





'''simple docstring'''

import json
import os
import unittest

from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class lowerCamelCase						(a__						,      unittest.TestCase					):
  _lowercase  :	int       					=				LEDTokenizer
  _lowercase  :	List[Any]       					=				LEDTokenizerFast
  _lowercase  :	Dict       					=				True







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






        """simple docstring"""





        super().setUp()
        _snake_case		:	Dict					     =     [
            '''l''',
            '''o''',
            '''w''',
            '''e''',
            '''r''',
            '''s''',
            '''t''',
            '''i''',
            '''d''',
            '''n''',
            '''\u0120''',
            '''\u0120l''',
            '''\u0120n''',
            '''\u0120lo''',
            '''\u0120low''',
            '''er''',
            '''\u0120lowest''',
            '''\u0120newer''',
            '''\u0120wider''',
            '''<unk>''',
        ]
        _snake_case		:	str					     =     dict(zip(lowercase__     ,     range(len(lowercase__		)		)		)		)
        _snake_case		:	int					     =     ['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
        _snake_case		:	List[Any]					     =     {'''unk_token''': '''<unk>'''}

        _snake_case		:	List[str]					     =     os.path.join(self.tmpdirname     ,     VOCAB_FILES_NAMES['''vocab_file''']		)
        _snake_case		:	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 				UpperCAmelCase_				(		self     ,     **lowercase__		)		->						str:






        """simple docstring"""





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







  def 				UpperCAmelCase_				(		self     ,     **lowercase__		)		->						List[Any]:






        """simple docstring"""





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







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






        """simple docstring"""





        return "lower newer", "lower newer"







  @cached_property
  def 				UpperCAmelCase_				(		self		)		->						Optional[Any]:






        """simple docstring"""





        return LEDTokenizer.from_pretrained('''allenai/led-base-16384'''		)







  @cached_property
  def 				UpperCAmelCase_				(		self		)		->						List[str]:






        """simple docstring"""





        return LEDTokenizerFast.from_pretrained('''allenai/led-base-16384'''		)







  @require_torch
  def 				UpperCAmelCase_				(		self		)		->						List[Any]:






        """simple docstring"""





        _snake_case		:	Any					     =     ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        _snake_case		:	Optional[Any]					     =     [0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
              _snake_case		:	Any					     =     tokenizer(lowercase__     ,     max_length=len(lowercase__		)     ,     padding=lowercase__     ,     return_tensors='''pt'''		)
              self.assertIsInstance(lowercase__     ,     lowercase__		)

              self.assertEqual((2, 9)     ,     batch.input_ids.shape		)
              self.assertEqual((2, 9)     ,     batch.attention_mask.shape		)
              _snake_case		:	Union[str, Any]					     =     batch.input_ids.tolist()[0]
              self.assertListEqual(lowercase__     ,     lowercase__		)







  @require_torch
  def 				UpperCAmelCase_				(		self		)		->						Dict:






        """simple docstring"""





        _snake_case		:	Tuple					     =     ['''A long paragraph for summarization.''', '''Another paragraph for summarization.''']
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
              _snake_case		:	Dict					     =     tokenizer(lowercase__     ,     padding=lowercase__     ,     return_tensors='''pt'''		)
              self.assertIn('''input_ids'''     ,     lowercase__		)
              self.assertIn('''attention_mask'''     ,     lowercase__		)
              self.assertNotIn('''labels'''     ,     lowercase__		)
              self.assertNotIn('''decoder_attention_mask'''     ,     lowercase__		)







  @require_torch
  def 				UpperCAmelCase_				(		self		)		->						int:






        """simple docstring"""





        _snake_case		:	Optional[Any]					     =     [
            '''Summary of the text.''',
            '''Another summary.''',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
              _snake_case		:	Union[str, Any]					     =     tokenizer(text_target=lowercase__     ,     max_length=32     ,     padding='''max_length'''     ,     return_tensors='''pt'''		)
              self.assertEqual(32     ,     targets['''input_ids'''].shape[1]		)







  @require_torch
  def 				UpperCAmelCase_				(		self		)		->						int:






        """simple docstring"""





        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
              _snake_case		:	Optional[Any]					     =     tokenizer(
                  ['''I am a small frog''' * 1_024, '''I am a small frog''']     ,     padding=lowercase__     ,     truncation=lowercase__     ,     return_tensors='''pt'''		)
              self.assertIsInstance(lowercase__     ,     lowercase__		)
              self.assertEqual(batch.input_ids.shape     ,     (2, 5_122)		)







