




'''simple docstring'''





import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


SCREAMING_SNAKE_CASE__      					=     logging.get_logger(__name__)


SCREAMING_SNAKE_CASE__      					=     {"vocab_file": "vocab.json", "merges_file": "merges.txt"}

SCREAMING_SNAKE_CASE__      					=     {
    "vocab_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/vocab.json",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/vocab.json"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/vocab.json"
        ),
    },
    "merges_file": {
        "allenai/longformer-base-4096": "https://huggingface.co/allenai/longformer-base-4096/resolve/main/merges.txt",
        "allenai/longformer-large-4096": (
            "https://huggingface.co/allenai/longformer-large-4096/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-finetuned-triviaqa": (
            "https://huggingface.co/allenai/longformer-large-4096-finetuned-triviaqa/resolve/main/merges.txt"
        ),
        "allenai/longformer-base-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-base-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
        "allenai/longformer-large-4096-extra.pos.embd.only": (
            "https://huggingface.co/allenai/longformer-large-4096-extra.pos.embd.only/resolve/main/merges.txt"
        ),
    },
}

SCREAMING_SNAKE_CASE__      					=     {
    "allenai/longformer-base-4096": 4096,
    "allenai/longformer-large-4096": 4096,
    "allenai/longformer-large-4096-finetuned-triviaqa": 4096,
    "allenai/longformer-base-4096-extra.pos.embd.only": 4096,
    "allenai/longformer-large-4096-extra.pos.embd.only": 4096,
}




@lru_cache()
# Copied from transformers.models.roberta.tokenization_roberta.bytes_to_unicode
def        lowerCamelCase  (				):





    '''simple docstring'''


    lowercase__		       =						(
        list(range(ord("!"       )     ,ord("~"       ) + 1       )       ) + list(range(ord("¡"       )     ,ord("¬"       ) + 1       )       ) + list(range(ord("®"       )     ,ord("ÿ"       ) + 1       )       )
    )
    lowercase__		       =						bs[:]
    lowercase__		       =						0
    for b in range(2**8       ):
        if b not in bs:
            bs.append(__A       )
            cs.append(2**8 + n       )
            n += 1
    lowercase__		       =						[chr(__A       ) for n in cs]
    return dict(zip(__A     ,__A       )       )




def        lowerCamelCase  (				_snake_case  :						Optional[int]       ):





    '''simple docstring'''


    lowercase__		       =						set()
    lowercase__		       =						word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)       )
        lowercase__		       =						char
    return pairs



class 				snake_case (_snake_case   ):
       lowerCAmelCase__  :Union[str, Any]						   =					VOCAB_FILES_NAMES
       lowerCAmelCase__  :int						   =					PRETRAINED_VOCAB_FILES_MAP
       lowerCAmelCase__  :Any						   =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       lowerCAmelCase__  :Union[str, Any]						   =					["input_ids", "attention_mask"]



       def __init__(				self     ,UpperCAmelCase_     ,UpperCAmelCase_     ,UpperCAmelCase_="replace"     ,UpperCAmelCase_="<s>"     ,UpperCAmelCase_="</s>"     ,UpperCAmelCase_="</s>"     ,UpperCAmelCase_="<s>"     ,UpperCAmelCase_="<unk>"     ,UpperCAmelCase_="<pad>"     ,UpperCAmelCase_="<mask>"     ,UpperCAmelCase_=False     ,**UpperCAmelCase_     ,)  ->							List[str]:
           lowercase__		       =						AddedToken(lowerCAmelCase__     ,lstrip=lowerCAmelCase__     ,rstrip=lowerCAmelCase__      ) if isinstance(lowerCAmelCase__     ,lowerCAmelCase__      ) else bos_token
           lowercase__		       =						AddedToken(lowerCAmelCase__     ,lstrip=lowerCAmelCase__     ,rstrip=lowerCAmelCase__      ) if isinstance(lowerCAmelCase__     ,lowerCAmelCase__      ) else eos_token
           lowercase__		       =						AddedToken(lowerCAmelCase__     ,lstrip=lowerCAmelCase__     ,rstrip=lowerCAmelCase__      ) if isinstance(lowerCAmelCase__     ,lowerCAmelCase__      ) else sep_token
           lowercase__		       =						AddedToken(lowerCAmelCase__     ,lstrip=lowerCAmelCase__     ,rstrip=lowerCAmelCase__      ) if isinstance(lowerCAmelCase__     ,lowerCAmelCase__      ) else cls_token
           lowercase__		       =						AddedToken(lowerCAmelCase__     ,lstrip=lowerCAmelCase__     ,rstrip=lowerCAmelCase__      ) if isinstance(lowerCAmelCase__     ,lowerCAmelCase__      ) else unk_token
           lowercase__		       =						AddedToken(lowerCAmelCase__     ,lstrip=lowerCAmelCase__     ,rstrip=lowerCAmelCase__      ) if isinstance(lowerCAmelCase__     ,lowerCAmelCase__      ) else pad_token

