'''simple docstring'''

from typing import Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_images
from ...utils import TensorType, logging


A_     :						Optional[int]    							=logging.get_logger(__name__)


class     __UpperCAmelCase       ( lowercase_		):
  __A :				Optional[int]											= ["""pixel_values"""]





  def __init__(	self    ,     _lowerCamelCase = True    ,     _lowerCamelCase = 1 / 255    ,     _lowerCamelCase = True    ,     _lowerCamelCase = 8    ,     **_lowerCamelCase    ,     ):
     super().__init__(**_lowerCamelCase )

     lowerCAmelCase_			=      do_rescale
     lowerCAmelCase_			=      rescale_factor
     lowerCAmelCase_			=      do_pad
     lowerCAmelCase_			=      pad_size





  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase = None    ,     **_lowerCamelCase ):
     return rescale(_lowerCamelCase    ,     scale=_lowerCamelCase    ,     data_format=_lowerCamelCase    ,     **_lowerCamelCase )





  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase    ,     _lowerCamelCase    ,     _lowerCamelCase = None ):
     lowerCAmelCase_	,lowerCAmelCase_			=      get_image_size(_lowerCamelCase )
     lowerCAmelCase_			=      (old_height // size + 1) * size - old_height
     lowerCAmelCase_			=      (old_width // size + 1) * size - old_width

     return pad(_lowerCamelCase    ,     ((0, pad_height), (0, pad_width))    ,     mode='''symmetric'''    ,     data_format=_lowerCamelCase )







  def 						UpperCAmelCase_	(	self    ,     _lowerCamelCase    ,     _lowerCamelCase = None    ,     _lowerCamelCase = None    ,     _lowerCamelCase = None    ,     _lowerCamelCase = None    ,     _lowerCamelCase = None    ,     _lowerCamelCase = ChannelDimension.FIRST    ,     **_lowerCamelCase    ,     ):
     lowerCAmelCase_			=      do_rescale if do_rescale is not None else self.do_rescale
     lowerCAmelCase_			=      rescale_factor if rescale_factor is not None else self.rescale_factor
     lowerCAmelCase_			=      do_pad if do_pad is not None else self.do_pad
     lowerCAmelCase_			=      pad_size if pad_size is not None else self.pad_size

     lowerCAmelCase_			=      make_list_of_images(_lowerCamelCase )

     if not valid_images(_lowerCamelCase ):
        raise ValueError(
            '''Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, '''
            '''torch.Tensor, tf.Tensor or jax.ndarray.''' )

     if do_rescale and rescale_factor is None:
        raise ValueError('''Rescale factor must be specified if do_rescale is True.''' )

     # All transformations expect numpy arrays.
     lowerCAmelCase_			=      [to_numpy_array(_lowerCamelCase ) for image in images]

     if do_rescale:
        lowerCAmelCase_			=      [self.rescale(image=_lowerCamelCase    ,     scale=_lowerCamelCase ) for image in images]

     if do_pad:
        lowerCAmelCase_			=      [self.pad(_lowerCamelCase    ,     size=_lowerCamelCase ) for image in images]

     lowerCAmelCase_			=      [to_channel_dimension_format(_lowerCamelCase    ,     _lowerCamelCase ) for image in images]

     lowerCAmelCase_			=      {'''pixel_values''': images}
     return BatchFeature(data=_lowerCamelCase    ,     tensor_type=_lowerCamelCase )









'''simple docstring'''

import unittest

from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class     __lowerCAmelCase		(lowercase_    ,	unittest.TestCase	):





      '''simple docstring'''






      lowerCAmelCase__   :	str       =				RoFormerTokenizer
      lowerCAmelCase__   :	Dict       =				RoFormerTokenizerFast
      lowerCAmelCase__   :	List[str]       =				True
      lowerCAmelCase__   :	List[str]       =				True



      def  UpperCamelCase__						(self       :       Dict					):

             '''simple docstring'''







             super().setUp()



      def  UpperCamelCase__						(self       :       List[str]  ,		**UpperCamelCase       :       Dict					):

             '''simple docstring'''







             return self.tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''  ,		**UpperCamelCase					)



      def  UpperCamelCase__						(self       :       List[str]  ,		**UpperCamelCase       :       int					):

             '''simple docstring'''







             return self.rust_tokenizer_class.from_pretrained('''junnyu/roformer_chinese_base'''  ,		**UpperCamelCase					)



      def  UpperCamelCase__						(self       :       List[str]					):

             '''simple docstring'''







             lowercase__      =					'''永和服装饰品有限公司,今天天气非常好'''
             lowercase__      =					'''永和 服装 饰品 有限公司 , 今 天 天 气 非常 好'''
             return input_text, output_text



      def  UpperCamelCase__						(self       :       int					):

             '''simple docstring'''







             lowercase__      =					self.get_tokenizer()
             lowercase__     ,lowercase__      =					self.get_chinese_input_output_texts()
             lowercase__      =					tokenizer.tokenize(UpperCamelCase					)

             self.assertListEqual(UpperCamelCase  ,		output_text.split()					)

             lowercase__      =					tokens + [tokenizer.unk_token]
             lowercase__      =					[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase					)  ,		UpperCamelCase					)



      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             lowercase__      =					self.get_rust_tokenizer()
             lowercase__     ,lowercase__      =					self.get_chinese_input_output_texts()
             lowercase__      =					tokenizer.tokenize(UpperCamelCase					)
             self.assertListEqual(UpperCamelCase  ,		output_text.split()					)
             lowercase__      =					tokens + [tokenizer.unk_token]
             lowercase__      =					[22943, 21332, 34431, 45904, 117, 306, 1231, 1231, 2653, 33994, 1266, 100]
             self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCamelCase					)  ,		UpperCamelCase					)



      def  UpperCamelCase__						(self       :       str					):

             '''simple docstring'''







             pass



      def  UpperCamelCase__						(self       :       Any					):

             '''simple docstring'''







             pass






      def  UpperCamelCase__						(self       :       Union[str, Any]					):

             '''simple docstring'''







             pass




