public static TorchTensor From(double[] rawArray, long[] dimensions)
{
unsafe
{
fixed(double *parray = rawArray)
{
return(DoubleTensor.From((IntPtr)parray, dimensions));
}
}
}
public static TorchTensor From(double[] rawArray, long[] dimensions, bool requiresGrad = false)
{
unsafe
{
fixed(double *parray = rawArray)
{
return(DoubleTensor.From((IntPtr)parray, dimensions, requiresGrad));
}
}
}
public static TorchTensor ToTorchTensor <T>(this T scalar, bool requiresGrad = false)
{
if (requiresGrad && typeof(T) != typeof(float) && typeof(T) != typeof(double))
{
throw new ArgumentException(nameof(requiresGrad), "Only floating point types support gradients.");
}
switch (true)
{
case bool _ when typeof(T) == typeof(byte):
{
return(ByteTensor.From((byte)(object)scalar, requiresGrad));
}
case bool _ when typeof(T) == typeof(short):
{
return(ShortTensor.From((short)(object)scalar, requiresGrad));
}
case bool _ when typeof(T) == typeof(int):
{
return(IntTensor.From((int)(object)scalar, requiresGrad));
}
case bool _ when typeof(T) == typeof(long):
{
return(LongTensor.From((long)(object)scalar, requiresGrad));
}
case bool _ when typeof(T) == typeof(double):
{
return(DoubleTensor.From((double)(object)scalar, requiresGrad));
}
case bool _ when typeof(T) == typeof(float):
{
return(FloatTensor.From((float)(object)scalar, requiresGrad));
}
default: throw new NotImplementedException($"Creating tensor of type {typeof(T)} is not supported.");
}
}
public static TorchTensor ToTorchTensor <T>(this T scalar)
{
switch (true)
{
case bool _ when typeof(T) == typeof(byte):
{
return(ByteTensor.From((byte)(object)scalar));
}
case bool _ when typeof(T) == typeof(short):
{
return(ShortTensor.From((short)(object)scalar));
}
case bool _ when typeof(T) == typeof(int):
{
return(IntTensor.From((int)(object)scalar));
}
case bool _ when typeof(T) == typeof(long):
{
return(LongTensor.From((long)(object)scalar));
}
case bool _ when typeof(T) == typeof(double):
{
return(DoubleTensor.From((double)(object)scalar));
}
case bool _ when typeof(T) == typeof(float):
{
return(FloatTensor.From((float)(object)scalar));
}
default: throw new NotImplementedException($"Creating tensor of type {typeof(T)} is not supported.");
}
}
public static TorchTensor ToTorchTensor <T>(this T[] rawArray, long[] dimensions)
{
switch (true)
{
case bool _ when typeof(T) == typeof(byte):
{
return(ByteTensor.From(rawArray as byte[], dimensions));
}
case bool _ when typeof(T) == typeof(short):
{
return(ShortTensor.From(rawArray as short[], dimensions));
}
case bool _ when typeof(T) == typeof(int):
{
return(IntTensor.From(rawArray as int[], dimensions));
}
case bool _ when typeof(T) == typeof(long):
{
return(LongTensor.From(rawArray as long[], dimensions));
}
case bool _ when typeof(T) == typeof(double):
{
return(DoubleTensor.From(rawArray as double[], dimensions));
}
case bool _ when typeof(T) == typeof(float):
{
return(FloatTensor.From(rawArray as float[], dimensions));
}
default: throw new NotImplementedException($"Creating tensor of type {typeof(T)} is not supported.");
}
}
public static TorchTensor ToTorchTensor <T>(this T[] rawArray, long[] dimensions, bool doCopy = false, bool requiresGrad = false)
{
switch (true)
{
case bool _ when typeof(T) == typeof(byte):
{
var result = ByteTensor.From(rawArray as byte[], dimensions, requiresGrad);
if (doCopy)
{
return(result.Clone());
}
return(result);
}
case bool _ when typeof(T) == typeof(short):
{
var result = ShortTensor.From(rawArray as short[], dimensions, requiresGrad);
if (doCopy)
{
return(result.Clone());
}
return(result);
}
case bool _ when typeof(T) == typeof(int):
{
var result = IntTensor.From(rawArray as int[], dimensions, requiresGrad);
if (doCopy)
{
return(result.Clone());
}
return(result);
}
case bool _ when typeof(T) == typeof(long):
{
var result = LongTensor.From(rawArray as long[], dimensions, requiresGrad);
if (doCopy)
{
return(result.Clone());
}
return(result);
}
case bool _ when typeof(T) == typeof(double):
{
var result = DoubleTensor.From(rawArray as double[], dimensions, requiresGrad);
if (doCopy)
{
return(result.Clone());
}
return(result);
}
case bool _ when typeof(T) == typeof(float):
{
var result = FloatTensor.From(rawArray as float[], dimensions, requiresGrad);
if (doCopy)
{
return(result.Clone());
}
return(result);
}
default: throw new NotImplementedException($"Creating tensor of type {typeof(T)} is not supported.");
}
}