


import os
import pickle
import unittest

from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
    VOCAB_FILES_NAMES,
    BertJapaneseTokenizer,
    CharacterTokenizer,
    JumanppTokenizer,
    MecabTokenizer,
    SudachiTokenizer,
    WordpieceTokenizer,
)
from transformers.testing_utils import custom_tokenizers, require_jumanpp, require_sudachi

from ...test_tokenization_common import TokenizerTesterMixin



@custom_tokenizers
class        A     (		_a	, unittest.TestCase	):







     '''simple docstring'''







     lowerCamelCase :						List[str]            =   BertJapaneseTokenizer
     lowerCamelCase :						Optional[Any]            =   False
     lowerCamelCase :						Optional[int]            =   True

     def 					UpperCAmelCase__       (				self    :							List[str]):
      super().setUp()

      _lowercase:       str						=				[
          "[UNK]",
          "[CLS]",
          "[SEP]",
          "こんにちは",
          "こん",
          "にちは",
          "ばんは",
          "##こん",
          "##にちは",
          "##ばんは",
          "世界",
          "##世界",
          "、",
          "##、",
          "。",
          "##。",
      ]

      _lowercase:       Dict						=				os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES["vocab_file"])
      with open(self.vocab_file			,				"w"			,				encoding="utf-8") as vocab_writer:
       vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))

     def 					UpperCAmelCase__       (				self    :							str			,				_UpperCamelCase    :							List[str]):
      _lowercase:       Tuple						=				"こんにちは、世界。 \nこんばんは、世界。"
      _lowercase:       str						=				"こんにちは 、 世界 。 こんばんは 、 世界 。"
      return input_text, output_text

     def 					UpperCAmelCase__       (				self    :							str			,				_UpperCamelCase    :							Optional[Any]):
      _lowercase					,	_lowercase:       List[str]						=				self.get_input_output_texts(A_)
      _lowercase:       int						=				tokenizer.encode(A_			,				add_special_tokens=A_)
      _lowercase:       Optional[int]						=				tokenizer.decode(A_			,				clean_up_tokenization_spaces=A_)
      return text, ids

     def 					UpperCAmelCase__       (				self    :							Union[str, Any]):
      pass  # TODO add if relevant

     def 					UpperCAmelCase__       (				self    :							List[Any]):
      pass  # TODO add if relevant

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

     def 					UpperCAmelCase__       (				self    :							Any):
      _lowercase:       Optional[Any]						=				self.tokenizer_class(self.vocab_file)

      _lowercase:       int						=				tokenizer.tokenize("こんにちは、世界。\nこんばんは、世界。")
      self.assertListEqual(A_			,				["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"])
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A_)			,				[3, 12, 10, 14, 4, 9, 12, 10, 14])

     def 					UpperCAmelCase__       (				self    :							List[str]):
      _lowercase:       int						=				self.tokenizer_class(self.vocab_file			,				word_tokenizer_type="mecab")
      self.assertIsNotNone(A_)

      _lowercase:       int						=				"こんにちは、世界。\nこんばんは、世界。"
      _lowercase:       int						=				tokenizer.tokenize(A_)
      self.assertListEqual(A_			,				["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"])
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A_)			,				[3, 12, 10, 14, 4, 9, 12, 10, 14])

      _lowercase:       Optional[Any]						=				os.path.join(self.tmpdirname			,				"tokenizer.bin")
      with open(A_			,				"wb") as handle:
       pickle.dump(A_			,				A_)

      with open(A_			,				"rb") as handle:
       _lowercase:       Union[str, Any]						=				pickle.load(A_)

      _lowercase:       Dict						=				tokenizer_new.tokenize(A_)

      self.assertListEqual(A_			,				A_)

     def 					UpperCAmelCase__       (				self    :							Optional[int]):
      _lowercase:       Dict						=				MecabTokenizer(mecab_dic="ipadic")

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップルストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]			,				)

     def 					UpperCAmelCase__       (				self    :							List[Any]):


      try:
       _lowercase:       Dict						=				MecabTokenizer(mecab_dic="unidic_lite")
      except ModuleNotFoundError:
       return

