





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 OwlViTImageProcessor, OwlViTProcessor
@require_vision
class SCREAMING_SNAKE_CASE_  (    unittest.TestCase    ):






						def UpperCAmelCase_ (					self					:					List[str]		)							->			int:







							"""simple docstring"""


							snake_case_						:	int      =		tempfile.mkdtemp()

							# fmt: off
							snake_case_						:	Tuple      =		['''''', '''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
							snake_case_						:	List[Any]      =		dict(zip(lowerCAmelCase__						,      range(len(lowerCAmelCase__		)		)		)		)
							snake_case_						:	Optional[Any]      =		['''#version: 0.2''', '''l o''', '''lo w</w>''', '''e r</w>''', '''''']
							snake_case_						:	List[str]      =		{'''unk_token''': '''<unk>'''}

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

							snake_case_						:	Optional[Any]      =		{
							    '''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],
							}
							snake_case_						:	List[str]      =		os.path.join(self.tmpdirname						,      lowerCAmelCase__		)
							with open(self.image_processor_file						,      'w'						,      encoding='utf-8'		) as fp:
								json.dump(lowerCAmelCase__						,      lowerCAmelCase__		)






						def UpperCAmelCase_ (					self					:					List[Any]						,      **_A					:					Dict		)							->			Dict:







							"""simple docstring"""


							return CLIPTokenizer.from_pretrained(self.tmpdirname						,      pad_token='!'						,      **lowerCAmelCase__		)






						def UpperCAmelCase_ (					self					:					Union[str, Any]						,      **_A					:					Any		)							->			str:







							"""simple docstring"""


							return CLIPTokenizerFast.from_pretrained(self.tmpdirname						,      pad_token='!'						,      **lowerCAmelCase__		)






						def UpperCAmelCase_ (					self					:					Optional[Any]						,      **_A					:					int		)							->			Optional[int]:







							"""simple docstring"""


							return OwlViTImageProcessor.from_pretrained(self.tmpdirname						,      **lowerCAmelCase__		)






						def UpperCAmelCase_ (					self					:					Tuple		)							->			str:







							"""simple docstring"""


							shutil.rmtree(self.tmpdirname		)






						def UpperCAmelCase_ (					self					:					Optional[int]		)							->			Any:







							"""simple docstring"""


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

							snake_case_						:	int      =		[Image.fromarray(np.moveaxis(lowerCAmelCase__						,      0						,      -1		)		) for x in image_inputs]

							return image_inputs






						def UpperCAmelCase_ (					self					:					List[str]		)							->			int:







							"""simple docstring"""


							snake_case_						:	int      =		self.get_tokenizer()
							snake_case_						:	Tuple      =		self.get_rust_tokenizer()
							snake_case_						:	List[str]      =		self.get_image_processor()

							snake_case_						:	str      =		OwlViTProcessor(tokenizer=lowerCAmelCase__						,      image_processor=lowerCAmelCase__		)
							processor_slow.save_pretrained(self.tmpdirname		)
							snake_case_						:	Union[str, Any]      =		OwlViTProcessor.from_pretrained(self.tmpdirname						,      use_fast=lowerCAmelCase__		)

							snake_case_						:	List[str]      =		OwlViTProcessor(tokenizer=lowerCAmelCase__						,      image_processor=lowerCAmelCase__		)
							processor_fast.save_pretrained(self.tmpdirname		)
							snake_case_						:	List[Any]      =		OwlViTProcessor.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						,      lowerCAmelCase__		)
							self.assertIsInstance(processor_fast.tokenizer						,      lowerCAmelCase__		)

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






						def UpperCAmelCase_ (					self					:					Optional[Any]		)							->			Tuple:







							"""simple docstring"""


							snake_case_						:	Optional[Any]      =		OwlViTProcessor(tokenizer=self.get_tokenizer()						,      image_processor=self.get_image_processor()		)
							processor.save_pretrained(self.tmpdirname		)

							snake_case_						:	Any      =		self.get_tokenizer(bos_token='(BOS)'						,      eos_token='(EOS)'		)
							snake_case_						:	int      =		self.get_image_processor(do_normalize=lowerCAmelCase__		)

							snake_case_						:	str      =		OwlViTProcessor.from_pretrained(
							    self.tmpdirname						,      bos_token='(BOS)'						,      eos_token='(EOS)'						,      do_normalize=lowerCAmelCase__		)

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

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






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







							"""simple docstring"""


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

							snake_case_						:	Dict      =		OwlViTProcessor(tokenizer=lowerCAmelCase__						,      image_processor=lowerCAmelCase__		)

							snake_case_						:	Union[str, Any]      =		self.prepare_image_inputs()

							snake_case_						:	Tuple      =		image_processor(lowerCAmelCase__						,      return_tensors='np'		)
							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 UpperCAmelCase_ (					self					:					Union[str, Any]		)							->			Union[str, Any]:







							"""simple docstring"""


							snake_case_						:	Dict      =		self.get_image_processor()
							snake_case_						:	Any      =		self.get_tokenizer()

							snake_case_						:	Dict      =		OwlViTProcessor(tokenizer=lowerCAmelCase__						,      image_processor=lowerCAmelCase__		)

							snake_case_						:	Optional[int]      =		'''lower newer'''

							snake_case_						:	Dict      =		processor(text=lowerCAmelCase__						,      return_tensors='np'		)

							snake_case_						:	Optional[int]      =		tokenizer(lowerCAmelCase__						,      return_tensors='np'		)

							for key in encoded_tok.keys():
								self.assertListEqual(encoded_tok[key][0].tolist()						,      encoded_processor[key][0].tolist()		)






						def UpperCAmelCase_ (					self					:					str		)							->			str:







							"""simple docstring"""


							snake_case_						:	Tuple      =		self.get_image_processor()
							snake_case_						:	Tuple      =		self.get_tokenizer()

							snake_case_						:	Union[str, Any]      =		OwlViTProcessor(tokenizer=lowerCAmelCase__						,      image_processor=lowerCAmelCase__		)

							snake_case_						:	Optional[Any]      =		'''lower newer'''
							snake_case_						:	Any      =		self.prepare_image_inputs()

							snake_case_						:	List[Any]      =		processor(text=lowerCAmelCase__						,      images=lowerCAmelCase__		)

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

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






						def UpperCAmelCase_ (					self					:					Any		)							->			Tuple:







							"""simple docstring"""


							snake_case_						:	Optional[Any]      =		'''google/owlvit-base-patch32'''
							snake_case_						:	str      =		OwlViTProcessor.from_pretrained(lowerCAmelCase__		)

							snake_case_						:	Optional[int]      =		['''cat''', '''nasa badge''']
							snake_case_						:	Dict      =		processor(text=lowerCAmelCase__		)

							snake_case_						:	Optional[Any]      =		16
							self.assertListEqual(list(inputs.keys()		)						,      ['input_ids', 'attention_mask']		)
							self.assertEqual(inputs['input_ids'].shape						,      (2, seq_length)		)

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






						def UpperCAmelCase_ (					self					:					List[str]		)							->			Optional[int]:







							"""simple docstring"""


							snake_case_						:	Optional[int]      =		'''google/owlvit-base-patch32'''
							snake_case_						:	Dict      =		OwlViTProcessor.from_pretrained(lowerCAmelCase__		)

							snake_case_						:	Any      =		[['''cat''', '''nasa badge'''], ['''person''']]
							snake_case_						:	Optional[int]      =		processor(text=lowerCAmelCase__		)

							snake_case_						:	List[Any]      =		16
							snake_case_						:	List[str]      =		len(lowerCAmelCase__		)
							snake_case_						:	Dict      =		max([len(lowerCAmelCase__		) for texts in input_texts]		)

							self.assertListEqual(list(inputs.keys()		)						,      ['input_ids', 'attention_mask']		)
							self.assertEqual(inputs['input_ids'].shape						,      (batch_size * num_max_text_queries, seq_length)		)

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






						def UpperCAmelCase_ (					self					:					Tuple		)							->			List[Any]:







							"""simple docstring"""


							snake_case_						:	Dict      =		'''google/owlvit-base-patch32'''
							snake_case_						:	Any      =		OwlViTProcessor.from_pretrained(lowerCAmelCase__		)

							snake_case_						:	Any      =		['''cat''', '''nasa badge''']
							snake_case_						:	Union[str, Any]      =		processor(text=lowerCAmelCase__		)

							snake_case_						:	str      =		16
							snake_case_						:	List[str]      =		inputs['''input_ids''']
							snake_case_						:	Union[str, Any]      =		[
							    [49406, 2368, 49407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
							    [49406, 6841, 11301, 49407, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
							]

							self.assertListEqual(list(inputs.keys()		)						,      ['input_ids', 'attention_mask']		)
							self.assertEqual(inputs['input_ids'].shape						,      (2, seq_length)		)
							self.assertListEqual(list(input_ids[0]		)						,      predicted_ids[0]		)
							self.assertListEqual(list(input_ids[1]		)						,      predicted_ids[1]		)






						def UpperCAmelCase_ (					self					:					str		)							->			str:







							"""simple docstring"""


							snake_case_						:	Any      =		self.get_image_processor()
							snake_case_						:	List[str]      =		self.get_tokenizer()

							snake_case_						:	Any      =		OwlViTProcessor(tokenizer=lowerCAmelCase__						,      image_processor=lowerCAmelCase__		)

							snake_case_						:	Optional[Any]      =		self.prepare_image_inputs()
							snake_case_						:	Optional[Any]      =		self.prepare_image_inputs()

							snake_case_						:	int      =		processor(images=lowerCAmelCase__						,      query_images=lowerCAmelCase__		)

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

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






						def UpperCAmelCase_ (					self					:					Optional[Any]		)							->			Tuple:







							"""simple docstring"""


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

							snake_case_						:	List[str]      =		OwlViTProcessor(tokenizer=lowerCAmelCase__						,      image_processor=lowerCAmelCase__		)

							snake_case_						:	Any      =		[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

							snake_case_						:	str      =		processor.batch_decode(lowerCAmelCase__		)
							snake_case_						:	List[Any]      =		tokenizer.batch_decode(lowerCAmelCase__		)

							self.assertListEqual(lowerCAmelCase__						,      lowerCAmelCase__		)





from ..utils import DummyObject, requires_backends
class        _lowercase      (			metaclass=A__       ):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE__				:			Optional[int]						=		['''keras_nlp''']


				def __init__(       self			:Tuple			,			*lowerCAmelCase__			:Optional[Any]			,			**lowerCAmelCase__			:Dict	)		->			Dict:
										requires_backends(self			,			['''keras_nlp''']	)
