




"""simple docstring"""

import json
import os
import unittest

from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
    VOCAB_FILES_NAMES,
    GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class 							lowercase_			(	__lowerCAmelCase     ,      unittest.TestCase				):



 '''simple docstring'''
 UpperCAmelCase       :	List[str]     =      GPTSanJapaneseTokenizer
 UpperCAmelCase       :	str     =      False
 UpperCAmelCase       :	List[Any]     =      {'''do_clean_text''': False, '''add_prefix_space''': False}

 def      lowerCAmelCase_				(					self			:			str						):
       super().setUp()

       # fmt: off
       _A     =  ['こん', 'こんに', 'にちは', 'ばんは', '世界,㔺界', '、', '。', '<BR>', '<SP>', '<TAB>', '<URL>', '<EMAIL>', '<TEL>', '<DATE>', '<PRICE>', '<BLOCK>', '<KIGOU>', '<U2000U2BFF>', '<|emoji1|>', '<unk>', '<|bagoftoken|>', '<|endoftext|>']
       # fmt: on
       _A     =  {'emoji': {'\ud83d\ude00': '<|emoji1|>'}, 'emoji_inv': {'<|emoji1|>': '\ud83d\ude00'}}  # 😀
       _A     =  {'unk_token': '<unk>'}

       _A     =  os.path.join(self.tmpdirname       ,				VOCAB_FILES_NAMES['vocab_file']						)
       _A     =  os.path.join(self.tmpdirname       ,				VOCAB_FILES_NAMES['emoji_file']						)
       with open(self.vocab_file       ,				'w'       ,				encoding='utf-8'						) as vocab_writer:
             vocab_writer.write(''.join([x + '\n' for x in vocab_tokens]						)						)
       with open(self.emoji_file       ,				'w'						) as emoji_writer:
             emoji_writer.write(json.dumps(_UpperCAmelCase						)						)

 def      lowerCAmelCase_				(					self			:			Union[str, Any]       ,				**_UpperCAmelCase			:			int						):
       kwargs.update(self.special_tokens_map						)
       return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname       ,				**_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Optional[Any]       ,				_UpperCAmelCase			:			Dict						):
       _A     =  'こんにちは、世界。 \nこんばんは、㔺界。😀'
       _A     =  'こんにちは、世界。 \nこんばんは、世界。😀'
       return input_text, output_text

 def      lowerCAmelCase_				(					self			:			Dict       ,				_UpperCAmelCase			:			Any						):
       _A  ,       _A     =  self.get_input_output_texts(_UpperCAmelCase						)
       _A     =  tokenizer.encode(_UpperCAmelCase       ,				add_special_tokens=_UpperCAmelCase						)
       _A     =  tokenizer.decode(_UpperCAmelCase       ,				clean_up_tokenization_spaces=_UpperCAmelCase						)
       return text, ids

 def      lowerCAmelCase_				(					self			:			str						):
       pass  # TODO add if relevant

 def      lowerCAmelCase_				(					self			:			Dict						):
       pass  # TODO add if relevant

 def      lowerCAmelCase_				(					self			:			Optional[Any]						):
       pass  # TODO add if relevant

 def      lowerCAmelCase_				(					self			:			Tuple						):
       _A     =  self.get_tokenizer()

       # Testing tokenization
       _A     =  'こんにちは、世界。　こんばんは、㔺界。'
       _A     =  ['こん', 'にちは', '、', '世界', '。', '<SP>', 'こん', 'ばんは', '、', '㔺界', '。']
       _A     =  tokenizer.tokenize(_UpperCAmelCase						)
       self.assertListEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)

       # Testing conversion to ids without special tokens
       _A     =  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
       _A     =  tokenizer.convert_tokens_to_ids(_UpperCAmelCase						)
       self.assertListEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)

       # Testing conversion to ids with special tokens
       _A     =  tokens + [tokenizer.unk_token]
       _A     =  [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
       _A     =  tokenizer.convert_tokens_to_ids(_UpperCAmelCase						)
       self.assertListEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Dict						):
       _A     =  self.get_tokenizer()

       # Testing tokenization
       _A     =  'こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。'
       _A     =  'こんにちは、、、、世界。こんばんは、、、、世界。'
       _A     =  tokenizer.encode(_UpperCAmelCase						)
       _A     =  tokenizer.decode(_UpperCAmelCase						)
       self.assertEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)

 @slow
 def      lowerCAmelCase_				(					self			:			str						):
       _A     =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'						)

       # Testing tokenization
       _A     =  'こんにちは、世界。'
       _A     =  'こんばんは、㔺界。😀'
       _A     =  'こんにちは、世界。こんばんは、世界。😀'
       _A     =  tokenizer.encode(prefix_text + input_text						)
       _A     =  tokenizer.encode(''       ,				prefix_text=prefix_text + input_text						)
       _A     =  tokenizer.encode(_UpperCAmelCase       ,				prefix_text=_UpperCAmelCase						)
       _A     =  tokenizer.decode(_UpperCAmelCase						)
       _A     =  tokenizer.decode(_UpperCAmelCase						)
       _A     =  tokenizer.decode(_UpperCAmelCase						)
       self.assertEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)
       self.assertEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)
       self.assertEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)

 @slow
 def      lowerCAmelCase_				(					self			:			int						):
       _A     =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'						)

       # Testing tokenization
       _A     =  'こんにちは、世界。'
       _A     =  'こんばんは、㔺界。😀'

       _A     =  len(tokenizer.encode(_UpperCAmelCase						)						) - 2
       _A     =  len(tokenizer.encode(_UpperCAmelCase						)						) - 2

