




"""simple docstring"""





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       a_     (      self      :    Tuple):


						"""simple docstring"""




						__UpperCAmelCase	: str		=					tempfile.mkdtemp()

						# fmt: off
						__UpperCAmelCase	: Any		=					["", "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
						__UpperCAmelCase	: List[Any]		=					dict(zip(UpperCamelCase_      ,  range(len(UpperCamelCase_))))
						__UpperCAmelCase	: Optional[int]		=					["#version: 0.2", "l o", "lo w</w>", "e r</w>", ""]
						__UpperCAmelCase	: int		=					{"unk_token": "<unk>"}

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

						__UpperCAmelCase	: int		=					{
						    "do_resize": True,
						    "size": 20,
						    "do_center_crop": True,
						    "crop_size": 18,
						    "do_normalize": True,
						    "image_mean": [0.48145466, 0.4578275, 0.40821073],
						    "image_std": [0.26862954, 0.26130258, 0.27577711],
						}
						__UpperCAmelCase	: Union[str, Any]		=					os.path.join(self.tmpdirname      ,  UpperCamelCase_)
						with open(self.image_processor_file      ,  "w"      ,  encoding="utf-8") as fp:
									json.dump(UpperCamelCase_      ,  UpperCamelCase_)


			def       a_     (      self      :    List[Any]      ,  **UpperCamelCase_      :    Optional[int]):


						"""simple docstring"""




						return CLIPTokenizer.from_pretrained(self.tmpdirname      ,  pad_token="!"      ,  **UpperCamelCase_)


			def       a_     (      self      :    Union[str, Any]      ,  **UpperCamelCase_      :    List[str]):


						"""simple docstring"""




						return CLIPTokenizerFast.from_pretrained(self.tmpdirname      ,  pad_token="!"      ,  **UpperCamelCase_)


			def       a_     (      self      :    List[str]      ,  **UpperCamelCase_      :    Tuple):


						"""simple docstring"""




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


			def       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




						shutil.rmtree(self.tmpdirname)


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


						"""simple docstring"""




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

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

						return image_inputs


			def       a_     (      self      :    Any):


						"""simple docstring"""




						__UpperCAmelCase	: int		=					self.get_tokenizer()
						__UpperCAmelCase	: Optional[Any]		=					self.get_rust_tokenizer()
						__UpperCAmelCase	: Tuple		=					self.get_image_processor()

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

						__UpperCAmelCase	: int		=					OwlViTProcessor(tokenizer=UpperCamelCase_      ,  image_processor=UpperCamelCase_)
						processor_fast.save_pretrained(self.tmpdirname)
						__UpperCAmelCase	: Tuple		=					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       a_     (      self      :    Optional[int]):


						"""simple docstring"""




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

						__UpperCAmelCase	: int		=					self.get_tokenizer(bos_token="(BOS)"      ,  eos_token="(EOS)")
						__UpperCAmelCase	: Optional[Any]		=					self.get_image_processor(do_normalize=UpperCamelCase_)

						__UpperCAmelCase	: List[str]		=					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       a_     (      self      :    Dict):


						"""simple docstring"""




						__UpperCAmelCase	: Tuple		=					self.get_image_processor()
						__UpperCAmelCase	: List[str]		=					self.get_tokenizer()

						__UpperCAmelCase	: int		=					OwlViTProcessor(tokenizer=UpperCamelCase_      ,  image_processor=UpperCamelCase_)

						__UpperCAmelCase	: Tuple		=					self.prepare_image_inputs()

						__UpperCAmelCase	: Tuple		=					image_processor(UpperCamelCase_      ,  return_tensors="np")
						__UpperCAmelCase	: List[Any]		=					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       a_     (      self      :    Optional[int]):


						"""simple docstring"""




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

						__UpperCAmelCase	: str		=					OwlViTProcessor(tokenizer=UpperCamelCase_      ,  image_processor=UpperCamelCase_)

						__UpperCAmelCase	: List[str]		=					"lower newer"

						__UpperCAmelCase	: Any		=					processor(text=UpperCamelCase_      ,  return_tensors="np")

						__UpperCAmelCase	: Optional[int]		=					tokenizer(UpperCamelCase_      ,  return_tensors="np")

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


			def       a_     (      self      :    Optional[Any]):


						"""simple docstring"""




						__UpperCAmelCase	: Any		=					self.get_image_processor()
						__UpperCAmelCase	: str		=					self.get_tokenizer()

						__UpperCAmelCase	: Dict		=					OwlViTProcessor(tokenizer=UpperCamelCase_      ,  image_processor=UpperCamelCase_)

						__UpperCAmelCase	: int		=					"lower newer"
						__UpperCAmelCase	: Optional[int]		=					self.prepare_image_inputs()

						__UpperCAmelCase	: Union[str, Any]		=					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       a_     (      self      :    Optional[int]):


						"""simple docstring"""




