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ProdEnvMatAMixOp: move filter_ftype out of nsamples loop #2604

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Jun 25, 2023
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ProdEnvMatAMixOp: move filter_ftype out of nsamples loop #2604

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42 changes: 21 additions & 21 deletions source/op/prod_env_mat_multi_device.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -1135,6 +1135,12 @@
context->allocate_output(context_output_index++, nmask_shape,
&nmask_tensor));

Tensor fake_type_tensor; // all zeros
TensorShape fake_type_shape;
fake_type_shape.AddDim(nsamples * nall);
OP_REQUIRES_OK(context, context->allocate_temp(DT_INT32, fake_type_shape,

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source/op/prod_env_mat_multi_device.cc#L1141 

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&fake_type_tensor));

FPTYPE* p_em = descrpt_tensor->flat<FPTYPE>().data();
FPTYPE* p_em_deriv = descrpt_deriv_tensor->flat<FPTYPE>().data();
FPTYPE* p_rij = rij_tensor->flat<FPTYPE>().data();
Expand All @@ -1146,6 +1152,20 @@
const FPTYPE* avg = avg_tensor.flat<FPTYPE>().data();
const FPTYPE* std = std_tensor.flat<FPTYPE>().data();
const int* p_type = type_tensor.flat<int>().data();
int* p_f_type = fake_type_tensor.flat<int>().data();

if (device == "GPU") {
#if GOOGLE_CUDA
deepmd::filter_ftype_gpu_cuda(p_f_type, p_type, nsamples * nall);
#endif
#if TENSORFLOW_USE_ROCM
deepmd::filter_ftype_gpu_rocm(p_f_type, p_type, nsamples * nall);
#endif
} else if (device == "CPU") {
for (int ii = 0; ii < nsamples * nall; ii++) {
p_f_type[ii] = (p_type[ii] < 0) ? -1 : 0;
}
}

// loop over samples
for (int_64 ff = 0; ff < nsamples; ++ff) {
Expand All @@ -1158,6 +1178,7 @@
const FPTYPE* coord = p_coord + ff * nall * 3;
const FPTYPE* box = p_box + ff * 9;
const int* type = p_type + ff * nall;
const int* f_type = p_f_type + ff * nall;

if (device == "GPU") {
#if GOOGLE_CUDA
Expand All @@ -1171,13 +1192,6 @@
int frame_nall = nall;
int mesh_tensor_size = static_cast<int>(mesh_tensor.NumElements());
std::vector<Tensor> tensor_list(7);
Tensor fake_type; // all zeros
TensorShape fake_type_shape;
fake_type_shape.AddDim(nall);
OP_REQUIRES_OK(context, context->allocate_temp(
DT_INT32, fake_type_shape, &fake_type));
deepmd::filter_ftype_gpu_cuda(fake_type.flat<int>().data(), type, nall);
const int* f_type = fake_type.flat<int>().data();
// prepare coord and nlist
_prepare_coord_nlist_gpu<FPTYPE>(
context, &tensor_list[0], &coord, coord_cpy, &f_type, type_cpy,
Expand Down Expand Up @@ -1222,13 +1236,6 @@
int frame_nall = nall;
int mesh_tensor_size = static_cast<int>(mesh_tensor.NumElements());
std::vector<Tensor> tensor_list(7);
Tensor fake_type; // all zeros
TensorShape fake_type_shape;
fake_type_shape.AddDim(nall);
OP_REQUIRES_OK(context, context->allocate_temp(
DT_INT32, fake_type_shape, &fake_type));
deepmd::filter_ftype_gpu_rocm(fake_type.flat<int>().data(), type, nall);
const int* f_type = fake_type.flat<int>().data();
// prepare coord and nlist
_prepare_coord_nlist_gpu_rocm<FPTYPE>(
context, &tensor_list[0], &coord, coord_cpy, &f_type, type_cpy,
Expand Down Expand Up @@ -1271,13 +1278,6 @@
std::vector<FPTYPE> coord_cpy;
std::vector<int> type_cpy;
int frame_nall = nall;
std::vector<int> fake_type(nall, 0);
for (int ii = 0; ii < nall; ii++) {
if (type[ii] < 0) {
fake_type[ii] = -1;
}
}
const int* f_type = &fake_type[0];
// prepare coord and nlist
_prepare_coord_nlist_cpu<FPTYPE>(
context, &coord, coord_cpy, &f_type, type_cpy, idx_mapping, inlist,
Expand Down