"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple

from tokenizers import processors

from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
	from .tokenization_mbart import MBartTokenizer
else:
	lowercase__ 	=     None


lowercase__ 	=     logging.get_logger(__name__)


lowercase__ 	=     {'vocab_file': 'sentencepiece.bpe.model', 'tokenizer_file': 'tokenizer.json'}

lowercase__ 	=     {
    'vocab_file': {
        'facebook/mbart-large-en-ro': (
            'https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/sentencepiece.bpe.model'
        ),
        'facebook/mbart-large-cc25': (
            'https://huggingface.co/facebook/mbart-large-cc25/resolve/main/sentencepiece.bpe.model'
        ),
    },
    'tokenizer_file': {
        'facebook/mbart-large-en-ro': 'https://huggingface.co/facebook/mbart-large-en-ro/resolve/main/tokenizer.json',
        'facebook/mbart-large-cc25': 'https://huggingface.co/facebook/mbart-large-cc25/resolve/main/tokenizer.json',
    },
}

lowercase__ 	=     {
    'facebook/mbart-large-en-ro': 1024,
    'facebook/mbart-large-cc25': 1024,
}

# fmt: off
lowercase__ 	=     ['ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX', 'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP', 'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN', 'zh_CN']




class        __snake_case	(					__lowerCAmelCase    ):
						a__				=		VOCAB_FILES_NAMES
						a__				=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						a__				=		PRETRAINED_VOCAB_FILES_MAP
						a__				=		["""input_ids""", """attention_mask"""]
						a__				=		MBartTokenizer

						a__				=		[]
						a__				=		[]



						def __init__(						self   ,      lowercase=None   ,      lowercase=None   ,      lowercase="<s>"   ,      lowercase="</s>"   ,      lowercase="</s>"   ,      lowercase="<s>"   ,      lowercase="<unk>"   ,      lowercase="<pad>"   ,      lowercase="<mask>"   ,      lowercase=None   ,      lowercase=None   ,      lowercase=None   ,      **lowercase   ,      )     ->      Tuple:





								'''simple docstring'''





								a__:					List[str]      							=     AddedToken(lowercase   ,      lstrip=lowercase   ,      rstrip=lowercase) if isinstance(lowercase   ,      lowercase) else mask_token

								super().__init__(
								    vocab_file=lowercase   ,      tokenizer_file=lowercase   ,      bos_token=lowercase   ,      eos_token=lowercase   ,      sep_token=lowercase   ,      cls_token=lowercase   ,      unk_token=lowercase   ,      pad_token=lowercase   ,      mask_token=lowercase   ,      src_lang=lowercase   ,      tgt_lang=lowercase   ,      additional_special_tokens=lowercase   ,      **lowercase   ,      )

								a__:					Tuple      							=     vocab_file
								a__:					Union[str, Any]      							=     False if not self.vocab_file else True

								a__:					Union[str, Any]      							=     FAIRSEQ_LANGUAGE_CODES.copy()

								if additional_special_tokens is not None:
										# Only add those special tokens if they are not already there.
										_additional_special_tokens.extend(
										    [t for t in additional_special_tokens if t not in _additional_special_tokens])

								self.add_special_tokens({'additional_special_tokens': _additional_special_tokens})
								a__:					int      							=     {
								    lang_code: self.convert_tokens_to_ids(lowercase) for lang_code in FAIRSEQ_LANGUAGE_CODES
								}

								a__:					List[Any]      							=     src_lang if src_lang is not None else 'en_XX'
								a__:					Tuple      							=     self.convert_tokens_to_ids(self._src_lang)
								a__:					str      							=     tgt_lang
								self.set_src_lang_special_tokens(self._src_lang)



						@property
						def   lowerCamelCase_       (						self)     ->      str:





								'''simple docstring'''





								return self._src_lang



						@src_lang.setter
						def   lowerCamelCase_       (						self   ,      lowercase)     ->      None:





								'''simple docstring'''





								a__:					Tuple      							=     new_src_lang
								self.set_src_lang_special_tokens(self._src_lang)



						def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      List[int]:





								'''simple docstring'''





								if token_ids_a is None:
										return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens



						def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      List[int]:





								'''simple docstring'''





								a__:					Any      							=     [self.sep_token_id]
								a__:					List[str]      							=     [self.cls_token_id]

								if token_ids_a is None:
										return len(cls + token_ids_a + sep) * [0]
								return len(cls + token_ids_a + sep + sep + token_ids_a + sep) * [0]



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





								'''simple docstring'''





								if src_lang is None or tgt_lang is None:
										raise ValueError('Translation requires a `src_lang` and a `tgt_lang` for this model')
								a__:					Union[str, Any]      							=     src_lang
								a__:					Any      							=     self(lowercase   ,      add_special_tokens=lowercase   ,      return_tensors=lowercase   ,      **lowercase)
								a__:					str      							=     self.convert_tokens_to_ids(lowercase)
								a__:					Any      							=     tgt_lang_id
								return inputs



						def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = "en_XX"   ,      lowercase = None   ,      lowercase = "ro_RO"   ,      **lowercase   ,      )     ->      BatchEncoding:





								'''simple docstring'''





								a__:					Any      							=     src_lang
								a__:					List[Any]      							=     tgt_lang
								return super().prepare_seqaseq_batch(lowercase   ,      lowercase   ,      **lowercase)



						def   lowerCamelCase_       (						self)     ->      Dict:





								'''simple docstring'''





								return self.set_src_lang_special_tokens(self.src_lang)



						def   lowerCamelCase_       (						self)     ->      List[Any]:





								'''simple docstring'''





								return self.set_tgt_lang_special_tokens(self.tgt_lang)



						def   lowerCamelCase_       (						self   ,      lowercase)     ->      None:





								'''simple docstring'''





								a__:					int      							=     self.convert_tokens_to_ids(lowercase)
								a__:					List[Any]      							=     []
								a__:					List[str]      							=     [self.eos_token_id, self.cur_lang_code]

								a__:					Dict      							=     self.convert_ids_to_tokens(self.prefix_tokens)
								a__:					Any      							=     self.convert_ids_to_tokens(self.suffix_tokens)

								a__:					int      							=     processors.TemplateProcessing(
								    single=prefix_tokens_str + ['$A'] + suffix_tokens_str   ,      pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str   ,      special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str   ,      self.prefix_tokens + self.suffix_tokens))   ,      )



						def   lowerCamelCase_       (						self   ,      lowercase)     ->      None:





								'''simple docstring'''





								a__:					str      							=     self.convert_tokens_to_ids(lowercase)
								a__:					List[Any]      							=     []
								a__:					Dict      							=     [self.eos_token_id, self.cur_lang_code]

								a__:					Any      							=     self.convert_ids_to_tokens(self.prefix_tokens)
								a__:					Optional[Any]      							=     self.convert_ids_to_tokens(self.suffix_tokens)

								a__:					str      							=     processors.TemplateProcessing(
								    single=prefix_tokens_str + ['$A'] + suffix_tokens_str   ,      pair=prefix_tokens_str + ['$A', '$B'] + suffix_tokens_str   ,      special_tokens=list(zip(prefix_tokens_str + suffix_tokens_str   ,      self.prefix_tokens + self.suffix_tokens))   ,      )



						def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase = None)     ->      Tuple[str]:





								'''simple docstring'''





								if not self.can_save_slow_tokenizer:
										raise ValueError(
										    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
										    'tokenizer.')

								if not os.path.isdir(lowercase):
										logger.error(f'Vocabulary path ({save_directory}) should be a directory.')
										return
								a__:					Any      							=     os.path.join(
								    lowercase   ,      (filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'])

								if os.path.abspath(self.vocab_file) != os.path.abspath(lowercase):
										copyfile(self.vocab_file   ,      lowercase)

								return (out_vocab_file,)



"""simple docstring"""
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock

import torch

from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accelerate.utils import write_basic_config