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]			,				)

     def 					UpperCAmelCase__       (				self    :							str):


      try:
       _lowercase:       Dict						=				MecabTokenizer(mecab_dic="unidic")
      except ModuleNotFoundError:
       return

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]			,				)

     def 					UpperCAmelCase__       (				self    :							Dict):
      _lowercase:       int						=				MecabTokenizer(do_lower_case=A_			,				mecab_dic="ipadic")

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップルストア", "で", "iphone", "8", "が", "発売", "さ", "れ", "た", "。"]			,				)

     def 					UpperCAmelCase__       (				self    :							List[str]):


      try:
       _lowercase:       Dict						=				MecabTokenizer(
           do_lower_case=A_			,				normalize_text=A_			,				mecab_option="-d /usr/local/lib/mecab/dic/jumandic")
      except RuntimeError:
       # if dict doesn't exist in the system, previous code raises this error.
       return

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["ｱｯﾌﾟﾙストア", "で", "iPhone", "８", "が", "発売", "さ", "れた", "\u3000", "。"]			,				)

     def 					UpperCAmelCase__       (				self    :							Any):
      _lowercase:       Tuple						=				MecabTokenizer(normalize_text=A_			,				mecab_dic="ipadic")

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["ｱｯﾌﾟﾙストア", "で", "iPhone", "８", "が", "発売", "さ", "れ", "た", "　", "。"]			,				)

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							str):
      _lowercase:       str						=				self.tokenizer_class(self.vocab_file			,				word_tokenizer_type="sudachi")
      self.assertIsNotNone(A_)

      _lowercase:       int						=				"こんにちは、世界。\nこんばんは、世界。"
      _lowercase:       int						=				tokenizer.tokenize(A_)
      self.assertListEqual(A_			,				["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"])
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A_)			,				[3, 12, 10, 14, 4, 9, 12, 10, 14])

      _lowercase:       Optional[Any]						=				os.path.join(self.tmpdirname			,				"tokenizer.bin")
      with open(A_			,				"wb") as handle:
       pickle.dump(A_			,				A_)

      with open(A_			,				"rb") as handle:
       _lowercase:       List[Any]						=				pickle.load(A_)

      _lowercase:       Dict						=				tokenizer_new.tokenize(A_)

      self.assertListEqual(A_			,				A_)

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							Tuple):
      _lowercase:       Dict						=				SudachiTokenizer(sudachi_dict_type="core")

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				[" ", "\t", "アップル", "ストア", "で", "iPhone", "8", " ", "が", " ", " ", "\n ", "発売", "さ", "れ", "た", " ", "。", " ", " "]			,				)

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							Optional[Any]):
      _lowercase:       Optional[Any]						=				SudachiTokenizer(sudachi_dict_type="core"			,				sudachi_split_mode="A")

      self.assertListEqual(tokenizer.tokenize("外国人参政権")			,				["外国", "人", "参政", "権"])

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							Union[str, Any]):
      _lowercase:       Optional[int]						=				SudachiTokenizer(sudachi_dict_type="core"			,				sudachi_split_mode="B")

      self.assertListEqual(tokenizer.tokenize("外国人参政権")			,				["外国人", "参政権"])

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							List[Any]):
      _lowercase:       Dict						=				SudachiTokenizer(sudachi_dict_type="core"			,				sudachi_split_mode="C")

      self.assertListEqual(tokenizer.tokenize("外国人参政権")			,				["外国人参政権"])

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							Tuple):
      _lowercase:       Dict						=				SudachiTokenizer(do_lower_case=A_			,				sudachi_dict_type="core")

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				[" ", "\t", "アップル", "ストア", "で", "iphone", "8", " ", "が", " ", " ", "\n ", "発売", "さ", "れ", "た", " ", "。", " ", " "]			,				)

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							int):
      _lowercase:       Dict						=				SudachiTokenizer(normalize_text=A_			,				sudachi_dict_type="core")

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				[" ", "\t", "ｱｯﾌﾟﾙ", "ストア", "で", "iPhone", "８", " ", "が", " ", " ", "\n ", "発売", "さ", "れ", "た", "\u3000", "。", " ", " "]			,				)

     @require_sudachi
     def 					UpperCAmelCase__       (				self    :							List[Any]):
      _lowercase:       Dict						=				SudachiTokenizer(trim_whitespace=A_			,				sudachi_dict_type="core")

