

"""simple docstring"""




import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
      from PIL import Image

      from transformers import CLIPSegProcessor, ViTImageProcessor







@require_vision
class      __lowercase			(    unittest.TestCase					):

  def    __lowercase       (  self		:			Optional[int]    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Optional[int]					   =					tempfile.mkdtemp()

   # fmt: off
   UpperCAmelCase__					:  Optional[int]					   =					["""l""", """o""", """w""", """e""", """r""", """s""", """t""", """i""", """d""", """n""", """lo""", """l</w>""", """w</w>""", """r</w>""", """t</w>""", """low</w>""", """er</w>""", """lowest</w>""", """newer</w>""", """wider""", """<unk>""", """<|startoftext|>""", """<|endoftext|>"""]
   # fmt: on
   UpperCAmelCase__					:  Optional[Any]					   =					dict(zip(A_					,range(len(A_    )    )    )    )
   UpperCAmelCase__					:  str					   =					["""#version: 0.2""", """l o""", """lo w</w>""", """e r</w>""", """"""]
   UpperCAmelCase__					:  Dict					   =					{"""unk_token""": """<unk>"""}

   UpperCAmelCase__					:  Optional[int]					   =					os.path.join(self.tmpdirname					,VOCAB_FILES_NAMES["""vocab_file"""]    )
   UpperCAmelCase__					:  List[str]					   =					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(A_    ) + """\n"""    )
   with open(self.merges_file					,"""w"""					,encoding="""utf-8"""    ) as fp:
    fp.write("""\n""".join(A_    )    )

   UpperCAmelCase__					:  List[str]					   =					{
       """do_resize""": True,
       """size""": 20,
       """do_center_crop""": True,
       """crop_size""": 18,
       """do_normalize""": True,
       """image_mean""": [0.4_8_1_4_5_4_6_6, 0.4_5_7_8_2_7_5, 0.4_0_8_2_1_0_7_3],
       """image_std""": [0.2_6_8_6_2_9_5_4, 0.2_6_1_3_0_2_5_8, 0.2_7_5_7_7_7_1_1],
   }
   UpperCAmelCase__					:  List[str]					   =					os.path.join(self.tmpdirname					,A_    )
   with open(self.image_processor_file					,"""w"""					,encoding="""utf-8"""    ) as fp:
    json.dump(A_					,A_    )

  def    __lowercase       (  self		:			Optional[Any]					,**A		:			Dict    ):






   '''simple docstring'''
   return CLIPTokenizer.from_pretrained(self.tmpdirname					,**A_    )

  def    __lowercase       (  self		:			Optional[int]					,**A		:			str    ):






   '''simple docstring'''
   return CLIPTokenizerFast.from_pretrained(self.tmpdirname					,**A_    )

  def    __lowercase       (  self		:			Any					,**A		:			Tuple    ):






   '''simple docstring'''
   return ViTImageProcessor.from_pretrained(self.tmpdirname					,**A_    )

  def    __lowercase       (  self		:			Optional[int]    ):






   '''simple docstring'''
   shutil.rmtree(self.tmpdirname    )

  def    __lowercase       (  self		:			int    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Dict					   =					[np.random.randint(255					,size=(3, 30, 400)					,dtype=np.uinta    )]

   UpperCAmelCase__					:  List[Any]					   =					[Image.fromarray(np.moveaxis(A_					,0					,-1    )    ) for x in image_inputs]

   return image_inputs

  def    __lowercase       (  self		:			Optional[Any]    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Any					   =					self.get_tokenizer()
   UpperCAmelCase__					:  List[Any]					   =					self.get_rust_tokenizer()
   UpperCAmelCase__					:  Any					   =					self.get_image_processor()

   UpperCAmelCase__					:  List[Any]					   =					CLIPSegProcessor(tokenizer=A_					,image_processor=A_    )
   processor_slow.save_pretrained(self.tmpdirname    )
   UpperCAmelCase__					:  Dict					   =					CLIPSegProcessor.from_pretrained(self.tmpdirname					,use_fast=A_    )

