void checkSize(CheckedFrom c, const TensorGeometryArg& t, IntList sizes) {
checkDim(c, t, sizes.size());
if (!t->sizes().equals(sizes)) {
std::ostringstream oss;
oss << "Expected tensor of size " << sizes << ", but got tensor of size "
<< t->sizes() << " for " << t
<< " (while checking arguments for " << c << ")";
throw std::runtime_error(oss.str());
}
}
ALOperator::ALOperator(const std::vector<std::vector<int> > & vars,
const Teuchos::RCP<Epetra_Operator> & content,
double gamma, const std::string & label) :
Teko::Epetra::BlockedEpetraOperator(vars, content, label),
pressureMassMatrix_(Teuchos::null), gamma_(gamma)
{
checkDim(vars);
SetContent(vars, content);
BuildALOperator();
}
Tensor adaptive_avg_pool1d(const Tensor & self, IntList output_size) {
checkDim("adaptive_avg_pool1d", TensorArg(self, "self", 1), 3);
check1d("output_size", output_size);
auto output = at::adaptive_avg_pool2d(
self.unsqueeze(2),
{1, output_size[0]});
return output.squeeze(2);
}
std::tuple<Tensor,Tensor> adaptive_max_pool1d(const Tensor & self, IntList output_size) {
checkDim("adaptive_max_pool1d", TensorArg(self, "self", 1), 3);
check1d("output_size", output_size);
Tensor output, indices;
std::tie(output, indices) = at::adaptive_max_pool2d(
self.unsqueeze(2),
{1, output_size[0]});
return std::make_tuple(output.squeeze(2), indices.squeeze(2));
}
std::tuple<Tensor,Tensor> max_pool1d(
const Tensor & self, IntList kernel_size, IntList stride, IntList padding,
IntList dilation, bool ceil_mode) {
if (stride.empty()) {
stride = kernel_size;
}
checkDim("max_pool1d", TensorArg(self, "self", 1), 3);
check1d("kernel_size", kernel_size);
check1d("stride", stride);
check1d("padding", padding);
check1d("dilation", dilation);
Tensor output, indices;
std::tie(output, indices) = at::max_pool2d(
self.unsqueeze(2),
{1, kernel_size[0]},
{1, stride[0]},
{0, padding[0]},
{1, dilation[0]},
ceil_mode);
return std::make_tuple(output.squeeze(2), indices.squeeze(2));
}
