




'''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      lowerCAmelCase (			unittest.TestCase):


       def    lowerCAmelCase   ( self	)   ->	int:



            '''simple docstring'''




            __snake_case            =	tempfile.mkdtemp()

            # fmt: off
            __snake_case            =	['''[UNK]''', '''[CLS]''', '''[SEP]''', '''[PAD]''', '''[MASK]''', '''want''', '''##want''', '''##ed''', '''wa''', '''un''', '''runn''', '''##ing''', ''',''', '''low''', '''lowest''']
            # fmt: on
            __snake_case            =	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]	)	)

            __snake_case            =	{
                '''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],
            }
            __snake_case            =	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     ,	**__SCREAMING_SNAKE_CASE	)   ->	int:



            '''simple docstring'''




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


       def    lowerCAmelCase   ( self     ,	**__SCREAMING_SNAKE_CASE	)   ->	Tuple:



            '''simple docstring'''




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


       def    lowerCAmelCase   ( self	)   ->	str:



            '''simple docstring'''




            shutil.rmtree(self.tmpdirname	)


       def    lowerCAmelCase   ( self	)   ->	Tuple:



            '''simple docstring'''




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

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

            return image_inputs


       def    lowerCAmelCase   ( self	)   ->	Optional[Any]:



            '''simple docstring'''




            __snake_case            =	self.get_tokenizer()
            __snake_case            =	self.get_image_processor()

            __snake_case            =	VisionTextDualEncoderProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,	image_processor=__SCREAMING_SNAKE_CASE	)

            processor.save_pretrained(self.tmpdirname	)
            __snake_case            =	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     ,	__SCREAMING_SNAKE_CASE	)


       def    lowerCAmelCase   ( self	)   ->	List[str]:



            '''simple docstring'''




            __snake_case            =	VisionTextDualEncoderProcessor(
                tokenizer=self.get_tokenizer()     ,	image_processor=self.get_image_processor()	)
            processor.save_pretrained(self.tmpdirname	)

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

            __snake_case            =	VisionTextDualEncoderProcessor.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     ,	(BertTokenizer, BertTokenizerFast)	)

            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'''




            __snake_case            =	self.get_image_processor()
            __snake_case            =	self.get_tokenizer()

            __snake_case            =	VisionTextDualEncoderProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,	image_processor=__SCREAMING_SNAKE_CASE	)

            __snake_case            =	self.prepare_image_inputs()

            __snake_case            =	image_processor(__SCREAMING_SNAKE_CASE     ,	return_tensors='''np'''	)
            __snake_case            =	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	)   ->	List[str]:



            '''simple docstring'''




            __snake_case            =	self.get_image_processor()
            __snake_case            =	self.get_tokenizer()

            __snake_case            =	VisionTextDualEncoderProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,	image_processor=__SCREAMING_SNAKE_CASE	)

            __snake_case            =	'''lower newer'''

            __snake_case            =	processor(text=__SCREAMING_SNAKE_CASE	)

            __snake_case            =	tokenizer(__SCREAMING_SNAKE_CASE	)

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


       def    lowerCAmelCase   ( self	)   ->	Union[str, Any]:



            '''simple docstring'''




            __snake_case            =	self.get_image_processor()
            __snake_case            =	self.get_tokenizer()

            __snake_case            =	VisionTextDualEncoderProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,	image_processor=__SCREAMING_SNAKE_CASE	)

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

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

            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(__SCREAMING_SNAKE_CASE	):
                 processor()


       def    lowerCAmelCase   ( self	)   ->	Union[str, Any]:



            '''simple docstring'''




            __snake_case            =	self.get_image_processor()
            __snake_case            =	self.get_tokenizer()

            __snake_case            =	VisionTextDualEncoderProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,	image_processor=__SCREAMING_SNAKE_CASE	)

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

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

            self.assertListEqual(__SCREAMING_SNAKE_CASE     ,	__SCREAMING_SNAKE_CASE	)




       def    lowerCAmelCase   ( self	)   ->	List[str]:



            '''simple docstring'''




            __snake_case            =	self.get_image_processor()
            __snake_case            =	self.get_tokenizer()

            __snake_case            =	VisionTextDualEncoderProcessor(tokenizer=__SCREAMING_SNAKE_CASE     ,	image_processor=__SCREAMING_SNAKE_CASE	)

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

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

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







'''simple docstring'''




import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
						import torch

						from transformers.generation import DisjunctiveConstraint






@require_torch
class 							a__(   unittest.TestCase      ):


			'''simple docstring'''






			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2, 4], [1, 2, 3, 4]]
					lowerCAmelCase     =    DisjunctiveConstraint(__lowerCAmelCase)
					self.assertTrue(isinstance(dc.token_ids			,       __lowerCAmelCase))

					with self.assertRaises(__lowerCAmelCase):
							DisjunctiveConstraint(torch.LongTensor([[1, 2, 4], [1, 2, 3]]))

					with self.assertRaises(__lowerCAmelCase):
							DisjunctiveConstraint([torch.LongTensor([1, 2, 4]), torch.LongTensor([1, 2, 3, 4, 5])])



			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2], [1, 2, 3, 4]]

					with self.assertRaises(__lowerCAmelCase):
							DisjunctiveConstraint(__lowerCAmelCase)  # fails here



			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2, 3], [1, 2, 4]]

					lowerCAmelCase     =    DisjunctiveConstraint(__lowerCAmelCase)

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(1)
					lowerCAmelCase     =    stepped is True and completed is False and reset is False
					self.assertTrue(__lowerCAmelCase)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(2)
					lowerCAmelCase     =    stepped is True and completed is False and reset is False
					self.assertTrue(__lowerCAmelCase)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1, 2])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(3)
					lowerCAmelCase     =    stepped is True and completed is True and reset is False
					self.assertTrue(__lowerCAmelCase)
					self.assertTrue(dc.completed)  # Completed!
					self.assertTrue(dc.current_seq == [1, 2, 3])







			def 				a_			(  self):




					"""simple docstring"""


					lowerCAmelCase     =    [[1, 2, 3], [1, 2, 4, 5], [1, 2, 5]]

					lowerCAmelCase     =    DisjunctiveConstraint(__lowerCAmelCase)

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(1)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(2)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1, 2])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(4)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.current_seq == [1, 2, 4])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(5)
					self.assertTrue(dc.completed)  # Completed!
					self.assertTrue(dc.current_seq == [1, 2, 4, 5])

					dc.reset()

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(1)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.remaining() == 3)
					self.assertTrue(dc.current_seq == [1])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(2)
					self.assertTrue(not dc.completed)
					self.assertTrue(dc.remaining() == 2)
					self.assertTrue(dc.current_seq == [1, 2])

					lowerCAmelCase   ,	lowerCAmelCase   ,	lowerCAmelCase     =    dc.update(5)
					self.assertTrue(dc.completed)  # Completed!
					self.assertTrue(dc.remaining() == 0)
					self.assertTrue(dc.current_seq == [1, 2, 5])




