'''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


__SCREAMING_SNAKE_CASE       :     Optional[Any]     =  """Run commands across TPU VMs for initial setup before running `accelerate launch`."""

def 	UpperCamelCase_							(					_UpperCAmelCase  :      Union[str, Any]=None    )    ->    Tuple:


       """simple docstring"""







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

def 	UpperCamelCase_							(					_UpperCAmelCase  :      int    )    ->    str:


       """simple docstring"""







       _UpperCAmelCase     :  Union[str, Any]							      =    None

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

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

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


def 	UpperCamelCase_							(					)    ->    Any:


       """simple docstring"""







       _UpperCAmelCase     :  Any							      =    tpu_command_parser()
       _UpperCAmelCase     :  Tuple							      =    parser.parse_args()

       tpu_command_launcher(_UpperCAmelCase    )








import unittest

from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


UpperCAmelCase						:   List[str]			  =     '''▁'''

UpperCAmelCase						:   Optional[Any]			  =     get_tests_dir('''fixtures/test_sentencepiece.model''')





@require_sentencepiece
class 						_A(					snake_case__				, unittest.TestCase   ):


				"""simple docstring"""


				UpperCamelCase    :  Optional[int]					    =	BertGenerationTokenizer
				UpperCamelCase    :  str					    =	False
				UpperCamelCase    :  Tuple					    =	True



				def 					UpperCAmelCase_		(			self     ):
									super().setUp()

									__A	:						Tuple       =				BertGenerationTokenizer(_A     ,					keep_accents=_A     )
									tokenizer.save_pretrained(self.tmpdirname     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				'<s>'
									__A	:						str       =				1

									self.assertEqual(self.get_tokenizer()._convert_token_to_id(_A     )     ,					_A     )
									self.assertEqual(self.get_tokenizer()._convert_id_to_token(_A     )     ,					_A     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						int       =				list(self.get_tokenizer().get_vocab().keys()     )

									self.assertEqual(vocab_keys[0]     ,					'<unk>'     )
									self.assertEqual(vocab_keys[1]     ,					'<s>'     )
									self.assertEqual(vocab_keys[-1]     ,					'<pad>'     )
									self.assertEqual(len(_A     )     ,					1002     )



				def 					UpperCAmelCase_		(			self     ):
									self.assertEqual(self.get_tokenizer().vocab_size     ,					1000     )



				def 					UpperCAmelCase_		(			self     ):
									__A	:						str       =				BertGenerationTokenizer(_A     ,					keep_accents=_A     )

									__A	:						Dict       =				tokenizer.tokenize('This is a test'     )
									self.assertListEqual(_A     ,					['▁This', '▁is', '▁a', '▁t', 'est']     )

									self.assertListEqual(
									    tokenizer.convert_tokens_to_ids(_A     )     ,					[285, 46, 10, 170, 382]     ,					)

									__A	:						int       =				tokenizer.tokenize('I was born in 92000, and this is falsé.'     )
									self.assertListEqual(
									    _A     ,					[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '9',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        'é',
									        '.',
									    ]     ,					)
									__A	:						Dict       =				tokenizer.convert_tokens_to_ids(_A     )
									self.assertListEqual(
									    _A     ,					[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]     ,					)

									__A	:						Optional[int]       =				tokenizer.convert_ids_to_tokens(_A     )
									self.assertListEqual(
									    _A     ,					[
									        SPIECE_UNDERLINE + 'I',
									        SPIECE_UNDERLINE + 'was',
									        SPIECE_UNDERLINE + 'b',
									        'or',
									        'n',
									        SPIECE_UNDERLINE + 'in',
									        SPIECE_UNDERLINE + '',
									        '<unk>',
									        '2',
									        '0',
									        '0',
									        '0',
									        ',',
									        SPIECE_UNDERLINE + 'and',
									        SPIECE_UNDERLINE + 'this',
									        SPIECE_UNDERLINE + 'is',
									        SPIECE_UNDERLINE + 'f',
									        'al',
									        's',
									        '<unk>',
									        '.',
									    ]     ,					)



