



"""simple docstring"""





import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple

from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


if is_torch_available():
  lowerCamelCase       	=						"""pt"""
elif is_tf_available():
  lowerCamelCase       	=						"""tf"""
else:
  lowerCamelCase       	=						"""jax"""
class 				lowercase__       (   SCREAMING_SNAKE_CASE    , unittest.TestCase				):







       '''simple docstring'''


       UpperCamelCase						=					PerceiverTokenizer
       UpperCamelCase						=					False



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


             '''simple docstring'''




             super().setUp()
             UpperCAmelCase_      			=							PerceiverTokenizer()
             tokenizer.save_pretrained(self.tmpdirname   )



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


             '''simple docstring'''




             return PerceiverTokenizer.from_pretrained("deepmind/language-perceiver"   )



       def 					lowercase__    (							self      :  List[str]		,    **_UpperCAmelCase      :  Dict   )			->						PerceiverTokenizer:


             '''simple docstring'''




             return self.tokenizer_class.from_pretrained(self.tmpdirname		,    **_UpperCAmelCase   )



       def 					lowercase__    (							self      :  Dict		,    _UpperCAmelCase      :  Dict		,    _UpperCAmelCase      :  Optional[Any]=False		,    _UpperCAmelCase      :  Tuple=20		,    _UpperCAmelCase      :  Dict=5   )			->						Tuple[str, list]:


             '''simple docstring'''




             UpperCAmelCase_      			=							[]
             for i in range(len(_UpperCAmelCase   )   ):
                   try:
                         UpperCAmelCase_      			=							tokenizer.decode([i]		,    clean_up_tokenization_spaces=_UpperCAmelCase   )
                   except UnicodeDecodeError:
                         pass
                   toks.append((i, tok)   )

             UpperCAmelCase_      			=							list(filter(lambda _UpperCAmelCase   : re.match(r"^[ a-zA-Z]+$"		,    t[1]   )		,    _UpperCAmelCase   )   )
             UpperCAmelCase_      			=							list(filter(lambda _UpperCAmelCase   : [t[0]] == tokenizer.encode(t[1]		,    add_special_tokens=_UpperCAmelCase   )		,    _UpperCAmelCase   )   )
             if max_length is not None and len(_UpperCAmelCase   ) > max_length:
                   UpperCAmelCase_      			=							toks[:max_length]
             if min_length is not None and len(_UpperCAmelCase   ) < min_length and len(_UpperCAmelCase   ) > 0:
                   while len(_UpperCAmelCase   ) < min_length:
                         UpperCAmelCase_      			=							toks + toks
        # toks_str = [t[1] for t in toks]
             UpperCAmelCase_      			=							[t[0] for t in toks]

             # Ensure consistency
             UpperCAmelCase_      			=							tokenizer.decode(_UpperCAmelCase		,    clean_up_tokenization_spaces=_UpperCAmelCase   )
             if " " not in output_txt and len(_UpperCAmelCase   ) > 1:
                   UpperCAmelCase_      			=							(
                       tokenizer.decode([toks_ids[0]]		,    clean_up_tokenization_spaces=_UpperCAmelCase   )
                       + " "
                       + tokenizer.decode(toks_ids[1:]		,    clean_up_tokenization_spaces=_UpperCAmelCase   )
                   )
             if with_prefix_space:
                   UpperCAmelCase_      			=							" " + output_txt
             UpperCAmelCase_      			=							tokenizer.encode(_UpperCAmelCase		,    add_special_tokens=_UpperCAmelCase   )
             return output_txt, output_ids



       def 					lowercase__    (							self      :  Any   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.perceiver_tokenizer
             UpperCAmelCase_      			=							"Unicode €."
             UpperCAmelCase_      			=							tokenizer(_UpperCAmelCase   )
             UpperCAmelCase_      			=							[4, 91, 116, 111, 105, 117, 106, 107, 38, 232, 136, 178, 52, 5]
             self.assertEqual(encoded["input_ids"]		,    _UpperCAmelCase   )