           # Mask token behave like a normal word, i.e. include the space before it
           lowercase__		       =						AddedToken(lowerCAmelCase__     ,lstrip=lowerCAmelCase__     ,rstrip=lowerCAmelCase__      ) if isinstance(lowerCAmelCase__     ,lowerCAmelCase__      ) else mask_token

           super().__init__(
               errors=lowerCAmelCase__     ,bos_token=lowerCAmelCase__     ,eos_token=lowerCAmelCase__     ,unk_token=lowerCAmelCase__     ,sep_token=lowerCAmelCase__     ,cls_token=lowerCAmelCase__     ,pad_token=lowerCAmelCase__     ,mask_token=lowerCAmelCase__     ,add_prefix_space=lowerCAmelCase__     ,**lowerCAmelCase__     ,)

           with open(lowerCAmelCase__     ,encoding="utf-8"      ) as vocab_handle:
               lowercase__		       =						json.load(lowerCAmelCase__      )
           lowercase__		       =						{v: k for k, v in self.encoder.items()}
           lowercase__		       =						errors  # how to handle errors in decoding
           lowercase__		       =						bytes_to_unicode()
           lowercase__		       =						{v: k for k, v in self.byte_encoder.items()}
           with open(lowerCAmelCase__     ,encoding="utf-8"      ) as merges_handle:
               lowercase__		       =						merges_handle.read().split("\n"      )[1:-1]
           lowercase__		       =						[tuple(merge.split()      ) for merge in bpe_merges]
           lowercase__		       =						dict(zip(lowerCAmelCase__     ,range(len(lowerCAmelCase__      )      )      )      )
           lowercase__		       =						{}
           lowercase__		       =						add_prefix_space

           # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
           lowercase__		       =						re.compile(R"'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"      )



       @property
       def 							_a      (				self      )  ->							Optional[int]:
           return len(self.encoder      )



       def 							_a      (				self      )  ->							str:
           return dict(self.encoder     ,**self.added_tokens_encoder      )



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							int:
           if token in self.cache:
               return self.cache[token]
           lowercase__		       =						tuple(lowerCAmelCase__      )
           lowercase__		       =						get_pairs(lowerCAmelCase__      )

           if not pairs:
               return token

           while True:
               lowercase__		       =						min(lowerCAmelCase__     ,key=lambda UpperCAmelCase_      : self.bpe_ranks.get(lowerCAmelCase__     ,float("inf"      )      )      )
               if bigram not in self.bpe_ranks:
                   break
               lowercase__       ,       lowercase__		       =						bigram
               lowercase__		       =						[]
               lowercase__		       =						0
               while i < len(lowerCAmelCase__      ):
                   try:
                       lowercase__		       =						word.index(lowerCAmelCase__     ,lowerCAmelCase__      )
                   except ValueError:
                       new_word.extend(word[i:]      )
                       break
                   else:
                       new_word.extend(word[i:j]      )
                       lowercase__		       =						j

                   if word[i] == first and i < len(lowerCAmelCase__      ) - 1 and word[i + 1] == second:
                       new_word.append(first + second      )
                       i += 2
                   else:
                       new_word.append(word[i]      )
                       i += 1
               lowercase__		       =						tuple(lowerCAmelCase__      )
               lowercase__		       =						new_word
               if len(lowerCAmelCase__      ) == 1:
                   break
               else:
                   lowercase__		       =						get_pairs(lowerCAmelCase__      )
           lowercase__		       =						" ".join(lowerCAmelCase__      )
           lowercase__		       =						word
           return word



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							str:
           lowercase__		       =						[]
           for token in re.findall(self.pat     ,lowerCAmelCase__      ):
               lowercase__		       =						"".join(
                   self.byte_encoder[b] for b in token.encode("utf-8"      )      )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
               bpe_tokens.extend(bpe_token for bpe_token in self.bpe(lowerCAmelCase__      ).split(" "      )      )
           return bpe_tokens



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							str:
           return self.encoder.get(lowerCAmelCase__     ,self.encoder.get(self.unk_token      )      )



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							Tuple:
           return self.decoder.get(lowerCAmelCase__      )



       def 							_a      (				self     ,UpperCAmelCase_      )  ->							Tuple:
           lowercase__		       =						"".join(lowerCAmelCase__      )
           lowercase__		       =						bytearray([self.byte_decoder[c] for c in text]      ).decode("utf-8"     ,errors=self.errors      )
           return text



