


'''simple docstring'''

import itertools
import json
import os
import unittest

from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin





@require_tokenizers
class      snake_case    (    lowercase			,						unittest.TestCase			):





  """simple docstring"""




  _lowerCamelCase		    =  LongformerTokenizer
  _lowerCamelCase		    =  True
  _lowerCamelCase		    =  LongformerTokenizerFast
  _lowerCamelCase		    =  True






  def   snake_case		(    self     ):







   """simple docstring"""
   super().setUp()

   # Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
   lowerCamelCase_      =  [
       "l",
       "o",
       "w",
       "e",
       "r",
       "s",
       "t",
       "i",
       "d",
       "n",
       "\u0120",
       "\u0120l",
       "\u0120n",
       "\u0120lo",
       "\u0120low",
       "er",
       "\u0120lowest",
       "\u0120newer",
       "\u0120wider",
       "<unk>",
   ]
   lowerCamelCase_      =  dict(zip(_lowerCAmelCase			,  range(len(_lowerCAmelCase     )     )     )     )
   lowerCamelCase_      =  ["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
   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:
    fp.write(json.dumps(_lowerCAmelCase     ) + "\n"     )
   with open(self.merges_file			,  "w"			,  encoding="utf-8"     ) as fp:
    fp.write("\n".join(_lowerCAmelCase     )     )






  def   snake_case		(    self			,  **UpperCamelCase     ):







   """simple docstring"""
   kwargs.update(self.special_tokens_map     )
   return self.tokenizer_class.from_pretrained(self.tmpdirname			,  **_lowerCAmelCase     )






  def   snake_case		(    self			,  **UpperCamelCase     ):







   """simple docstring"""
   kwargs.update(self.special_tokens_map     )
   return self.rust_tokenizer_class.from_pretrained(self.tmpdirname			,  **_lowerCAmelCase     )






  def   snake_case		(    self			,  UpperCamelCase     ):







   """simple docstring"""
   lowerCamelCase_      =  "lower newer"
   lowerCamelCase_      =  "lower newer"
   return input_text, output_text






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  self.tokenizer_class(self.vocab_file			,  self.merges_file			,  **self.special_tokens_map     )
   lowerCamelCase_      =  "lower newer"
   lowerCamelCase_      =  ["l", "o", "w", "er", "\u0120", "n", "e", "w", "er"]
   lowerCamelCase_      =  tokenizer.tokenize(_lowerCAmelCase     )  # , add_prefix_space=True)
   self.assertListEqual(_lowerCAmelCase			,  _lowerCAmelCase     )

   lowerCamelCase_      =  tokens + [tokenizer.unk_token]
   lowerCamelCase_      =  [0, 1, 2, 15, 10, 9, 3, 2, 15, 19]
   self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCAmelCase     )			,  _lowerCAmelCase     )






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  self.get_tokenizer()

   self.assertListEqual(tokenizer.encode("Hello world!"			,  add_special_tokens=_lowerCAmelCase     )			,  [0, 3_1414, 232, 328, 2]     )
   self.assertListEqual(
       tokenizer.encode("Hello world! cécé herlolip 418"			,  add_special_tokens=_lowerCAmelCase     )			,  [0, 3_1414, 232, 328, 740, 1140, 1_2695, 69, 4_6078, 1588, 2]			,  )






  @slow
  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  self.tokenizer_class.from_pretrained("allenai/longformer-base-4096"     )

   lowerCamelCase_      =  tokenizer.encode("sequence builders"			,  add_special_tokens=_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.encode("multi-sequence build"			,  add_special_tokens=_lowerCAmelCase     )

   lowerCamelCase_      =  tokenizer.encode(
       "sequence builders"			,  add_special_tokens=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.encode(
       "sequence builders"			,  "multi-sequence build"			,  add_special_tokens=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase     )

   lowerCamelCase_      =  tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.build_inputs_with_special_tokens(_lowerCAmelCase			,  _lowerCAmelCase     )

   assert encoded_sentence == encoded_text_from_decode
   assert encoded_pair == encoded_pair_from_decode






  def   snake_case		(    self     ):







   """simple docstring"""
   lowerCamelCase_      =  self.get_tokenizer()

   lowerCamelCase_      =  "Encode this sequence."
   lowerCamelCase_      =  tokenizer.byte_encoder[" ".encode("utf-8"     )[0]]

   # Testing encoder arguments
   lowerCamelCase_      =  tokenizer.encode(_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
   self.assertNotEqual(_lowerCAmelCase			,  _lowerCAmelCase     )

   lowerCamelCase_      =  tokenizer.encode(_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.convert_ids_to_tokens(encoded[0]     )[0]
   self.assertEqual(_lowerCAmelCase			,  _lowerCAmelCase     )

   tokenizer.add_special_tokens({"bos_token": "<s>"}     )
   lowerCamelCase_      =  tokenizer.encode(_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.convert_ids_to_tokens(encoded[1]     )[0]
   self.assertNotEqual(_lowerCAmelCase			,  _lowerCAmelCase     )

