public NativeOnnxTensorMemory(IntPtr onnxValueHandle)
{
IntPtr typeAndShape = IntPtr.Zero;
try
{
NativeApiStatus.VerifySuccess(NativeMethods.ONNXRuntimeGetTensorShapeAndType(onnxValueHandle, out typeAndShape));
TensorElementType elemType = NativeMethods.ONNXRuntimeGetTensorElementType(typeAndShape);
Type type = null;
int width = 0;
TensorElementTypeConverter.GetTypeAndWidth(elemType, out type, out width);
if (typeof(T) != type)
{
throw new NotSupportedException(nameof(NativeOnnxTensorMemory <T>) + " does not support T = " + nameof(T));
}
_elementWidth = width;
_onnxValueHandle = onnxValueHandle;
// derive the databuffer pointer, element_count, element_width, and shape
NativeApiStatus.VerifySuccess(NativeMethods.ONNXRuntimeGetTensorMutableData(_onnxValueHandle, out _dataBufferHandle));
// throws OnnxRuntimeException if native call failed
ulong dimension = NativeMethods.ONNXRuntimeGetNumOfDimensions(typeAndShape);
long count = NativeMethods.ONNXRuntimeGetTensorShapeElementCount(typeAndShape); // count can be negative.
if (count < 0)
{
throw new NotSupportedException("Symbolic dimensions in the tensor is not supported");
}
long[] shape = new long[dimension];
NativeMethods.ONNXRuntimeGetDimensions(typeAndShape, shape, dimension); //Note: shape must be alive during the call
_elementCount = (int)count;
_dimensions = new int[dimension];
for (ulong i = 0; i < dimension; i++)
{
_dimensions[i] = (int)shape[i];
}
}
catch (Exception e)
{
//TODO: cleanup any partially created state
//Do not call ReleaseTensor here. If the constructor has thrown exception, then this NativeOnnxTensorWrapper is not created, so caller should take appropriate action to dispose
throw e;
}
finally
{
if (typeAndShape != IntPtr.Zero)
{
NativeMethods.ONNXRuntimeReleaseObject(typeAndShape);
}
}
}