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れ", "た", "。"]			,				)

     @require_jumanpp
     def 					UpperCAmelCase__       (				self    :							Any):
      _lowercase:       List[Any]						=				self.tokenizer_class(self.vocab_file			,				word_tokenizer_type="jumanpp")
      self.assertIsNotNone(A_)

      _lowercase:       Optional[int]						=				"こんにちは、世界。\nこんばんは、世界。"
      _lowercase:       Optional[int]						=				tokenizer.tokenize(A_)
      self.assertListEqual(A_			,				["こんにちは", "、", "世界", "。", "こん", "##ばんは", "、", "世界", "。"])
      self.assertListEqual(tokenizer.convert_tokens_to_ids(A_)			,				[3, 12, 10, 14, 4, 9, 12, 10, 14])

      _lowercase:       Optional[Any]						=				os.path.join(self.tmpdirname			,				"tokenizer.bin")
      with open(A_			,				"wb") as handle:
       pickle.dump(A_			,				A_)

      with open(A_			,				"rb") as handle:
       _lowercase:       Tuple						=				pickle.load(A_)

      _lowercase:       int						=				tokenizer_new.tokenize(A_)

      self.assertListEqual(A_			,				A_)

     @require_jumanpp
     def 					UpperCAmelCase__       (				self    :							Tuple):
      _lowercase:       Tuple						=				JumanppTokenizer()

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップル", "ストア", "で", "iPhone", "8", "\u3000", "が", "\u3000", "\u3000", "\u3000", "発売", "さ", "れた", "\u3000", "。"]			,				)

     @require_jumanpp
     def 					UpperCAmelCase__       (				self    :							List[Any]):
      _lowercase:       Union[str, Any]						=				JumanppTokenizer(do_lower_case=A_)

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップル", "ストア", "で", "iphone", "8", "\u3000", "が", "\u3000", "\u3000", "\u3000", "発売", "さ", "れた", "\u3000", "。"]			,				)

     @require_jumanpp
     def 					UpperCAmelCase__       (				self    :							Tuple):
      _lowercase:       Optional[Any]						=				JumanppTokenizer(normalize_text=A_)

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["ｱ", "ｯ", "ﾌ", "ﾟ", "ﾙ", "ストア", "で", "iPhone", "８", "\u3000", "が", "\u3000", "\u3000", "\u3000", "発売", "さ", "れた", "\u3000", "。"]			,				)

     @require_jumanpp
     def 					UpperCAmelCase__       (				self    :							str):
      _lowercase:       Any						=				JumanppTokenizer(trim_whitespace=A_)

      self.assertListEqual(
          tokenizer.tokenize(" \tｱｯﾌﾟﾙストアでiPhone８ が  \n 発売された　。  ")			,				["アップル", "ストア", "で", "iPhone", "8", "が", "発売", "さ", "れた", "。"]			,				)

     @require_jumanpp
     def 					UpperCAmelCase__       (				self    :							Dict):
      _lowercase:       Optional[int]						=				JumanppTokenizer()

      self.assertListEqual(
          tokenizer.tokenize("ありがとうございますm(_ _)ｍ見つけるのが大変です。")			,				["ありがとう", "ございます", "m(_ _)m", "見つける", "の", "が", "大変です", "。"]			,				)

     def 					UpperCAmelCase__       (				self    :							str):
      _lowercase:       Optional[Any]						=				["[UNK]", "[CLS]", "[SEP]", "こんにちは", "こん", "にちは", "ばんは", "##こん", "##にちは", "##ばんは"]

      _lowercase:       Optional[int]						=				{}
      for i, token in enumerate(A_):
       _lowercase:       Any						=				i
      _lowercase:       List[Any]						=				WordpieceTokenizer(vocab=A_			,				unk_token="[UNK]")

      self.assertListEqual(tokenizer.tokenize("")			,				[])

      self.assertListEqual(tokenizer.tokenize("こんにちは")			,				["こんにちは"])

      self.assertListEqual(tokenizer.tokenize("こんばんは")			,				["こん", "##ばんは"])

      self.assertListEqual(tokenizer.tokenize("こんばんは こんばんにちは こんにちは")			,				["こん", "##ばんは", "[UNK]", "こんにちは"])

     def 					UpperCAmelCase__       (				self    :							Any):
      _lowercase:       int						=				BertJapaneseTokenizer.from_pretrained("nlp-waseda/roberta-base-japanese-with-auto-jumanpp")
      _lowercase:       Any						=				tokenizer.subword_tokenizer

