




'''simple docstring'''





import unittest

from transformers import DonutProcessor


_SCREAMING_SNAKE_CASE							:   List[Any]      		= "naver-clova-ix/donut-base"




class  _snake_case		(	unittest.TestCase							):




			def    lowerCAmelCase__				(					self							)				->				Optional[int]:

										'''simple docstring'''




										snake_case_						=      DonutProcessor.from_pretrained(a__							)




			def    lowerCAmelCase__				(					self							)				->				str:

										'''simple docstring'''




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

										snake_case_						=      (
										    "<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>"
										)
										snake_case_						=      self.processor.tokenajson(a__							)

										self.assertDictEqual(a__				,							a__							)












'''simple docstring'''







import json
import os
import shutil
import tempfile
import unittest

import numpy as np

from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_vision_available


if is_vision_available():
			from PIL import Image

			from transformers import VisionTextDualEncoderProcessor, ViTImageProcessor

@require_tokenizers
@require_vision
class _lowercase	(				unittest.TestCase		):




							def 		lowerCamelCase_				(							self:				Dict     ):
														lowerCamelCase__					:	int         =       tempfile.mkdtemp()

														# fmt: off
														lowerCamelCase__					:	int         =       ["""[UNK]""", """[CLS]""", """[SEP]""", """[PAD]""", """[MASK]""", """want""", """##want""", """##ed""", """wa""", """un""", """runn""", """##ing""", """,""", """low""", """lowest"""]
														# fmt: on
														lowerCamelCase__					:	Union[str, Any]         =       os.path.join(self.tmpdirname			,							VOCAB_FILES_NAMES["""vocab_file"""]     )
														with open(self.vocab_file			,							"""w"""			,							encoding="""utf-8"""     ) as vocab_writer:
																					vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]     )     )

														lowerCamelCase__					:	Tuple         =       {
														    """do_resize""": True,
														    """size""": {"""height""": 18, """width""": 18},
														    """do_normalize""": True,
														    """image_mean""": [0.5, 0.5, 0.5],
														    """image_std""": [0.5, 0.5, 0.5],
														}
														lowerCamelCase__					:	Tuple         =       os.path.join(self.tmpdirname			,							UpperCamelCase__     )
														with open(self.image_processor_file			,							"""w"""			,							encoding="""utf-8"""     ) as fp:
																					json.dump(UpperCamelCase__			,							UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				str			,							**UpperCamelCase__:				List[str]     ):
														return BertTokenizer.from_pretrained(self.tmpdirname			,							**UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				int			,							**UpperCamelCase__:				Tuple     ):
														return ViTImageProcessor.from_pretrained(self.tmpdirname			,							**UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Optional[Any]     ):
														shutil.rmtree(self.tmpdirname     )




							def 		lowerCamelCase_				(							self:				Any     ):
														lowerCamelCase__					:	List[Any]         =       [np.random.randint(255			,							size=(3, 30, 400)			,							dtype=np.uinta     )]

														lowerCamelCase__					:	Tuple         =       [Image.fromarray(np.moveaxis(UpperCamelCase__			,							0			,							-1     )     ) for x in image_inputs]

														return image_inputs




							def 		lowerCamelCase_				(							self:				int     ):
														lowerCamelCase__					:	Optional[Any]         =       self.get_tokenizer()
														lowerCamelCase__					:	Dict         =       self.get_image_processor()

														lowerCamelCase__					:	Optional[Any]         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														processor.save_pretrained(self.tmpdirname     )
														lowerCamelCase__					:	int         =       VisionTextDualEncoderProcessor.from_pretrained(self.tmpdirname     )

														self.assertEqual(processor.tokenizer.get_vocab()			,							tokenizer.get_vocab()     )
														self.assertIsInstance(processor.tokenizer			,							(BertTokenizer, BertTokenizerFast)     )

														self.assertEqual(processor.image_processor.to_json_string()			,							image_processor.to_json_string()     )
														self.assertIsInstance(processor.image_processor			,							UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				Tuple     ):
														lowerCamelCase__					:	Dict         =       VisionTextDualEncoderProcessor(
														    tokenizer=self.get_tokenizer()			,							image_processor=self.get_image_processor()     )
														processor.save_pretrained(self.tmpdirname     )

