


'''simple docstring'''





import json
import os
import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import IMAGE_PROCESSOR_NAME, is_torch_available, is_vision_available


if is_torch_available():
			import torch


if is_vision_available():
			from PIL import Image

			from transformers import MgpstrProcessor, ViTImageProcessor




@require_torch
@require_vision
class    UpperCAmelCase					(       unittest.TestCase    ):
			lowercase						= ViTImageProcessor if is_vision_available() else None




			@property
			def   lowerCamelCase_					(						self							:		str						):







						"""simple docstring"""







						return self.image_processor_tester.prepare_image_processor_dict()




			def   lowerCamelCase_					(						self							:		Optional[int]						):







						"""simple docstring"""







						UpperCamelCase         =					(3, 3_2, 1_2_8)
						UpperCamelCase         =					tempfile.mkdtemp()

						# fmt: off
						UpperCamelCase         =					["""[GO]""", """[s]""", """0""", """1""", """2""", """3""", """4""", """5""", """6""", """7""", """8""", """9""", """a""", """b""", """c""", """d""", """e""", """f""", """g""", """h""", """i""", """j""", """k""", """l""", """m""", """n""", """o""", """p""", """q""", """r""", """s""", """t""", """u""", """v""", """w""", """x""", """y""", """z"""]
						# fmt: on
						UpperCamelCase         =					dict(zip(__magic_name__       ,       range(len(__magic_name__						)						)						)						)

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

						UpperCamelCase         =					{
						    """do_normalize""": False,
						    """do_resize""": True,
						    """image_processor_type""": """ViTImageProcessor""",
						    """resample""": 3,
						    """size""": {"""height""": 3_2, """width""": 1_2_8},
						}
						UpperCamelCase         =					os.path.join(self.tmpdirname       ,       __magic_name__						)
						with open(self.image_processor_file       ,       """w"""       ,       encoding="""utf-8"""						) as fp:
									json.dump(__magic_name__       ,       __magic_name__						)




			def   lowerCamelCase_					(						self							:		int       ,       **__magic_name__							:		Optional[Any]						):







						"""simple docstring"""







						return MgpstrTokenizer.from_pretrained(self.tmpdirname       ,       **__magic_name__						)




			def   lowerCamelCase_					(						self							:		List[str]       ,       **__magic_name__							:		Optional[int]						):







						"""simple docstring"""







						return ViTImageProcessor.from_pretrained(self.tmpdirname       ,       **__magic_name__						)




			def   lowerCamelCase_					(						self							:		Optional[int]						):







						"""simple docstring"""







						shutil.rmtree(self.tmpdirname						)




			def   lowerCamelCase_					(						self							:		Tuple						):







						"""simple docstring"""







						UpperCamelCase         =					np.random.randint(2_5_5       ,       size=(3, 3_0, 4_0_0)       ,       dtype=np.uinta						)

						UpperCamelCase         =					Image.fromarray(np.moveaxis(__magic_name__       ,       0       ,       -1						)						)

						return image_input




			def   lowerCamelCase_					(						self							:		str						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_tokenizer()
						UpperCamelCase         =					self.get_image_processor()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)
						processor.save_pretrained(self.tmpdirname						)
						UpperCamelCase         =					MgpstrProcessor.from_pretrained(self.tmpdirname       ,       use_fast=__magic_name__						)

						self.assertEqual(processor.char_tokenizer.get_vocab()       ,       tokenizer.get_vocab()						)
						self.assertIsInstance(processor.char_tokenizer       ,       __magic_name__						)

						self.assertEqual(processor.image_processor.to_json_string()       ,       image_processor.to_json_string()						)
						self.assertIsInstance(processor.image_processor       ,       __magic_name__						)




			def   lowerCamelCase_					(						self							:		Dict						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_tokenizer()
						UpperCamelCase         =					self.get_image_processor()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)
						processor.save_pretrained(self.tmpdirname						)

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

						UpperCamelCase         =					MgpstrProcessor.from_pretrained(
						    self.tmpdirname       ,       bos_token="""(BOS)"""       ,       eos_token="""(EOS)"""       ,       do_normalize=__magic_name__       ,       padding_value=1.0						)

						self.assertEqual(processor.char_tokenizer.get_vocab()       ,       tokenizer_add_kwargs.get_vocab()						)
						self.assertIsInstance(processor.char_tokenizer       ,       __magic_name__						)

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




			def   lowerCamelCase_					(						self							:		Optional[int]						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_image_processor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)

						UpperCamelCase         =					self.prepare_image_inputs()

						UpperCamelCase         =					image_processor(__magic_name__       ,       return_tensors="""np"""						)
						UpperCamelCase         =					processor(images=__magic_name__       ,       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							:		List[Any]						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_image_processor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)

						UpperCamelCase         =					"""test"""

						UpperCamelCase         =					processor(text=__magic_name__						)

