



'''simple docstring'''





import os
from typing import List, Union

import tensorflow as tf
from tensorflow_text import BertTokenizer as BertTokenizerLayer
from tensorflow_text import FastBertTokenizer, ShrinkLongestTrimmer, case_fold_utfa, combine_segments, pad_model_inputs

from .tokenization_bert import BertTokenizer






class  lowerCamelCase_   (    tf.keras.layers.Layer					):
  """simple docstring"""




  def __init__(			self				:     Optional[Any]      ,     _a				:     List      ,     _a				:     bool      ,     _a				:     int = None      ,     _a				:     int = None      ,     _a				:     int = None      ,     _a				:     str = "longest"      ,     _a				:     bool = True      ,     _a				:     int = 512      ,     _a				:     int = None      ,     _a				:     bool = True      ,     _a				:     bool = True      ,     _a				:     bool = True      ,     **_a				:     Optional[int]      ,     ) -> Any:
    super().__init__()
    if use_fast_bert_tokenizer:
      __lowerCamelCase	:	Tuple   	=			FastBertTokenizer(
          _a      ,     token_out_type=tf.intaa      ,     lower_case_nfd_strip_accents=_a      ,     **_a       )
    else:
      __lowerCamelCase	:	str   	=			tf.lookup.StaticVocabularyTable(
          tf.lookup.KeyValueTensorInitializer(
              keys=_a      ,     key_dtype=tf.string      ,     values=tf.range(tf.size(_a      ,     out_type=tf.intaa       )      ,     dtype=tf.intaa       )      ,     value_dtype=tf.intaa      ,     )      ,     num_oov_buckets=1      ,     )
      __lowerCamelCase	:	List[str]   	=			BertTokenizerLayer(
          _a      ,     token_out_type=tf.intaa      ,     lower_case=_a      ,     **_a       )

    __lowerCamelCase	:	Union[str, Any]   	=			vocab_list
    __lowerCamelCase	:	int   	=			do_lower_case
    __lowerCamelCase	:	List[Any]   	=			cls_token_id or vocab_list.index('[CLS]'       )
    __lowerCamelCase	:	List[str]   	=			sep_token_id or vocab_list.index('[SEP]'       )
    __lowerCamelCase	:	Any   	=			pad_token_id or vocab_list.index('[PAD]'       )
    __lowerCamelCase	:	str   	=			ShrinkLongestTrimmer(max_length - 3      ,     axis=1       )  # Allow room for special tokens
    __lowerCamelCase	:	Optional[Any]   	=			max_length
    __lowerCamelCase	:	Any   	=			padding
    __lowerCamelCase	:	Optional[int]   	=			truncation
    __lowerCamelCase	:	List[Any]   	=			pad_to_multiple_of
    __lowerCamelCase	:	List[Any]   	=			return_token_type_ids
    __lowerCamelCase	:	List[str]   	=			return_attention_mask




  @classmethod
  def 						_lowercase					(			cls				:     Tuple      ,     _a				:     "PreTrainedTokenizerBase"      ,     **_a				:     List[Any]       ) -> int:  # noqa: F821
    __lowerCamelCase	:	Optional[Any]   	=			kwargs.pop('do_lower_case'      ,     _a       )
    __lowerCamelCase	:	Dict   	=			tokenizer.do_lower_case if do_lower_case is None else do_lower_case
    __lowerCamelCase	:	List[Any]   	=			kwargs.pop('cls_token_id'      ,     _a       )
    __lowerCamelCase	:	Tuple   	=			tokenizer.cls_token_id if cls_token_id is None else cls_token_id
    __lowerCamelCase	:	Any   	=			kwargs.pop('sep_token_id'      ,     _a       )
    __lowerCamelCase	:	Any   	=			tokenizer.sep_token_id if sep_token_id is None else sep_token_id
    __lowerCamelCase	:	List[Any]   	=			kwargs.pop('pad_token_id'      ,     _a       )
    __lowerCamelCase	:	Dict   	=			tokenizer.pad_token_id if pad_token_id is None else pad_token_id