														lowerCamelCase__					:	int         =       self.get_tokenizer(bos_token="""(BOS)"""			,							eos_token="""(EOS)"""     )
														lowerCamelCase__					:	List[Any]         =       self.get_image_processor(do_normalize=UpperCamelCase__			,							padding_value=1.0     )

														lowerCamelCase__					:	Tuple         =       VisionTextDualEncoderProcessor.from_pretrained(
														    self.tmpdirname			,							bos_token="""(BOS)"""			,							eos_token="""(EOS)"""			,							do_normalize=UpperCamelCase__			,							padding_value=1.0     )

														self.assertEqual(processor.tokenizer.get_vocab()			,							tokenizer_add_kwargs.get_vocab()     )
														self.assertIsInstance(processor.tokenizer			,							(BertTokenizer, BertTokenizerFast)     )

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




							def 		lowerCamelCase_				(							self:				Union[str, Any]     ):
														lowerCamelCase__					:	Optional[Any]         =       self.get_image_processor()
														lowerCamelCase__					:	Union[str, Any]         =       self.get_tokenizer()

														lowerCamelCase__					:	Any         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	List[Any]         =       self.prepare_image_inputs()

														lowerCamelCase__					:	List[str]         =       image_processor(UpperCamelCase__			,							return_tensors="""np"""     )
														lowerCamelCase__					:	Optional[Any]         =       processor(images=UpperCamelCase__			,							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:				Optional[int]     ):
														lowerCamelCase__					:	Any         =       self.get_image_processor()
														lowerCamelCase__					:	List[str]         =       self.get_tokenizer()

														lowerCamelCase__					:	List[Any]         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	List[Any]         =       """lower newer"""

														lowerCamelCase__					:	Union[str, Any]         =       processor(text=UpperCamelCase__     )

														lowerCamelCase__					:	Any         =       tokenizer(UpperCamelCase__     )

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




							def 		lowerCamelCase_				(							self:				Dict     ):
														lowerCamelCase__					:	Optional[Any]         =       self.get_image_processor()
														lowerCamelCase__					:	List[Any]         =       self.get_tokenizer()

														lowerCamelCase__					:	List[Any]         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	Any         =       """lower newer"""
														lowerCamelCase__					:	Dict         =       self.prepare_image_inputs()

														lowerCamelCase__					:	Tuple         =       processor(text=UpperCamelCase__			,							images=UpperCamelCase__     )

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

														# test if it raises when no input is passed
														with self.assertRaises(UpperCamelCase__     ):
																					processor()




							def 		lowerCamelCase_				(							self:				int     ):
														lowerCamelCase__					:	List[str]         =       self.get_image_processor()
														lowerCamelCase__					:	List[str]         =       self.get_tokenizer()

														lowerCamelCase__					:	int         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

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

														lowerCamelCase__					:	Union[str, Any]         =       processor.batch_decode(UpperCamelCase__     )
														lowerCamelCase__					:	Dict         =       tokenizer.batch_decode(UpperCamelCase__     )

														self.assertListEqual(UpperCamelCase__			,							UpperCamelCase__     )




							def 		lowerCamelCase_				(							self:				List[str]     ):
														lowerCamelCase__					:	Any         =       self.get_image_processor()
														lowerCamelCase__					:	Union[str, Any]         =       self.get_tokenizer()

														lowerCamelCase__					:	int         =       VisionTextDualEncoderProcessor(tokenizer=UpperCamelCase__			,							image_processor=UpperCamelCase__     )

														lowerCamelCase__					:	Optional[Any]         =       """lower newer"""
														lowerCamelCase__					:	str         =       self.prepare_image_inputs()

														lowerCamelCase__					:	int         =       processor(text=UpperCamelCase__			,							images=UpperCamelCase__     )

														self.assertListEqual(list(inputs.keys()     )			,							processor.model_input_names     )