				@cached_property
				def 					UpperCAmelCase_		(			self     ):
									return BertGenerationTokenizer.from_pretrained('google/bert_for_seq_generation_L-24_bbc_encoder'     )



				@slow
				def 					UpperCAmelCase_		(			self     ):
									__A	:						List[Any]       =				'Hello World!'
									__A	:						Optional[Any]       =				[18536, 2260, 101]

									self.assertListEqual(_A     ,					self.big_tokenizer.encode(_A     )     )



				@slow
				def 					UpperCAmelCase_		(			self     ):
									__A	:						Dict       =				(
									    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
									    ' add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth'
									)
									__A	:						int       =				[
									    871,
									    419,
									    358,
									    946,
									    991,
									    2521,
									    452,
									    358,
									    1357,
									    387,
									    7751,
									    3536,
									    112,
									    985,
									    456,
									    126,
									    865,
									    938,
									    5400,
									    5734,
									    458,
									    1368,
									    467,
									    786,
									    2462,
									    5246,
									    1159,
									    633,
									    865,
									    4519,
									    457,
									    582,
									    852,
									    2557,
									    427,
									    916,
									    508,
									    405,
									    34324,
									    497,
									    391,
									    408,
									    11342,
									    1244,
									    385,
									    100,
									    938,
									    985,
									    456,
									    574,
									    362,
									    12597,
									    3200,
									    3129,
									    1172,
									]

									self.assertListEqual(_A     ,					self.big_tokenizer.encode(_A     )     )



				@require_torch
				@slow
				def 					UpperCAmelCase_		(			self     ):
									import torch

									from transformers import BertGenerationConfig, BertGenerationEncoder

									# Build sequence
									__A	:						Tuple       =				list(self.big_tokenizer.get_vocab().keys()     )[:10]
									__A	:						List[Any]       =				' '.join(_A     )
									__A	:						Union[str, Any]       =				self.big_tokenizer.encode_plus(_A     ,					return_tensors='pt'     ,					return_token_type_ids=_A     )
									__A	:						Optional[Any]       =				self.big_tokenizer.batch_encode_plus(
									    [sequence + ' ' + sequence]     ,					return_tensors='pt'     ,					return_token_type_ids=_A     )

									__A	:						int       =				BertGenerationConfig()
									__A	:						List[str]       =				BertGenerationEncoder(_A     )

									assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

									with torch.no_grad():
														model(**_A     )
														model(**_A     )





				@slow
				def 					UpperCAmelCase_		(			self     ):
									# fmt: off
									__A	:						str       =				{'input_ids': [[39286, 458, 36335, 2001, 456, 13073, 13266, 455, 113, 7746, 1741, 11157, 391, 13073, 13266, 455, 113, 3967, 35412, 113, 4936, 109, 3870, 2377, 113, 30084, 45720, 458, 134, 17496, 112, 503, 11672, 113, 118, 112, 5665, 13347, 38687, 112, 1496, 31389, 112, 3268, 47264, 134, 962, 112, 16377, 8035, 23130, 430, 12169, 15518, 28592, 458, 146, 41697, 109, 391, 12169, 15518, 16689, 458, 146, 41358, 109, 452, 726, 4034, 111, 763, 35412, 5082, 388, 1903, 111, 9051, 391, 2870, 48918, 1900, 1123, 550, 998, 112, 9586, 15985, 455, 391, 410, 22955, 37636, 114], [448, 17496, 419, 3663, 385, 763, 113, 27533, 2870, 3283, 13043, 1639, 24713, 523, 656, 24013, 18550, 2521, 517, 27014, 21244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 11786, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [484, 2169, 7687, 21932, 18146, 726, 363, 17032, 3391, 114, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
									# fmt: on

									self.tokenizer_integration_test_util(
									    expected_encoding=_A     ,					model_name='google/bert_for_seq_generation_L-24_bbc_encoder'     ,					revision='c817d1fd1be2ffa69431227a1fe320544943d4db'     ,					)




