
from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType





class       __A(				UpperCAmelCase       ):
					SCREAMING_SNAKE_CASE			    =    ['''image_processor''', '''tokenizer''']
					SCREAMING_SNAKE_CASE			    =    '''BlipImageProcessor'''
					SCREAMING_SNAKE_CASE			    =    ('''BertTokenizer''', '''BertTokenizerFast''')

					def __init__(	self					:     List[Any]   ,					__UpperCamelCase					:     int   ,					__UpperCamelCase					:     Tuple   ):
												lowerCamelCase_							  =					False
												super().__init__(__UpperCamelCase   ,					__UpperCamelCase   )
												lowerCamelCase_							  =					self.image_processor

					def __call__(	self					:     Tuple   ,					__UpperCamelCase					:     ImageInput = None   ,					__UpperCamelCase					:     Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None   ,					__UpperCamelCase					:     bool = True   ,					__UpperCamelCase					:     Union[bool, str, PaddingStrategy] = False   ,					__UpperCamelCase					:     Union[bool, str, TruncationStrategy] = None   ,					__UpperCamelCase					:     Optional[int] = None   ,					__UpperCamelCase					:     int = 0   ,					__UpperCamelCase					:     Optional[int] = None   ,					__UpperCamelCase					:     Optional[bool] = None   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = False   ,					__UpperCamelCase					:     bool = True   ,					__UpperCamelCase					:     Optional[Union[str, TensorType]] = None   ,					**__UpperCamelCase					:     str   ,					):
												if images is None and text is None:
																			raise ValueError("""You have to specify either images or text."""   )

												# Get only text
												if images is None:
																			lowerCamelCase_							  =					self.tokenizer
																			lowerCamelCase_							  =					self.tokenizer(
																			    text=__UpperCamelCase   ,					add_special_tokens=__UpperCamelCase   ,					padding=__UpperCamelCase   ,					truncation=__UpperCamelCase   ,					max_length=__UpperCamelCase   ,					stride=__UpperCamelCase   ,					pad_to_multiple_of=__UpperCamelCase   ,					return_attention_mask=__UpperCamelCase   ,					return_overflowing_tokens=__UpperCamelCase   ,					return_special_tokens_mask=__UpperCamelCase   ,					return_offsets_mapping=__UpperCamelCase   ,					return_token_type_ids=__UpperCamelCase   ,					return_length=__UpperCamelCase   ,					verbose=__UpperCamelCase   ,					return_tensors=__UpperCamelCase   ,					**__UpperCamelCase   ,					)
																			return text_encoding

												# add pixel_values
												lowerCamelCase_							  =					self.image_processor(__UpperCamelCase   ,					return_tensors=__UpperCamelCase   )

												if text is not None:
																			lowerCamelCase_							  =					self.tokenizer(
																			    text=__UpperCamelCase   ,					add_special_tokens=__UpperCamelCase   ,					padding=__UpperCamelCase   ,					truncation=__UpperCamelCase   ,					max_length=__UpperCamelCase   ,					stride=__UpperCamelCase   ,					pad_to_multiple_of=__UpperCamelCase   ,					return_attention_mask=__UpperCamelCase   ,					return_overflowing_tokens=__UpperCamelCase   ,					return_special_tokens_mask=__UpperCamelCase   ,					return_offsets_mapping=__UpperCamelCase   ,					return_token_type_ids=__UpperCamelCase   ,					return_length=__UpperCamelCase   ,					verbose=__UpperCamelCase   ,					return_tensors=__UpperCamelCase   ,					**__UpperCamelCase   ,					)
												else:
																			lowerCamelCase_							  =					None

												if text_encoding is not None:
																			encoding_image_processor.update(__UpperCamelCase   )

												return encoding_image_processor

					def    lowercase__      (	self					:     int   ,					*__UpperCamelCase					:     List[str]   ,					**__UpperCamelCase					:     List[str]   ):
												return self.tokenizer.batch_decode(*__UpperCamelCase   ,					**__UpperCamelCase   )

					def    lowercase__      (	self					:     Dict   ,					*__UpperCamelCase					:     Optional[Any]   ,					**__UpperCamelCase					:     Dict   ):
												return self.tokenizer.decode(*__UpperCamelCase   ,					**__UpperCamelCase   )



