



"""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    _A	(     unittest.TestCase   ):



       def 		_lowerCamelCase      (		self							:					str):


           '''simple docstring'''

           __a							=    tempfile.mkdtemp()

           # fmt: off
           __a							=    ['''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
           __a							=    dict(zip(__SCREAMING_SNAKE_CASE					,		range(len(__SCREAMING_SNAKE_CASE))))
           __a							=    ['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
           __a							=    {'''unk_token''': '''<unk>'''}

           __a							=    os.path.join(self.tmpdirname					,		VOCAB_FILES_NAMES['''vocab_file'''])
           __a							=    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(__SCREAMING_SNAKE_CASE) + '''\n''')
           with open(self.merges_file					,		'''w'''					,		encoding='''utf-8''') as fp:
               fp.write('''\n'''.join(__SCREAMING_SNAKE_CASE))

           __a							=    {
               '''do_resize''': True,
               '''size''': 20,
               '''do_center_crop''': True,
               '''crop_size''': 18,
               '''do_normalize''': True,
               '''image_mean''': [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
               '''image_std''': [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
           }
           __a							=    os.path.join(self.tmpdirname					,		__SCREAMING_SNAKE_CASE)
           with open(self.image_processor_file					,		'''w'''					,		encoding='''utf-8''') as fp:
               json.dump(__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE)



       def 		_lowerCamelCase      (		self							:					Optional[int]					,		**__SCREAMING_SNAKE_CASE							:					int):


           '''simple docstring'''

           return CLIPTokenizer.from_pretrained(self.tmpdirname					,		**__SCREAMING_SNAKE_CASE)



       def 		_lowerCamelCase      (		self							:					Union[str, Any]					,		**__SCREAMING_SNAKE_CASE							:					Any):


           '''simple docstring'''

           return CLIPTokenizerFast.from_pretrained(self.tmpdirname					,		**__SCREAMING_SNAKE_CASE)



       def 		_lowerCamelCase      (		self							:					List[str]					,		**__SCREAMING_SNAKE_CASE							:					Dict):


           '''simple docstring'''

           return ViTImageProcessor.from_pretrained(self.tmpdirname					,		**__SCREAMING_SNAKE_CASE)



       def 		_lowerCamelCase      (		self							:					Tuple):


           '''simple docstring'''

           shutil.rmtree(self.tmpdirname)



       def 		_lowerCamelCase      (		self							:					Dict):


           '''simple docstring'''

           __a							=    [np.random.randint(255					,		size=(3, 30, 400)					,		dtype=np.uinta)]

           __a							=    [Image.fromarray(np.moveaxis(__SCREAMING_SNAKE_CASE					,		0					,		-1)) for x in image_inputs]

           return image_inputs



       def 		_lowerCamelCase      (		self							:					Dict):


           '''simple docstring'''

           __a							=    self.get_tokenizer()
           __a							=    self.get_rust_tokenizer()
           __a							=    self.get_image_processor()

           __a							=    CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE					,		image_processor=__SCREAMING_SNAKE_CASE)
           processor_slow.save_pretrained(self.tmpdirname)
           __a							=    CLIPSegProcessor.from_pretrained(self.tmpdirname					,		use_fast=__SCREAMING_SNAKE_CASE)

           __a							=    CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE					,		image_processor=__SCREAMING_SNAKE_CASE)
           processor_fast.save_pretrained(self.tmpdirname)
           __a							=    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					,		__SCREAMING_SNAKE_CASE)
           self.assertIsInstance(processor_fast.tokenizer					,		__SCREAMING_SNAKE_CASE)

           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					,		__SCREAMING_SNAKE_CASE)
           self.assertIsInstance(processor_fast.image_processor					,		__SCREAMING_SNAKE_CASE)



       def 		_lowerCamelCase      (		self							:					str):


           '''simple docstring'''

           __a							=    CLIPSegProcessor(tokenizer=self.get_tokenizer()					,		image_processor=self.get_image_processor())
           processor.save_pretrained(self.tmpdirname)

           __a							=    self.get_tokenizer(bos_token='''(BOS)'''					,		eos_token='''(EOS)''')
           __a							=    self.get_image_processor(do_normalize=__SCREAMING_SNAKE_CASE					,		padding_value=1.0)

