def run_onnxruntime(self, model_path, inputs, output_names):
"""Run test against onnxruntime backend."""
from onnxruntime_customops import get_library_path
import onnxruntime as rt
opt = rt.SessionOptions()
opt.register_custom_ops_library(get_library_path())
m = rt.InferenceSession(model_path, opt)
results = m.run(output_names, inputs)
return results
def run_onnxruntime(self,
model_path,
inputs,
output_names,
use_custom_ops=False):
"""Run test against onnxruntime backend."""
import onnxruntime as rt
providers = ['CPUExecutionProvider']
if rt.get_device() == "GPU":
gpus = os.environ.get("CUDA_VISIBLE_DEVICES")
if gpus is None or len(gpus) > 1:
providers = ['CUDAExecutionProvider']
opt = rt.SessionOptions()
if use_custom_ops:
from onnxruntime_customops import get_library_path
opt.register_custom_ops_library(get_library_path())
# in case of issues with the runtime, one can enable more logging
# opt.log_severity_level = 0
# opt.log_verbosity_level = 255
# opt.enable_profiling = True
m = rt.InferenceSession(model_path, opt, providers=providers)
results = m.run(output_names, inputs)
return results