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fluidnet_cxx's Issues

Namespace change ATen

namespace at:: in cpp-extension will change in PyTorch v1.0 to namespace torch:: (Cpp API). This will have to be changed when updating to newer version

Plume.py with pre-trained model And config.yaml file.

Hi,

I tried to run plume simulation with pre-trained model.
and I figured out I need config file for pre-trained model.

So, can you add config file for pre-trained model?
Or can I just use default trainConfig.yaml for pre-trained model?

Thank you for reading.

Cpp extensions do not work

At execution, in the function Advect Scalar, called from advection.py input arguments behave as Variable type (grad is computed) whereas intermediate objects in the function are just Tensor type.

at::Tensor advectScalar
(
  float dt, T src, T U, T flags,
  const std::string method_str,
  int bnd,
  const bool sample_outside_fluid,
  const float maccormack_strength
) {
  // Size checking done in python side
  int bsz = flags.size(0);
  int d = flags.size(2);
  int h = flags.size(3);
  int w = flags.size(4);

  bool is3D = (U.size(1) == 3);

  src.set_requires_grad(false);
  U.set_requires_grad(false);
  flags.set_requires_grad(false);

  T s_dst = zeros_like(src);

  T fwd = zeros_like(src);
  T bwd = zeros_like(src);
  T fwd_pos = zeros_like(U);
  T bwd_pos = zeros_like(U);

  std::cout << "Is variable?" << std::endl;
  std::cout << src.is_variable() << std::endl;
  // returns 1, should be 0
  std::cout << U.is_variable() << std::endl;
  // returns 1, should be 0
  std::cout << flags.is_variable() << std::endl;
  // returns 1, should be 0

All should be of Tensor type as no backpropagation is required in the advection part.

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