/// <summary>
/// Abses the minimum maximum.
/// </summary>
/// <param name="storage">The storage.</param>
/// <param name="tensor">The tensor.</param>
/// <returns>Tuple<System.Double, System.Double>.</returns>
private static Tuple <double, double> AbsMinMax(Storage storage, NDArray tensor)
{
if (storage.ElementCount == 0)
{
return(Tuple.Create(0.0, 0.0));
}
double min = storage.GetElementAsFloat(0);
double max = storage.GetElementAsFloat(0);
// HACK this is a hacky way of iterating over the elements of the tensor.
// if the tensor has holes, this will incorrectly include those elements
// in the iteration.
var minOffset = tensor.StorageOffset;
var maxOffset = minOffset + TensorDimensionHelpers.GetStorageSize(tensor.Shape, tensor.Strides) - 1;
for (long i = minOffset; i <= maxOffset; ++i)
{
var item = storage.GetElementAsFloat(i);
if (item < min)
{
min = item;
}
if (item > max)
{
max = item;
}
}
return(Tuple.Create(Math.Abs(min), Math.Abs(max)));
}
/// <summary>
/// Initializes a new instance of the <see cref="NDArray"/> class.
/// </summary>
/// <param name="allocator">The allocator.</param>
/// <param name="elementType">Type of the element.</param>
/// <param name="sizes">The sizes.</param>
/// <param name="strides">The strides.</param>
public NDArray(IAllocator allocator, DType elementType, long[] sizes, long[] strides)
{
this.shape = sizes;
this.strides = strides;
this.storageOffset = 0;
this.storage = allocator.Allocate(elementType, TensorDimensionHelpers.GetStorageSize(sizes, strides));
}
// Prepend singleton dimensions until DimensionCount equals newDimCount
/// <summary>
/// Pads to dim count.
/// </summary>
/// <param name="newDimCount">The new dim count.</param>
/// <returns>Tensor.</returns>
private NDArray PadToDimCount(int newDimCount)
{
var newSizes = Pad1Prepend(this.shape, newDimCount);
var newStrides = TensorDimensionHelpers.GetContiguousStride(newSizes);
Array.Copy(this.strides, 0, newStrides, newStrides.Length - this.strides.Length, this.strides.Length);
return(new NDArray(newSizes, newStrides, this.storage, this.storageOffset));
}
/// <summary>
/// Elements the count.
/// </summary>
/// <returns>System.Int64.</returns>
public long ElementCount()
{
if (elementCount.HasValue)
{
return(elementCount.Value);
}
elementCount = TensorDimensionHelpers.ElementCount(shape);
return(elementCount.Value);
}
/// <summary>
/// Views the specified sizes.
/// </summary>
/// <param name="sizes">The sizes.</param>
/// <returns>Tensor.</returns>
/// <exception cref="InvalidOperationException">
/// Cannot use View on a non-contiguous tensor000
/// or
/// Output tensor must have the same number of elements as the input
/// </exception>
public NDArray View(params long[] sizes)
{
if (!this.IsContiguous())
{
throw new InvalidOperationException("Cannot use View on a non-contiguous tensor");
}
if (this.ElementCount() != TensorDimensionHelpers.ElementCount(sizes))
{
throw new InvalidOperationException("Output tensor must have the same number of elements as the input");
}
return(new NDArray(sizes, TensorDimensionHelpers.GetContiguousStride(sizes), this.storage, this.storageOffset));
}
/// <summary>
/// Determines whether [is int only] [the specified storage].
/// </summary>
/// <param name="storage">The storage.</param>
/// <param name="tensor">The tensor.</param>
/// <returns><c>true</c> if [is int only] [the specified storage]; otherwise, <c>false</c>.</returns>
private static bool IsIntOnly(Storage storage, NDArray tensor)
{
// HACK this is a hacky way of iterating over the elements of the tensor.
// if the tensor has holes, this will incorrectly include those elements
// in the iteration.
var minOffset = tensor.StorageOffset;
var maxOffset = minOffset + TensorDimensionHelpers.GetStorageSize(tensor.Shape, tensor.Strides) - 1;
for (long i = minOffset; i <= maxOffset; ++i)
{
var value = Convert.ToDouble((object)storage.GetElementAsFloat(i));
if (value != Math.Ceiling(value))
{
return(false);
}
}
return(true);
}
/// <summary>
/// Construct a new tensor, using the given allocator to construct a storage. The new tensor
/// will be contiguous in memory. The tensor's elements will not be initialized.
/// </summary>
/// <param name="allocator"></param>
/// <param name="elementType"></param>
/// <param name="sizes"></param>
/// <summary>
/// Initializes a new instance of the <see cref="NDArray"/> class.
/// </summary>
/// <param name="allocator">The allocator.</param>
/// <param name="elementType">Type of the element.</param>
/// <param name="sizes">The sizes.</param>
public NDArray(IAllocator allocator, DType elementType, params long[] sizes)
: this(allocator, elementType, sizes, TensorDimensionHelpers.GetContiguousStride(sizes))
{
}