    __lowerCamelCase	:	List[Any]   	=			tokenizer.get_vocab()
    __lowerCamelCase	:	int   	=			sorted([(wordpiece, idx) for wordpiece, idx in vocab.items()]      ,     key=lambda _a       : x[1]       )
    __lowerCamelCase	:	Any   	=			[entry[0] for entry in vocab]
    return cls(
        vocab_list=_a      ,     do_lower_case=_a      ,     cls_token_id=_a      ,     sep_token_id=_a      ,     pad_token_id=_a      ,     **_a      ,     )




  @classmethod
  def 						_lowercase					(			cls				:     Dict      ,     _a				:     Union[str, os.PathLike]      ,     *_a				:     List[str]      ,     **_a				:     str       ) -> Optional[int]:
    try:
      __lowerCamelCase	:	List[Any]   	=			BertTokenizer.from_pretrained(_a      ,     *_a      ,     **_a       )
    except:  # noqa: E722
      from .tokenization_bert_fast import BertTokenizerFast

      __lowerCamelCase	:	Any   	=			BertTokenizerFast.from_pretrained(_a      ,     *_a      ,     **_a       )
    return cls.from_tokenizer(_a      ,     **_a       )




  def 						_lowercase					(			self				:     Dict      ,     _a				:     List[str]       ) -> List[str]:
    if self.do_lower_case:
      __lowerCamelCase	:	int   	=			case_fold_utfa(_a       )
    __lowerCamelCase	:	Any   	=			self.tf_tokenizer.tokenize(_a       )
    return tokens.merge_dims(1      ,     -1       )




  def 						_lowercase					(			self				:     int      ,     _a				:     Dict      ,     _a				:     Union[str, Any]=None      ,     _a				:     Tuple=None      ,     _a				:     int=None      ,     _a				:     Any=None      ,     _a				:     Optional[Any]=None      ,     _a				:     Tuple=None      ,     _a				:     List[Any]=None      ,     ) -> Optional[int]:
    if padding is None:
      __lowerCamelCase	:	Optional[Any]   	=			self.padding
    if padding not in ("longest", "max_length"):
      raise ValueError('Padding must be either \'longest\' or \'max_length\'!'       )
    if max_length is not None and text_pair is not None:
      # Because we have to instantiate a Trimmer to do it properly
      raise ValueError('max_length cannot be overridden at call time when truncating paired texts!'       )
    if max_length is None:
      __lowerCamelCase	:	Any   	=			self.max_length
    if truncation is None:
      __lowerCamelCase	:	int   	=			self.truncation
    if pad_to_multiple_of is None:
      __lowerCamelCase	:	List[Any]   	=			self.pad_to_multiple_of
    if return_token_type_ids is None:
      __lowerCamelCase	:	Dict   	=			self.return_token_type_ids
    if return_attention_mask is None:
      __lowerCamelCase	:	Optional[Any]   	=			self.return_attention_mask
    if not isinstance(_a      ,     tf.Tensor       ):
      __lowerCamelCase	:	Optional[int]   	=			tf.convert_to_tensor(_a       )
    if text_pair is not None and not isinstance(_a      ,     tf.Tensor       ):
      __lowerCamelCase	:	Any   	=			tf.convert_to_tensor(_a       )
    if text_pair is not None:
      if text.shape.rank > 1:
        raise ValueError('text argument should not be multidimensional when a text pair is supplied!'       )
      if text_pair.shape.rank > 1:
        raise ValueError('text_pair should not be multidimensional!'       )
    if text.shape.rank == 2:
      __lowerCamelCase	,__lowerCamelCase	:	Optional[int]   	=			text[:, 0], text[:, 1]
    __lowerCamelCase	:	Dict   	=			self.unpaired_tokenize(_a       )
    if text_pair is None:  # Unpaired text
      if truncation:
        __lowerCamelCase	:	Union[str, Any]   	=			text[:, : max_length - 2]  # Allow room for special tokens
      __lowerCamelCase	,__lowerCamelCase	:	str   	=			combine_segments(
          (text,)      ,     start_of_sequence_id=self.cls_token_id      ,     end_of_segment_id=self.sep_token_id       )
    else:  # Paired text
      __lowerCamelCase	:	List[Any]   	=			self.unpaired_tokenize(_a       )
      if truncation:
        __lowerCamelCase	,__lowerCamelCase	:	Tuple   	=			self.paired_trimmer.trim([text, text_pair]       )
      __lowerCamelCase	,__lowerCamelCase	:	str   	=			combine_segments(
          (text, text_pair)      ,     start_of_sequence_id=self.cls_token_id      ,     end_of_segment_id=self.sep_token_id       )
    if padding == "longest":
      __lowerCamelCase	:	str   	=			input_ids.bounding_shape(axis=1       )
      if pad_to_multiple_of is not None:
        # No ceiling division in tensorflow, so we negate floordiv instead
        __lowerCamelCase	:	int   	=			pad_to_multiple_of * (-tf.math.floordiv(-pad_length      ,     _a       ))
    else:
      __lowerCamelCase	:	Tuple   	=			max_length

