
"""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       (    __UpperCAmelCase    ,	unittest.TestCase		):
	lowercase_				=     GPTSanJapaneseTokenizer
	lowercase_				=     False
	lowercase_				=     {'do_clean_text': False, 'add_prefix_space': False}




	def       _UpperCamelCase   (			self )		->							Dict:
			super().setUp()

			# fmt: off
			lowerCamelCase					:      Tuple          =   ['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
			lowerCamelCase					:      List[str]          =   {'emoji': {'\ud83d\ude00': '<|emoji1|>'}, 'emoji_inv': {'<|emoji1|>': '\ud83d\ude00'}}  # 😀
			lowerCamelCase					:      List[str]          =   {'unk_token': '<unk>'}

			lowerCamelCase					:      Dict          =   os.path.join(self.tmpdirname		,			VOCAB_FILES_NAMES['vocab_file'] )
			lowerCamelCase					:      int          =   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       _UpperCamelCase   (			self		,			**UpperCAmelCase_ )		->							List[str]:
			kwargs.update(self.special_tokens_map )
			return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname		,			**UpperCAmelCase_ )




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_ )		->							List[str]:
			lowerCamelCase					:      Tuple          =   'こんにちは、世界。 \nこんばんは、㔺界。😀'
			lowerCamelCase					:      List[str]          =   'こんにちは、世界。 \nこんばんは、世界。😀'
			return input_text, output_text




	def       _UpperCamelCase   (			self		,			UpperCAmelCase_ )		->							Dict:
			lowerCamelCase     ,   lowerCamelCase					:      List[Any]          =   self.get_input_output_texts(UpperCAmelCase_ )
			lowerCamelCase					:      int          =   tokenizer.encode(UpperCAmelCase_		,			add_special_tokens=UpperCAmelCase_ )
			lowerCamelCase					:      Optional[Any]          =   tokenizer.decode(UpperCAmelCase_		,			clean_up_tokenization_spaces=UpperCAmelCase_ )
			return text, ids




	def       _UpperCamelCase   (			self )		->							int:
			pass  # TODO add if relevant




	def       _UpperCamelCase   (			self )		->							Optional[int]:
			pass  # TODO add if relevant




	def       _UpperCamelCase   (			self )		->							Tuple:
			pass  # TODO add if relevant




	def       _UpperCamelCase   (			self )		->							Any:
			lowerCamelCase					:      Dict          =   self.get_tokenizer()

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

			# Testing conversion to ids without special tokens
			lowerCamelCase					:      Optional[Any]          =   [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6]
			lowerCamelCase					:      Union[str, Any]          =   tokenizer.convert_tokens_to_ids(UpperCAmelCase_ )
			self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )

			# Testing conversion to ids with special tokens
			lowerCamelCase					:      Union[str, Any]          =   tokens + [tokenizer.unk_token]
			lowerCamelCase					:      Optional[int]          =   [0, 2, 5, 4, 6, 8, 0, 3, 5, 4, 6, 19]
			lowerCamelCase					:      Union[str, Any]          =   tokenizer.convert_tokens_to_ids(UpperCAmelCase_ )
			self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	def       _UpperCamelCase   (			self )		->							int:
			lowerCamelCase					:      Optional[int]          =   self.get_tokenizer()

			# Testing tokenization
			lowerCamelCase					:      str          =   'こんにちは、<|bagoftoken|>世界。こんばんは、<|bagoftoken|>㔺界。'
			lowerCamelCase					:      str          =   'こんにちは、、、、世界。こんばんは、、、、世界。'
			lowerCamelCase					:      int          =   tokenizer.encode(UpperCAmelCase_ )
			lowerCamelCase					:      List[Any]          =   tokenizer.decode(UpperCAmelCase_ )
			self.assertEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	@slow
	def       _UpperCamelCase   (			self )		->							Optional[int]:
			lowerCamelCase					:      Any          =   self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese' )

			# Testing tokenization
			lowerCamelCase					:      Optional[Any]          =   'こんにちは、世界。'
			lowerCamelCase					:      str          =   'こんばんは、㔺界。😀'
			lowerCamelCase					:      List[Any]          =   'こんにちは、世界。こんばんは、世界。😀'
			lowerCamelCase					:      int          =   tokenizer.encode(prefix_text + input_text )
			lowerCamelCase					:      Dict          =   tokenizer.encode(''		,			prefix_text=prefix_text + input_text )
			lowerCamelCase					:      Union[str, Any]          =   tokenizer.encode(UpperCAmelCase_		,			prefix_text=UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   tokenizer.decode(UpperCAmelCase_ )
			lowerCamelCase					:      List[Any]          =   tokenizer.decode(UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   tokenizer.decode(UpperCAmelCase_ )
			self.assertEqual(UpperCAmelCase_		,			UpperCAmelCase_ )
			self.assertEqual(UpperCAmelCase_		,			UpperCAmelCase_ )
			self.assertEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	@slow
	def       _UpperCamelCase   (			self )		->							Optional[Any]:
			lowerCamelCase					:      Optional[Any]          =   self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese' )

