
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 				UpperCAmelCase (    unittest.TestCase    ):




	'''simple docstring'''





	def 							UpperCamelCase_    (			self   :					int					):
					__A       =					tempfile.mkdtemp()

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

					__A       =					os.path.join(self.tmpdirname				,VOCAB_FILES_NAMES["vocab_file"]					)
					__A       =					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					)					)

					__A       =					{
					    "do_resize": True,
					    "size": 20,
					    "do_center_crop": True,
					    "crop_size": 18,
					    "do_normalize": True,
					    "image_mean": [0.48_14_54_66, 0.4_57_82_75, 0.40_82_10_73],
					    "image_std": [0.26_86_29_54, 0.26_13_02_58, 0.27_57_77_11],
					}
					__A       =					os.path.join(self.tmpdirname				,__UpperCAmelCase					)
					with open(self.image_processor_file				,"w"				,encoding="utf-8"					) as fp:
									json.dump(__UpperCAmelCase				,__UpperCAmelCase					)






	def 							UpperCamelCase_    (			self   :					Tuple				,**A   :					Dict					):
					return CLIPTokenizer.from_pretrained(self.tmpdirname				,pad_token="!"				,**__UpperCAmelCase					)






	def 							UpperCamelCase_    (			self   :					Optional[Any]				,**A   :					int					):
					return CLIPTokenizerFast.from_pretrained(self.tmpdirname				,pad_token="!"				,**__UpperCAmelCase					)






	def 							UpperCamelCase_    (			self   :					List[Any]				,**A   :					Dict					):
					return OwlViTImageProcessor.from_pretrained(self.tmpdirname				,**__UpperCAmelCase					)






	def 							UpperCamelCase_    (			self   :					str					):
					shutil.rmtree(self.tmpdirname					)






	def 							UpperCamelCase_    (			self   :					Dict					):
					__A       =					[np.random.randint(2_55				,size=(3, 30, 4_00)				,dtype=np.uinta					)]

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

					return image_inputs






	def 							UpperCamelCase_    (			self   :					Tuple					):
					__A       =					self.get_tokenizer()
					__A       =					self.get_rust_tokenizer()
					__A       =					self.get_image_processor()

					__A       =					OwlViTProcessor(tokenizer=__UpperCAmelCase				,image_processor=__UpperCAmelCase					)
					processor_slow.save_pretrained(self.tmpdirname					)
					__A       =					OwlViTProcessor.from_pretrained(self.tmpdirname				,use_fast=__UpperCAmelCase					)

					__A       =					OwlViTProcessor(tokenizer=__UpperCAmelCase				,image_processor=__UpperCAmelCase					)
					processor_fast.save_pretrained(self.tmpdirname					)
					__A       =					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 							UpperCamelCase_    (			self   :					str					):
					__A       =					OwlViTProcessor(tokenizer=self.get_tokenizer()				,image_processor=self.get_image_processor()					)
					processor.save_pretrained(self.tmpdirname					)

					__A       =					self.get_tokenizer(bos_token="(BOS)"				,eos_token="(EOS)"					)
					__A       =					self.get_image_processor(do_normalize=__UpperCAmelCase					)

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

					__A       =					OwlViTProcessor(tokenizer=__UpperCAmelCase				,image_processor=__UpperCAmelCase					)

					__A       =					self.prepare_image_inputs()

					__A       =					image_processor(__UpperCAmelCase				,return_tensors="np"					)
					__A       =					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 							UpperCamelCase_    (			self   :					Dict					):
					__A       =					self.get_image_processor()
					__A       =					self.get_tokenizer()

					__A       =					OwlViTProcessor(tokenizer=__UpperCAmelCase				,image_processor=__UpperCAmelCase					)

					__A       =					"lower newer"

					__A       =					processor(text=__UpperCAmelCase				,return_tensors="np"					)

					__A       =					tokenizer(__UpperCAmelCase				,return_tensors="np"					)

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






	def 							UpperCamelCase_    (			self   :					List[Any]					):
					__A       =					self.get_image_processor()
					__A       =					self.get_tokenizer()

