





'''simple docstring'''




import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
							import torch


if is_vision_available():
							from PIL import Image

							from transformers import MgpstrProcessor, ViTImageProcessor




@require_torch
@require_vision
class      UpperCamelCase__					(					unittest.TestCase			):




					"""simple docstring"""
					SCREAMING_SNAKE_CASE__				=	ViTImageProcessor if is_vision_available() else None


					@property
					def lowerCamelCase_			(						self				:			List[Any]						):

							'''simple docstring'''



							return self.image_processor_tester.prepare_image_processor_dict()


					def lowerCamelCase_			(						self				:			int						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Dict		=			(3, 32, 1_28)
							SCREAMING_SNAKE_CASE :				List[str]		=			tempfile.mkdtemp()

							# fmt: off
							SCREAMING_SNAKE_CASE :				List[Any]		=			["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
							# fmt: on
							SCREAMING_SNAKE_CASE :				List[Any]		=			dict(zip(lowerCamelCase_      ,						range(len(lowerCamelCase_						)						)						)						)

							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			os.path.join(self.tmpdirname      ,						VOCAB_FILES_NAMES["""vocab_file"""]						)
							with open(self.vocab_file      ,						"""w"""      ,						encoding="""utf-8"""						) as fp:
									fp.write(json.dumps(lowerCamelCase_						) + """\n"""						)

							SCREAMING_SNAKE_CASE :				Any		=			{
							    """do_normalize""": False,
							    """do_resize""": True,
							    """image_processor_type""": """ViTImageProcessor""",
							    """resample""": 3,
							    """size""": {"""height""": 32, """width""": 1_28},
							}
							SCREAMING_SNAKE_CASE :				str		=			os.path.join(self.tmpdirname      ,						lowerCamelCase_						)
							with open(self.image_processor_file      ,						"""w"""      ,						encoding="""utf-8"""						) as fp:
									json.dump(lowerCamelCase_      ,						lowerCamelCase_						)


					def lowerCamelCase_			(						self				:			Dict      ,						**lowerCamelCase_				:			Optional[int]						):

							'''simple docstring'''



							return MgpstrTokenizer.from_pretrained(self.tmpdirname      ,						**lowerCamelCase_						)


					def lowerCamelCase_			(						self				:			Optional[Any]      ,						**lowerCamelCase_				:			Optional[Any]						):

							'''simple docstring'''



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


					def lowerCamelCase_			(						self				:			Tuple						):

							'''simple docstring'''



							shutil.rmtree(self.tmpdirname						)


					def lowerCamelCase_			(						self				:			Optional[Any]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				List[Any]		=			np.random.randint(2_55      ,						size=(3, 30, 4_00)      ,						dtype=np.uinta						)

							SCREAMING_SNAKE_CASE :				int		=			Image.fromarray(np.moveaxis(lowerCamelCase_      ,						0      ,						-1						)						)

							return image_input


					def lowerCamelCase_			(						self				:			List[str]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Tuple		=			self.get_tokenizer()
							SCREAMING_SNAKE_CASE :				str		=			self.get_image_processor()

							SCREAMING_SNAKE_CASE :				Any		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)
							processor.save_pretrained(self.tmpdirname						)
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			MgpstrProcessor.from_pretrained(self.tmpdirname      ,						use_fast=lowerCamelCase_						)

							self.assertEqual(processor.char_tokenizer.get_vocab()      ,						tokenizer.get_vocab()						)
							self.assertIsInstance(processor.char_tokenizer      ,						lowerCamelCase_						)

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


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

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			self.get_tokenizer()
							SCREAMING_SNAKE_CASE :				List[str]		=			self.get_image_processor()

							SCREAMING_SNAKE_CASE :				Optional[Any]		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)
							processor.save_pretrained(self.tmpdirname						)

							SCREAMING_SNAKE_CASE :				Dict		=			self.get_tokenizer(bos_token="""(BOS)"""      ,						eos_token="""(EOS)"""						)
							SCREAMING_SNAKE_CASE :				str		=			self.get_image_processor(do_normalize=lowerCamelCase_      ,						padding_value=1.0						)

							SCREAMING_SNAKE_CASE :				List[str]		=			MgpstrProcessor.from_pretrained(
							    self.tmpdirname      ,						bos_token="""(BOS)"""      ,						eos_token="""(EOS)"""      ,						do_normalize=lowerCamelCase_      ,						padding_value=1.0						)

							self.assertEqual(processor.char_tokenizer.get_vocab()      ,						tokenizer_add_kwargs.get_vocab()						)
							self.assertIsInstance(processor.char_tokenizer      ,						lowerCamelCase_						)

