





"""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  __A       (  _UpperCAmelCase      ,   unittest.TestCase      ):
				__A								=			GPTSanJapaneseTokenizer
				__A								=			False
				__A								=			{"do_clean_text": False, "add_prefix_space": False}


				def _snake_case    (						self							):
								super().setUp()

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

								lowerCamelCase			=os.path.join(self.tmpdirname				,	VOCAB_FILES_NAMES["""vocab_file"""]							)
								lowerCamelCase			=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 _snake_case    (						self				,	**UpperCAmelCase_							):
								kwargs.update(self.special_tokens_map							)
								return GPTSanJapaneseTokenizer.from_pretrained(self.tmpdirname				,	**_UpperCAmelCase							)


				def _snake_case    (						self				,	UpperCAmelCase_							):
								lowerCamelCase			='''こんにちは、世界。 \nこんばんは、㔺界。😀'''
								lowerCamelCase			='''こんにちは、世界。 \nこんばんは、世界。😀'''
								return input_text, output_text


				def _snake_case    (						self				,	UpperCAmelCase_							):
								lowerCamelCase			=self.get_input_output_texts(_UpperCAmelCase							)
								lowerCamelCase			=tokenizer.encode(_UpperCAmelCase				,	add_special_tokens=_UpperCAmelCase							)
								lowerCamelCase			=tokenizer.decode(_UpperCAmelCase				,	clean_up_tokenization_spaces=_UpperCAmelCase							)
								return text, ids


				def _snake_case    (						self							):
								pass  # TODO add if relevant


				def _snake_case    (						self							):
								pass  # TODO add if relevant


				def _snake_case    (						self							):
								pass  # TODO add if relevant


				def _snake_case    (						self							):
								lowerCamelCase			=self.get_tokenizer()

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

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

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


				def _snake_case    (						self							):
								lowerCamelCase			=self.get_tokenizer()

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


				@slow
				def _snake_case    (						self							):
								lowerCamelCase			=self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""							)

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


				@slow
				def _snake_case    (						self							):
								lowerCamelCase			=self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""							)

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

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

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

								lowerCamelCase			=tokenizer(prefix_text + input_text							).token_type_ids
								lowerCamelCase			=tokenizer(""""""				,	prefix_text=prefix_text + input_text							).token_type_ids
								lowerCamelCase			=tokenizer(_UpperCAmelCase				,	prefix_text=_UpperCAmelCase							).token_type_ids
								self.assertListEqual(_UpperCAmelCase				,	_UpperCAmelCase							)
								self.assertListEqual(_UpperCAmelCase				,	_UpperCAmelCase							)
								self.assertListEqual(_UpperCAmelCase				,	_UpperCAmelCase							)


				@slow
				def _snake_case    (						self							):
								lowerCamelCase			=self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""							)

								lowerCamelCase			=tokenizer.encode("""あンいワ"""							)
								lowerCamelCase			=tokenizer.encode(""""""				,	prefix_text="""あンいワ"""							)
								lowerCamelCase			=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 _snake_case    (						self							):
								lowerCamelCase			=self.tokenizer_class.from_pretrained("""Tanrei/GPTSAN-japanese"""							)

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

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


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












from __future__ import annotations

from typing import Dict

from ...configuration_utils import PretrainedConfig


UpperCAmelCase__  :     Optional[Any]   			={
    '''susnato/ernie-m-base_pytorch''': '''https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json''',
    '''susnato/ernie-m-large_pytorch''': '''https://huggingface.co/susnato/ernie-m-large_pytorch/blob/main/config.json''',
}

class  __A       (  a      ):
				__A								=			"""ernie_m"""
				__A								=			{"dropout": "classifier_dropout", "num_classes": "num_labels"}


				def __init__(						self				,	UpperCAmelCase_ = 250002				,	UpperCAmelCase_ = 768				,	UpperCAmelCase_ = 12				,	UpperCAmelCase_ = 12				,	UpperCAmelCase_ = 3072				,	UpperCAmelCase_ = "gelu"				,	UpperCAmelCase_ = 0.1				,	UpperCAmelCase_ = 0.1				,	UpperCAmelCase_ = 514				,	UpperCAmelCase_ = 0.0_2				,	UpperCAmelCase_ = 1				,	UpperCAmelCase_ = 1E-05				,	UpperCAmelCase_=None				,	UpperCAmelCase_=False				,	UpperCAmelCase_=0.0				,	**UpperCAmelCase_				,	):
								super().__init__(pad_token_id=UpperCAmelCase_				,	**UpperCAmelCase_							)
								lowerCamelCase			=vocab_size
								lowerCamelCase			=hidden_size
								lowerCamelCase			=num_hidden_layers
								lowerCamelCase			=num_attention_heads
								lowerCamelCase			=intermediate_size
								lowerCamelCase			=hidden_act
								lowerCamelCase			=hidden_dropout_prob
								lowerCamelCase			=attention_probs_dropout_prob
								lowerCamelCase			=max_position_embeddings
								lowerCamelCase			=initializer_range
								lowerCamelCase			=layer_norm_eps
								lowerCamelCase			=classifier_dropout
								lowerCamelCase			=is_decoder
								lowerCamelCase			=act_dropout