             # decoding
             UpperCAmelCase_      			=							tokenizer.decode(_UpperCAmelCase   )
             self.assertEqual(_UpperCAmelCase		,    "[CLS]Unicode €.[SEP]"   )

             UpperCAmelCase_      			=							tokenizer("e è é ê ë"   )
             UpperCAmelCase_      			=							[4, 107, 38, 201, 174, 38, 201, 175, 38, 201, 176, 38, 201, 177, 5]
             self.assertEqual(encoded["input_ids"]		,    _UpperCAmelCase   )
             # decoding
             UpperCAmelCase_      			=							tokenizer.decode(_UpperCAmelCase   )
             self.assertEqual(_UpperCAmelCase		,    "[CLS]e è é ê ë[SEP]"   )

             # encode/decode, but with `encode` instead of `__call__`
             self.assertEqual(tokenizer.decode(tokenizer.encode("e è é ê ë"   )   )		,    "[CLS]e è é ê ë[SEP]"   )



       def 					lowercase__    (							self      :  Tuple   )			->						Optional[int]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.perceiver_tokenizer
             UpperCAmelCase_      			=							["A long paragraph for summarization.", "Another paragraph for summarization."]
             # fmt: off
             UpperCAmelCase_      			=							[4, 71, 38, 114, 117, 116, 109, 38, 118, 103, 120, 103, 109, 120, 103, 118, 110, 38, 108, 117, 120, 38, 121, 123, 115, 115, 103, 120, 111, 128, 103, 122, 111, 117, 116, 52, 5, 0]
             # fmt: on
             UpperCAmelCase_      			=							tokenizer(_UpperCAmelCase		,    padding=_UpperCAmelCase		,    return_tensors=_UpperCAmelCase   )
             self.assertIsInstance(_UpperCAmelCase		,    _UpperCAmelCase   )

             if FRAMEWORK != "jax":
                   UpperCAmelCase_      			=							list(batch.input_ids.numpy()[0]   )
             else:
                   UpperCAmelCase_      			=							list(batch.input_ids.tolist()[0]   )

             self.assertListEqual(_UpperCAmelCase		,    _UpperCAmelCase   )

             self.assertEqual((2, 38)		,    batch.input_ids.shape   )
             self.assertEqual((2, 38)		,    batch.attention_mask.shape   )



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


             '''simple docstring'''




             UpperCAmelCase_      			=							self.perceiver_tokenizer
             UpperCAmelCase_      			=							["A long paragraph for summarization.", "Another paragraph for summarization."]
             UpperCAmelCase_      			=							tokenizer(_UpperCAmelCase		,    padding=_UpperCAmelCase		,    return_tensors=_UpperCAmelCase   )
             # check if input_ids are returned and no decoder_input_ids
             self.assertIn("input_ids"		,    _UpperCAmelCase   )
             self.assertIn("attention_mask"		,    _UpperCAmelCase   )
             self.assertNotIn("decoder_input_ids"		,    _UpperCAmelCase   )
             self.assertNotIn("decoder_attention_mask"		,    _UpperCAmelCase   )



       def 					lowercase__    (							self      :  Optional[int]   )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.perceiver_tokenizer
             UpperCAmelCase_      			=							[
                 "Summary of the text.",
                 "Another summary.",
             ]
             UpperCAmelCase_      			=							tokenizer(
                 text_target=_UpperCAmelCase		,    max_length=32		,    padding="max_length"		,    truncation=_UpperCAmelCase		,    return_tensors=_UpperCAmelCase   )
             self.assertEqual(32		,    targets["input_ids"].shape[1]   )



       def 					lowercase__    (							self      :  int   )			->						Optional[Any]:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.get_tokenizers()
             for tokenizer in tokenizers:
                   with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
                         self.assertNotEqual(tokenizer.model_max_length		,    42   )

