Skip to content

fix c++ interface bug #3613

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 12 commits into from
Mar 28, 2024
Merged

fix c++ interface bug #3613

Changes from 2 commits
Commits
Show all changes
12 commits
Select commit Hold shift + click to select a range
e1383a1
fix c++ bug
CaRoLZhangxy Mar 27, 2024
0e035c2
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 27, 2024
837a2c5
fix compile error
CaRoLZhangxy Mar 27, 2024
b7808e2
fix get gpu num
CaRoLZhangxy Mar 27, 2024
002d634
fix gpu id
CaRoLZhangxy Mar 27, 2024
68846bd
Merge branch 'devel' of https://github.com/deepmodeling/deepmd-kit in…
CaRoLZhangxy Mar 28, 2024
6ed68f0
fix ener seg fault
CaRoLZhangxy Mar 28, 2024
7d871c8
test
CaRoLZhangxy Mar 28, 2024
de14a32
fix float exception
CaRoLZhangxy Mar 28, 2024
811ff3a
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 28, 2024
9b151d5
remove gpu input when call on cpu
CaRoLZhangxy Mar 28, 2024
a4ae015
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Mar 28, 2024
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
43 changes: 41 additions & 2 deletions source/api_cc/src/DeepPotPT.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -47,6 +47,12 @@ void DeepPotPT::init(const std::string& model,
std::cout << "load model from: " << model << " to gpu " << gpu_rank
<< std::endl;
}
int gpu_num = -1;
DPGetDeviceCount(gpu_num);
if (gpu_id > gpu_num) {
throw deepmd::deepmd_exception(
"current rank" + gpu_id + "is larger than the number of gpu" + gpu_num);
}
module = torch::jit::load(model, device);

torch::jit::FusionStrategy strategy;
Expand Down Expand Up @@ -107,7 +113,6 @@ void DeepPotPT::compute(ENERGYVTYPE& ener,
}
auto int_options = torch::TensorOptions().dtype(torch::kInt64);
auto int32_options = torch::TensorOptions().dtype(torch::kInt32);

// select real atoms
std::vector<VALUETYPE> dcoord, dforce, aparam_, datom_energy, datom_virial;
std::vector<int> datype, fwd_map, bkw_map;
Expand All @@ -116,6 +121,24 @@ void DeepPotPT::compute(ENERGYVTYPE& ener,
select_real_atoms_coord(dcoord, datype, aparam_, nghost_real, fwd_map,
bkw_map, nall_real, nloc_real, coord, atype, aparam,
nghost, ntypes, 1, daparam, nall, aparam_nall);
int nloc = nall_real - nghost_real;
int nframes = 1;
if (nloc == 0) {
// no backward map needed
// dforce of size nall * 3
force.resize(static_cast<size_t>(nframes) * fwd_map.size() * 3);
fill(force.begin(), force.end(), (VALUETYPE)0.0);
// dvirial of size 9
virial.resize(static_cast<size_t>(nframes) * 9);
fill(virial.begin(), virial.end(), (VALUETYPE)0.0);
// datom_energy_ of size nall
atom_energy.resize(static_cast<size_t>(nframes) * fwd_map.size());
fill(atom_energy.begin(), atom_energy.end(), (VALUETYPE)0.0);
// datom_virial_ of size nall * 9
atom_virial.resize(static_cast<size_t>(nframes) * fwd_map.size() * 9);
fill(atom_virial.begin(), atom_virial.end(), (VALUETYPE)0.0);
return;
}
std::vector<VALUETYPE> coord_wrapped = dcoord;
at::Tensor coord_wrapped_Tensor =
torch::from_blob(coord_wrapped.data(), {1, nall_real, 3}, options)
Expand Down Expand Up @@ -185,7 +208,6 @@ void DeepPotPT::compute(ENERGYVTYPE& ener,
datom_virial.assign(
cpu_atom_virial_.data_ptr<VALUETYPE>(),
cpu_atom_virial_.data_ptr<VALUETYPE>() + cpu_atom_virial_.numel());
int nframes = 1;
// bkw map
force.resize(static_cast<size_t>(nframes) * fwd_map.size() * 3);
atom_energy.resize(static_cast<size_t>(nframes) * fwd_map.size());
Expand Down Expand Up @@ -249,6 +271,23 @@ void DeepPotPT::compute(ENERGYVTYPE& ener,
floatType = torch::kFloat32;
}
auto int_options = torch::TensorOptions().dtype(torch::kInt64);
int nframes = 1;
if (natoms == 0) {
// no backward map needed
// dforce of size nall * 3
force_.resize(static_cast<size_t>(nframes) * natoms * 3);
fill(force_.begin(), force_.end(), (VALUETYPE)0.0);
// dvirial of size 9
virial.resize(static_cast<size_t>(nframes) * 9);
fill(virial.begin(), virial.end(), (VALUETYPE)0.0);
// datom_energy_ of size nall
atom_energy.resize(static_cast<size_t>(nframes) * natoms);
fill(atom_energy.begin(), atom_energy.end(), (VALUETYPE)0.0);
// datom_virial_ of size nall * 9
atom_virial.resize(static_cast<size_t>(nframes) * natoms * 9);
fill(atom_virial.begin(), atom_virial.end(), (VALUETYPE)0.0);
return;
}
std::vector<torch::jit::IValue> inputs;
at::Tensor coord_wrapped_Tensor =
torch::from_blob(coord_wrapped.data(), {1, natoms, 3}, options)
Expand Down
Loading