




import pytest

from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict

@pytest.mark.parametrize(
    'split_dict'     ,							[
        SplitDict(),
        SplitDict({'train': SplitInfo(name='train'     ,							num_bytes=13_37     ,							num_examples=42     ,							dataset_name='my_dataset'					)}					),
        SplitDict({'train': SplitInfo(name='train'     ,							num_bytes=13_37     ,							num_examples=42					)}					),
        SplitDict({'train': SplitInfo()}					),
    ]     ,							)
def       _SCREAMING_SNAKE_CASE      (							lowercase     :	SplitDict					):


      '''simple docstring'''



      lowerCamelCase_							=   split_dict._to_yaml_list()
      assert len(lowercase					) == len(lowercase					)
      lowerCamelCase_							=   SplitDict._from_yaml_list(lowercase					)
      for split_name, split_info in split_dict.items():
            # dataset_name field is deprecated, and is therefore not part of the YAML dump
            lowerCamelCase_							=   None
            # the split name of split_dict takes over the name of the split info object
            lowerCamelCase_							=   split_name
      assert split_dict == reloaded






@pytest.mark.parametrize(
    'split_info'     ,							[SplitInfo(), SplitInfo(dataset_name=lowercase					), SplitInfo(dataset_name='my_dataset'					)]					)
def       _SCREAMING_SNAKE_CASE      (							lowercase     :	str					):


      '''simple docstring'''



      lowerCamelCase_							=   asdict(SplitDict({'train': split_info}					)					)
      assert "dataset_name" in split_dict_asdict["train"]
      assert split_dict_asdict["train"]["dataset_name"] == split_info.dataset_name









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))



