import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


_lowercase							:      str      							=get_tests_dir('''fixtures/test_sentencepiece.model''')


if is_torch_available():
      from transformers.models.plbart.modeling_plbart import shift_tokens_right

_lowercase							:      List[Any]      							=5_0_0_0_3
_lowercase							:      Union[str, Any]      							=5_0_0_0_2



@require_sentencepiece
@require_tokenizers
class  SCREAMING_SNAKE_CASE_ (					a__   ,						unittest.TestCase			):
  '''simple docstring'''


  lowercase		:     List[Any]            =				PLBartTokenizer
  lowercase		:     List[Any]            =				None
  lowercase		:     Union[str, Any]            =				False







  def 		SCREAMING_SNAKE_CASE_		(				self    :					int     )    ->				Union[str, Any]:
         super().setUp()

         # We have a SentencePiece fixture for testing
         A						:     List[str]         =PLBartTokenizer(lowerCAmelCase__      ,	language_codes='base'      ,	keep_accents=lowerCAmelCase__     )
         tokenizer.save_pretrained(self.tmpdirname     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				Dict:
         A						:     Optional[int]         =PLBartTokenizer(lowerCAmelCase__      ,	language_codes='base'      ,	keep_accents=lowerCAmelCase__     )

         A						:     Optional[int]         =tokenizer.tokenize('This is a test'     )
         self.assertListEqual(lowerCAmelCase__      ,	['▁This', '▁is', '▁a', '▁t', 'est']     )

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(lowerCAmelCase__     )      ,	[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]      ,	)

         A						:     List[Any]         =tokenizer.tokenize('I was born in 92000, and this is falsé.'     )
         self.assertListEqual(
             lowerCAmelCase__      ,	[
                 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						:     Union[str, Any]         =tokenizer.convert_tokens_to_ids(lowerCAmelCase__     )
         self.assertListEqual(
             lowerCAmelCase__      ,	[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]      ,	)

         A						:     Tuple         =tokenizer.convert_ids_to_tokens(lowerCAmelCase__     )
         self.assertListEqual(
             lowerCAmelCase__      ,	[
                 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>',
                 '.',
             ]      ,	)

         A						:     Optional[int]         =tokenizer.vocab_size
         A						:     Any         =[tokenizer.convert_ids_to_tokens(lowerCAmelCase__     ) for x in range(end - 4      ,	lowerCAmelCase__     )]

         self.assertListEqual(lowerCAmelCase__      ,	['__java__', '__python__', '__en_XX__', '<mask>']     )

         A						:     Any         ="java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
         A						:     Optional[int]         =tokenizer(lowerCAmelCase__     ).input_ids
         self.assertEqual(
             tokenizer.decode(lowerCAmelCase__      ,	skip_special_tokens=lowerCAmelCase__      ,	clean_up_tokenization_spaces=lowerCAmelCase__     )      ,	lowerCAmelCase__      ,	)







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple     )    ->				Tuple:
         A						:     Any         =PLBartTokenizer(lowerCAmelCase__      ,	language_codes='multi'      ,	keep_accents=lowerCAmelCase__     )

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

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(lowerCAmelCase__     )      ,	[value + tokenizer.fairseq_offset for value in [2_85, 46, 10, 1_70, 3_82]]      ,	)

         A						:     int         =tokenizer.tokenize('I was born in 92000, and this is falsé.'     )
         self.assertListEqual(
             lowerCAmelCase__      ,	[
                 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						:     str         =tokenizer.convert_tokens_to_ids(lowerCAmelCase__     )
         self.assertListEqual(
             lowerCAmelCase__      ,	[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 6_02, 3_47, 3_47, 3_47, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]      ,	)