					__A       =					OwlViTProcessor(tokenizer=__UpperCAmelCase				,image_processor=__UpperCAmelCase					)

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

					__A       =					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 							UpperCamelCase_    (			self   :					int					):
					__A       =					"google/owlvit-base-patch32"
					__A       =					OwlViTProcessor.from_pretrained(__UpperCAmelCase					)

					__A       =					["cat", "nasa badge"]
					__A       =					processor(text=__UpperCAmelCase					)

					__A       =					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 							UpperCamelCase_    (			self   :					Any					):
					__A       =					"google/owlvit-base-patch32"
					__A       =					OwlViTProcessor.from_pretrained(__UpperCAmelCase					)

					__A       =					[["cat", "nasa badge"], ["person"]]
					__A       =					processor(text=__UpperCAmelCase					)

					__A       =					16
					__A       =					len(__UpperCAmelCase					)
					__A       =					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 							UpperCamelCase_    (			self   :					Tuple					):
					__A       =					"google/owlvit-base-patch32"
					__A       =					OwlViTProcessor.from_pretrained(__UpperCAmelCase					)

					__A       =					["cat", "nasa badge"]
					__A       =					processor(text=__UpperCAmelCase					)

					__A       =					16
					__A       =					inputs["input_ids"]
					__A       =					[
					    [4_94_06, 23_68, 4_94_07, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
					    [4_94_06, 68_41, 1_13_01, 4_94_07, 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   :					Optional[int]					):
					__A       =					self.get_image_processor()
					__A       =					self.get_tokenizer()

					__A       =					OwlViTProcessor(tokenizer=__UpperCAmelCase				,image_processor=__UpperCAmelCase					)

					__A       =					self.prepare_image_inputs()
					__A       =					self.prepare_image_inputs()

					__A       =					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 							UpperCamelCase_    (			self   :					Any					):
					__A       =					self.get_image_processor()
					__A       =					self.get_tokenizer()

					__A       =					OwlViTProcessor(tokenizer=__UpperCAmelCase				,image_processor=__UpperCAmelCase					)

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

					__A       =					processor.batch_decode(__UpperCAmelCase					)
					__A       =					tokenizer.batch_decode(__UpperCAmelCase					)

					self.assertListEqual(__UpperCAmelCase				,__UpperCAmelCase					)








UpperCAmelCase__      			=						'''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''







def     a_   ()				->						None:



					"""simple docstring"""
					__a					:						Dict      =					input("Enter message: "      )
					__a					:						Dict      =					input("Enter key [alphanumeric]: "      )
					__a					:						str      =					input("Encrypt/Decrypt [e/d]: "      )

					if mode.lower().startswith("e"      ):
										__a					:						List[str]      =					"encrypt"
										__a					:						Union[str, Any]      =					encrypt_message(__A				,       __A      )
					elif mode.lower().startswith("d"      ):
										__a					:						int      =					"decrypt"
										__a					:						List[str]      =					decrypt_message(__A				,       __A      )

					print(f'\n{mode.title()}ed message:'      )
					print(__A      )







def     a_   (__A				,       __A      )				->						str:



					"""simple docstring"""
					return translate_message(__A				,       __A				,       "encrypt"      )







def     a_   (__A				,       __A      )				->						str:



					"""simple docstring"""
					return translate_message(__A				,       __A				,       "decrypt"      )







def     a_   (__A				,       __A				,       __A      )				->						str:



					"""simple docstring"""
					__a					:						Union[str, Any]      =					[]
					__a					:						Tuple      =					0
					__a					:						Dict      =					key.upper()

					for symbol in message:
										__a					:						Dict      =					LETTERS.find(symbol.upper()      )
										if num != -1:
															if mode == "encrypt":
																				num += LETTERS.find(key[key_index]      )
															elif mode == "decrypt":
																				num -= LETTERS.find(key[key_index]      )

															num %= len(__A      )

															if symbol.isupper():
																				translated.append(LETTERS[num]      )
															elif symbol.islower():
																				translated.append(LETTERS[num].lower()      )

															key_index += 1
															if key_index == len(__A      ):
																				__a					:						List[str]      =					0
										else:
															translated.append(__A      )
					return "".join(__A      )


if __name__ == "__main__":
			main()