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None      )  ->							Tuple[str]:
           if not os.path.isdir(lowerCAmelCase__      ):
               logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''      )
               return
           lowercase__		       =						os.path.join(
               lowerCAmelCase__     ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]      )
           lowercase__		       =						os.path.join(
               lowerCAmelCase__     ,(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]      )

           with open(lowerCAmelCase__     ,"w"     ,encoding="utf-8"      ) as f:
               f.write(json.dumps(self.encoder     ,indent=2     ,sort_keys=lowerCAmelCase__     ,ensure_ascii=lowerCAmelCase__      ) + "\n"      )

           lowercase__		       =						0
           with open(lowerCAmelCase__     ,"w"     ,encoding="utf-8"      ) as writer:
               writer.write("#version: 0.2\n"      )
               for bpe_tokens, token_index in sorted(self.bpe_ranks.items()     ,key=lambda UpperCAmelCase_      : kv[1]      ):
                   if index != token_index:
                       logger.warning(
                           F'''Saving vocabulary to {merge_file}: BPE merge indices are not consecutive.'''
                           " Please check that the tokenizer is not corrupted!"      )
                       lowercase__		       =						token_index
                   writer.write(" ".join(lowerCAmelCase__      ) + "\n"      )
                   index += 1

           return vocab_file, merge_file



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None      )  ->							List[int]:
           if token_ids_a is None:
               return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
           lowercase__		       =						[self.cls_token_id]
           lowercase__		       =						[self.sep_token_id]
           return cls + token_ids_a + sep + sep + token_ids_a + sep



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None     ,UpperCAmelCase_ = False      )  ->							List[int]:
           if already_has_special_tokens:
               return super().get_special_tokens_mask(
                   token_ids_a=lowerCAmelCase__     ,token_ids_a=lowerCAmelCase__     ,already_has_special_tokens=lowerCAmelCase__      )

           if token_ids_a is None:
               return [1] + ([0] * len(lowerCAmelCase__      )) + [1]
           return [1] + ([0] * len(lowerCAmelCase__      )) + [1, 1] + ([0] * len(lowerCAmelCase__      )) + [1]



       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_ = None      )  ->							List[int]:
           lowercase__		       =						[self.sep_token_id]
           lowercase__		       =						[self.cls_token_id]

           if token_ids_a is None:
               return len(cls + token_ids_a + sep      ) * [0]
           return len(cls + token_ids_a + sep + sep + token_ids_a + sep      ) * [0]







       def 							_a      (				self     ,UpperCAmelCase_     ,UpperCAmelCase_=False     ,**UpperCAmelCase_      )  ->							str:
           lowercase__		       =						kwargs.pop("add_prefix_space"     ,self.add_prefix_space      )
           if (is_split_into_words or add_prefix_space) and (len(lowerCAmelCase__      ) > 0 and not text[0].isspace()):
               lowercase__		       =						" " + text
           return (text, kwargs)









'''simple docstring'''





import os
import time

import numpy as np
import onnxruntime as ort


SCREAMING_SNAKE_CASE__      					=     "1"
SCREAMING_SNAKE_CASE__      					=     "0"
SCREAMING_SNAKE_CASE__      					=     "1"

SCREAMING_SNAKE_CASE__      					=     ort.SessionOptions()
SCREAMING_SNAKE_CASE__      					=     ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print("Create inference session...")
SCREAMING_SNAKE_CASE__      					=     ["TensorrtExecutionProvider", "CUDAExecutionProvider"]
SCREAMING_SNAKE_CASE__      					=     ort.InferenceSession("model.onnx", sess_options=sess_opt, providers=execution_provider)
SCREAMING_SNAKE_CASE__      					=     ort.RunOptions()

SCREAMING_SNAKE_CASE__      					=     128
SCREAMING_SNAKE_CASE__      					=     1
SCREAMING_SNAKE_CASE__      					=     np.ones((batch, sequence), dtype=np.intaa)
SCREAMING_SNAKE_CASE__      					=     np.ones((batch, sequence), dtype=np.intaa)
SCREAMING_SNAKE_CASE__      					=     np.ones((batch, sequence), dtype=np.intaa)

print("Warm up phase...")
sess.run(
    None,
    {
        sess.get_inputs()[0].name: input_ids,
        sess.get_inputs()[1].name: attention_mask,
        sess.get_inputs()[2].name: token_type_ids,
    },
    run_options=run_opt,
)

print("Start inference...")
SCREAMING_SNAKE_CASE__      					=     time.time()
SCREAMING_SNAKE_CASE__      					=     2000
SCREAMING_SNAKE_CASE__      					=     {}
for iter in range(max_iters):
 SCREAMING_SNAKE_CASE__      					=     sess.run(
     None,
     {
         sess.get_inputs()[0].name: input_ids,
         sess.get_inputs()[1].name: attention_mask,
         sess.get_inputs()[2].name: token_type_ids,
     },
     run_options=run_opt,
 )
print("Average Inference Time = {:.3f} ms".format((time.time() - start_time) * 1000 / max_iters))