         A						:     Union[str, Any]         =tokenizer.convert_ids_to_tokens(lowerCAmelCase__     )
         self.assertListEqual(
             lowerCAmelCase__      ,	[
                 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>',
                 '.',
             ]      ,	)
         A						:     Dict         =tokenizer.vocab_size
         A						:     List[Any]         =[tokenizer.convert_ids_to_tokens(lowerCAmelCase__     ) for x in range(end - 7      ,	lowerCAmelCase__     )]

         self.assertListEqual(
             lowerCAmelCase__      ,	['__java__', '__python__', '__en_XX__', '__javascript__', '__php__', '__ruby__', '__go__']     )
         A						:     List[str]         ="java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
         A						:     int         =tokenizer(lowerCAmelCase__     ).input_ids
         self.assertEqual(
             tokenizer.decode(lowerCAmelCase__      ,	skip_special_tokens=lowerCAmelCase__      ,	clean_up_tokenization_spaces=lowerCAmelCase__     )      ,	lowerCAmelCase__      ,	)







@require_torch
@require_sentencepiece
@require_tokenizers
class  SCREAMING_SNAKE_CASE_ (					unittest.TestCase			):
  '''simple docstring'''


  lowercase		:     int            =				"""uclanlp/plbart-python-en_XX"""
  lowercase		:     Tuple            =				[
      """def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])""",
      """def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""",
  ]
  lowercase		:     List[Any]            =				[
      """Returns the maximum value of a b c.""",
      """Sums the values of a b c.""",
  ]
  lowercase		:     List[Any]            =				[
      134,
      5452,
      33460,
      33441,
      33463,
      33465,
      33463,
      33449,
      988,
      20,
      33456,
      19,
      33456,
      771,
      39,
      4258,
      889,
      3318,
      33441,
      33463,
      33465,
      33463,
      33449,
      2471,
      2,
      PYTHON_CODE,
  ]







  @classmethod
  def 		SCREAMING_SNAKE_CASE_		(				cls    :					List[Any]     )    ->				List[Any]:
         A						:     PLBartTokenizer         =PLBartTokenizer.from_pretrained(
             cls.checkpoint_name      ,	language_codes='base'      ,	src_lang='python'      ,	tgt_lang='en_XX'     )
         A						:     Optional[Any]         =1
         return cls







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				List[str]:
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__java__']      ,	5_00_01     )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__python__']      ,	5_00_02     )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids['__en_XX__']      ,	5_00_03     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[Any]     )    ->				int:
         A						:     List[str]         =self.tokenizer.batch_encode_plus(self.src_text     ).input_ids[0]
         self.assertListEqual(self.expected_src_tokens      ,	lowerCAmelCase__     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict     )    ->				int:
         self.assertIn(lowerCAmelCase__      ,	self.tokenizer.all_special_ids     )
         A						:     List[str]         =[EN_CODE, 90_37, 3_34_42, 57, 7_52, 1_53, 14, 56, 18, 9, 2]
         A						:     List[Any]         =self.tokenizer.decode(lowerCAmelCase__      ,	skip_special_tokens=lowerCAmelCase__     )
         A						:     Dict         =self.tokenizer.decode(generated_ids[1:]      ,	skip_special_tokens=lowerCAmelCase__     )
         self.assertEqual(lowerCAmelCase__      ,	lowerCAmelCase__     )
         self.assertNotIn(self.tokenizer.eos_token      ,	lowerCAmelCase__     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Dict     )    ->				List[Any]:
         A						:     Union[str, Any]         =["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
         self.assertIsInstance(src_text[0]      ,	lowerCAmelCase__     )
         A						:     Optional[Any]         =10
         A						:     Tuple         =self.tokenizer(lowerCAmelCase__      ,	max_length=lowerCAmelCase__      ,	truncation=lowerCAmelCase__     ).input_ids[0]
         self.assertEqual(ids[-2]      ,	2     )
         self.assertEqual(ids[-1]      ,	lowerCAmelCase__     )
         self.assertEqual(len(lowerCAmelCase__     )      ,	lowerCAmelCase__     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				Tuple:
         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(['<mask>', '__java__']     )      ,	[5_00_04, 5_00_01]     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					List[str]     )    ->				Tuple:
         A						:     str         =tempfile.mkdtemp()
         A						:     int         =self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(lowerCAmelCase__     )
         A						:     List[str]         =PLBartTokenizer.from_pretrained(lowerCAmelCase__     )
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids      ,	lowerCAmelCase__     )







