



from typing import List

import PIL
import torch
from PIL import Image

from ...configuration_utils import ConfigMixin
from ...models.modeling_utils import ModelMixin
from ...utils import PIL_INTERPOLATION

class 						lowerCamelCase_     (			__UpperCamelCase    ,__UpperCamelCase    ):






						'''simple docstring'''







						def __init__(						self   :      int			)   ->					Optional[Any]:
									super().__init__()

									self.register_buffer("watermark_image"						,						torch.zeros((62, 62, 4)			)			)
									A				:       Union[str, Any]														=    None







						def       SCREAMING_SNAKE_CASE__		(						self   :      Union[str, Any]						,						__lowerCamelCase   :      List[PIL.Image.Image]						,						__lowerCamelCase   :      List[str]=None			)   ->					List[str]:
									A				:       Union[str, Any]														=    images[0].height
									A				:       List[Any]														=    images[0].width

									A				:       str														=    sample_size or h

									A				:       Union[str, Any]														=    min(h / sample_size						,						w / sample_size			)
									A				:       Union[str, Any]														=    (int(h / coef			), int(w / coef			)) if coef < 1 else (h, w)

									A				:       int														=    10_24**2, img_w * img_h
									A				:       int														=    (Sa / Sa) ** 0.5
									A				:       str														=    int(K * 62			), img_w - int(14 * K			), img_h - int(14 * K			)

									if self.watermark_image_as_pil is None:
												A				:       Dict														=    self.watermark_image.to(torch.uinta			).cpu().numpy()
												A				:       str														=    Image.fromarray(a_						,						mode="RGBA"			)
												A				:       Dict														=    watermark_image

									A				:       Any														=    self.watermark_image_as_pil.resize(
									    (wm_size, wm_size)						,						PIL_INTERPOLATION["bicubic"]						,						reducing_gap=a_			)

									for pil_img in images:
												pil_img.paste(a_						,						box=(wm_x - wm_size, wm_y - wm_size, wm_x, wm_y)						,						mask=wm_img.split()[-1]			)

									return images




import json
import os
import unittest

from transformers import HerbertTokenizer, HerbertTokenizerFast
from transformers.models.herbert.tokenization_herbert import VOCAB_FILES_NAMES
from transformers.testing_utils import get_tests_dir, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin

@require_tokenizers
class 						UpperCAmelCase__     (     __UpperCamelCase		,unittest.TestCase  ):




			'''simple docstring'''






			UpperCamelCase     		=			HerbertTokenizer
			UpperCamelCase     		=			HerbertTokenizerFast
			UpperCamelCase     		=			True




			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					super().setUp()

					# Use a simpler test file without japanese/chinese characters
					with open(F'{get_tests_dir()}/fixtures/sample_text_no_unicode.txt'			,			encoding='''utf-8'''					) as f_data:
							__UpperCAmelCase       :	List[str]						=      f_data.read().replace('''\n\n'''			,			'''\n'''					).strip()

					__UpperCAmelCase       :	Dict						=      [
					    '''<s>''',
					    '''</s>''',
					    '''l''',
					    '''o''',
					    '''w''',
					    '''e''',
					    '''r''',
					    '''s''',
					    '''t''',
					    '''i''',
					    '''d''',
					    '''n''',
					    '''w</w>''',
					    '''r</w>''',
					    '''t</w>''',
					    '''lo''',
					    '''low''',
					    '''er</w>''',
					    '''low</w>''',
					    '''lowest</w>''',
					    '''newer</w>''',
					    '''wider</w>''',
					    ''',</w>''',
					    '''<unk>''',
					]
					__UpperCAmelCase       :	Tuple						=      dict(zip(a_			,			range(len(a_					)					)					)					)
					__UpperCAmelCase       :	Optional[int]						=      ['''l o 123''', '''lo w 1456''', '''e r</w> 1789''', '''''']

					__UpperCAmelCase       :	str						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''vocab_file''']					)
					__UpperCAmelCase       :	List[str]						=      os.path.join(self.tmpdirname			,			VOCAB_FILES_NAMES['''merges_file''']					)
					with open(self.vocab_file			,			'''w'''					) as fp:
							fp.write(json.dumps(a_					)					)
					with open(self.merges_file			,			'''w'''					) as fp:
							fp.write('''\n'''.join(a_					)					)




			def 					snake_case__	(  self				:					Union[str, Any]			,			a_				:					Optional[Any]					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[str]						=      '''lower newer'''
					__UpperCAmelCase       :	List[Any]						=      '''lower newer'''
					return input_text, output_text




			def 					snake_case__	(  self				:					int					):
					'''simple docstring'''





					__UpperCAmelCase       :	Any						=      self.tokenizer_class(vocab_file=self.vocab_file			,			merges_file=self.merges_file					)

					__UpperCAmelCase       :	Optional[int]						=      '''lower'''
					__UpperCAmelCase       :	Any						=      ['''low''', '''er</w>''']
					__UpperCAmelCase       :	Any						=      tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	int						=      tokens + ['''<unk>''']
					__UpperCAmelCase       :	Optional[Any]						=      [16, 17, 23]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(a_					)			,			a_					)




			def 					snake_case__	(  self				:					List[Any]					):
					'''simple docstring'''





					if not self.test_rust_tokenizer:
							return

					__UpperCAmelCase       :	str						=      self.get_tokenizer()
					__UpperCAmelCase       :	Optional[int]						=      self.get_rust_tokenizer()

					__UpperCAmelCase       :	Tuple						=      '''lower,newer'''

					__UpperCAmelCase       :	Optional[int]						=      tokenizer.tokenize(a_					)
					__UpperCAmelCase       :	Tuple						=      rust_tokenizer.tokenize(a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Optional[Any]						=      tokenizer.encode(a_			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	Union[str, Any]						=      rust_tokenizer.encode(a_			,			add_special_tokens=a_					)
					self.assertListEqual(a_			,			a_					)

					__UpperCAmelCase       :	Tuple						=      self.get_rust_tokenizer()
					__UpperCAmelCase       :	Union[str, Any]						=      tokenizer.encode(a_					)
					__UpperCAmelCase       :	str						=      rust_tokenizer.encode(a_					)
					self.assertListEqual(a_			,			a_					)




			@slow
			def 					snake_case__	(  self				:					Tuple					):
					'''simple docstring'''





					__UpperCAmelCase       :	List[Any]						=      self.tokenizer_class.from_pretrained('''allegro/herbert-base-cased'''					)

					__UpperCAmelCase       :	Tuple						=      tokenizer.encode('''konstruowanie sekwencji'''			,			add_special_tokens=a_					)
					__UpperCAmelCase       :	int						=      tokenizer.encode('''konstruowanie wielu sekwencji'''			,			add_special_tokens=a_					)

					__UpperCAmelCase       :	Union[str, Any]						=      tokenizer.build_inputs_with_special_tokens(a_					)
					__UpperCAmelCase       :	Any						=      tokenizer.build_inputs_with_special_tokens(a_			,			a_					)

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