   UpperCAmelCase__					:  Union[str, Any]					   =					CLIPSegProcessor(tokenizer=A_					,image_processor=A_    )
   processor_fast.save_pretrained(self.tmpdirname    )
   UpperCAmelCase__					:  int					   =					CLIPSegProcessor.from_pretrained(self.tmpdirname    )

   self.assertEqual(processor_slow.tokenizer.get_vocab()					,tokenizer_slow.get_vocab()    )
   self.assertEqual(processor_fast.tokenizer.get_vocab()					,tokenizer_fast.get_vocab()    )
   self.assertEqual(tokenizer_slow.get_vocab()					,tokenizer_fast.get_vocab()    )
   self.assertIsInstance(processor_slow.tokenizer					,A_    )
   self.assertIsInstance(processor_fast.tokenizer					,A_    )

   self.assertEqual(processor_slow.image_processor.to_json_string()					,image_processor.to_json_string()    )
   self.assertEqual(processor_fast.image_processor.to_json_string()					,image_processor.to_json_string()    )
   self.assertIsInstance(processor_slow.image_processor					,A_    )
   self.assertIsInstance(processor_fast.image_processor					,A_    )

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






   '''simple docstring'''
   UpperCAmelCase__					:  Union[str, Any]					   =					CLIPSegProcessor(tokenizer=self.get_tokenizer()					,image_processor=self.get_image_processor()    )
   processor.save_pretrained(self.tmpdirname    )

   UpperCAmelCase__					:  Tuple					   =					self.get_tokenizer(bos_token="""(BOS)"""					,eos_token="""(EOS)"""    )
   UpperCAmelCase__					:  Union[str, Any]					   =					self.get_image_processor(do_normalize=A_					,padding_value=1.0    )

   UpperCAmelCase__					:  List[Any]					   =					CLIPSegProcessor.from_pretrained(
       self.tmpdirname					,bos_token="""(BOS)"""					,eos_token="""(EOS)"""					,do_normalize=A_					,padding_value=1.0    )

   self.assertEqual(processor.tokenizer.get_vocab()					,tokenizer_add_kwargs.get_vocab()    )
   self.assertIsInstance(processor.tokenizer					,A_    )

   self.assertEqual(processor.image_processor.to_json_string()					,image_processor_add_kwargs.to_json_string()    )
   self.assertIsInstance(processor.image_processor					,A_    )

  def    __lowercase       (  self		:			Any    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Tuple					   =					self.get_image_processor()
   UpperCAmelCase__					:  List[Any]					   =					self.get_tokenizer()

   UpperCAmelCase__					:  str					   =					CLIPSegProcessor(tokenizer=A_					,image_processor=A_    )

   UpperCAmelCase__					:  Optional[int]					   =					self.prepare_image_inputs()

   UpperCAmelCase__					:  Optional[int]					   =					image_processor(A_					,return_tensors="""np"""    )
   UpperCAmelCase__					:  str					   =					processor(images=A_					,return_tensors="""np"""    )

   for key in input_feat_extract.keys():
    self.assertAlmostEqual(input_feat_extract[key].sum()					,input_processor[key].sum()					,delta=1e-2    )

  def    __lowercase       (  self		:			List[str]    ):






   '''simple docstring'''
   UpperCAmelCase__					:  int					   =					self.get_image_processor()
   UpperCAmelCase__					:  Optional[Any]					   =					self.get_tokenizer()

   UpperCAmelCase__					:  str					   =					CLIPSegProcessor(tokenizer=A_					,image_processor=A_    )

   UpperCAmelCase__					:  Dict					   =					"""lower newer"""

   UpperCAmelCase__					:  List[str]					   =					processor(text=A_    )

   UpperCAmelCase__					:  str					   =					tokenizer(A_    )

   for key in encoded_tok.keys():
    self.assertListEqual(encoded_tok[key]					,encoded_processor[key]    )

  def    __lowercase       (  self		:			List[Any]    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Optional[Any]					   =					self.get_image_processor()
   UpperCAmelCase__					:  Union[str, Any]					   =					self.get_tokenizer()

   UpperCAmelCase__					:  str					   =					CLIPSegProcessor(tokenizer=A_					,image_processor=A_    )

   UpperCAmelCase__					:  List[Any]					   =					"""lower newer"""
   UpperCAmelCase__					:  Union[str, Any]					   =					self.prepare_image_inputs()

   UpperCAmelCase__					:  List[str]					   =					processor(text=A_					,images=A_    )

   self.assertListEqual(list(inputs.keys()    )					,["""input_ids""", """attention_mask""", """pixel_values"""]    )