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


					def lowerCamelCase_			(						self				:			Optional[Any]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				List[str]		=			self.get_image_processor()
							SCREAMING_SNAKE_CASE :				Dict		=			self.get_tokenizer()

							SCREAMING_SNAKE_CASE :				Optional[int]		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Dict		=			self.prepare_image_inputs()

							SCREAMING_SNAKE_CASE :				Dict		=			image_processor(lowerCamelCase_      ,						return_tensors="""np"""						)
							SCREAMING_SNAKE_CASE :				Any		=			processor(images=lowerCamelCase_      ,						return_tensors="""np"""						)

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


					def lowerCamelCase_			(						self				:			Optional[Any]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				int		=			self.get_image_processor()
							SCREAMING_SNAKE_CASE :				Optional[Any]		=			self.get_tokenizer()

							SCREAMING_SNAKE_CASE :				str		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Any		=			"""test"""

							SCREAMING_SNAKE_CASE :				Dict		=			processor(text=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Tuple		=			tokenizer(lowerCamelCase_						)
							for key in encoded_tok.keys():
									self.assertListEqual(encoded_tok[key]      ,						encoded_processor[key]						)


					def lowerCamelCase_			(						self				:			Optional[Any]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Optional[int]		=			self.get_image_processor()
							SCREAMING_SNAKE_CASE :				str		=			self.get_tokenizer()

							SCREAMING_SNAKE_CASE :				List[Any]		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Optional[Any]		=			"""test"""
							SCREAMING_SNAKE_CASE :				Any		=			self.prepare_image_inputs()

							SCREAMING_SNAKE_CASE :				Tuple		=			processor(text=lowerCamelCase_      ,						images=lowerCamelCase_						)

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

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


					def lowerCamelCase_			(						self				:			str						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			self.get_image_processor()
							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			self.get_tokenizer()

							SCREAMING_SNAKE_CASE :				Dict		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9], [3, 4, 3, 1, 1, 8, 9]]

							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			processor.char_decode(lowerCamelCase_						)
							SCREAMING_SNAKE_CASE :				List[Any]		=			tokenizer.batch_decode(lowerCamelCase_						)
							SCREAMING_SNAKE_CASE :				List[str]		=			[seq.replace(""" """      ,						""""""						) for seq in decoded_tok]

							self.assertListEqual(lowerCamelCase_      ,						lowerCamelCase_						)


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

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				int		=			self.get_image_processor()
							SCREAMING_SNAKE_CASE :				Optional[int]		=			self.get_tokenizer()

							SCREAMING_SNAKE_CASE :				Any		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Dict		=			None
							SCREAMING_SNAKE_CASE :				List[Any]		=			self.prepare_image_inputs()

							SCREAMING_SNAKE_CASE :				List[Any]		=			processor(text=lowerCamelCase_      ,						images=lowerCamelCase_						)

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



					def lowerCamelCase_			(						self				:			int						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				List[str]		=			self.get_image_processor()
							SCREAMING_SNAKE_CASE :				Optional[int]		=			self.get_tokenizer()

							SCREAMING_SNAKE_CASE :				Tuple		=			MgpstrProcessor(tokenizer=lowerCamelCase_      ,						image_processor=lowerCamelCase_						)

							SCREAMING_SNAKE_CASE :				Union[str, Any]		=			torch.randn(1      ,						27      ,						38						)
							SCREAMING_SNAKE_CASE :				Any		=			torch.randn(1      ,						27      ,						5_02_57						)
							SCREAMING_SNAKE_CASE :				List[str]		=			torch.randn(1      ,						27      ,						3_05_22						)

							SCREAMING_SNAKE_CASE :				str		=			processor.batch_decode([char_input, bpe_input, wp_input]						)

							self.assertListEqual(list(results.keys()						)      ,						["""generated_text""", """scores""", """char_preds""", """bpe_preds""", """wp_preds"""]						)










'''simple docstring'''




import unittest

from transformers import DonutProcessor


__UpperCAmelCase            =       """naver-clova-ix/donut-base"""




class      UpperCamelCase__					(					unittest.TestCase			):




					"""simple docstring"""


					def lowerCamelCase_			(						self				:			List[str]						):

							'''simple docstring'''



							SCREAMING_SNAKE_CASE :				Any		=			DonutProcessor.from_pretrained(lowerCamelCase_						)



					def lowerCamelCase_			(						self				:			Tuple						):

							'''simple docstring'''



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

							SCREAMING_SNAKE_CASE :				List[Any]		=			(
							    """<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>"""
							)
							SCREAMING_SNAKE_CASE :				List[Any]		=			self.processor.tokenajson(lowerCamelCase_						)

							self.assertDictEqual(lowerCamelCase_      ,						lowerCamelCase_						)



