
'''simple docstring'''







import os
import time

import numpy as np
import onnxruntime as ort


lowercase					:							List[str]   =      "1"
lowercase					:							Tuple   =      "0"
lowercase					:							Optional[Any]   =      "1"

lowercase					:							List[Any]   =      ort.SessionOptions()
lowercase					:							Union[str, Any]   =      ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print("Create inference session...")
lowercase					:							Any   =      ["TensorrtExecutionProvider", "CUDAExecutionProvider"]
lowercase					:							Union[str, Any]   =      ort.InferenceSession("model.onnx", sess_options=sess_opt, providers=execution_provider)
lowercase					:							List[Any]   =      ort.RunOptions()

lowercase					:							List[Any]   =      128
lowercase					:							Union[str, Any]   =      1
lowercase					:							str   =      np.ones((batch, sequence), dtype=np.intaa)
lowercase					:							Any   =      np.ones((batch, sequence), dtype=np.intaa)
lowercase					:							Optional[int]   =      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...")
lowercase					:							Optional[Any]   =      time.time()
lowercase					:							Optional[Any]   =      2000
lowercase					:							List[str]   =      {}
for iter in range(max_iters):
					lowercase					:							int   =      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))



'''simple docstring'''







from typing import List, Optional

from tokenizers import ByteLevelBPETokenizer

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer


lowercase					:							Optional[Any]   =      logging.get_logger(__name__)

lowercase					:							str   =      {
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
    "tokenizer_config_file": "tokenizer_config.json",
}

lowercase					:							Optional[Any]   =      {
    "vocab_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"
    },
    "merges_file": {
        "facebook/blenderbot_small-90M": "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"
    },
    "tokenizer_config_file": {
        "facebook/blenderbot_small-90M": (
            "https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"
        )
    },
}

lowercase					:							List[Any]   =      {
    "facebook/blenderbot_small-90M": 512,
}


class 		__UpperCAmelCase   (      _lowerCamelCase		):
							__lowercase   	= VOCAB_FILES_NAMES
							__lowercase   	= PRETRAINED_VOCAB_FILES_MAP
							__lowercase   	= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__lowercase   	= BlenderbotSmallTokenizer


							def __init__( self					,     lowerCAmelCase_=None					,     lowerCAmelCase_=None					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_="<|endoftext|>"					,     lowerCAmelCase_=False					,     lowerCAmelCase_=True					,     **lowerCAmelCase_					,     ):





								"""simple docstring"""






								super().__init__(
								    ByteLevelBPETokenizer(
								        vocab=lowerCAmelCase_					,     merges=lowerCAmelCase_					,     add_prefix_space=lowerCAmelCase_					,     trim_offsets=lowerCAmelCase_					,     )					,     bos_token=lowerCAmelCase_					,     eos_token=lowerCAmelCase_					,     unk_token=lowerCAmelCase_					,     **lowerCAmelCase_					,     )
								_snake_case     		=	add_prefix_space


							def 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_=None						):





								"""simple docstring"""






								_snake_case     		=	[self.bos_token_id] + token_ids_a + [self.eos_token_id]
								if token_ids_a is None:
									return output

								return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]




							def 				lowerCamelCase       ( self					,     lowerCAmelCase_					,     lowerCAmelCase_ = None						):





								"""simple docstring"""






								_snake_case     		=	[self.sep_token_id]
								_snake_case     		=	[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]