    __lowerCamelCase	,__lowerCamelCase	:	Dict   	=			pad_model_inputs(_a      ,     max_seq_length=_a      ,     pad_value=self.pad_token_id       )
    __lowerCamelCase	:	Optional[int]   	=			{'input_ids': input_ids}
    if return_attention_mask:
      __lowerCamelCase	:	Union[str, Any]   	=			attention_mask
    if return_token_type_ids:
      __lowerCamelCase	,__lowerCamelCase	:	Any   	=			pad_model_inputs(
          _a      ,     max_seq_length=_a      ,     pad_value=self.pad_token_id       )
      __lowerCamelCase	:	Dict   	=			token_type_ids
    return output




  def 						_lowercase					(			self				:     Optional[int]       ) -> Optional[Any]:
    return {
        "vocab_list": self.vocab_list,
        "do_lower_case": self.do_lower_case,
        "cls_token_id": self.cls_token_id,
        "sep_token_id": self.sep_token_id,
        "pad_token_id": self.pad_token_id,
    }











'''simple docstring'''





import unittest

from diffusers import __version__
from diffusers.utils import deprecate






class  lowerCamelCase_   (    unittest.TestCase					):
  """simple docstring"""




  a_							 =""".""".join([str(int(__version__.split("""."""					)[0]					) + 1					)] + __version__.split("""."""					)[1:]					)
  a_							 ="""0.0.1"""




  def 						_lowercase					(			self				:     Optional[Any]       ) -> int:
    __lowerCamelCase	:	Any   	=			{'deprecated_arg': 4}

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	:	Optional[int]   	=			deprecate('deprecated_arg'      ,     self.higher_version      ,     'message'      ,     take_from=_a       )

    assert output == 4
    assert (
        str(warning.warning       )
        == f'The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'
        " message"
    )




  def 						_lowercase					(			self				:     Union[str, Any]       ) -> Optional[int]:
    __lowerCamelCase	:	int   	=			{'deprecated_arg': 4}

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	:	Optional[Any]   	=			deprecate(('deprecated_arg', self.higher_version, 'message')      ,     take_from=_a       )

    assert output == 4
    assert (
        str(warning.warning       )
        == f'The `deprecated_arg` argument is deprecated and will be removed in version {self.higher_version}.'
        " message"
    )




  def 						_lowercase					(			self				:     int       ) -> Optional[Any]:
    __lowerCamelCase	:	Optional[int]   	=			{'deprecated_arg_1': 4, 'deprecated_arg_2': 8}
    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	,__lowerCamelCase	:	Any   	=			deprecate(
          ('deprecated_arg_1', self.higher_version, 'Hey')      ,     ('deprecated_arg_2', self.higher_version, 'Hey')      ,     take_from=_a      ,     )
    assert output_a == 4
    assert output_a == 8
    assert (
        str(warning.warnings[0].message       )
        == "The `deprecated_arg_1` argument is deprecated and will be removed in version"
        f' {self.higher_version}. Hey'
    )
    assert (
        str(warning.warnings[1].message       )
        == "The `deprecated_arg_2` argument is deprecated and will be removed in version"
        f' {self.higher_version}. Hey'
    )