					@property
					def    lowercase__      (	self					:     Optional[int]   ):
												lowerCamelCase_							  =					self.tokenizer.model_input_names
												lowerCamelCase_							  =					self.image_processor.model_input_names
												return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names   )   )







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       __A(				unittest.TestCase       ):

					def    lowercase__      (	self					:     Union[str, Any]   ):
												lowerCamelCase_							  =					tempfile.mkdtemp()

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

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

												lowerCamelCase_							  =					{
												    """do_resize""": True,
												    """size""": 2_0,
												    """do_center_crop""": True,
												    """crop_size""": 1_8,
												    """do_normalize""": True,
												    """image_mean""": [0.48145466, 0.4578275, 0.40821073],
												    """image_std""": [0.26862954, 0.26130258, 0.27577711],
												}
												lowerCamelCase_							  =					os.path.join(self.tmpdirname   ,					__UpperCamelCase   )
												with open(self.image_processor_file   ,					"""w"""   ,					encoding="""utf-8"""   ) as fp:
																			json.dump(__UpperCamelCase   ,					__UpperCamelCase   )

					def    lowercase__      (	self					:     str   ,					**__UpperCamelCase					:     Optional[Any]   ):
												return CLIPTokenizer.from_pretrained(self.tmpdirname   ,					pad_token="""!"""   ,					**__UpperCamelCase   )

					def    lowercase__      (	self					:     Any   ,					**__UpperCamelCase					:     List[Any]   ):
												return CLIPTokenizerFast.from_pretrained(self.tmpdirname   ,					pad_token="""!"""   ,					**__UpperCamelCase   )

					def    lowercase__      (	self					:     List[Any]   ,					**__UpperCamelCase					:     Optional[int]   ):
												return OwlViTImageProcessor.from_pretrained(self.tmpdirname   ,					**__UpperCamelCase   )

					def    lowercase__      (	self					:     Union[str, Any]   ):
												shutil.rmtree(self.tmpdirname   )

					def    lowercase__      (	self					:     str   ):
												lowerCamelCase_							  =					[np.random.randint(2_5_5   ,					size=(3, 3_0, 4_0_0)   ,					dtype=np.uinta   )]

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

												return image_inputs

					def    lowercase__      (	self					:     Optional[int]   ):
												lowerCamelCase_							  =					self.get_tokenizer()
												lowerCamelCase_							  =					self.get_rust_tokenizer()
												lowerCamelCase_							  =					self.get_image_processor()

												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=__UpperCamelCase   ,					image_processor=__UpperCamelCase   )
												processor_slow.save_pretrained(self.tmpdirname   )
												lowerCamelCase_							  =					OwlViTProcessor.from_pretrained(self.tmpdirname   ,					use_fast=__UpperCamelCase   )

												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=__UpperCamelCase   ,					image_processor=__UpperCamelCase   )
												processor_fast.save_pretrained(self.tmpdirname   )
												lowerCamelCase_							  =					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   ,					__UpperCamelCase   )
												self.assertIsInstance(processor_fast.tokenizer   ,					__UpperCamelCase   )

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

					def    lowercase__      (	self					:     Optional[int]   ):
												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=self.get_tokenizer()   ,					image_processor=self.get_image_processor()   )
												processor.save_pretrained(self.tmpdirname   )

												lowerCamelCase_							  =					self.get_tokenizer(bos_token="""(BOS)"""   ,					eos_token="""(EOS)"""   )
												lowerCamelCase_							  =					self.get_image_processor(do_normalize=__UpperCamelCase   )

												lowerCamelCase_							  =					OwlViTProcessor.from_pretrained(
												    self.tmpdirname   ,					bos_token="""(BOS)"""   ,					eos_token="""(EOS)"""   ,					do_normalize=__UpperCamelCase   )

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

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

					def    lowercase__      (	self					:     Any   ):
												lowerCamelCase_							  =					self.get_image_processor()
												lowerCamelCase_							  =					self.get_tokenizer()