           __a							=    CLIPSegProcessor.from_pretrained(
               self.tmpdirname					,		bos_token='''(BOS)'''					,		eos_token='''(EOS)'''					,		do_normalize=__SCREAMING_SNAKE_CASE					,		padding_value=1.0)

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

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



       def 		_lowerCamelCase      (		self							:					int):


           '''simple docstring'''

           __a							=    self.get_image_processor()
           __a							=    self.get_tokenizer()

           __a							=    CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE					,		image_processor=__SCREAMING_SNAKE_CASE)

           __a							=    self.prepare_image_inputs()

           __a							=    image_processor(__SCREAMING_SNAKE_CASE					,		return_tensors='''np''')
           __a							=    processor(images=__SCREAMING_SNAKE_CASE					,		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 		_lowerCamelCase      (		self							:					Union[str, Any]):


           '''simple docstring'''

           __a							=    self.get_image_processor()
           __a							=    self.get_tokenizer()

           __a							=    CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE					,		image_processor=__SCREAMING_SNAKE_CASE)

           __a							=    '''lower newer'''

           __a							=    processor(text=__SCREAMING_SNAKE_CASE)

           __a							=    tokenizer(__SCREAMING_SNAKE_CASE)

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



       def 		_lowerCamelCase      (		self							:					str):


           '''simple docstring'''

           __a							=    self.get_image_processor()
           __a							=    self.get_tokenizer()

           __a							=    CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE					,		image_processor=__SCREAMING_SNAKE_CASE)

           __a							=    '''lower newer'''
           __a							=    self.prepare_image_inputs()

           __a							=    processor(text=__SCREAMING_SNAKE_CASE					,		images=__SCREAMING_SNAKE_CASE)

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

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



       def 		_lowerCamelCase      (		self							:					List[str]):


           '''simple docstring'''

           __a							=    self.get_image_processor()
           __a							=    self.get_tokenizer()

           __a							=    CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE					,		image_processor=__SCREAMING_SNAKE_CASE)

           __a							=    self.prepare_image_inputs()
           __a							=    self.prepare_image_inputs()

           __a							=    processor(images=__SCREAMING_SNAKE_CASE					,		visual_prompt=__SCREAMING_SNAKE_CASE)

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

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





       def 		_lowerCamelCase      (		self							:					str):


           '''simple docstring'''

           __a							=    self.get_image_processor()
           __a							=    self.get_tokenizer()

           __a							=    CLIPSegProcessor(tokenizer=__SCREAMING_SNAKE_CASE					,		image_processor=__SCREAMING_SNAKE_CASE)

           __a							=    [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

           __a							=    processor.batch_decode(__SCREAMING_SNAKE_CASE)
           __a							=    tokenizer.batch_decode(__SCREAMING_SNAKE_CASE)

           self.assertListEqual(__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE)










import unittest

from transformers import DonutProcessor


__snake_case						:List[str]						=					'''naver-clova-ix/donut-base'''

class    _A	(     unittest.TestCase   ):



       def 		_lowerCamelCase      (		self							:					List[str]):


           '''simple docstring'''

           __a							=    DonutProcessor.from_pretrained(__SCREAMING_SNAKE_CASE)





       def 		_lowerCamelCase      (		self							:					Tuple):


           '''simple docstring'''

           __a							=    {
               '''name''': '''John Doe''',
               '''age''': '''99''',
               '''city''': '''Atlanta''',
               '''state''': '''GA''',
               '''zip''': '''30301''',
               '''phone''': '''123-4567''',
               '''nicknames''': [{'''nickname''': '''Johnny'''}, {'''nickname''': '''JD'''}],
           }

           __a							=    (
               '''<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>'''
               '''<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>'''
               '''<s_nicknames><s_nickname>Johnny</s_nickname>'''
               '''<sep/><s_nickname>JD</s_nickname></s_nicknames>'''
           )
           __a							=    self.processor.tokenajson(__SCREAMING_SNAKE_CASE)

           self.assertDictEqual(__SCREAMING_SNAKE_CASE					,		__SCREAMING_SNAKE_CASE)