			# Testing tokenization
			lowerCamelCase					:      Any          =   'こんにちは、世界。'
			lowerCamelCase					:      int          =   'こんばんは、㔺界。😀'

			lowerCamelCase					:      int          =   len(tokenizer.encode(UpperCAmelCase_ ) ) - 2
			lowerCamelCase					:      int          =   len(tokenizer.encode(UpperCAmelCase_ ) ) - 2

			lowerCamelCase					:      List[str]          =   [1] + [0] * (len_prefix + len_text + 1)
			lowerCamelCase					:      List[str]          =   [1] * (len_prefix + len_text + 1) + [0]
			lowerCamelCase					:      List[Any]          =   [1] + [1] * (len_prefix) + [0] * (len_text + 1)

			lowerCamelCase					:      List[Any]          =   tokenizer(prefix_text + input_text ).token_type_ids
			lowerCamelCase					:      List[str]          =   tokenizer(''		,			prefix_text=prefix_text + input_text ).token_type_ids
			lowerCamelCase					:      Dict          =   tokenizer(UpperCAmelCase_		,			prefix_text=UpperCAmelCase_ ).token_type_ids
			self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )
			self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )
			self.assertListEqual(UpperCAmelCase_		,			UpperCAmelCase_ )




	@slow
	def       _UpperCamelCase   (			self )		->							int:
			lowerCamelCase					:      str          =   self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese' )

			lowerCamelCase					:      List[str]          =   tokenizer.encode('あンいワ' )
			lowerCamelCase					:      Optional[int]          =   tokenizer.encode(''		,			prefix_text='あンいワ' )
			lowerCamelCase					:      Union[str, Any]          =   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       _UpperCamelCase   (			self )		->							Dict:
			lowerCamelCase					:      Union[str, Any]          =   self.tokenizer_class.from_pretrained('Tanrei/GPTSAN-japanese' )

			lowerCamelCase					:      Union[str, Any]          =   [['武田信玄', 'は、'], ['織田信長', 'の配下の、']]
			lowerCamelCase					:      int          =   tokenizer(UpperCAmelCase_		,			padding=UpperCAmelCase_ )
			lowerCamelCase					:      Union[str, Any]          =   tokenizer.batch_encode_plus(UpperCAmelCase_		,			padding=UpperCAmelCase_ )

			# fmt: off
			lowerCamelCase					:      Dict          =   [[35993, 8640, 25948, 35998, 30647, 35675, 35999, 35999], [35993, 10382, 9868, 35998, 30646, 9459, 30646, 35675]]
			lowerCamelCase					:      Dict          =   [[1, 1, 1, 0, 0, 0, 0, 0], [1, 1, 1, 0, 0, 0, 0, 0]]
			lowerCamelCase					:      List[Any]          =   [[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       _UpperCamelCase   (			self )		->							List[Any]:
			# Intentionally convert some words to accommodate character fluctuations unique to Japanese
			pass




	def       _UpperCamelCase   (			self )		->							List[Any]:
			# tokenizer has no padding token
			pass








"""simple docstring"""

import copy

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


_A						=			logging.get_logger(__name__)






class 	_lowercase       (    __UpperCAmelCase		):
	lowercase_				=     'encoder-decoder'
	lowercase_				=     True




	def __init__(			self		,			**UpperCAmelCase_ )		->							str:
			super().__init__(**UpperCAmelCase_ )
			assert (
			    "encoder" in kwargs and "decoder" in kwargs
			), "Config has to be initialized with encoder and decoder config"
			lowerCamelCase					:      List[Any]          =   kwargs.pop('encoder' )
			lowerCamelCase					:      Optional[int]          =   encoder_config.pop('model_type' )
			lowerCamelCase					:      str          =   kwargs.pop('decoder' )
			lowerCamelCase					:      Dict          =   decoder_config.pop('model_type' )

			from ..auto.configuration_auto import AutoConfig

			lowerCamelCase					:      int          =   AutoConfig.for_model(UpperCAmelCase_		,			**UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   AutoConfig.for_model(UpperCAmelCase_		,			**UpperCAmelCase_ )
			lowerCamelCase					:      List[str]          =   True




	@classmethod
	def       _UpperCamelCase   (			cls		,			UpperCAmelCase_		,			UpperCAmelCase_		,			**UpperCAmelCase_ )		->							PretrainedConfig:
			logger.info('Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config' )
			lowerCamelCase					:      str          =   True
			lowerCamelCase					:      Optional[Any]          =   True

			return cls(encoder=encoder_config.to_dict()		,			decoder=decoder_config.to_dict()		,			**UpperCAmelCase_ )




	def       _UpperCamelCase   (			self )		->							Union[str, Any]:
			lowerCamelCase					:      Union[str, Any]          =   copy.deepcopy(self.__dict__ )
			lowerCamelCase					:      Union[str, Any]          =   self.encoder.to_dict()
			lowerCamelCase					:      List[Any]          =   self.decoder.to_dict()
			lowerCamelCase					:      Tuple          =   self.__class__.model_type
			return output






