public static Tensor permute(this Tensor x, params int[] dims)
{
var y_shape = new int[x.__shape.Length];
for (int i = 0; i < x.__shape.Length; i++)
{
y_shape[i] = x.__shape[dims[i]];
}
var y = new Tensor(y_shape, x.dtype, (!torch.autograd.grad_mode.no_grad.prev) && x.requires_grad);
switch (x.dtype)
{
case torch.float16:
{
MKL.Permute(x.__half, x.__shape, x.__strides, dims, y.__half, y.__shape, y.__strides);
if (y.requires_grad)
{
y.__backward_fn = () =>
{
MKL.dPermute(x.grad.__half, x.__shape, x.__strides, dims, y.grad.__half, y.__shape, y.__strides);
if (x.__backward_fn != null)
{
x.__backward_fn();
}
};
}
break;
}
case torch.float32:
{
MKL.Permute(x.__float, x.__shape, x.__strides, dims, y.__float, y.__shape, y.__strides);
if (y.requires_grad)
{
y.__backward_fn = () =>
{
MKL.dPermute(x.grad.__float, x.__shape, x.__strides, dims, y.grad.__float, y.__shape, y.__strides);
if (x.__backward_fn != null)
{
x.__backward_fn();
}
};
}
break;
}
case torch.float64:
{
MKL.Permute(x.__double, x.__shape, x.__strides, dims, y.__double, y.__shape, y.__strides);
if (y.requires_grad)
{
y.__backward_fn = () =>
{
MKL.dPermute(x.grad.__double, x.__shape, x.__strides, dims, y.grad.__double, y.__shape, y.__strides);
if (x.__backward_fn != null)
{
x.__backward_fn();
}
};
}
break;
}
case torch.int8:
{
MKL.Permute(x.__int8, x.__shape, x.__strides, dims, y.__int8, y.__shape, y.__strides);
break;
}
case torch.uint8:
{
MKL.Permute(x.__uint8, x.__shape, x.__strides, dims, y.__uint8, y.__shape, y.__strides);
break;
}
case torch.int16:
{
MKL.Permute(x.__int16, x.__shape, x.__strides, dims, y.__int16, y.__shape, y.__strides);
break;
}
case torch.int32:
{
MKL.Permute(x.__int32, x.__shape, x.__strides, dims, y.__int32, y.__shape, y.__strides);
break;
}
case torch.int64:
{
MKL.Permute(x.__int64, x.__shape, x.__strides, dims, y.__int64, y.__shape, y.__strides);
break;
}
case torch.@bool:
{
MKL.Permute(x.__bool, x.__shape, x.__strides, dims, y.__bool, y.__shape, y.__strides);
break;
}
}
return(y);
}