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 _a       (	snake_case__   ,							unittest.TestCase ):

	'''simple docstring'''



	lowerCamelCase_   :      Any       =	HerbertTokenizer
	lowerCamelCase_   :      List[str]       =	HerbertTokenizerFast
	lowerCamelCase_   :      List[str]       =	True

	def 					__UpperCAmelCase(       self   ):
			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:
					__A							:   str	  =				f_data.read().replace("\n\n"							,			"\n"   ).strip()

			__A							:   Optional[int]	  =				[
			    '<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>',
			]
			__A							:   Optional[Any]	  =				dict(zip(__UpperCAmelCase							,			range(len(__UpperCAmelCase   )   )   )   )
			__A							:   Union[str, Any]	  =				['l o 123', 'lo w 1456', 'e r</w> 1789', '']

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

	def 					__UpperCAmelCase(       self							,			__UpperCAmelCase   ):
			__A							:   List[str]	  =				'lower newer'
			__A							:   int	  =				'lower newer'
			return input_text, output_text

	def 					__UpperCAmelCase(       self   ):
			__A							:   Dict	  =				self.tokenizer_class(vocab_file=self.vocab_file							,			merges_file=self.merges_file   )

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

			__A							:   List[str]	  =				tokens + ['<unk>']
			__A							:   int	  =				[16, 17, 23]
			self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase   )							,			__UpperCAmelCase   )

	def 					__UpperCAmelCase(       self   ):
			if not self.test_rust_tokenizer:
					return

			__A							:   Tuple	  =				self.get_tokenizer()
			__A							:   Tuple	  =				self.get_rust_tokenizer()

			__A							:   Dict	  =				'lower,newer'

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

			__A							:   str	  =				tokenizer.encode(__UpperCAmelCase							,			add_special_tokens=__UpperCAmelCase   )
			__A							:   Any	  =				rust_tokenizer.encode(__UpperCAmelCase							,			add_special_tokens=__UpperCAmelCase   )
			self.assertListEqual(__UpperCAmelCase							,			__UpperCAmelCase   )

			__A							:   str	  =				self.get_rust_tokenizer()
			__A							:   Tuple	  =				tokenizer.encode(__UpperCAmelCase   )
			__A							:   Dict	  =				rust_tokenizer.encode(__UpperCAmelCase   )
			self.assertListEqual(__UpperCAmelCase							,			__UpperCAmelCase   )







	@slow
	def 					__UpperCAmelCase(       self   ):
			__A							:   Any	  =				self.tokenizer_class.from_pretrained("allegro/herbert-base-cased"   )

			__A							:   Any	  =				tokenizer.encode("konstruowanie sekwencji"							,			add_special_tokens=__UpperCAmelCase   )
			__A							:   Any	  =				tokenizer.encode("konstruowanie wielu sekwencji"							,			add_special_tokens=__UpperCAmelCase   )

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

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






from dataclasses import dataclass
from typing import List, Optional, Union

import numpy as np
import PIL
from PIL import Image

from ...utils import is_torch_available, is_transformers_available


if is_transformers_available() and is_torch_available():
					from .image_encoder import PaintByExampleImageEncoder
					from .pipeline_paint_by_example import PaintByExamplePipeline