  @require_torch
  def 				UpperCAmelCase_				(		self		)		->						Tuple:






        """simple docstring"""





        _snake_case		:	str					     =     ['''A long paragraph for summarization.''']
        _snake_case		:	int					     =     [
            '''Summary of the text.''',
        ]
        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
              _snake_case		:	Optional[Any]					     =     tokenizer(lowercase__     ,     return_tensors='''pt'''		)
              _snake_case		:	Union[str, Any]					     =     tokenizer(text_target=lowercase__     ,     return_tensors='''pt'''		)
              _snake_case		:	Tuple					     =     inputs['''input_ids''']
              _snake_case		:	List[str]					     =     targets['''input_ids''']
              self.assertTrue((input_ids[:, 0] == tokenizer.bos_token_id).all().item()		)
              self.assertTrue((labels[:, 0] == tokenizer.bos_token_id).all().item()		)
              self.assertTrue((input_ids[:, -1] == tokenizer.eos_token_id).all().item()		)
              self.assertTrue((labels[:, -1] == tokenizer.eos_token_id).all().item()		)







  @require_torch
  def 				UpperCAmelCase_				(		self		)		->						Union[str, Any]:






        """simple docstring"""





        for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
              _snake_case		:	Union[str, Any]					     =     ['''Summary of the text.''', '''Another summary.''']
              _snake_case		:	int					     =     [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

              _snake_case		:	str					     =     tokenizer(lowercase__     ,     padding=lowercase__		)
              _snake_case		:	str					     =     [[0] * len(lowercase__		) for x in encoded_output['''input_ids''']]
              _snake_case		:	List[str]					     =     tokenizer.pad(lowercase__		)
              self.assertSequenceEqual(outputs['''global_attention_mask''']     ,     lowercase__		)







  def 				UpperCAmelCase_				(		self		)		->						Any:






        """simple docstring"""





        pass







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






        """simple docstring"""





        for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
              with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''		):
                    _snake_case		:	int					     =     self.rust_tokenizer_class.from_pretrained(lowercase__     ,     **lowercase__		)
                    _snake_case		:	str					     =     self.tokenizer_class.from_pretrained(lowercase__     ,     **lowercase__		)
                    _snake_case		:	List[Any]					     =     '''A, <mask> AllenNLP sentence.'''
                    _snake_case		:	Tuple					     =     tokenizer_r.encode_plus(lowercase__     ,     add_special_tokens=lowercase__     ,     return_token_type_ids=lowercase__		)
                    _snake_case		:	Union[str, Any]					     =     tokenizer_p.encode_plus(lowercase__     ,     add_special_tokens=lowercase__     ,     return_token_type_ids=lowercase__		)
                    self.assertEqual(sum(tokens_r['''token_type_ids''']		)     ,     sum(tokens_p['''token_type_ids''']		)		)
                    self.assertEqual(
                        sum(tokens_r['''attention_mask''']		) / len(tokens_r['''attention_mask''']		)     ,     sum(tokens_p['''attention_mask''']		) / len(tokens_p['''attention_mask''']		)     ,     )

                    _snake_case		:	Dict					     =     tokenizer_r.convert_ids_to_tokens(tokens_r['''input_ids''']		)
                    _snake_case		:	Union[str, Any]					     =     tokenizer_p.convert_ids_to_tokens(tokens_p['''input_ids''']		)
                    self.assertSequenceEqual(tokens_p['''input_ids''']     ,     [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]		)
                    self.assertSequenceEqual(tokens_r['''input_ids''']     ,     [0, 250, 6, 50_264, 3_823, 487, 21_992, 3_645, 4, 2]		)

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









'''simple docstring'''

import pickle
import unittest

import torch

from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu





@require_cpu
class lowerCamelCase						(unittest.TestCase					):







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






        """simple docstring"""





        _snake_case		:	Any					     =     torch.nn.Linear(10     ,     10		)
        _snake_case		:	Optional[int]					     =     torch.optim.SGD(model.parameters()     ,     0.1		)
        _snake_case		:	List[str]					     =     Accelerator()
        _snake_case		:	Optional[Any]					     =     accelerator.prepare(lowercase__		)
        try:
              pickle.loads(pickle.dumps(lowercase__		)		)
        except Exception as e:
              self.fail(F'''Accelerated optimizer pickling failed with {e}'''		)
        AcceleratorState._reset_state()