						__UpperCAmelCase	: List[Any]		=					"google/owlvit-base-patch32"
						__UpperCAmelCase	: Any		=					OwlViTProcessor.from_pretrained(UpperCamelCase_)

						__UpperCAmelCase	: Tuple		=					["cat", "nasa badge"]
						__UpperCAmelCase	: List[str]		=					processor(text=UpperCamelCase_)

						__UpperCAmelCase	: List[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(UpperCamelCase_):
									processor()


			def       a_     (      self      :    Tuple):


						"""simple docstring"""




						__UpperCAmelCase	: Union[str, Any]		=					"google/owlvit-base-patch32"
						__UpperCAmelCase	: str		=					OwlViTProcessor.from_pretrained(UpperCamelCase_)

						__UpperCAmelCase	: Dict		=					[["cat", "nasa badge"], ["person"]]
						__UpperCAmelCase	: List[Any]		=					processor(text=UpperCamelCase_)

						__UpperCAmelCase	: Optional[Any]		=					16
						__UpperCAmelCase	: Optional[int]		=					len(UpperCamelCase_)
						__UpperCAmelCase	: Optional[Any]		=					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       a_     (      self      :    Tuple):


						"""simple docstring"""




						__UpperCAmelCase	: Union[str, Any]		=					"google/owlvit-base-patch32"
						__UpperCAmelCase	: Dict		=					OwlViTProcessor.from_pretrained(UpperCamelCase_)

						__UpperCAmelCase	: Any		=					["cat", "nasa badge"]
						__UpperCAmelCase	: List[Any]		=					processor(text=UpperCamelCase_)

						__UpperCAmelCase	: Optional[int]		=					16
						__UpperCAmelCase	: Optional[int]		=					inputs["input_ids"]
						__UpperCAmelCase	: Optional[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       a_     (      self      :    Union[str, Any]):


						"""simple docstring"""




						__UpperCAmelCase	: Union[str, Any]		=					self.get_image_processor()
						__UpperCAmelCase	: Optional[int]		=					self.get_tokenizer()

						__UpperCAmelCase	: Any		=					OwlViTProcessor(tokenizer=UpperCamelCase_      ,  image_processor=UpperCamelCase_)

						__UpperCAmelCase	: Tuple		=					self.prepare_image_inputs()
						__UpperCAmelCase	: Optional[int]		=					self.prepare_image_inputs()

						__UpperCAmelCase	: Tuple		=					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       a_     (      self      :    int):


						"""simple docstring"""




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

						__UpperCAmelCase	: Any		=					OwlViTProcessor(tokenizer=UpperCamelCase_      ,  image_processor=UpperCamelCase_)

						__UpperCAmelCase	: int		=					[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

						__UpperCAmelCase	: Optional[int]		=					processor.batch_decode(UpperCamelCase_)
						__UpperCAmelCase	: int		=					tokenizer.batch_decode(UpperCamelCase_)

						self.assertListEqual(UpperCamelCase_      ,  UpperCamelCase_)








"""simple docstring"""





import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format



class      a__				:
			lowercase_    =	None


			def       a_     (      self      :    List[Any]):


						"""simple docstring"""




						__UpperCAmelCase	: Optional[Any]		=					self.feature_extraction_class(**self.feat_extract_dict)
						__UpperCAmelCase	: Any		=					json.loads(feat_extract.to_json_string())
						for key, value in self.feat_extract_dict.items():
									self.assertEqual(obj[key]      ,  UpperCamelCase_)


			def       a_     (      self      :    Tuple):


						"""simple docstring"""




						__UpperCAmelCase	: Optional[Any]		=					self.feature_extraction_class(**self.feat_extract_dict)

						with tempfile.TemporaryDirectory() as tmpdirname:
									__UpperCAmelCase	: Dict		=					os.path.join(UpperCamelCase_      ,  "feat_extract.json")
									feat_extract_first.to_json_file(UpperCamelCase_)
									__UpperCAmelCase	: Optional[Any]		=					self.feature_extraction_class.from_json_file(UpperCamelCase_)

						self.assertEqual(feat_extract_second.to_dict()      ,  feat_extract_first.to_dict())


			def       a_     (      self      :    List[str]):


						"""simple docstring"""




						__UpperCAmelCase	: Optional[Any]		=					self.feature_extraction_class(**self.feat_extract_dict)

						with tempfile.TemporaryDirectory() as tmpdirname:
									__UpperCAmelCase	: Tuple		=					feat_extract_first.save_pretrained(UpperCamelCase_)[0]
									check_json_file_has_correct_format(UpperCamelCase_)
									__UpperCAmelCase	: List[Any]		=					self.feature_extraction_class.from_pretrained(UpperCamelCase_)

						self.assertEqual(feat_extract_second.to_dict()      ,  feat_extract_first.to_dict())


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


						"""simple docstring"""




						__UpperCAmelCase	: Union[str, Any]		=					self.feature_extraction_class()
						self.assertIsNotNone(UpperCamelCase_)


