

"""simple docstring"""




import os
import unittest

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

from ...test_tokenization_common import TokenizerTesterMixin


class 		_A       (			__a				,       unittest.TestCase					):
      __a								=	PhobertTokenizer
      __a								=	False





      def 					_lowerCamelCase  (  self		)   ->					Any:
         super().setUp()

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

         lowerCamelCase__						=			os.path.join(self.tmpdirname    ,						VOCAB_FILES_NAMES["vocab_file"]		)
         lowerCamelCase__						=			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(SCREAMING_SNAKE_CASE__		)		)





      def 					_lowerCamelCase  (  self    ,						**SCREAMING_SNAKE_CASE__		)   ->					Tuple:
         kwargs.update(self.special_tokens_map		)
         return PhobertTokenizer.from_pretrained(self.tmpdirname    ,						**SCREAMING_SNAKE_CASE__		)





      def 					_lowerCamelCase  (  self    ,						SCREAMING_SNAKE_CASE__		)   ->					Tuple:
         lowerCamelCase__						=			"Tôi là VinAI Research"
         lowerCamelCase__						=			"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:
         lowerCamelCase__						=			PhobertTokenizer(self.vocab_file    ,						self.merges_file    ,						**self.special_tokens_map		)
         lowerCamelCase__						=			"Tôi là VinAI Research"
         lowerCamelCase__						=			"T@@ ô@@ i l@@ à V@@ i@@ n@@ A@@ I R@@ e@@ s@@ e@@ a@@ r@@ c@@ h".split()
         lowerCamelCase__						=			tokenizer.tokenize(SCREAMING_SNAKE_CASE__		)
         print(SCREAMING_SNAKE_CASE__		)
         self.assertListEqual(SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__		)

         lowerCamelCase__						=			tokens + [tokenizer.unk_token]

         lowerCamelCase__						=			[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(SCREAMING_SNAKE_CASE__		)    ,						SCREAMING_SNAKE_CASE__		)







"""simple docstring"""




import copy

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


SCREAMING_SNAKE_CASE_     :			Dict	  =			logging.get_logger(__name__)


class 		_A       (			__a					):
      __a								=	'encoder-decoder'
      __a								=	True





      def __init__(  self    ,						**SCREAMING_SNAKE_CASE__		)   ->					Optional[int]:
         super().__init__(**SCREAMING_SNAKE_CASE__		)
         assert (
             "encoder" in kwargs and "decoder" in kwargs
         ), "Config has to be initialized with encoder and decoder config"
         lowerCamelCase__						=			kwargs.pop("encoder"		)
         lowerCamelCase__						=			encoder_config.pop("model_type"		)
         lowerCamelCase__						=			kwargs.pop("decoder"		)
         lowerCamelCase__						=			decoder_config.pop("model_type"		)

         from ..auto.configuration_auto import AutoConfig

         lowerCamelCase__						=			AutoConfig.for_model(SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			AutoConfig.for_model(SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)
         lowerCamelCase__						=			True





      @classmethod
      def 					_lowerCamelCase  (  cls    ,						SCREAMING_SNAKE_CASE__    ,						SCREAMING_SNAKE_CASE__    ,						**SCREAMING_SNAKE_CASE__		)   ->					PretrainedConfig:
         logger.info("Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config"		)
         lowerCamelCase__						=			True
         lowerCamelCase__						=			True

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





      def 					_lowerCamelCase  (  self		)   ->					int:
         lowerCamelCase__						=			copy.deepcopy(self.__dict__		)
         lowerCamelCase__						=			self.encoder.to_dict()
         lowerCamelCase__						=			self.decoder.to_dict()
         lowerCamelCase__						=			self.__class__.model_type
         return output




