"""simple docstring"""
import itertools
import json
import os
import unittest

from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin




@require_tokenizers
class    __snake_case       (     lowerCamelCase__       ,      unittest.TestCase				):
      a__        =		RobertaTokenizer
      a__        =		RobertaTokenizerFast
      a__        =		True
      a__        =		{'cls_token': '<s>'}



      def   lowerCamelCase_   (						self)	->			Union[str, Any]:





        '''simple docstring'''





        super().setUp()

        # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
        a__:     List[Any]										=	[
            'l',
            'o',
            'w',
            'e',
            'r',
            's',
            't',
            'i',
            'd',
            'n',
            '\u0120',
            '\u0120l',
            '\u0120n',
            '\u0120lo',
            '\u0120low',
            'er',
            '\u0120lowest',
            '\u0120newer',
            '\u0120wider',
            '<unk>',
        ]
        a__:     Tuple										=	dict(zip(lowercase__    ,			range(len(lowercase__))))
        a__:     str										=	['#version: 0.2', '\u0120 l', '\u0120l o', '\u0120lo w', 'e r', '']
        a__:     Tuple										=	{'unk_token': '<unk>'}

        a__:     Optional[Any]										=	os.path.join(self.tmpdirname    ,			VOCAB_FILES_NAMES['vocab_file'])
        a__:     int										=	os.path.join(self.tmpdirname    ,			VOCAB_FILES_NAMES['merges_file'])
        with open(self.vocab_file    ,			'w'    ,			encoding='utf-8') as fp:
          fp.write(json.dumps(lowercase__) + '\n')
        with open(self.merges_file    ,			'w'    ,			encoding='utf-8') as fp:
          fp.write('\n'.join(lowercase__))



      def   lowerCamelCase_   (						self    ,			**lowercase)	->			Dict:





        '''simple docstring'''





        kwargs.update(self.special_tokens_map)
        return self.tokenizer_class.from_pretrained(self.tmpdirname    ,			**lowercase__)



      def   lowerCamelCase_   (						self    ,			**lowercase)	->			Tuple:





        '''simple docstring'''





        kwargs.update(self.special_tokens_map)
        return RobertaTokenizerFast.from_pretrained(self.tmpdirname    ,			**lowercase__)



      def   lowerCamelCase_   (						self    ,			lowercase)	->			Dict:





        '''simple docstring'''





        a__:     Tuple										=	'lower newer'
        a__:     str										=	'lower newer'
        return input_text, output_text



      def   lowerCamelCase_   (						self)	->			Any:





        '''simple docstring'''





        a__:     Optional[Any]										=	self.tokenizer_class(self.vocab_file    ,			self.merges_file    ,			**self.special_tokens_map)
        a__:     Optional[Any]										=	'lower newer'
        a__:     str										=	['l', 'o', 'w', 'er', '\u0120', 'n', 'e', 'w', 'er']
        a__:     Tuple										=	tokenizer.tokenize(lowercase__)  # , add_prefix_space=True)
        self.assertListEqual(lowercase__    ,			lowercase__)

        a__:     List[Any]										=	tokens + [tokenizer.unk_token]
        a__:     int										=	[0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(lowercase__)    ,			lowercase__)



      def   lowerCamelCase_   (						self)	->			Tuple:





        '''simple docstring'''





        a__:     Any										=	self.get_tokenizer()

        self.assertListEqual(tokenizer.encode('Hello world!'    ,			add_special_tokens=lowercase__)    ,			[0, 3_14_14, 2_32, 3_28, 2])
        self.assertListEqual(
            tokenizer.encode('Hello world! cécé herlolip 418'    ,			add_special_tokens=lowercase__)    ,			[0, 3_14_14, 2_32, 3_28, 7_40, 11_40, 1_26_95, 69, 4_60_78, 15_88, 2]    ,			)



      @slow
      def   lowerCamelCase_   (						self)	->			Optional[Any]:





        '''simple docstring'''





        a__:     str										=	self.tokenizer_class.from_pretrained('roberta-base')

        a__:     Optional[int]										=	tokenizer.encode('sequence builders'    ,			add_special_tokens=lowercase__)
        a__:     Tuple										=	tokenizer.encode('multi-sequence build'    ,			add_special_tokens=lowercase__)

        a__:     str										=	tokenizer.encode(
            'sequence builders'    ,			add_special_tokens=lowercase__    ,			add_prefix_space=lowercase__)
        a__:     Tuple										=	tokenizer.encode(
            'sequence builders'    ,			'multi-sequence build'    ,			add_special_tokens=lowercase__    ,			add_prefix_space=lowercase__)

        a__:     Union[str, Any]										=	tokenizer.build_inputs_with_special_tokens(lowercase__)
        a__:     str										=	tokenizer.build_inputs_with_special_tokens(lowercase__    ,			lowercase__)

        assert encoded_sentence == encoded_text_from_decode
        assert encoded_pair == encoded_pair_from_decode



      def   lowerCamelCase_   (						self)	->			Dict:





        '''simple docstring'''





        a__:     str										=	self.get_tokenizer()

        a__:     str										=	'Encode this sequence.'
        a__:     str										=	tokenizer.byte_encoder[' '.encode('utf-8')[0]]