						UpperCamelCase         =					tokenizer(__magic_name__						)
						for key in encoded_tok.keys():
									self.assertListEqual(encoded_tok[key]       ,       encoded_processor[key]						)




			def   lowerCamelCase_					(						self							:		Optional[Any]						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_image_processor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)

						UpperCamelCase         =					"""test"""
						UpperCamelCase         =					self.prepare_image_inputs()

						UpperCamelCase         =					processor(text=__magic_name__       ,       images=__magic_name__						)

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

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




			def   lowerCamelCase_					(						self							:		Dict						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_image_processor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)

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

						UpperCamelCase         =					processor.char_decode(__magic_name__						)
						UpperCamelCase         =					tokenizer.batch_decode(__magic_name__						)
						UpperCamelCase         =					[seq.replace(""" """       ,       """"""						) for seq in decoded_tok]

						self.assertListEqual(__magic_name__       ,       __magic_name__						)




			def   lowerCamelCase_					(						self							:		int						):







						"""simple docstring"""







						UpperCamelCase         =					self.get_image_processor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)

						UpperCamelCase         =					None
						UpperCamelCase         =					self.prepare_image_inputs()

						UpperCamelCase         =					processor(text=__magic_name__       ,       images=__magic_name__						)

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





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







						"""simple docstring"""







						UpperCamelCase         =					self.get_image_processor()
						UpperCamelCase         =					self.get_tokenizer()

						UpperCamelCase         =					MgpstrProcessor(tokenizer=__magic_name__       ,       image_processor=__magic_name__						)

						UpperCamelCase         =					torch.randn(1       ,       2_7       ,       3_8						)
						UpperCamelCase         =					torch.randn(1       ,       2_7       ,       5_0_2_5_7						)
						UpperCamelCase         =					torch.randn(1       ,       2_7       ,       3_0_5_2_2						)

						UpperCamelCase         =					processor.batch_decode([char_input, bpe_input, wp_input]						)

						self.assertListEqual(list(results.keys()						)       ,       ["""generated_text""", """scores""", """char_preds""", """bpe_preds""", """wp_preds"""]						)








import os
import random
import sys

from . import cryptomath_module as cryptomath
from . import rabin_miller

__snake_case            =   3






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		int	):





			"""simple docstring"""




			print("""Generating primitive root of p"""	)
			while True:
						UpperCamelCase         =					random.randrange(3       ,  SCREAMING_SNAKE_CASE_	)
						if pow(SCREAMING_SNAKE_CASE_       ,  2       ,  SCREAMING_SNAKE_CASE_	) == 1:
									continue
						if pow(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_	) == 1:
									continue
						return g






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		int	):





			"""simple docstring"""




			print("""Generating prime p..."""	)
			UpperCamelCase         =					rabin_miller.generate_large_prime(SCREAMING_SNAKE_CASE_	)  # select large prime number.
			UpperCamelCase         =					primitive_root(SCREAMING_SNAKE_CASE_	)  # one primitive root on modulo p.
			UpperCamelCase         =					random.randrange(3       ,  SCREAMING_SNAKE_CASE_	)  # private_key -> have to be greater than 2 for safety.
			UpperCamelCase         =					cryptomath.find_mod_inverse(pow(SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_       ,  SCREAMING_SNAKE_CASE_	)       ,  SCREAMING_SNAKE_CASE_	)

			UpperCamelCase         =					(key_size, e_a, e_a, p)
			UpperCamelCase         =					(key_size, d)

			return public_key, private_key






def 							_lowercase    (		SCREAMING_SNAKE_CASE_   :		str       ,  SCREAMING_SNAKE_CASE_   :		int	):





			"""simple docstring"""




			if os.path.exists(f'{name}_pubkey.txt'	) or os.path.exists(f'{name}_privkey.txt'	):
						print("""\nWARNING:"""	)
						print(
						    f'"{name}_pubkey.txt" or "{name}_privkey.txt" already exists. \n'
						    """Use a different name or delete these files and re-run this program."""	)
						sys.exit()

			UpperCamelCase  ,  UpperCamelCase         =					generate_key(SCREAMING_SNAKE_CASE_	)
			print(f'\nWriting public key to file {name}_pubkey.txt...'	)
			with open(f'{name}_pubkey.txt'       ,  """w"""	) as fo:
						fo.write(f'{public_key[0]},{public_key[1]},{public_key[2]},{public_key[3]}'	)

			print(f'Writing private key to file {name}_privkey.txt...'	)
			with open(f'{name}_privkey.txt'       ,  """w"""	) as fo:
						fo.write(f'{private_key[0]},{private_key[1]}'	)






def 							_lowercase    (		):





			"""simple docstring"""




			print("""Making key files..."""	)
			make_key_files("""elgamal"""       ,  2_048	)
			print("""Key files generation successful"""	)


if __name__ == "__main__":
			main()




