wiki40b", "config_name": "en"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.compressed"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.nq.no_index"},
    {"dataset": "wiki_dpr", "config_name": "psgs_w100.multiset.no_index"},
    {"dataset": "natural_questions", "config_name": "default"},
]





def 		__snake_case(							_lowerCAmelCase=True						)						->					Dict:
      if with_config:
            return [
                {
                    "testcase_name": d["dataset"] + "/" + d["config_name"],
                    "dataset": d["dataset"],
                    "config_name": d["config_name"],
                }
                for d in DATASETS_ON_HF_GCP
            ]
      else:
            return [
                {"testcase_name": dataset, "dataset": dataset} for dataset in {d["dataset"] for d in DATASETS_ON_HF_GCP}
            ]







@parameterized.named_parameters(list_datasets_on_hf_gcp_parameters(with_config=_a      )      )
class        UpperCAmelCase_			(			_a      ):
    """simple docstring"""







    lowercase   =						None
    lowercase   =						None




    def lowerCamelCase			(       self   :	List[Any]					,	snake_case_   :	Union[str, Any]					,	snake_case_   :	Optional[int]		):
          with TemporaryDirectory() as tmp_dir:
                snake_case__    :       Dict       		= dataset_module_factory(snake_case_					,	cache_dir=snake_case_		)

                snake_case__    :       Optional[int]       		= import_main_class(dataset_module.module_path					,	dataset=snake_case_		)

                snake_case__    :       DatasetBuilder       		= builder_cls(
                    cache_dir=snake_case_					,	config_name=snake_case_					,	hash=dataset_module.hash					,	)

                snake_case__    :       Dict       		= """/""".join(
                    [
                        HF_GCP_BASE_URL,
                        builder_instance._relative_data_dir(with_hash=snake_case_		).replace(os.sep					,	"""/"""		),
                        config.DATASET_INFO_FILENAME,
                    ]		)
                snake_case__    :       List[str]       		= cached_path(snake_case_					,	cache_dir=snake_case_		)
                self.assertTrue(os.path.exists(snake_case_		)		)





@pytest.mark.integration
def 		__snake_case(							_lowerCAmelCase						)						->					Tuple:
      snake_case__    :       Optional[int]       		= tmp_path_factory.mktemp("""test_hf_gcp"""						) / """test_wikipedia_simple"""
      snake_case__    :       Dict       		= dataset_module_factory("""wikipedia"""	,  cache_dir=_lowerCAmelCase						)
      snake_case__    :       Dict       		= import_main_class(dataset_module.module_path						)
      snake_case__    :       DatasetBuilder       		= builder_cls(
          cache_dir=_lowerCAmelCase	,  config_name="""20220301.frr"""	,  hash=dataset_module.hash	,  )
      # use the HF cloud storage, not the original download_and_prepare that uses apache-beam
      snake_case__    :       Any       		= None
      builder_instance.download_and_prepare()
      snake_case__    :       Union[str, Any]       		= builder_instance.as_dataset()
      assert ds





@pytest.mark.integration
def 		__snake_case(							_lowerCAmelCase						)						->					List[str]:
      snake_case__    :       Optional[int]       		= dataset_module_factory("""wikipedia"""	,  cache_dir=_lowerCAmelCase						)
      snake_case__    :       List[str]       		= import_main_class(dataset_module.module_path	,  dataset=_lowerCAmelCase						)
      snake_case__    :       DatasetBuilder       		= builder_cls(
          cache_dir=_lowerCAmelCase	,  config_name="""20220301.frr"""	,  hash=dataset_module.hash	,  )
      snake_case__    :       Any       		= builder_instance.as_streaming_dataset()
      assert ds
      assert isinstance(_lowerCAmelCase	,  _lowerCAmelCase						)
      assert "train" in ds
      assert isinstance(ds["""train"""]	,  _lowerCAmelCase						)
      assert next(iter(ds["""train"""]						)						)
