public void CopyToArray(Array array)
{
var elementType = DTypeBuilder.FromCLRType(array.GetType().GetElementType());
if (!this.IsContiguous())
{
throw new InvalidOperationException("Tensor must be contiguous to copy from CLR array");
}
if (this.ElementCount() != array.LongLength)
{
throw new InvalidOperationException("Tensor and array must have the same number of elements");
}
if (this.ElementType != elementType)
{
throw new InvalidOperationException("Tensor and array must have the same element types");
}
var handle = GCHandle.Alloc(array, GCHandleType.Pinned);
try
{
var length = Buffer.ByteLength(array);
this.Storage.CopyFromStorage(handle.AddrOfPinnedObject(), this.StorageOffset, length);
}
finally
{
handle.Free();
}
}
public static Tensor FromArray(IAllocator allocator, Array array)
{
// From the CLI spec(section 8.9.1):
// Array elements shall be laid out within the array object in row - major order
// (i.e., the elements associated with the rightmost array dimension shall be laid out contiguously from lowest to highest index).
// The actual storage allocated for each array element can include platform - specific padding.
// This is already in the order we want - and here we will (potentially incorrectly) assume that there is no
// 'platform-specific padding'. This appears to be a reasonable assumption on both CLR and Mono.
// Assuming no platform-specific padding allows us to use memcpy instead of iterating and copying each element
var elementType = DTypeBuilder.FromCLRType(array.GetType().GetElementType());
var dimSizes = Enumerable.Range(0, array.Rank).Select(x => (long)array.GetLength(x)).ToArray();
var result = new Tensor(allocator, elementType, dimSizes);
result.CopyFrom(array);
return(result);
}
