


import os
import unittest

from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer

from ...test_tokenization_common import TokenizerTesterMixin



class 							A   (	UpperCAmelCase__			,  unittest.TestCase							):
					'''simple docstring'''






					A__      =			PhobertTokenizer
					A__      =			False

					def   lowerCamelCase__					(self   :						Tuple		)						->       Tuple:




							"""simple docstring"""


							super().setUp()

							# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
							lowercase__					      =		["""T@@""", """i""", """I""", """R@@""", """r""", """e@@"""]
							lowercase__					      =		dict(zip(_UpperCAmelCase				, range(len(_UpperCAmelCase		)		)		)		)
							lowercase__					      =		["""#version: 0.2""", """l à</w>"""]
							lowercase__					      =		{"""unk_token""": """<unk>"""}

							lowercase__					      =		os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES["""vocab_file"""]		)
							lowercase__					      =		os.path.join(self.tmpdirname				, VOCAB_FILES_NAMES["""merges_file"""]		)

							with open(self.vocab_file				, """w"""				, encoding="""utf-8"""		) as fp:
									for token in vocab_tokens:
											fp.write(f'''{token} {vocab_tokens[token]}\n'''		)
							with open(self.merges_file				, """w"""				, encoding="""utf-8"""		) as fp:
									fp.write("""\n""".join(_UpperCAmelCase		)		)

					def   lowerCamelCase__					(self   :						Tuple				, **_UpperCAmelCase   :						Optional[Any]		)						->       Tuple:




							"""simple docstring"""


							kwargs.update(self.special_tokens_map		)
							return PhobertTokenizer.from_pretrained(self.tmpdirname				, **_UpperCAmelCase		)

					def   lowerCamelCase__					(self   :						Dict				, _UpperCAmelCase   :						Dict		)						->       Tuple:




							"""simple docstring"""


							lowercase__					      =		"""Tôi là VinAI Research"""
							lowercase__					      =		"""T<unk> i <unk> <unk> <unk> <unk> <unk> <unk> I Re<unk> e<unk> <unk> <unk> <unk>"""
							return input_text, output_text


					def   lowerCamelCase__					(self   :						Tuple		)						->       Optional[Any]:




							"""simple docstring"""


							lowercase__					      =		PhobertTokenizer(self.vocab_file				, self.merges_file				, **self.special_tokens_map		)
							lowercase__					      =		"""Tôi là VinAI Research"""
							lowercase__					      =		"""T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h""".split()
							lowercase__					      =		tokenizer.tokenize(_UpperCAmelCase		)
							print(_UpperCAmelCase		)
							self.assertListEqual(_UpperCAmelCase				, _UpperCAmelCase		)

							lowercase__					      =		tokens + [tokenizer.unk_token]

							lowercase__					      =		[4, 3, 5, 3, 3, 3, 3, 3, 3, 6, 7, 9, 3, 9, 3, 3, 3, 3, 3]
							self.assertListEqual(tokenizer.convert_tokens_to_ids(_UpperCAmelCase		)				, _UpperCAmelCase		)





from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


A	:		Union[str, Any]    =       logging.get_logger(__name__)

A	:		int    =       {
    'andreasmadsen/efficient_mlm_m0.40': (
        'https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json'
    ),
}



class 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					A__      =			'''roberta-prelayernorm'''

					def __init__(self   :						Dict				, _UpperCAmelCase   :						List[Any]=5_0265				, _UpperCAmelCase   :						List[Any]=768				, _UpperCAmelCase   :						str=12				, _UpperCAmelCase   :						Any=12				, _UpperCAmelCase   :						Any=3072				, _UpperCAmelCase   :						int="gelu"				, _UpperCAmelCase   :						Tuple=0.1				, _UpperCAmelCase   :						Tuple=0.1				, _UpperCAmelCase   :						Any=512				, _UpperCAmelCase   :						Dict=2				, _UpperCAmelCase   :						int=0.02				, _UpperCAmelCase   :						List[Any]=1E-1_2				, _UpperCAmelCase   :						Tuple=1				, _UpperCAmelCase   :						int=0				, _UpperCAmelCase   :						int=2				, _UpperCAmelCase   :						Optional[Any]="absolute"				, _UpperCAmelCase   :						int=True				, _UpperCAmelCase   :						Optional[int]=None				, **_UpperCAmelCase   :						Any				, )						->       List[str]:




							"""simple docstring"""


							super().__init__(pad_token_id=_UpperCAmelCase				, bos_token_id=_UpperCAmelCase				, eos_token_id=_UpperCAmelCase				, **_UpperCAmelCase		)

							lowercase__					      =		vocab_size
							lowercase__					      =		hidden_size
							lowercase__					      =		num_hidden_layers
							lowercase__					      =		num_attention_heads
							lowercase__					      =		hidden_act
							lowercase__					      =		intermediate_size
							lowercase__					      =		hidden_dropout_prob
							lowercase__					      =		attention_probs_dropout_prob
							lowercase__					      =		max_position_embeddings
							lowercase__					      =		type_vocab_size
							lowercase__					      =		initializer_range
							lowercase__					      =		layer_norm_eps
							lowercase__					      =		position_embedding_type
							lowercase__					      =		use_cache
							lowercase__					      =		classifier_dropout






class 							A   (	UpperCAmelCase__							):
					'''simple docstring'''






					@property
					def   lowerCamelCase__					(self   :						Any		)						->       Mapping[str, Mapping[int, str]]:




							"""simple docstring"""


							if self.task == "multiple-choice":
									lowercase__					      =		{0: """batch""", 1: """choice""", 2: """sequence"""}
							else:
									lowercase__					      =		{0: """batch""", 1: """sequence"""}
							return OrderedDict(
							    [
							        ("""input_ids""", dynamic_axis),
							        ("""attention_mask""", dynamic_axis),
							    ]		)