   # Testing spaces after special tokens
   lowerCamelCase_      =  "<mask>"
   tokenizer.add_special_tokens(
       {"mask_token": AddedToken(_lowerCAmelCase			,  lstrip=_lowerCAmelCase			,  rstrip=_lowerCAmelCase     )}     )  # mask token has a left space
   lowerCamelCase_      =  tokenizer.convert_tokens_to_ids(_lowerCAmelCase     )

   lowerCamelCase_      =  "Encode <mask> sequence"
   lowerCamelCase_      =  "Encode <mask>sequence"

   lowerCamelCase_      =  tokenizer.encode(_lowerCAmelCase     )
   lowerCamelCase_      =  encoded.index(_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
   self.assertEqual(_lowerCAmelCase			,  _lowerCAmelCase     )

   lowerCamelCase_      =  tokenizer.encode(_lowerCAmelCase     )
   lowerCamelCase_      =  encoded.index(_lowerCAmelCase     )
   lowerCamelCase_      =  tokenizer.convert_ids_to_tokens(encoded[mask_loc + 1]     )[0]
   self.assertNotEqual(_lowerCAmelCase			,  _lowerCAmelCase     )






  def   snake_case		(    self     ):







   """simple docstring"""
   pass






  def   snake_case		(    self     ):







   """simple docstring"""
   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
    with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(_lowerCAmelCase			,  **_lowerCAmelCase     )
     lowerCamelCase_      =  self.tokenizer_class.from_pretrained(_lowerCAmelCase			,  **_lowerCAmelCase     )
     lowerCamelCase_      =  "A, <mask> AllenNLP sentence."
     lowerCamelCase_      =  tokenizer_r.encode_plus(_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase			,  return_token_type_ids=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_p.encode_plus(_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase			,  return_token_type_ids=_lowerCAmelCase     )

     # token_type_ids should put 0 everywhere
     self.assertEqual(sum(tokens_r["token_type_ids"]     )			,  sum(tokens_p["token_type_ids"]     )     )

     # attention_mask should put 1 everywhere, so sum over length should be 1
     self.assertEqual(
         sum(tokens_r["attention_mask"]     ) / len(tokens_r["attention_mask"]     )			,  sum(tokens_p["attention_mask"]     ) / len(tokens_p["attention_mask"]     )			,  )

     lowerCamelCase_      =  tokenizer_r.convert_ids_to_tokens(tokens_r["input_ids"]     )
     lowerCamelCase_      =  tokenizer_p.convert_ids_to_tokens(tokens_p["input_ids"]     )

     # Rust correctly handles the space before the mask while python doesnt
     self.assertSequenceEqual(tokens_p["input_ids"]			,  [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]     )
     self.assertSequenceEqual(tokens_r["input_ids"]			,  [0, 250, 6, 5_0264, 3823, 487, 2_1992, 3645, 4, 2]     )

     self.assertSequenceEqual(
         _lowerCAmelCase			,  ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]     )
     self.assertSequenceEqual(
         _lowerCAmelCase			,  ["<s>", "A", ",", "<mask>", "ĠAllen", "N", "LP", "Ġsentence", ".", "</s>"]     )






  def   snake_case		(    self     ):







   """simple docstring"""
   for trim_offsets, add_prefix_space in itertools.product([True, False]			,  repeat=2     ):
    lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
        self.tmpdirname			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )

    lowerCamelCase_      =  json.loads(tokenizer_r.backend_tokenizer.pre_tokenizer.__getstate__()     )
    lowerCamelCase_      =  json.loads(tokenizer_r.backend_tokenizer.post_processor.__getstate__()     )

    self.assertEqual(pre_tokenizer_state["add_prefix_space"]			,  _lowerCAmelCase     )

    self.assertEqual(post_processor_state["add_prefix_space"]			,  _lowerCAmelCase     )
    self.assertEqual(post_processor_state["trim_offsets"]			,  _lowerCAmelCase     )







  def   snake_case		(    self     ):







   """simple docstring"""
   # Test which aims to verify that the offsets are well adapted to the argument `add_prefix_space` and
   # `trim_offsets`
   for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
    with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
     lowerCamelCase_      =  "hello"  # `hello` is a token in the vocabulary of `pretrained_name`
     lowerCamelCase_      =  f'''{text_of_1_token} {text_of_1_token}'''