      _lowercase:       Union[str, Any]						=				subword_tokenizer.tokenize("国境 の 長い トンネル を 抜ける と 雪国 であった 。")
      self.assertListEqual(A_			,				["▁国境", "▁の", "▁長い", "▁トンネル", "▁を", "▁抜ける", "▁と", "▁雪", "国", "▁であった", "▁。"])

      _lowercase:       int						=				subword_tokenizer.tokenize("こんばんは こんばん にち は こんにちは")
      self.assertListEqual(A_			,				["▁こん", "ばん", "は", "▁こん", "ばん", "▁に", "ち", "▁は", "▁こんにちは"])






     def 					UpperCAmelCase__       (				self    :							Optional[int]):
      _lowercase:       Dict						=				self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese")

      _lowercase:       Tuple						=				tokenizer.encode("ありがとう。"			,				add_special_tokens=A_)
      _lowercase:       Tuple						=				tokenizer.encode("どういたしまして。"			,				add_special_tokens=A_)

      _lowercase:       Dict						=				tokenizer.build_inputs_with_special_tokens(A_)
      _lowercase:       List[Any]						=				tokenizer.build_inputs_with_special_tokens(A_			,				A_)

      # 2 is for "[CLS]", 3 is for "[SEP]"
      assert encoded_sentence == [2] + text + [3]
      assert encoded_pair == [2] + text + [3] + text_a + [3]






@custom_tokenizers
class        A     (		_a	, unittest.TestCase	):







     '''simple docstring'''







     lowerCamelCase :						Union[str, Any]            =   BertJapaneseTokenizer
     lowerCamelCase :						Any            =   False

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

      _lowercase:       str						=				["[UNK]", "[CLS]", "[SEP]", "こ", "ん", "に", "ち", "は", "ば", "世", "界", "、", "。"]

      _lowercase:       Union[str, Any]						=				os.path.join(self.tmpdirname			,				VOCAB_FILES_NAMES["vocab_file"])
      with open(self.vocab_file			,				"w"			,				encoding="utf-8") as vocab_writer:
       vocab_writer.write("".join([x + "\n" for x in vocab_tokens]))

     def 					UpperCAmelCase__       (				self    :							Union[str, Any]			,				**_UpperCamelCase    :							Dict):
      return BertJapaneseTokenizer.from_pretrained(self.tmpdirname			,				subword_tokenizer_type="character"			,				**A_)

     def 					UpperCAmelCase__       (				self    :							Tuple			,				_UpperCamelCase    :							Tuple):
      _lowercase:       Optional[int]						=				"こんにちは、世界。 \nこんばんは、世界。"
      _lowercase:       List[str]						=				"こ ん に ち は 、 世 界 。 こ ん ば ん は 、 世 界 。"
      return input_text, output_text

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

     def 					UpperCAmelCase__       (				self    :							Tuple):
      pass  # TODO add if relevant

     def 					UpperCAmelCase__       (				self    :							int):
      pass  # TODO add if relevant

     def 					UpperCAmelCase__       (				self    :							str):
      _lowercase:       str						=				self.tokenizer_class(self.vocab_file			,				subword_tokenizer_type="character")

      _lowercase:       Union[str, Any]						=				tokenizer.tokenize("こんにちは、世界。 \nこんばんは、世界。")
      self.assertListEqual(
          A_			,				["こ", "ん", "に", "ち", "は", "、", "世", "界", "。", "こ", "ん", "ば", "ん", "は", "、", "世", "界", "。"])
      self.assertListEqual(
          tokenizer.convert_tokens_to_ids(A_)			,				[3, 4, 5, 6, 7, 11, 9, 10, 12, 3, 4, 8, 4, 7, 11, 9, 10, 12])

     def 					UpperCAmelCase__       (				self    :							Any):
      _lowercase:       Tuple						=				["[UNK]", "[CLS]", "[SEP]", "こ", "ん", "に", "ち", "は", "ば", "世", "界", "、", "。"]