        # Now let's start the test
             UpperCAmelCase_      			=							self.get_tokenizers()
             for tokenizer in tokenizers:
                   with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
                         # Isolate this from the other tests because we save additional tokens/etc
                         UpperCAmelCase_      			=							tempfile.mkdtemp()

                         UpperCAmelCase_      			=							" He is very happy, UNwant\u00E9d,running"
                         UpperCAmelCase_      			=							tokenizer.encode(_UpperCAmelCase		,    add_special_tokens=_UpperCAmelCase   )
                         tokenizer.save_pretrained(_UpperCAmelCase   )

                         UpperCAmelCase_      			=							tokenizer.__class__.from_pretrained(_UpperCAmelCase   )
                         UpperCAmelCase_      			=							after_tokenizer.encode(_UpperCAmelCase		,    add_special_tokens=_UpperCAmelCase   )
                         self.assertListEqual(_UpperCAmelCase		,    _UpperCAmelCase   )

                         shutil.rmtree(_UpperCAmelCase   )

             UpperCAmelCase_      			=							self.get_tokenizers(model_max_length=42   )
             for tokenizer in tokenizers:
                   with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
                         # Isolate this from the other tests because we save additional tokens/etc
                         UpperCAmelCase_      			=							tempfile.mkdtemp()

                         UpperCAmelCase_      			=							" He is very happy, UNwant\u00E9d,running"
                         tokenizer.add_tokens(["bim", "bambam"]   )
                         UpperCAmelCase_      			=							tokenizer.additional_special_tokens
                         additional_special_tokens.append("new_additional_special_token"   )
                         tokenizer.add_special_tokens({"additional_special_tokens": additional_special_tokens}   )
                         UpperCAmelCase_      			=							tokenizer.encode(_UpperCAmelCase		,    add_special_tokens=_UpperCAmelCase   )
                         tokenizer.save_pretrained(_UpperCAmelCase   )

                         UpperCAmelCase_      			=							tokenizer.__class__.from_pretrained(_UpperCAmelCase   )
                         UpperCAmelCase_      			=							after_tokenizer.encode(_UpperCAmelCase		,    add_special_tokens=_UpperCAmelCase   )
                         self.assertListEqual(_UpperCAmelCase		,    _UpperCAmelCase   )
                         self.assertIn("new_additional_special_token"		,    after_tokenizer.additional_special_tokens   )
                         self.assertEqual(after_tokenizer.model_max_length		,    42   )

                         UpperCAmelCase_      			=							tokenizer.__class__.from_pretrained(_UpperCAmelCase		,    model_max_length=43   )
                         self.assertEqual(tokenizer.model_max_length		,    43   )

                         shutil.rmtree(_UpperCAmelCase   )



       def 					lowercase__    (							self      :  str   )			->						str:


             '''simple docstring'''




             UpperCAmelCase_      			=							[]
             if self.test_slow_tokenizer:
                   tokenizer_list.append((self.tokenizer_class, self.get_tokenizer())   )

             if self.test_rust_tokenizer:
                   tokenizer_list.append((self.rust_tokenizer_class, self.get_rust_tokenizer())   )

             for tokenizer_class, tokenizer_utils in tokenizer_list:
                   with tempfile.TemporaryDirectory() as tmp_dir:
                         tokenizer_utils.save_pretrained(_UpperCAmelCase   )

                         with open(os.path.join(_UpperCAmelCase		,    "special_tokens_map.json"   )		,    encoding="utf-8"   ) as json_file:
                               UpperCAmelCase_      			=							json.load(_UpperCAmelCase   )

                         with open(os.path.join(_UpperCAmelCase		,    "tokenizer_config.json"   )		,    encoding="utf-8"   ) as json_file:
                               UpperCAmelCase_      			=							json.load(_UpperCAmelCase   )

                         UpperCAmelCase_      			=							[F"""<extra_id_{i}>""" for i in range(125   )]