     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
         _lowerCAmelCase			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_r(_lowerCAmelCase			,  return_offsets_mapping=_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
     self.assertEqual(encoding.offset_mapping[0]			,  (0, len(_lowerCAmelCase     ))     )
     self.assertEqual(
         encoding.offset_mapping[1]			,  (len(_lowerCAmelCase     ) + 1, len(_lowerCAmelCase     ) + 1 + len(_lowerCAmelCase     ))			,  )

     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
         _lowerCAmelCase			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_r(_lowerCAmelCase			,  return_offsets_mapping=_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
     self.assertEqual(encoding.offset_mapping[0]			,  (0, len(_lowerCAmelCase     ))     )
     self.assertEqual(
         encoding.offset_mapping[1]			,  (len(_lowerCAmelCase     ) + 1, len(_lowerCAmelCase     ) + 1 + len(_lowerCAmelCase     ))			,  )

     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
         _lowerCAmelCase			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_r(_lowerCAmelCase			,  return_offsets_mapping=_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
     self.assertEqual(encoding.offset_mapping[0]			,  (0, len(_lowerCAmelCase     ))     )
     self.assertEqual(
         encoding.offset_mapping[1]			,  (len(_lowerCAmelCase     ), len(_lowerCAmelCase     ) + 1 + len(_lowerCAmelCase     ))			,  )

     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
         _lowerCAmelCase			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_r(_lowerCAmelCase			,  return_offsets_mapping=_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
     self.assertEqual(encoding.offset_mapping[0]			,  (0, len(_lowerCAmelCase     ))     )
     self.assertEqual(
         encoding.offset_mapping[1]			,  (len(_lowerCAmelCase     ), len(_lowerCAmelCase     ) + 1 + len(_lowerCAmelCase     ))			,  )

     lowerCamelCase_      =  f''' {text}'''

     # tokenizer_r = self.rust_tokenizer_class.from_pretrained(
     #     pretrained_name, use_fast=True, add_prefix_space=True, trim_offsets=True
     # )
     # encoding = tokenizer_r(text, return_offsets_mapping=True, add_special_tokens=False)
     # self.assertEqual(encoding.offset_mapping[0], (1, 1 + len(text_of_1_token)))
     # self.assertEqual(
     #     encoding.offset_mapping[1],
     #     (1 + len(text_of_1_token) + 1, 1 + len(text_of_1_token) + 1 + len(text_of_1_token)),
     # )

     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
         _lowerCAmelCase			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_r(_lowerCAmelCase			,  return_offsets_mapping=_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
     self.assertEqual(encoding.offset_mapping[0]			,  (1, 1 + len(_lowerCAmelCase     ))     )
     self.assertEqual(
         encoding.offset_mapping[1]			,  (1 + len(_lowerCAmelCase     ) + 1, 1 + len(_lowerCAmelCase     ) + 1 + len(_lowerCAmelCase     ))			,  )

     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
         _lowerCAmelCase			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_r(_lowerCAmelCase			,  return_offsets_mapping=_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
     self.assertEqual(encoding.offset_mapping[0]			,  (0, 1 + len(_lowerCAmelCase     ))     )
     self.assertEqual(
         encoding.offset_mapping[1]			,  (1 + len(_lowerCAmelCase     ), 1 + len(_lowerCAmelCase     ) + 1 + len(_lowerCAmelCase     ))			,  )

     lowerCamelCase_      =  self.rust_tokenizer_class.from_pretrained(
         _lowerCAmelCase			,  use_fast=_lowerCAmelCase			,  add_prefix_space=_lowerCAmelCase			,  trim_offsets=_lowerCAmelCase     )
     lowerCamelCase_      =  tokenizer_r(_lowerCAmelCase			,  return_offsets_mapping=_lowerCAmelCase			,  add_special_tokens=_lowerCAmelCase     )
     self.assertEqual(encoding.offset_mapping[0]			,  (0, 1 + len(_lowerCAmelCase     ))     )
     self.assertEqual(
         encoding.offset_mapping[1]			,  (1 + len(_lowerCAmelCase     ), 1 + len(_lowerCAmelCase     ) + 1 + len(_lowerCAmelCase     ))			,  )









from typing import Union

import fire
import torch
from tqdm import tqdm



def 					UpperCAmelCase__     (   lowerCamelCase,	lowerCamelCase = "cpu",	lowerCamelCase = None      ):
  lowercase			:Optional[Any]							=  torch.load(lowerCamelCase,	map_location=lowerCamelCase      )
  for k, v in tqdm(state_dict.items()      ):
    if not isinstance(lowerCamelCase,	torch.Tensor      ):
      raise TypeError("FP16 conversion only works on paths that are saved state dicts, like pytorch_model.bin"      )
    lowercase			:List[Any]							=  v.half()
  if save_path is None:  # overwrite src_path
    lowercase			:Optional[Any]							=  src_path
  torch.save(lowerCamelCase,	lowerCamelCase      )


if __name__ == "__main__":
     fire.Fire(convert)