   # test if it raises when no input is passed
   with pytest.raises(A_    ):
    processor()

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






   '''simple docstring'''
   UpperCAmelCase__					:  int					   =					self.get_image_processor()
   UpperCAmelCase__					:  Union[str, Any]					   =					self.get_tokenizer()

   UpperCAmelCase__					:  Optional[int]					   =					CLIPSegProcessor(tokenizer=A_					,image_processor=A_    )

   UpperCAmelCase__					:  Tuple					   =					self.prepare_image_inputs()
   UpperCAmelCase__					:  Optional[int]					   =					self.prepare_image_inputs()

   UpperCAmelCase__					:  Optional[Any]					   =					processor(images=A_					,visual_prompt=A_    )

   self.assertListEqual(list(inputs.keys()    )					,["""pixel_values""", """conditional_pixel_values"""]    )

   # test if it raises when no input is passed
   with pytest.raises(A_    ):
    processor()




  def    __lowercase       (  self		:			Optional[int]    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Union[str, Any]					   =					self.get_image_processor()
   UpperCAmelCase__					:  int					   =					self.get_tokenizer()

   UpperCAmelCase__					:  str					   =					CLIPSegProcessor(tokenizer=A_					,image_processor=A_    )

   UpperCAmelCase__					:  Dict					   =					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

   UpperCAmelCase__					:  str					   =					processor.batch_decode(A_    )
   UpperCAmelCase__					:  Optional[Any]					   =					tokenizer.batch_decode(A_    )

   self.assertListEqual(A_					,A_    )








"""simple docstring"""




from ...configuration_utils import PretrainedConfig
from ...utils import logging


__UpperCAmelCase =				logging.get_logger(__name__)

__UpperCAmelCase =				{
    'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
    'microsoft/markuplm-large': 'https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json',
}







class      __lowercase			(    __lowerCamelCase					):
  snake_case_				       =       """markuplm"""

  def __init__(  self		:			str					,A		:			List[Any]=30_522					,A		:			Tuple=768					,A		:			str=12					,A		:			int=12					,A		:			int=3_072					,A		:			Optional[int]="gelu"					,A		:			Optional[int]=0.1					,A		:			Optional[int]=0.1					,A		:			Any=512					,A		:			Any=2					,A		:			str=0.0_2					,A		:			int=1e-12					,A		:			int=0					,A		:			str=0					,A		:			List[Any]=2					,A		:			List[str]=256					,A		:			Union[str, Any]=1_024					,A		:			List[Any]=216					,A		:			Any=1_001					,A		:			Optional[int]=32					,A		:			Any=50					,A		:			int="absolute"					,A		:			Dict=True					,A		:			int=None					,**A		:			Optional[int]					,):






   '''simple docstring'''
   super().__init__(
       pad_token_id=A					,bos_token_id=A					,eos_token_id=A					,**A					,)
   UpperCAmelCase__					:  Dict					   =					vocab_size
   UpperCAmelCase__					:  Union[str, Any]					   =					hidden_size
   UpperCAmelCase__					:  Optional[int]					   =					num_hidden_layers
   UpperCAmelCase__					:  Tuple					   =					num_attention_heads
   UpperCAmelCase__					:  Optional[Any]					   =					hidden_act
   UpperCAmelCase__					:  Any					   =					intermediate_size
   UpperCAmelCase__					:  Dict					   =					hidden_dropout_prob
   UpperCAmelCase__					:  Optional[Any]					   =					attention_probs_dropout_prob
   UpperCAmelCase__					:  Optional[int]					   =					max_position_embeddings
   UpperCAmelCase__					:  Dict					   =					type_vocab_size
   UpperCAmelCase__					:  Optional[Any]					   =					initializer_range
   UpperCAmelCase__					:  str					   =					layer_norm_eps
   UpperCAmelCase__					:  Any					   =					position_embedding_type
   UpperCAmelCase__					:  int					   =					use_cache
   UpperCAmelCase__					:  List[str]					   =					classifier_dropout
   # additional properties
   UpperCAmelCase__					:  Optional[int]					   =					max_depth
   UpperCAmelCase__					:  List[str]					   =					max_xpath_tag_unit_embeddings
   UpperCAmelCase__					:  Any					   =					max_xpath_subs_unit_embeddings
   UpperCAmelCase__					:  str					   =					tag_pad_id
   UpperCAmelCase__					:  Dict					   =					subs_pad_id
   UpperCAmelCase__					:  List[str]					   =					xpath_unit_hidden_size