                         UpperCAmelCase_      			=							added_tokens_extra_ids + [
                             "an_additional_special_token"
                         ]
                         UpperCAmelCase_      			=							added_tokens_extra_ids + [
                             "an_additional_special_token"
                         ]

                         with open(os.path.join(_UpperCAmelCase		,    "special_tokens_map.json"   )		,    "w"		,    encoding="utf-8"   ) as outfile:
                               json.dump(_UpperCAmelCase		,    _UpperCAmelCase   )
                         with open(os.path.join(_UpperCAmelCase		,    "tokenizer_config.json"   )		,    "w"		,    encoding="utf-8"   ) as outfile:
                               json.dump(_UpperCAmelCase		,    _UpperCAmelCase   )

                         # the following checks allow us to verify that our test works as expected, i.e. that the tokenizer takes
                         # into account the new value of additional_special_tokens given in the "tokenizer_config.json" and
                         # "special_tokens_map.json" files
                         UpperCAmelCase_      			=							tokenizer_class.from_pretrained(
                             _UpperCAmelCase		,    )
                         self.assertIn(
                             "an_additional_special_token"		,    tokenizer_without_change_in_init.additional_special_tokens   )
                         self.assertEqual(
                             ["an_additional_special_token"]		,    tokenizer_without_change_in_init.convert_ids_to_tokens(
                                 tokenizer_without_change_in_init.convert_tokens_to_ids(["an_additional_special_token"]   )   )		,    )

                         # Now we test that we can change the value of additional_special_tokens in the from_pretrained
                         UpperCAmelCase_      			=							added_tokens_extra_ids + [AddedToken("a_new_additional_special_token"		,    lstrip=_UpperCAmelCase   )]
                         UpperCAmelCase_      			=							tokenizer_class.from_pretrained(
                             _UpperCAmelCase		,    additional_special_tokens=_UpperCAmelCase		,    )

                         self.assertIn("a_new_additional_special_token"		,    tokenizer.additional_special_tokens   )
                         self.assertEqual(
                             ["a_new_additional_special_token"]		,    tokenizer.convert_ids_to_tokens(
                                 tokenizer.convert_tokens_to_ids(["a_new_additional_special_token"]   )   )		,    )



       def 					lowercase__    (							self      :  str   )			->						Tuple:


             '''simple docstring'''




             UpperCAmelCase_      			=							self.perceiver_tokenizer
             self.assertEqual(tokenizer.decode([178]   )		,    "�"   )



       def 					lowercase__    (							self      :  Tuple   )			->						int:


             '''simple docstring'''




             pass



       def 					lowercase__    (							self      :  List[Any]   )			->						Optional[Any]:


             '''simple docstring'''




             pass



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


             '''simple docstring'''




             pass



       def 					lowercase__    (							self      :  Dict   )			->						List[Any]:


             '''simple docstring'''




             pass







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


             '''simple docstring'''




             UpperCAmelCase_      			=							self.get_tokenizers(fast=_UpperCAmelCase		,    do_lower_case=_UpperCAmelCase   )
             for tokenizer in tokenizers:
                   with self.subTest(F"""{tokenizer.__class__.__name__}"""   ):
                         UpperCAmelCase_      			=							["[CLS]", "t", "h", "i", "s", " ", "i", "s", " ", "a", " ", "t", "e", "s", "t", "[SEP]"]
                         UpperCAmelCase_      			=							tokenizer.convert_tokens_to_string(_UpperCAmelCase   )

                         self.assertIsInstance(_UpperCAmelCase		,    _UpperCAmelCase   )









"""simple docstring"""





from .configuration_bert_masked import MaskedBertConfig
from .modeling_bert_masked import (
    MaskedBertForMultipleChoice,
    MaskedBertForQuestionAnswering,
    MaskedBertForSequenceClassification,
    MaskedBertForTokenClassification,
    MaskedBertModel,
)
from .modules import *