      _lowercase:       List[str]						=				{}
      for i, token in enumerate(A_):
       _lowercase:       Any						=				i
      _lowercase:       str						=				CharacterTokenizer(vocab=A_			,				unk_token="[UNK]")

      self.assertListEqual(tokenizer.tokenize("")			,				[])

      self.assertListEqual(tokenizer.tokenize("こんにちは")			,				["こ", "ん", "に", "ち", "は"])

      self.assertListEqual(tokenizer.tokenize("こんにちほ")			,				["こ", "ん", "に", "ち", "[UNK]"])






     def 					UpperCAmelCase__       (				self    :							Optional[int]):
      _lowercase:       Dict						=				self.tokenizer_class.from_pretrained("cl-tohoku/bert-base-japanese-char")

      _lowercase:       int						=				tokenizer.encode("ありがとう。"			,				add_special_tokens=A_)
      _lowercase:       int						=				tokenizer.encode("どういたしまして。"			,				add_special_tokens=A_)

      _lowercase:       int						=				tokenizer.build_inputs_with_special_tokens(A_)
      _lowercase:       Any						=				tokenizer.build_inputs_with_special_tokens(A_			,				A_)

      # 2 is for "[CLS]", 3 is for "[SEP]"
      assert encoded_sentence == [2] + text + [3]
      assert encoded_pair == [2] + text + [3] + text_a + [3]






@custom_tokenizers
class        A     (		unittest.TestCase	):







     '''simple docstring'''







     def 					UpperCAmelCase__       (				self    :							str):
      _lowercase:       Dict						=				"cl-tohoku/bert-base-japanese"
      _lowercase:       Optional[Any]						=				AutoTokenizer.from_pretrained(A_)
      self.assertIsInstance(A_			,				A_)






class        A     (		unittest.TestCase	):







     '''simple docstring'''







     def 					UpperCAmelCase__       (				self    :							int):
      _lowercase:       str						=				"cl-tohoku/bert-base-japanese"
      with self.assertLogs("transformers"			,				level="WARNING") as cm:
       BertTokenizer.from_pretrained(A_)
       self.assertTrue(
           cm.records[0].message.startswith(
               "The tokenizer class you load from this checkpoint is not the same type as the class this function"
               " is called from."))
      _lowercase:       str						=				"bert-base-cased"
      with self.assertLogs("transformers"			,				level="WARNING") as cm:
       BertJapaneseTokenizer.from_pretrained(A_)
       self.assertTrue(
           cm.records[0].message.startswith(
               "The tokenizer class you load from this checkpoint is not the same type as the class this function"
               " is called from."))





"""simple docstring"""

import argparse
import logging
from collections import namedtuple

import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer  # The authors' implementation

from transformers import BertTokenizer


logging.basicConfig(level=logging.INFO)
UpperCAmelCase__					=logging.getLogger(__name__)


UpperCAmelCase__					="Hello world! cécé herlolip"


UpperCAmelCase__					=namedtuple(
    "BertAbsConfig",
    [
        "temp_dir",
        "large",
        "use_bert_emb",
        "finetune_bert",
        "encoder",
        "share_emb",
        "max_pos",
        "enc_layers",
        "enc_hidden_size",
        "enc_heads",
        "enc_ff_size",
        "enc_dropout",
        "dec_layers",
        "dec_hidden_size",
        "dec_heads",
        "dec_ff_size",
        "dec_dropout",
    ],
)


def lowerCAmelCase_   (					UpperCamelCase__						:			Tuple					, UpperCamelCase__						:			Union[str, Any]			):






 """simple docstring"""







 __lowercase						=						BertAbsConfig(
     temp_dir="""."""					, finetune_bert=UpperCamelCase__					, large=UpperCamelCase__					, share_emb=UpperCamelCase__					, use_bert_emb=UpperCamelCase__					, encoder="""bert"""					, max_pos=512					, enc_layers=6					, enc_hidden_size=512					, enc_heads=8					, enc_ff_size=512					, enc_dropout=0.2					, dec_layers=6					, dec_hidden_size=768					, dec_heads=8					, dec_ff_size=2048					, dec_dropout=0.2					, )
 __lowercase						=						torch.load(UpperCamelCase__					, lambda UpperCamelCase__					, UpperCamelCase__			: storage			)
 __lowercase						=						AbsSummarizer(UpperCamelCase__					, torch.device("""cpu"""			)					, UpperCamelCase__			)
 original.eval()