												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=__UpperCamelCase   ,					image_processor=__UpperCamelCase   )

												lowerCamelCase_							  =					self.prepare_image_inputs()

												lowerCamelCase_							  =					image_processor(__UpperCamelCase   ,					return_tensors="""np"""   )
												lowerCamelCase_							  =					processor(images=__UpperCamelCase   ,					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    lowercase__      (	self					:     Union[str, Any]   ):
												lowerCamelCase_							  =					self.get_image_processor()
												lowerCamelCase_							  =					self.get_tokenizer()

												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=__UpperCamelCase   ,					image_processor=__UpperCamelCase   )

												lowerCamelCase_							  =					"""lower newer"""

												lowerCamelCase_							  =					processor(text=__UpperCamelCase   ,					return_tensors="""np"""   )

												lowerCamelCase_							  =					tokenizer(__UpperCamelCase   ,					return_tensors="""np"""   )

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

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

												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=__UpperCamelCase   ,					image_processor=__UpperCamelCase   )

												lowerCamelCase_							  =					"""lower newer"""
												lowerCamelCase_							  =					self.prepare_image_inputs()

												lowerCamelCase_							  =					processor(text=__UpperCamelCase   ,					images=__UpperCamelCase   )

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

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

					def    lowercase__      (	self					:     List[Any]   ):
												lowerCamelCase_							  =					"""google/owlvit-base-patch32"""
												lowerCamelCase_							  =					OwlViTProcessor.from_pretrained(__UpperCamelCase   )

												lowerCamelCase_							  =					["""cat""", """nasa badge"""]
												lowerCamelCase_							  =					processor(text=__UpperCamelCase   )

												lowerCamelCase_							  =					1_6
												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(__UpperCamelCase   ):
																			processor()

					def    lowercase__      (	self					:     Optional[int]   ):
												lowerCamelCase_							  =					"""google/owlvit-base-patch32"""
												lowerCamelCase_							  =					OwlViTProcessor.from_pretrained(__UpperCamelCase   )

												lowerCamelCase_							  =					[["""cat""", """nasa badge"""], ["""person"""]]
												lowerCamelCase_							  =					processor(text=__UpperCamelCase   )

												lowerCamelCase_							  =					1_6
												lowerCamelCase_							  =					len(__UpperCamelCase   )
												lowerCamelCase_							  =					max([len(__UpperCamelCase   ) 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(__UpperCamelCase   ):
																			processor()

					def    lowercase__      (	self					:     str   ):
												lowerCamelCase_							  =					"""google/owlvit-base-patch32"""
												lowerCamelCase_							  =					OwlViTProcessor.from_pretrained(__UpperCamelCase   )

												lowerCamelCase_							  =					["""cat""", """nasa badge"""]
												lowerCamelCase_							  =					processor(text=__UpperCamelCase   )

												lowerCamelCase_							  =					1_6
												lowerCamelCase_							  =					inputs["""input_ids"""]
												lowerCamelCase_							  =					[
												    [4_9_4_0_6, 2_3_6_8, 4_9_4_0_7, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
												    [4_9_4_0_6, 6_8_4_1, 1_1_3_0_1, 4_9_4_0_7, 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    lowercase__      (	self					:     int   ):
												lowerCamelCase_							  =					self.get_image_processor()
												lowerCamelCase_							  =					self.get_tokenizer()

												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=__UpperCamelCase   ,					image_processor=__UpperCamelCase   )

												lowerCamelCase_							  =					self.prepare_image_inputs()
												lowerCamelCase_							  =					self.prepare_image_inputs()

												lowerCamelCase_							  =					processor(images=__UpperCamelCase   ,					query_images=__UpperCamelCase   )

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

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



					def    lowercase__      (	self					:     Dict   ):
												lowerCamelCase_							  =					self.get_image_processor()
												lowerCamelCase_							  =					self.get_tokenizer()

												lowerCamelCase_							  =					OwlViTProcessor(tokenizer=__UpperCamelCase   ,					image_processor=__UpperCamelCase   )

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

												lowerCamelCase_							  =					processor.batch_decode(__UpperCamelCase   )
												lowerCamelCase_							  =					tokenizer.batch_decode(__UpperCamelCase   )

												self.assertListEqual(__UpperCamelCase   ,					__UpperCamelCase   )