        # Testing encoder arguments
        a__:     Optional[int]										=	tokenizer.encode(lowercase__    ,			add_special_tokens=lowercase__    ,			add_prefix_space=lowercase__)
        a__:     Any										=	tokenizer.convert_ids_to_tokens(encoded[0])[0]
        self.assertNotEqual(lowercase__    ,			lowercase__)

        a__:     Any										=	tokenizer.encode(lowercase__    ,			add_special_tokens=lowercase__    ,			add_prefix_space=lowercase__)
        a__:     Dict										=	tokenizer.convert_ids_to_tokens(encoded[0])[0]
        self.assertEqual(lowercase__    ,			lowercase__)

        tokenizer.add_special_tokens({'bos_token': '<s>'})
        a__:     Union[str, Any]										=	tokenizer.encode(lowercase__    ,			add_special_tokens=lowercase__)
        a__:     Any										=	tokenizer.convert_ids_to_tokens(encoded[1])[0]
        self.assertNotEqual(lowercase__    ,			lowercase__)

        # Testing spaces after special tokens
        a__:     int										=	'<mask>'
        tokenizer.add_special_tokens(
            {'mask_token': AddedToken(lowercase__    ,			lstrip=lowercase__    ,			rstrip=lowercase__)})  # mask token has a left space
        a__:     Optional[int]										=	tokenizer.convert_tokens_to_ids(lowercase__)

        a__:     Any										=	'Encode <mask> sequence'
        a__:     int										=	'Encode <mask>sequence'

        a__:     Optional[Any]										=	tokenizer.encode(lowercase__)
        a__:     Optional[int]										=	encoded.index(lowercase__)
        a__:     Any										=	tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
        self.assertEqual(lowercase__    ,			lowercase__)

        a__:     Dict										=	tokenizer.encode(lowercase__)
        a__:     Tuple										=	encoded.index(lowercase__)
        a__:     List[Any]										=	tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1])[0]
        self.assertNotEqual(lowercase__    ,			lowercase__)



      def   lowerCamelCase_   (						self)	->			Union[str, Any]:





        '''simple docstring'''





        pass



      def   lowerCamelCase_   (						self)	->			str:





        '''simple docstring'''





        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
            a__:     Optional[Any]										=	self.rust_tokenizer_class.from_pretrained(lowercase__    ,			**lowercase__)
            a__:     Union[str, Any]										=	self.tokenizer_class.from_pretrained(lowercase__    ,			**lowercase__)
            a__:     Union[str, Any]										=	'A, <mask> AllenNLP sentence.'
            a__:     Optional[int]										=	tokenizer_r.encode_plus(lowercase__    ,			add_special_tokens=lowercase__    ,			return_token_type_ids=lowercase__)
            a__:     Optional[int]										=	tokenizer_p.encode_plus(lowercase__    ,			add_special_tokens=lowercase__    ,			return_token_type_ids=lowercase__)

            # token_type_ids should put 0 everywhere
            self.assertEqual(sum(tokens_r['token_type_ids'])    ,			sum(tokens_p['token_type_ids']))

            # attention_mask should put 1 everywhere, so sum over length should be 1
            self.assertEqual(
                sum(tokens_r['attention_mask']) / len(tokens_r['attention_mask'])    ,			sum(tokens_p['attention_mask']) / len(tokens_p['attention_mask'])    ,			)

            a__:     Tuple										=	tokenizer_r.convert_ids_to_tokens(tokens_r['input_ids'])
            a__:     str										=	tokenizer_p.convert_ids_to_tokens(tokens_p['input_ids'])

            # Rust correctly handles the space before the mask while python doesnt
            self.assertSequenceEqual(tokens_p['input_ids']    ,			[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2])
            self.assertSequenceEqual(tokens_r['input_ids']    ,			[0, 2_50, 6, 5_02_64, 38_23, 4_87, 2_19_92, 36_45, 4, 2])

            self.assertSequenceEqual(
                lowercase__    ,			['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])
            self.assertSequenceEqual(
                lowercase__    ,			['<s>', 'A', ',', '<mask>', 'ĠAllen', 'N', 'LP', 'Ġsentence', '.', '</s>'])



      def   lowerCamelCase_   (						self)	->			Optional[int]:





        '''simple docstring'''





        for trim_offsets, add_prefix_space in itertools.product([True, False]    ,			repeat=2):
          a__:     List[Any]										=	self.rust_tokenizer_class.from_pretrained(
              self.tmpdirname    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)

          a__:     List[Any]										=	json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__())
          a__:     Optional[int]										=	json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__())

          self.assertEqual(pre_tokenizer_state['add_prefix_space']    ,			lowercase__)

          self.assertEqual(post_processor_state['add_prefix_space']    ,			lowercase__)
          self.assertEqual(post_processor_state['trim_offsets']    ,			lowercase__)



      def   lowerCamelCase_   (						self)	->			Dict:





        '''simple docstring'''