  def 						_lowercase					(			self				:     str       ) -> Optional[Any]:
    __lowerCamelCase	:	Optional[int]   	=			{'deprecated_arg': 4}

    with self.assertRaises(_a       ) as error:
      deprecate(('wrong_arg', self.higher_version, 'message')      ,     take_from=_a       )

    assert "test_deprecate_function_incorrect_arg in" in str(error.exception       )
    assert "line" in str(error.exception       )
    assert "got an unexpected keyword argument `deprecated_arg`" in str(error.exception       )




  def 						_lowercase					(			self				:     Optional[Any]       ) -> Union[str, Any]:
    with self.assertWarns(_a       ) as warning:
      deprecate(('deprecated_arg', self.higher_version, 'message')       )

    assert (
        str(warning.warning       )
        == f'`deprecated_arg` is deprecated and will be removed in version {self.higher_version}. message'
    )




  def 						_lowercase					(			self				:     Optional[Any]       ) -> Union[str, Any]:
    with self.assertWarns(_a       ) as warning:
      deprecate(
          ('deprecated_arg_1', self.higher_version, 'Hey')      ,     ('deprecated_arg_2', self.higher_version, 'Hey')      ,     )
    assert (
        str(warning.warnings[0].message       )
        == f'`deprecated_arg_1` is deprecated and will be removed in version {self.higher_version}. Hey'
    )
    assert (
        str(warning.warnings[1].message       )
        == f'`deprecated_arg_2` is deprecated and will be removed in version {self.higher_version}. Hey'
    )




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






    class  lowerCamelCase_   :
      """simple docstring"""




      a_							 =5

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	:	int   	=			deprecate(('arg', self.higher_version, 'message')      ,     take_from=Args()       )

    assert arg == 5
    assert (
        str(warning.warning       )
        == f'The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )




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






    class  lowerCamelCase_   :
      """simple docstring"""




      a_							 =5
      a_							 =7

    with self.assertWarns(_a       ) as warning:
      __lowerCamelCase	,__lowerCamelCase	:	List[str]   	=			deprecate(
          ('arg', self.higher_version, 'message')      ,     ('foo', self.higher_version, 'message')      ,     ('does not exist', self.higher_version, 'message')      ,     take_from=Args()      ,     )

    assert arg_a == 5
    assert arg_a == 7
    assert (
        str(warning.warning       )
        == f'The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )
    assert (
        str(warning.warnings[0].message       )
        == f'The `arg` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )
    assert (
        str(warning.warnings[1].message       )
        == f'The `foo` attribute is deprecated and will be removed in version {self.higher_version}. message'
    )




  def 						_lowercase					(			self				:     Union[str, Any]       ) -> List[str]:
    __lowerCamelCase	:	Union[str, Any]   	=			{'deprecated_arg': 4}

    with self.assertRaises(_a       ) as error:
      deprecate(('wrong_arg', self.lower_version, 'message')      ,     take_from=_a       )

    assert (
        str(error.exception       )
        == "The deprecation tuple ('wrong_arg', '0.0.1', 'message') should be removed since diffusers' version"
        f' {__version__} is >= {self.lower_version}'
    )




  def 						_lowercase					(			self				:     Optional[int]       ) -> str:
    with self.assertWarns(_a       ) as warning:
      deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')      ,     standard_warn=_a       )

    assert str(warning.warning       ) == "This message is better!!!"




  def 						_lowercase					(			self				:     List[Any]       ) -> Union[str, Any]:
    with self.assertWarns(_a       ) as warning:
      deprecate(('deprecated_arg', self.higher_version, 'This message is better!!!')      ,     standard_warn=_a       )
    assert str(warning.warning       ) == "This message is better!!!"
    assert "diffusers/tests/others/test_utils.py" in warning.filename