# DataLoaders built from `test_samples/MRPC` for quick testing
# Should mock `{script_name}.get_dataloaders` via:
# @mock.patch("{script_name}.get_dataloaders", mocked_dataloaders)

lowercase__ 	=     [
    'cross_validation.py',
    'gradient_accumulation.py',
    'local_sgd.py',
    'multi_process_metrics.py',
    'memory.py',
    'automatic_gradient_accumulation.py',
    'fsdp_with_peak_mem_tracking.py',
    'deepspeed_with_config_support.py',
    'megatron_lm_gpt_pretraining.py',
]




class        __snake_case	(					unittest.TestCase    ):



      def   lowerCamelCase_       (						self   ,      lowercase   ,      lowercase   ,      lowercase = None   ,      lowercase = None)     ->      Union[str, Any]:





        '''simple docstring'''





        a__:					List[Any]      							=     None
        a__:					Optional[Any]      							=     os.path.abspath(os.path.join('examples'   ,      'by_feature'))
        a__:					Optional[Any]      							=     os.path.abspath('examples')
        for item in os.listdir(lowercase):
          if item not in EXCLUDE_EXAMPLES:
            a__:					Dict      							=     os.path.join(lowercase   ,      lowercase)
            if os.path.isfile(lowercase) and ".py" in item_path:
              with self.subTest(
                  tested_script=lowercase   ,      feature_script=lowercase   ,      tested_section='main()' if parser_only else 'training_function()'   ,      ):
                a__:					List[Any]      							=     compare_against_test(
                    os.path.join(lowercase   ,      lowercase)   ,      lowercase   ,      lowercase   ,      lowercase)
                a__:					Dict      							=     '\n'.join(lowercase)
                if special_strings is not None:
                  for string in special_strings:
                    a__:					Union[str, Any]      							=     diff.replace(lowercase   ,      '')
                self.assertEqual(lowercase   ,      '')



      def   lowerCamelCase_       (						self)     ->      int:





        '''simple docstring'''





        self.one_complete_example('complete_nlp_example.py'   ,      lowercase)
        self.one_complete_example('complete_nlp_example.py'   ,      lowercase)



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





        '''simple docstring'''





        a__:					Dict      							=     os.path.abspath(os.path.join('examples'   ,      'cv_example.py'))
        a__:					Tuple      							=     [
            ' ' * 16 + '{\n\n',
            ' ' * 20 + '"accuracy": eval_metric["accuracy"],\n\n',
            ' ' * 20 + '"f1": eval_metric["f1"],\n\n',
            ' ' * 20 + '"train_loss": total_loss.item() / len(train_dataloader),\n\n',
            ' ' * 20 + '"epoch": epoch,\n\n',
            ' ' * 16 + '},\n\n',
            ' ' * 16 + 'step=epoch,\n',
            ' ' * 12,
            ' ' * 8 + 'for step, batch in enumerate(active_dataloader):\n',
        ]
        self.one_complete_example('complete_cv_example.py'   ,      lowercase   ,      lowercase   ,      lowercase)
        self.one_complete_example('complete_cv_example.py'   ,      lowercase   ,      lowercase   ,      lowercase)







@mock.patch.dict(os.environ	,				{"""TESTING_MOCKED_DATALOADERS""": """1"""}    )
class        __snake_case	(					__lowerCAmelCase    ):
      a__				=		False



      @classmethod
      def   lowerCamelCase_       (						cls)     ->      List[str]:





        '''simple docstring'''





        super().setUpClass()
        a__:					Dict      							=     tempfile.mkdtemp()
        a__:					Optional[int]      							=     os.path.join(cls._tmpdir   ,      'default_config.yml')

        write_basic_config(save_location=cls.configPath)
        a__:					List[str]      							=     ['accelerate', 'launch', '--config_file', cls.configPath]



      @classmethod
      def   lowerCamelCase_       (						cls)     ->      List[str]:





        '''simple docstring'''





        super().tearDownClass()
        shutil.rmtree(cls._tmpdir)



      def   lowerCamelCase_       (						self)     ->      List[str]:





        '''simple docstring'''





        a__:					Optional[Any]      							=     f'\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps epoch\n        --output_dir {self.tmpdir}\n        '.split()
        run_command(self._launch_args + testargs)
        self.assertTrue(os.path.exists(os.path.join(self.tmpdir   ,      'epoch_0')))



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





        '''simple docstring'''





        a__:					Any      							=     f'\n        examples/by_feature/checkpointing.py\n        --checkpointing_steps 1\n        --output_dir {self.tmpdir}\n        '.split()
        a__:					Tuple      							=     run_command(self._launch_args + testargs)
        self.assertTrue(os.path.exists(os.path.join(self.tmpdir   ,      'step_2')))



      def   lowerCamelCase_       (						self)     ->      str:





        '''simple docstring'''





        a__:					Optional[Any]      							=     f'\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir   ,      "epoch_0")}\n        '.split()
        a__:					Optional[int]      							=     run_command(self._launch_args + testargs   ,      return_stdout=lowercase)
        self.assertNotIn('epoch 0:'   ,      lowercase)
        self.assertIn('epoch 1:'   ,      lowercase)



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





        '''simple docstring'''





        a__:					int      							=     f'\n        examples/by_feature/checkpointing.py\n        --resume_from_checkpoint {os.path.join(self.tmpdir   ,      "step_2")}\n        '.split()
        a__:					List[str]      							=     run_command(self._launch_args + testargs   ,      return_stdout=lowercase)
        if torch.cuda.is_available():
          a__:					Union[str, Any]      							=     torch.cuda.device_count()
        else:
          a__:					Optional[int]      							=     1
        if num_processes > 1:
          self.assertNotIn('epoch 0:'   ,      lowercase)
          self.assertIn('epoch 1:'   ,      lowercase)
        else:
          self.assertIn('epoch 0:'   ,      lowercase)
          self.assertIn('epoch 1:'   ,      lowercase)



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





        '''simple docstring'''





        a__:					Dict      							=     '\n        examples/by_feature/cross_validation.py\n        --num_folds 2\n        '.split()
        with mock.patch.dict(os.environ   ,      {'TESTING_MOCKED_DATALOADERS': '0'}):
          a__:					Union[str, Any]      							=     run_command(self._launch_args + testargs   ,      return_stdout=lowercase)
          a__:					Union[str, Any]      							=     re.findall('({.+})'   ,      lowercase)
          a__:					Dict      							=     [r for r in results if 'accuracy' in r][-1]
          a__:					Optional[Any]      							=     ast.literal_eval(lowercase)
          self.assertGreaterEqual(results['accuracy']   ,      0.75)



      def   lowerCamelCase_       (						self)     ->      Tuple:





        '''simple docstring'''





        a__:					str      							=     ['examples/by_feature/multi_process_metrics.py']
        run_command(self._launch_args + testargs)



      @require_trackers
      @mock.patch.dict(os.environ   ,      {'WANDB_MODE': 'offline'})
      def   lowerCamelCase_       (						self)     ->      Tuple:





        '''simple docstring'''





        with tempfile.TemporaryDirectory() as tmpdir:
          a__:					List[str]      							=     f'\n            examples/by_feature/tracking.py\n            --with_tracking\n            --project_dir {tmpdir}\n            '.split()
          run_command(self._launch_args + testargs)
          self.assertTrue(os.path.exists(os.path.join(lowercase   ,      'tracking')))



      def   lowerCamelCase_       (						self)     ->      Tuple:





        '''simple docstring'''





        a__:					int      							=     ['examples/by_feature/gradient_accumulation.py']
        run_command(self._launch_args + testargs)



      def   lowerCamelCase_       (						self)     ->      List[Any]:





        '''simple docstring'''





        a__:					Union[str, Any]      							=     ['examples/by_feature/local_sgd.py']
        run_command(self._launch_args + testargs)