        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
          with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'):
            a__:     Tuple										=	'hello'  # `hello` is a token in the vocabulary of `pretrained_name`
            a__:     Optional[int]										=	f'{text_of_1_token} {text_of_1_token}'

            a__:     int										=	self.rust_tokenizer_class.from_pretrained(
                lowercase__    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)
            a__:     Optional[int]										=	tokenizer_r(lowercase__    ,			return_offsets_mapping=lowercase__    ,			add_special_tokens=lowercase__)
            self.assertEqual(encoding.offset_mapping[0]    ,			(0, len(lowercase__)))
            self.assertEqual(
                encoding.offset_mapping[1]    ,			(len(lowercase__) + 1, len(lowercase__) + 1 + len(lowercase__))    ,			)

            a__:     int										=	self.rust_tokenizer_class.from_pretrained(
                lowercase__    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)
            a__:     List[Any]										=	tokenizer_r(lowercase__    ,			return_offsets_mapping=lowercase__    ,			add_special_tokens=lowercase__)
            self.assertEqual(encoding.offset_mapping[0]    ,			(0, len(lowercase__)))
            self.assertEqual(
                encoding.offset_mapping[1]    ,			(len(lowercase__) + 1, len(lowercase__) + 1 + len(lowercase__))    ,			)

            a__:     Dict										=	self.rust_tokenizer_class.from_pretrained(
                lowercase__    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)
            a__:     Dict										=	tokenizer_r(lowercase__    ,			return_offsets_mapping=lowercase__    ,			add_special_tokens=lowercase__)
            self.assertEqual(encoding.offset_mapping[0]    ,			(0, len(lowercase__)))
            self.assertEqual(
                encoding.offset_mapping[1]    ,			(len(lowercase__), len(lowercase__) + 1 + len(lowercase__))    ,			)

            a__:     Optional[Any]										=	self.rust_tokenizer_class.from_pretrained(
                lowercase__    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)
            a__:     Optional[int]										=	tokenizer_r(lowercase__    ,			return_offsets_mapping=lowercase__    ,			add_special_tokens=lowercase__)
            self.assertEqual(encoding.offset_mapping[0]    ,			(0, len(lowercase__)))
            self.assertEqual(
                encoding.offset_mapping[1]    ,			(len(lowercase__), len(lowercase__) + 1 + len(lowercase__))    ,			)

            a__:     Union[str, Any]										=	f' {text}'

            # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
            #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
            # )
            # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
            # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
            # self.assertEqual(
            #     encoding.offset_mapping[1],
            #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
            # )

            a__:     Dict										=	self.rust_tokenizer_class.from_pretrained(
                lowercase__    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)
            a__:     Union[str, Any]										=	tokenizer_r(lowercase__    ,			return_offsets_mapping=lowercase__    ,			add_special_tokens=lowercase__)
            self.assertEqual(encoding.offset_mapping[0]    ,			(1, 1 + len(lowercase__)))
            self.assertEqual(
                encoding.offset_mapping[1]    ,			(1 + len(lowercase__) + 1, 1 + len(lowercase__) + 1 + len(lowercase__))    ,			)

            a__:     Tuple										=	self.rust_tokenizer_class.from_pretrained(
                lowercase__    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)
            a__:     Dict										=	tokenizer_r(lowercase__    ,			return_offsets_mapping=lowercase__    ,			add_special_tokens=lowercase__)
            self.assertEqual(encoding.offset_mapping[0]    ,			(0, 1 + len(lowercase__)))
            self.assertEqual(
                encoding.offset_mapping[1]    ,			(1 + len(lowercase__), 1 + len(lowercase__) + 1 + len(lowercase__))    ,			)

            a__:     Any										=	self.rust_tokenizer_class.from_pretrained(
                lowercase__    ,			use_fast=lowercase__    ,			add_prefix_space=lowercase__    ,			trim_offsets=lowercase__)
            a__:     str										=	tokenizer_r(lowercase__    ,			return_offsets_mapping=lowercase__    ,			add_special_tokens=lowercase__)
            self.assertEqual(encoding.offset_mapping[0]    ,			(0, 1 + len(lowercase__)))
            self.assertEqual(
                encoding.offset_mapping[1]    ,			(1 + len(lowercase__), 1 + len(lowercase__) + 1 + len(lowercase__))    ,			)





'''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


lowerCAmelCase__											=	'''Run commands across TPU VMs for initial setup before running `accelerate launch`.'''


def 		_A     (    A__=None      ):






 """simple docstring"""



 if subparsers is not None:
  __lowercase							  = subparsers.add_parser('''tpu-config'''     ,				description=_description      )
 else:
  __lowercase							  = argparse.ArgumentParser('''Accelerate tpu-config command'''     ,				description=_description      )
 # Core arguments
 __lowercase							  = 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.'''     ,				)
 __lowercase							  = 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__      ):






 """simple docstring"""



 __lowercase							  = None

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

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

 # Then send it to gcloud
 # Eventually try to use google-api-core to do this instead of subprocess
 __lowercase							  = ['''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     (    ):






 """simple docstring"""



 __lowercase							  = tpu_command_parser()
 __lowercase							  = parser.parse_args()

 tpu_command_launcher(A__      )