 __lowercase						=						BertAbsSummarizer(UpperCamelCase__					, torch.device("""cpu"""			)			)
 new_model.eval()

 # -------------------
 # Convert the weights
 # -------------------

 logging.info("""convert the model"""			)
 new_model.bert.load_state_dict(original.bert.state_dict()			)
 new_model.decoder.load_state_dict(original.decoder.state_dict()			)
 new_model.generator.load_state_dict(original.generator.state_dict()			)

 # ----------------------------------
 # Make sure the outpus are identical
 # ----------------------------------

 logging.info("""Make sure that the models' outputs are identical"""			)
 __lowercase						=						BertTokenizer.from_pretrained("""bert-base-uncased"""			)

 # prepare the model inputs
 __lowercase						=						tokenizer.encode("""This is sample éàalj'-."""			)
 encoder_input_ids.extend([tokenizer.pad_token_id] * (512 - len(UpperCamelCase__			))			)
 __lowercase						=						torch.tensor(UpperCamelCase__			).unsqueeze(0			)
 __lowercase						=						tokenizer.encode("""This is sample 3 éàalj'-."""			)
 decoder_input_ids.extend([tokenizer.pad_token_id] * (512 - len(UpperCamelCase__			))			)
 __lowercase						=						torch.tensor(UpperCamelCase__			).unsqueeze(0			)

 # failsafe to make sure the weights reset does not affect the
 # loaded weights.
 assert torch.max(torch.abs(original.generator[0].weight - new_model.generator[0].weight			)			) == 0

 # forward pass
 __lowercase						=						encoder_input_ids
 __lowercase						=						decoder_input_ids
 __lowercase						=						__lowercase						=						None
 __lowercase						=						None
 __lowercase						=						__lowercase						=						None
 __lowercase						=						__lowercase						=						None
 __lowercase						=						None

 # The original model does not apply the geneator layer immediatly but rather in
 # the beam search (where it combines softmax + linear layer). Since we already
 # apply the softmax in our generation process we only apply the linear layer here.
 # We make sure that the outputs of the full stack are identical
 __lowercase						=						original(UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__			)[0]
 __lowercase						=						original.generator(UpperCamelCase__			)

 __lowercase						=						new_model(
     UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__					, UpperCamelCase__			)[0]
 __lowercase						=						new_model.generator(UpperCamelCase__			)

 __lowercase						=						torch.max(torch.abs(output_converted_model - output_original_model			)			).item()
 print("""Maximum absolute difference beween weights: {:.2f}""".format(UpperCamelCase__			)			)
 __lowercase						=						torch.max(torch.abs(output_converted_generator - output_original_generator			)			).item()
 print("""Maximum absolute difference beween weights: {:.2f}""".format(UpperCamelCase__			)			)

 __lowercase						=						torch.allclose(UpperCamelCase__					, UpperCamelCase__					, atol=1E-3			)
 if are_identical:
  logging.info("""all weights are equal up to 1e-3"""			)
 else:
  raise ValueError("""the weights are different. The new model is likely different from the original one."""			)

 # The model has been saved with torch.save(model) and this is bound to the exact
 # directory structure. We save the state_dict instead.
 logging.info("""saving the model's state dictionary"""			)
 torch.save(
     new_model.state_dict()					, """./bertabs-finetuned-cnndm-extractive-abstractive-summarization/pytorch_model.bin"""			)


if __name__ == "__main__":
       UpperCAmelCase__					=argparse.ArgumentParser()
       parser.add_argument(
           "--bertabs_checkpoint_path",
           default=None,
           type=str,
           required=True,
           help="Path the official PyTorch dump.",
       )
       parser.add_argument(
           "--pytorch_dump_folder_path",
           default=None,
           type=str,
           required=True,
           help="Path to the output PyTorch model.",
       )
       UpperCAmelCase__					=parser.parse_args()

       convert_bertabs_checkpoints(
           args.bertabs_checkpoint_path,
           args.pytorch_dump_folder_path,
       )
