

"""simple docstring"""




import os
import unittest

from transformers import MPNetTokenizerFast
from transformers.models.mpnet.tokenization_mpnet import VOCAB_FILES_NAMES, MPNetTokenizer
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin






@require_tokenizers
class _UpperCamelCase							(							__A							,		unittest.TestCase				):
			'''simple docstring'''







			lowerCamelCase__          =MPNetTokenizer
			lowerCamelCase__          =MPNetTokenizerFast
			lowerCamelCase__          =True
			lowerCamelCase__          =True
			def 							__UpperCamelCase	(     self							:	List[Any]		)							->    Union[str, Any]:

				"""simple docstring"""

				super().setUp()

				SCREAMING_SNAKE_CASE				: List[str]			       =    [
				    "[UNK]",
				    "[CLS]",
				    "[SEP]",
				    "[PAD]",
				    "[MASK]",
				    "want",
				    "##want",
				    "##ed",
				    "wa",
				    "un",
				    "runn",
				    "##ing",
				    ",",
				    "low",
				    "lowest",
				]
				SCREAMING_SNAKE_CASE				: Tuple			       =    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]		)		)
			def 							__UpperCamelCase	(     self							:	Dict , a							:	List[Any]		)							->    str:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: List[str]			       =    "UNwant\u00E9d,running"
				SCREAMING_SNAKE_CASE				: int			       =    "unwanted, running"
				return input_text, output_text
			def 							__UpperCamelCase	(     self							:	int		)							->    Optional[int]:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: Union[str, Any]			       =    self.tokenizer_class(self.vocab_file		)

				SCREAMING_SNAKE_CASE				: Optional[Any]			       =    tokenizer.tokenize("UNwant\u00E9d,running"		)
				self.assertListEqual(a , ["un", "##want", "##ed", ",", "runn", "##ing"]		)
				self.assertListEqual(tokenizer.convert_tokens_to_ids(a		) , [9, 6, 7, 12, 10, 11]		)






			@slow
			def 							__UpperCamelCase	(     self							:	Optional[int]		)							->    str:

				"""simple docstring"""

				SCREAMING_SNAKE_CASE				: Dict			       =    self.tokenizer_class.from_pretrained("microsoft/mpnet-base"		)

				SCREAMING_SNAKE_CASE				: int			       =    tokenizer.encode("sequence builders" , add_special_tokens=a		)
				SCREAMING_SNAKE_CASE				: Tuple			       =    tokenizer.encode("multi-sequence build" , add_special_tokens=a		)

				SCREAMING_SNAKE_CASE				: Any			       =    tokenizer.build_inputs_with_special_tokens(a		)
				SCREAMING_SNAKE_CASE				: Union[str, Any]			       =    tokenizer.build_inputs_with_special_tokens(a , a		)

				assert encoded_sentence == [0] + text + [2]
				assert encoded_pair == [0] + text + [2] + [2] + text_a + [2]


import math
import os

import cva
import numpy as np

a_         =      255.0

def 	lowerCamelCase__	(   _a							,     _a):
	SCREAMING_SNAKE_CASE				: Optional[int]			       =    np.mean((original - contrast) ** 2)
	if mse == 0:
		return 100

	return 20 * math.logaa(PIXEL_MAX / math.sqrt(_a))

def 	lowerCamelCase__	(   ):
	SCREAMING_SNAKE_CASE				: List[Any]			       =    os.path.dirname(os.path.realpath(_a))
	# Loading images (original image and compressed image)
	SCREAMING_SNAKE_CASE				: Any			       =    cva.imread(os.path.join(_a							,     "image_data/original_image.png"))
	SCREAMING_SNAKE_CASE				: List[str]			       =    cva.imread(os.path.join(_a							,     "image_data/compressed_image.png")							,     1)

	SCREAMING_SNAKE_CASE				: List[Any]			       =    cva.imread(os.path.join(_a							,     "image_data/PSNR-example-base.png"))
	SCREAMING_SNAKE_CASE				: List[str]			       =    cva.imread(
	    os.path.join(_a							,     "image_data/PSNR-example-comp-10.jpg")							,     1)

	# Value expected: 29.73dB
	print("-- First Test --")
	print(f"PSNR value is {peak_signal_to_noise_ratio(_a							,     _a)} dB")

	# # Value expected: 31.53dB (Wikipedia Example)
	print("\n-- Second Test --")
	print(f"PSNR value is {peak_signal_to_noise_ratio(_a							,     _a)} dB")


if __name__ == "__main__":
			main()