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dlpack.cs
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dlpack.cs
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// Source: https://github.com/vadimkantorov/dotnetdlpack/blob/master/dlpack.cs
using System;
using System.Runtime.InteropServices;
using System.Runtime.CompilerServices;
namespace DLPack
{
public enum DLDeviceType : Int32
{
kDLCPU = 1,
kDLGPU = 2,
kDLCPUPinned = 3,
kDLOpenCL = 4,
kDLVulkan = 7,
kDLMetal = 8,
kDLVPI = 9,
kDLROCM = 10,
kDLExtDev = 12,
}
public enum DLDataTypeCode : Byte
{
kDLInt = 0,
kDLUInt = 1,
kDLFloat = 2,
kDLBfloat = 4,
}
[StructLayout(LayoutKind.Sequential)]
public struct DLDataType
{
public DLDataTypeCode type_code;
public Byte bits;
public UInt16 lanes;
public static DLDataType From<T>()
{
var dtype = new DLDataType();
dtype.lanes = 1;
dtype.bits = (Byte) (Unsafe.SizeOf<T>() * 8);
var t = typeof(T);
if(t == typeof(SByte) || t == typeof(Int16) || t == typeof(Int32) || t == typeof(Int64))
dtype.type_code = DLDataTypeCode.kDLInt;
else if(t == typeof(Byte) || t == typeof(UInt16) || t == typeof(UInt32) || t == typeof(UInt64))
dtype.type_code = DLDataTypeCode.kDLUInt;
else if(t == typeof(Single) || t == typeof(Double))
dtype.type_code = DLDataTypeCode.kDLFloat;
else
throw new Exception($"Type [{t}] is not supported");
return dtype;
}
}
[StructLayout(LayoutKind.Sequential)]
public struct DLContext
{
public DLDeviceType device_type;
public Int32 device_id;
}
[StructLayout(LayoutKind.Sequential)]
public struct DLTensor
{
public IntPtr data;
public DLContext ctx;
public Int32 ndim;
public DLDataType dtype;
public IntPtr shape;
public IntPtr strides;
public UInt64 byte_offset;
public bool CheckType<T, TT>() where T: unmanaged where TT: unmanaged
{
var T_dtype = DLDataType.From<T>();
var TT_dtype = DLDataType.From<TT>();
return dtype.type_code == T_dtype.type_code && dtype.bits == TT_dtype.bits && dtype.lanes == TT_dtype.lanes;
}
public unsafe ReadOnlySpan<Int64> ShapeSpan()
{
return shape != IntPtr.Zero ? new ReadOnlySpan<Int64>(shape.ToPointer(), ndim) : ReadOnlySpan<Int64>.Empty;
}
public unsafe Int64 Numel()
{
Int64 numel = 1;
var shape = ShapeSpan();
for(Int32 i = 0; i < ndim; i++)
numel *= shape[i];
return numel;
}
public unsafe ReadOnlySpan<Int64> StridesSpan(bool assumeRowMajorContiguousStrides = false)
{
return strides != IntPtr.Zero ? new ReadOnlySpan<Int64>(strides.ToPointer(), ndim) : assumeRowMajorContiguousStrides ? RowMajorContiguousStrides(ShapeSpan()) : ReadOnlySpan<Int64>.Empty;
}
public unsafe ReadOnlySpan<T> DataSpanLessThan2Gb<T>() where T : unmanaged
{
var bits = Numel() * dtype.bits * dtype.lanes;
Int32 length = (Int32)(bits / (Unsafe.SizeOf<T>() * 8));
return new ReadOnlySpan<T>(data.ToPointer(), length);
}
public unsafe T Read<T>(params Int64[] coords) where T : unmanaged
{
var strides = StridesSpan(assumeRowMajorContiguousStrides : true);
Int64 offset = 0;
for(Int32 i = 0; i < ndim; i++)
offset += strides[i] * coords[i];
T* ptr = (T*)data.ToPointer();
return ptr[offset];
}
public override string ToString()
{
var s_h_a_p_e = string.Join(",", ShapeSpan().ToArray());
var s_t_r_i_d_e_s = string.Join(",", StridesSpan().ToArray());
return $"type_code={dtype.type_code}, bits={dtype.bits}, lanes={dtype.lanes}, ndim={ndim}, shape=[{s_h_a_p_e}], strides=[{s_t_r_i_d_e_s}]";
}
public static Int64[] RowMajorContiguousStrides(ReadOnlySpan<Int64> shape)
{
var strides = new Int64[shape.Length];
for(Int32 i = 0; i < strides.Length; i++)
strides[i] = i == shape.Length - 1 ? 1 : shape[i + 1];
return strides;
}
public static Int64[] ShapeFromArray(Array array)
{
Int64[] shape = new Int64[array.Rank];
for(Int32 i = 0; i < array.Rank; i++)
shape[i] = array.GetLongLength(i);
return shape;
}
}
public delegate void DLDeleterFunc(ref DLManagedTensor self);
[StructLayout(LayoutKind.Sequential)]
public struct DLManagedTensor
{
public DLTensor dl_tensor;
public IntPtr manager_ctx;
public DLDeleterFunc deleter;
public void CallDeleter()
{
if(deleter != null)
deleter(ref this);
}
public static void EmptyDeleter(ref DLManagedTensor self)
{
}
public unsafe static DLManagedTensor FromBlob<T>(T* data, Int32 ndim, Int64* shape, Int64* strides = null) where T : unmanaged
{
var dl_managed_tensor = new DLManagedTensor();
dl_managed_tensor.dl_tensor.data = (IntPtr)data;
dl_managed_tensor.dl_tensor.ctx.device_type = DLDeviceType.kDLCPU;
dl_managed_tensor.dl_tensor.ndim = ndim;
dl_managed_tensor.dl_tensor.dtype = DLDataType.From<T>();
dl_managed_tensor.dl_tensor.shape = (IntPtr)shape;
dl_managed_tensor.dl_tensor.strides = (IntPtr)strides;
dl_managed_tensor.dl_tensor.byte_offset = 0;
dl_managed_tensor.deleter = EmptyDeleter;
return dl_managed_tensor;
}
}
}