


import numpy as np
import torch
from imwatermark import WatermarkEncoder


# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
A			:						Union[str, Any]        =  0B101100111110110010010000011110111011000110011110
# bin(x)[2:] gives bits of x as str, use int to convert them to 0/1
A			:						Any        =  [int(bit) for bit in bin(WATERMARK_MESSAGE)[2:]]



class 				A       :
					'''simple docstring'''






					def __init__(self       :		Union[str, Any]						)		->  Optional[int]:




							"""simple docstring"""


							lowercase__	     =						WATERMARK_BITS
							lowercase__	     =						WatermarkEncoder()

							self.encoder.set_watermark("""bits""" ,   self.watermark						)


					def     lowerCamelCase__	(self       :		Any ,   _UpperCAmelCase       :		torch.FloatTensor						)		->  Optional[Any]:




							"""simple docstring"""


							if images.shape[-1] < 256:
									return images

							lowercase__	     =						(255 * (images / 2 + 0.5)).cpu().permute(0 ,   2 ,   3 ,   1						).float().numpy()

							lowercase__	     =						[self.encoder.encode(_UpperCAmelCase ,   """dwtDct"""						) for image in images]

							lowercase__	     =						torch.from_numpy(np.array(_UpperCAmelCase						)						).permute(0 ,   3 ,   1 ,   2						)

							lowercase__	     =						torch.clamp(2 * (images / 255 - 0.5) ,   min=-1.0 ,   max=1.0						)
							return images








import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


_A					:				Dict				=			get_tests_dir("""fixtures/test_sentencepiece_bpe.model""")



class 					__snake_case	(  __SCREAMING_SNAKE_CASE			,     unittest.TestCase    ):


    '''simple docstring'''







    lowerCamelCase__    :		Any				=	BartphoTokenizer
    lowerCamelCase__    :		Tuple				=	False
    lowerCamelCase__    :		Dict				=	True



    def  lowercase_					(       self     ):





        '''simple docstring'''

        super().setUp()

        SCREAMING_SNAKE_CASE__											=			['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
        SCREAMING_SNAKE_CASE__											=			dict(zip(A_   ,				range(len(A_     )     )     )     )
        SCREAMING_SNAKE_CASE__											=			{'''unk_token''': '''<unk>'''}

        SCREAMING_SNAKE_CASE__											=			os.path.join(self.tmpdirname   ,				VOCAB_FILES_NAMES['''monolingual_vocab_file''']     )
        with open(self.monolingual_vocab_file   ,				'''w'''   ,				encoding='''utf-8'''     ) as fp:
            for token in vocab_tokens:
                fp.write(f'''{token} {vocab_tokens[token]}\n'''     )

        SCREAMING_SNAKE_CASE__											=			BartphoTokenizer(A_   ,				self.monolingual_vocab_file   ,				**self.special_tokens_map     )
        tokenizer.save_pretrained(self.tmpdirname     )



    def  lowercase_					(       self   ,				**A_     ):





        '''simple docstring'''

        kwargs.update(self.special_tokens_map     )
        return BartphoTokenizer.from_pretrained(self.tmpdirname   ,				**A_     )



    def  lowercase_					(       self   ,				A_     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			'''This is a là test'''
        SCREAMING_SNAKE_CASE__											=			'''This is a<unk><unk> test'''
        return input_text, output_text




    def  lowercase_					(       self     ):





        '''simple docstring'''

        SCREAMING_SNAKE_CASE__											=			BartphoTokenizer(A_   ,				self.monolingual_vocab_file   ,				**self.special_tokens_map     )
        SCREAMING_SNAKE_CASE__											=			'''This is a là test'''
        SCREAMING_SNAKE_CASE__											=			'''▁This ▁is ▁a ▁l à ▁t est'''.split()
        SCREAMING_SNAKE_CASE__											=			tokenizer.tokenize(A_     )
        self.assertListEqual(A_   ,				A_     )

        SCREAMING_SNAKE_CASE__											=			tokens + [tokenizer.unk_token]
        SCREAMING_SNAKE_CASE__											=			[4, 5, 6, 3, 3, 7, 8, 3]
        self.assertListEqual(tokenizer.convert_tokens_to_ids(A_     )   ,				A_     )
