





"""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 		lowercase					(					_UpperCAmelCase     ,  unittest.TestCase					):
      _SCREAMING_SNAKE_CASE					=      LEDTokenizer
      _SCREAMING_SNAKE_CASE					=      LEDTokenizerFast
      _SCREAMING_SNAKE_CASE					=      True





      def     _snake_case			(       self )		->     Union[str, Any]:
            super().setUp()
            lowerCAmelCase  						=       [
                """l""",
                """o""",
                """w""",
                """e""",
                """r""",
                """s""",
                """t""",
                """i""",
                """d""",
                """n""",
                """\u0120""",
                """\u0120l""",
                """\u0120n""",
                """\u0120lo""",
                """\u0120low""",
                """er""",
                """\u0120lowest""",
                """\u0120newer""",
                """\u0120wider""",
                """<unk>""",
            ]
            lowerCAmelCase  						=       dict(zip(lowercase      ,						range(len(lowercase ) ) ) )
            lowerCAmelCase  						=       ["""#version: 0.2""", """\u0120 l""", """\u0120l o""", """\u0120lo w""", """e r""", """"""]
            lowerCAmelCase  						=       {"""unk_token""": """<unk>"""}

            lowerCAmelCase  						=       os.path.join(self.tmpdirname      ,						VOCAB_FILES_NAMES["""vocab_file"""] )
            lowerCAmelCase  						=       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     _snake_case			(       self      ,						**lowercase )		->     Optional[Any]:
            kwargs.update(self.special_tokens_map )
            return self.tokenizer_class.from_pretrained(self.tmpdirname      ,						**lowercase )





      def     _snake_case			(       self      ,						**lowercase )		->     List[str]:
            kwargs.update(self.special_tokens_map )
            return self.rust_tokenizer_class.from_pretrained(self.tmpdirname      ,						**lowercase )





      def     _snake_case			(       self      ,						lowercase )		->     Optional[Any]:
            return "lower newer", "lower newer"





      @cached_property
      def     _snake_case			(       self )		->     Any:
            return LEDTokenizer.from_pretrained("""allenai/led-base-16384""" )





      @cached_property
      def     _snake_case			(       self )		->     Optional[Any]:
            return LEDTokenizerFast.from_pretrained("""allenai/led-base-16384""" )





      @require_torch
      def     _snake_case			(       self )		->     Tuple:
            lowerCAmelCase  						=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
            lowerCAmelCase  						=       [0, 250, 251, 17_818, 13, 39_186, 1_938, 4, 2]

            for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
                  lowerCAmelCase  						=       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 )
                  lowerCAmelCase  						=       batch.input_ids.tolist()[0]
                  self.assertListEqual(lowercase      ,						lowercase )





      @require_torch
      def     _snake_case			(       self )		->     List[str]:
            lowerCAmelCase  						=       ["""A long paragraph for summarization.""", """Another paragraph for summarization."""]
            for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
                  lowerCAmelCase  						=       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     _snake_case			(       self )		->     str:
            lowerCAmelCase  						=       [
                """Summary of the text.""",
                """Another summary.""",
            ]
            for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
                  lowerCAmelCase  						=       tokenizer(text_target=lowercase      ,						max_length=32      ,						padding="""max_length"""      ,						return_tensors="""pt""" )
                  self.assertEqual(32      ,						targets["""input_ids"""].shape[1] )





      @require_torch
      def     _snake_case			(       self )		->     Optional[Any]:
            for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
                  lowerCAmelCase  						=       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     _snake_case			(       self )		->     str:
            lowerCAmelCase  						=       ["""A long paragraph for summarization."""]
            lowerCAmelCase  						=       [
                """Summary of the text.""",
            ]
            for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
                  lowerCAmelCase  						=       tokenizer(lowercase      ,						return_tensors="""pt""" )
                  lowerCAmelCase  						=       tokenizer(text_target=lowercase      ,						return_tensors="""pt""" )
                  lowerCAmelCase  						=       inputs["""input_ids"""]
                  lowerCAmelCase  						=       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     _snake_case			(       self )		->     int:
            for tokenizer in [self.default_tokenizer, self.default_tokenizer_fast]:
                  lowerCAmelCase  						=       ["""Summary of the text.""", """Another summary."""]
                  lowerCAmelCase  						=       [[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, -1, -1]]

                  lowerCAmelCase  						=       tokenizer(lowercase      ,						padding=lowercase )
                  lowerCAmelCase  						=       [[0] * len(lowercase ) for x in encoded_output["""input_ids"""]]
                  lowerCAmelCase  						=       tokenizer.pad(lowercase )
                  self.assertSequenceEqual(outputs["""global_attention_mask"""]      ,						lowercase )





      def     _snake_case			(       self )		->     Optional[Any]:
            pass





      def     _snake_case			(       self )		->     List[Any]:
            for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
                  with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})' ):
                        lowerCAmelCase  						=       self.rust_tokenizer_class.from_pretrained(lowercase      ,						**lowercase )
                        lowerCAmelCase  						=       self.tokenizer_class.from_pretrained(lowercase      ,						**lowercase )
                        lowerCAmelCase  						=       """A, <mask> AllenNLP sentence."""
                        lowerCAmelCase  						=       tokenizer_r.encode_plus(lowercase      ,						add_special_tokens=lowercase      ,						return_token_type_ids=lowercase )
                        lowerCAmelCase  						=       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"""] )      ,						)

                        lowerCAmelCase  						=       tokenizer_r.convert_ids_to_tokens(tokens_r["""input_ids"""] )
                        lowerCAmelCase  						=       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>"""] )










from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCAmelCase		       =							{
    '''configuration_canine''': ['''CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CanineConfig'''],
    '''tokenization_canine''': ['''CanineTokenizer'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 __lowerCAmelCase		       =							[
     '''CANINE_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''CanineForMultipleChoice''',
     '''CanineForQuestionAnswering''',
     '''CanineForSequenceClassification''',
     '''CanineForTokenClassification''',
     '''CanineLayer''',
     '''CanineModel''',
     '''CaninePreTrainedModel''',
     '''load_tf_weights_in_canine''',
 ]


if TYPE_CHECKING:
 from .configuration_canine import CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP, CanineConfig
 from .tokenization_canine import CanineTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_canine import (
      CANINE_PRETRAINED_MODEL_ARCHIVE_LIST,
      CanineForMultipleChoice,
      CanineForQuestionAnswering,
      CanineForSequenceClassification,
      CanineForTokenClassification,
      CanineLayer,
      CanineModel,
      CaninePreTrainedModel,
      load_tf_weights_in_canine,
  )


else:
 import sys

 __lowerCAmelCase		       =							_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)


