onnxruntime/csharp/src/Microsoft.ML.OnnxRuntime/NativeOnnxTensorMemory.cs
2018-11-22 20:56:43 -08:00

188 lines
5.6 KiB
C#

// Copyright (c) Microsoft Corporation. All rights reserved.
// Licensed under the MIT License.
using System;
using System.Collections.Generic;
using System.Text;
using System.Buffers;
using System.Runtime.CompilerServices;
using System.Runtime.InteropServices;
using System.Threading;
namespace Microsoft.ML.OnnxRuntime
{
internal class NativeOnnxTensorMemory<T> : MemoryManager<T>
{
private bool _disposed;
private int _referenceCount;
private IntPtr _onnxValueHandle;
private IntPtr _dataBufferHandle;
private int _elementCount;
private int _elementWidth;
private int[] _dimensions;
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);
}
}
}
~NativeOnnxTensorMemory()
{
Dispose(false);
}
public bool IsDisposed => _disposed;
protected bool IsRetained => _referenceCount > 0;
public int[] Dimensions
{
get
{
return _dimensions;
}
}
public int Rank
{
get
{
return _dimensions.Length;
}
}
public override Span<T> GetSpan()
{
if (IsDisposed)
throw new ObjectDisposedException(nameof(NativeOnnxTensorMemory<T>));
Span<T> span = null;
unsafe
{
span = new Span<T>((void*)_dataBufferHandle, _elementCount);
}
return span;
}
public override MemoryHandle Pin(int elementIndex = 0)
{
//Note: always pin the full buffer and return
unsafe
{
if (elementIndex >= _elementCount)
{
throw new ArgumentOutOfRangeException(nameof(elementIndex));
}
Retain();
return new MemoryHandle((void*)((int)_dataBufferHandle + elementIndex*_elementWidth)); //could not use Unsafe.Add
}
}
public override void Unpin()
{
Release();
}
private bool Release()
{
int newRefCount = Interlocked.Decrement(ref _referenceCount);
if (newRefCount < 0)
{
throw new InvalidOperationException("Unmatched Release/Retain");
}
return newRefCount != 0;
}
private void Retain()
{
if (IsDisposed)
{
throw new ObjectDisposedException(nameof(NativeOnnxTensorMemory<T>));
}
Interlocked.Increment(ref _referenceCount);
}
protected override void Dispose(bool disposing)
{
if (_disposed)
{
return;
}
if (disposing)
{
// do managed objects cleanup
}
NativeMethods.ReleaseONNXValue(_onnxValueHandle);
_disposed = true;
}
protected override bool TryGetArray(out ArraySegment<T> arraySegment)
{
// cannot expose managed array
arraySegment = default(ArraySegment<T>);
return false;
}
}
}