





import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert 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 AlignProcessor, EfficientNetImageProcessor

@require_vision
class        __SCREAMING_SNAKE_CASE					(     unittest.TestCase       ):






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			tempfile.mkdtemp()

														UpperCamelCase__				     =			[
														    """[UNK]""",
														    """[CLS]""",
														    """[SEP]""",
														    """[PAD]""",
														    """[MASK]""",
														    """want""",
														    """##want""",
														    """##ed""",
														    """wa""",
														    """un""",
														    """runn""",
														    """##ing""",
														    """,""",
														    """low""",
														    """lowest""",
														]
														UpperCamelCase__				     =			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]  )  )

														UpperCamelCase__				     =			{
														    """do_resize""": True,
														    """size""": 20,
														    """do_center_crop""": True,
														    """crop_size""": 18,
														    """do_normalize""": True,
														    """image_mean""": [0.4814_5466, 0.457_8275, 0.4082_1073],
														    """image_std""": [0.2686_2954, 0.2613_0258, 0.2757_7711],
														}
														UpperCamelCase__				     =			os.path.join(self.tmpdirname  , __lowerCAmelCase  )
														with open(self.image_processor_file  , """w"""  , encoding="""utf-8"""  ) as fp:
																					json.dump(__lowerCAmelCase  , __lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
														return BertTokenizer.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
														return BertTokenizerFast.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  , **__lowerCAmelCase  ):
														return EfficientNetImageProcessor.from_pretrained(self.tmpdirname  , **__lowerCAmelCase  )






							def 				_lowerCamelCase		(						self  ):
														shutil.rmtree(self.tmpdirname  )






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			[np.random.randint(255  , size=(3, 30, 400)  , dtype=np.uinta  )]
														UpperCamelCase__				     =			[Image.fromarray(np.moveaxis(__lowerCAmelCase  , 0  , -1  )  ) for x in image_inputs]
														return image_inputs






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_tokenizer()
														UpperCamelCase__				     =			self.get_rust_tokenizer()
														UpperCamelCase__				     =			self.get_image_processor()

														UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )
														processor_slow.save_pretrained(self.tmpdirname  )
														UpperCamelCase__				     =			AlignProcessor.from_pretrained(self.tmpdirname  , use_fast=__lowerCAmelCase  )

														UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )
														processor_fast.save_pretrained(self.tmpdirname  )
														UpperCamelCase__				     =			AlignProcessor.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 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			AlignProcessor(tokenizer=self.get_tokenizer()  , image_processor=self.get_image_processor()  )
														processor.save_pretrained(self.tmpdirname  )

														UpperCamelCase__				     =			self.get_tokenizer(bos_token="""(BOS)"""  , eos_token="""(EOS)"""  )
														UpperCamelCase__				     =			self.get_image_processor(do_normalize=__lowerCAmelCase  , padding_value=1.0  )

														UpperCamelCase__				     =			AlignProcessor.from_pretrained(
														    self.tmpdirname  , bos_token="""(BOS)"""  , eos_token="""(EOS)"""  , do_normalize=__lowerCAmelCase  , padding_value=1.0  )

														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 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

														UpperCamelCase__				     =			self.prepare_image_inputs()

														UpperCamelCase__				     =			image_processor(__lowerCAmelCase  , return_tensors="""np"""  )
														UpperCamelCase__				     =			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 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

														UpperCamelCase__				     =			"""lower newer"""

														UpperCamelCase__				     =			processor(text=__lowerCAmelCase  )

														UpperCamelCase__				     =			tokenizer(__lowerCAmelCase  , padding="""max_length"""  , max_length=64  )

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






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

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

														UpperCamelCase__				     =			processor(text=__lowerCAmelCase  , images=__lowerCAmelCase  )

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

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






							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

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

														UpperCamelCase__				     =			processor.batch_decode(__lowerCAmelCase  )
														UpperCamelCase__				     =			tokenizer.batch_decode(__lowerCAmelCase  )

														self.assertListEqual(__lowerCAmelCase  , __lowerCAmelCase  )







							def 				_lowerCamelCase		(						self  ):
														UpperCamelCase__				     =			self.get_image_processor()
														UpperCamelCase__				     =			self.get_tokenizer()

														UpperCamelCase__				     =			AlignProcessor(tokenizer=__lowerCAmelCase  , image_processor=__lowerCAmelCase  )

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

														UpperCamelCase__				     =			processor(text=__lowerCAmelCase  , images=__lowerCAmelCase  )

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











UpperCamelCase__											= "ABCDEFGHIJKLMNOPQRSTUVWXYZ"





def     _UpperCamelCase     ():






							"""simple docstring"""





							UpperCamelCase__				     =			input("""Enter message: """       )
							UpperCamelCase__				     =			input("""Enter key [alphanumeric]: """       )
							UpperCamelCase__				     =			input("""Encrypt/Decrypt [e/d]: """       )

							if mode.lower().startswith("""e"""       ):
														UpperCamelCase__				     =			"""encrypt"""
														UpperCamelCase__				     =			encrypt_message(a__   ,			a__       )
							elif mode.lower().startswith("""d"""       ):
														UpperCamelCase__				     =			"""decrypt"""
														UpperCamelCase__				     =			decrypt_message(a__   ,			a__       )

							print(f"""\n{mode.title()}ed message:"""       )
							print(a__       )





def     _UpperCamelCase     (a__   :str   ,			a__   :str       ):






							"""simple docstring"""





							return translate_message(a__   ,			a__   ,			"""encrypt"""       )





def     _UpperCamelCase     (a__   :str   ,			a__   :str       ):






							"""simple docstring"""





							return translate_message(a__   ,			a__   ,			"""decrypt"""       )





def     _UpperCamelCase     (a__   :str   ,			a__   :str   ,			a__   :str       ):






							"""simple docstring"""





							UpperCamelCase__				     =			[]
							UpperCamelCase__				     =			0
							UpperCamelCase__				     =			key.upper()

							for symbol in message:
														UpperCamelCase__				     =			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__       ):
																												UpperCamelCase__				     =			0
														else:
																					translated.append(a__       )
							return "".join(a__       )


if __name__ == "__main__":
					main()




