Description
This is my custom operator definition:
@onnx_op(op_type='LocatePostNms',
domain='ai.onnx.contrib',
inputs=[PyCustomOpDef.dt_float, PyCustomOpDef.dt_int32, PyCustomOpDef.dt_float, PyCustomOpDef.dt_float,
PyCustomOpDef.dt_int32, PyCustomOpDef.dt_float],
outputs=[PyCustomOpDef.dt_float, PyCustomOpDef.dt_int32],
attrs={"classNumber": PyCustomOpDef.dt_int32,
"iou_thresh": PyCustomOpDef.dt_float,
"scale": PyCustomOpDef.dt_double,
"side": PyCustomOpDef.dt_int32,
"topk": PyCustomOpDef.dt_int32,
"type": PyCustomOpDef.dt_int32}
)
def locatepostnms_compute(p0, l0, b0, p1, l1, b1, **kwargs):
classNumber = kwargs['classNumber']
iou_thresh = kwargs['iou_thresh']
scale = kwargs['scale']
side = kwargs['side']
topk = kwargs['topk']
type = kwargs['type']
padded_box, result_cnt = cvt_compute（x）
return padded_box, result_cnt
I just using:
sess_options = rt.SessionOptions()
sess_options.register_custom_ops_library(onnxruntime_extensions.get_library_path())
to register the custom operator, and it works
but when comes to
rt.InferenceSession().run()
the program crashed and reported: Process finished with exit code -1073740791 (0xC0000409)
I have no idea with this issue, could you give me some suggesstion about that?
By the way, how to quantize this model with custom op in onnxruntime python?
onnxruntime. quantization. quantize. quantize_static report error:
onnx.onnx_cpp2py_export.shape_inference.InferenceError: [TypeInferenceError] Cannot infer type and shape for node name 453. No opset import for domain ai.onnx.contrib optype LocatePostNms