  @require_torch
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Tuple     )    ->				Optional[int]:
         A						:     List[Any]         =self.tokenizer(self.src_text      ,	text_target=self.tgt_text      ,	padding=lowerCAmelCase__      ,	return_tensors='pt'     )
         A						:     str         =shift_tokens_right(batch['labels']      ,	self.tokenizer.pad_token_id     )

         # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
         self.assertEqual(batch.input_ids[1][-2:].tolist()      ,	[2, PYTHON_CODE]     )
         self.assertEqual(batch.decoder_input_ids[1][0]      ,	lowerCAmelCase__     )
         self.assertEqual(batch.decoder_input_ids[1][-1]      ,	2     )
         self.assertEqual(batch.labels[1][-2:].tolist()      ,	[2, EN_CODE]     )







  @require_torch
  def 		SCREAMING_SNAKE_CASE_		(				self    :					int     )    ->				Dict:
         A						:     Optional[int]         =self.tokenizer(
             self.src_text      ,	text_target=self.tgt_text      ,	padding=lowerCAmelCase__      ,	truncation=lowerCAmelCase__      ,	max_length=len(self.expected_src_tokens     )      ,	return_tensors='pt'      ,	)
         A						:     Optional[int]         =shift_tokens_right(batch['labels']      ,	self.tokenizer.pad_token_id     )

         self.assertIsInstance(lowerCAmelCase__      ,	lowerCAmelCase__     )

         self.assertEqual((2, 26)      ,	batch.input_ids.shape     )
         self.assertEqual((2, 26)      ,	batch.attention_mask.shape     )
         A						:     Union[str, Any]         =batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens      ,	lowerCAmelCase__     )
         self.assertEqual(2      ,	batch.decoder_input_ids[0, -1]     )  # EOS
         # Test that special tokens are reset
         self.assertEqual(self.tokenizer.prefix_tokens      ,	[]     )
         self.assertEqual(self.tokenizer.suffix_tokens      ,	[self.tokenizer.eos_token_id, PYTHON_CODE]     )







  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				Any:
         A						:     Optional[Any]         =self.tokenizer(self.src_text      ,	padding=lowerCAmelCase__      ,	truncation=lowerCAmelCase__      ,	max_length=3      ,	return_tensors='pt'     )
         A						:     List[str]         =self.tokenizer(
             text_target=self.tgt_text      ,	padding=lowerCAmelCase__      ,	truncation=lowerCAmelCase__      ,	max_length=10      ,	return_tensors='pt'     )
         A						:     List[Any]         =targets["input_ids"]
         A						:     Tuple         =shift_tokens_right(lowerCAmelCase__      ,	self.tokenizer.pad_token_id     )

         self.assertEqual(batch.input_ids.shape[1]      ,	3     )
         self.assertEqual(batch.decoder_input_ids.shape[1]      ,	10     )







  @require_torch
  def 		SCREAMING_SNAKE_CASE_		(				self    :					Union[str, Any]     )    ->				List[Any]:
         A						:     List[Any]         =self.tokenizer._build_translation_inputs(
             'A test'      ,	return_tensors='pt'      ,	src_lang='en_XX'      ,	tgt_lang='java'     )

         self.assertEqual(
             nested_simplify(lowerCAmelCase__     )      ,	{
                 # A, test, EOS, en_XX
                 'input_ids': [[1_50, 2_42, 2, 5_00_03]],
                 'attention_mask': [[1, 1, 1, 1]],
                 # java
                 'forced_bos_token_id': 5_00_01,
             }      ,	)







# 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()