       _A     =  [1] + [0] * (len_prefix + len_text + 1)
       _A     =  [1] * (len_prefix + len_text + 1) + [0]
       _A     =  [1] + [1] * (len_prefix) + [0] * (len_text + 1)

       _A     =  tokenizer(prefix_text + input_text						).token_type_ids
       _A     =  tokenizer(''       ,				prefix_text=prefix_text + input_text						).token_type_ids
       _A     =  tokenizer(_UpperCAmelCase       ,				prefix_text=_UpperCAmelCase						).token_type_ids
       self.assertListEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)
       self.assertListEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)
       self.assertListEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)

 @slow
 def      lowerCAmelCase_				(					self			:			List[Any]						):
       _A     =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'						)

       _A     =  tokenizer.encode('あンいワ'						)
       _A     =  tokenizer.encode(''       ,				prefix_text='あンいワ'						)
       _A     =  tokenizer.encode('いワ'       ,				prefix_text='あン'						)

       self.assertEqual(tokenizer.decode(_UpperCAmelCase						)       ,				tokenizer.decode(_UpperCAmelCase						)						)
       self.assertEqual(tokenizer.decode(_UpperCAmelCase						)       ,				tokenizer.decode(_UpperCAmelCase						)						)
       self.assertNotEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)
       self.assertNotEqual(_UpperCAmelCase       ,				_UpperCAmelCase						)
       self.assertEqual(x_token_a[1]       ,				x_token_a[-1]						)  # SEG token
       self.assertEqual(x_token_a[1]       ,				x_token_a[3]						)  # SEG token

 @slow
 def      lowerCAmelCase_				(					self			:			int						):
       _A     =  self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese'						)

       _A     =  [['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
       _A     =  tokenizer(_UpperCAmelCase       ,				padding=_UpperCAmelCase						)
       _A     =  tokenizer.batch_encode_plus(_UpperCAmelCase       ,				padding=_UpperCAmelCase						)

       # fmt: off
       _A     =  [[35_993, 8_640, 25_948, 35_998, 30_647, 35_675, 35_999, 35_999], [35_993, 10_382, 9_868, 35_998, 30_646, 9_459, 30_646, 35_675]]
       _A     =  [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
       _A     =  [[1, 1, 1, 1, 1, 1, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1]]
       # fmt: on
       self.assertListEqual(x_token.input_ids       ,				_UpperCAmelCase						)
       self.assertListEqual(x_token.token_type_ids       ,				_UpperCAmelCase						)
       self.assertListEqual(x_token.attention_mask       ,				_UpperCAmelCase						)
       self.assertListEqual(x_token_a.input_ids       ,				_UpperCAmelCase						)
       self.assertListEqual(x_token_a.token_type_ids       ,				_UpperCAmelCase						)
       self.assertListEqual(x_token_a.attention_mask       ,				_UpperCAmelCase						)

 def      lowerCAmelCase_				(					self			:			Optional[Any]						):
       # Intentionally convert some words to accommodate character fluctuations unique to Japanese
       pass



 def      lowerCAmelCase_				(					self			:			Tuple						):
       # tokenizer has no padding token
       pass







"""simple docstring"""

from ...configuration_utils import PretrainedConfig
from ...utils import logging


a							      =     logging.get_logger(__name__)

a							      =     {
    '''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
    # See all ViT MAE models at https://huggingface.co/models?filter=vit-mae
}





class 							lowercase_			(	__lowerCAmelCase				):



 '''simple docstring'''
 UpperCAmelCase       :	int     =      '''vit_mae'''

 def __init__(					self			:			Union[str, Any]       ,				_UpperCAmelCase			:			Optional[int]=768       ,				_UpperCAmelCase			:			Tuple=12       ,				_UpperCAmelCase			:			Optional[Any]=12       ,				_UpperCAmelCase			:			Optional[int]=3_072       ,				_UpperCAmelCase			:			Any="gelu"       ,				_UpperCAmelCase			:			Optional[Any]=0.0       ,				_UpperCAmelCase			:			Optional[int]=0.0       ,				_UpperCAmelCase			:			Dict=0.02       ,				_UpperCAmelCase			:			List[Any]=1E-1_2       ,				_UpperCAmelCase			:			Optional[Any]=224       ,				_UpperCAmelCase			:			int=16       ,				_UpperCAmelCase			:			str=3       ,				_UpperCAmelCase			:			Tuple=True       ,				_UpperCAmelCase			:			int=16       ,				_UpperCAmelCase			:			str=512       ,				_UpperCAmelCase			:			int=8       ,				_UpperCAmelCase			:			List[Any]=2_048       ,				_UpperCAmelCase			:			Optional[Any]=0.75       ,				_UpperCAmelCase			:			List[str]=False       ,				**_UpperCAmelCase			:			Union[str, Any]       ,				):
       super().__init__(**_UpperCAmelCase						)

       _A     =  hidden_size
       _A     =  num_hidden_layers
       _A     =  num_attention_heads
       _A     =  intermediate_size
       _A     =  hidden_act
       _A     =  hidden_dropout_prob
       _A     =  attention_probs_dropout_prob
       _A     =  initializer_range
       _A     =  layer_norm_eps
       _A     =  image_size
       _A     =  patch_size
       _A     =  num_channels
       _A     =  qkv_bias
       _A     =  decoder_num_attention_heads
       _A     =  decoder_hidden_size
       _A     =  decoder_num_hidden_layers
       _A     =  decoder_intermediate_size
       _A     =  mask_ratio
       _A     =  norm_pix_loss

