




import inspect
import warnings
from typing import Any, Dict, Optional, Union

from packaging import version

def       _SCREAMING_SNAKE_CASE      (							*lowercase     :	Dict     ,							lowercase     :	Optional[Union[Dict, Any]] = None     ,							lowercase     :	Optional[int]=True     ,							lowercase     :	Optional[Any]=2					):


      '''simple docstring'''



      from .. import __version__

      lowerCamelCase_							=   take_from
      lowerCamelCase_							=   ()
      if not isinstance(args[0]     ,							lowercase					):
            lowerCamelCase_							=   (args,)

      for attribute, version_name, message in args:
            if version.parse(version.parse(lowercase					).base_version					) >= version.parse(lowercase					):
                  raise ValueError(
                      f"""The deprecation tuple {(attribute, version_name, message)} should be removed since diffusers'"""
                      f""" version {__version__} is >= {version_name}"""					)

            lowerCamelCase_							=   None
            if isinstance(lowercase     ,							lowercase					) and attribute in deprecated_kwargs:
                  values += (deprecated_kwargs.pop(lowercase					),)
                  lowerCamelCase_							=   f"""The `{attribute}` argument is deprecated and will be removed in version {version_name}."""
            elif hasattr(lowercase     ,							lowercase					):
                  values += (getattr(lowercase     ,							lowercase					),)
                  lowerCamelCase_							=   f"""The `{attribute}` attribute is deprecated and will be removed in version {version_name}."""
            elif deprecated_kwargs is None:
                  lowerCamelCase_							=   f"""`{attribute}` is deprecated and will be removed in version {version_name}."""

            if warning is not None:
                  lowerCamelCase_							=   warning + ' ' if standard_warn else ''
                  warnings.warn(warning + message     ,							lowercase     ,							stacklevel=lowercase					)

      if isinstance(lowercase     ,							lowercase					) and len(lowercase					) > 0:
            lowerCamelCase_							=   inspect.getouterframes(inspect.currentframe()					)[1]
            lowerCamelCase_							=   call_frame.filename
            lowerCamelCase_							=   call_frame.lineno
            lowerCamelCase_							=   call_frame.function
            lowerCamelCase_					,    lowerCamelCase_							=   next(iter(deprecated_kwargs.items()					)					)
            raise TypeError(f"""{function} in {filename} line {line_number-1} got an unexpected keyword argument `{key}`"""					)

      if len(lowercase					) == 0:
            return
      elif len(lowercase					) == 1:
            return values[0]
      return values









import os
import time

import numpy as np
import onnxruntime as ort


lowerCamelCase    :		int			   =       "1"
lowerCamelCase    :		int			   =       "0"
lowerCamelCase    :		Union[str, Any]			   =       "1"

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

lowerCamelCase    :		List[str]			   =       128
lowerCamelCase    :		List[Any]			   =       1
lowerCamelCase    :		Union[str, Any]			   =       np.ones((batch, sequence), dtype=np.intaa)
lowerCamelCase    :		Dict			   =       np.ones((batch, sequence), dtype=np.intaa)
lowerCamelCase    :		Optional[Any]			   =       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...")
lowerCamelCase    :		int			   =       time.time()
lowerCamelCase    :		Dict			   =       2_000
lowerCamelCase    :		Any			   =       {}
for iter in range(max_iters):
 lowerCamelCase    :		Union[str, Any]			   =       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) * 1_000 / max_iters))



