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Merged
merged 1 commit into from
Feb 28, 2025
Merged

Code format is standardized and adapted to cuda12.6 on Windows platform #71284

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46 changes: 25 additions & 21 deletions paddle/fluid/operators/data_norm_op.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -129,19 +129,22 @@ class DataNormKernel<T, phi::GPUContext> : public framework::OpKernel<T> {
"The dims of Input(X) should be greater than 0."));

const T *batch_size_in =
ctx.Input<phi::DenseTensor>("BatchSize")->data<T>();
const T *batch_sum_in = ctx.Input<phi::DenseTensor>("BatchSum")->data<T>();
ctx.Input<phi::DenseTensor>("BatchSize")->template data<T>();
const T *batch_sum_in =
ctx.Input<phi::DenseTensor>("BatchSum")->template data<T>();
const T *batch_square_sum_in =
ctx.Input<phi::DenseTensor>("BatchSquareSum")->data<T>();
auto *x_data = x->data<T>();
ctx.Input<phi::DenseTensor>("BatchSquareSum")->template data<T>();
auto *x_data = x->template data<T>();

// alloc memory
T *y_data =
ctx.Output<phi::DenseTensor>("Y")->mutable_data<T>(ctx.GetPlace());
T *y_data = ctx.Output<phi::DenseTensor>("Y")->template mutable_data<T>(
ctx.GetPlace());
T *mean_out_data =
ctx.Output<phi::DenseTensor>("Means")->mutable_data<T>(ctx.GetPlace());
ctx.Output<phi::DenseTensor>("Means")->template mutable_data<T>(
ctx.GetPlace());
T *scale_out_data =
ctx.Output<phi::DenseTensor>("Scales")->mutable_data<T>(ctx.GetPlace());
ctx.Output<phi::DenseTensor>("Scales")->template mutable_data<T>(
ctx.GetPlace());

auto stream = ctx.template device_context<phi::GPUContext>().stream();

Expand Down Expand Up @@ -185,31 +188,32 @@ class DataNormGradKernel<T, phi::GPUContext> : public framework::OpKernel<T> {
}
T *d_batch_size =
ctx.Output<phi::DenseTensor>(framework::GradVarName("BatchSize"))
->mutable_data<T>(ctx.GetPlace());
->template mutable_data<T>(ctx.GetPlace());
T *d_batch_sum =
ctx.Output<phi::DenseTensor>(framework::GradVarName("BatchSum"))
->mutable_data<T>(ctx.GetPlace());
->template mutable_data<T>(ctx.GetPlace());
T *d_batch_square_sum =
ctx.Output<phi::DenseTensor>(framework::GradVarName("BatchSquareSum"))
->mutable_data<T>(ctx.GetPlace());
->template mutable_data<T>(ctx.GetPlace());

auto stream = ctx.template device_context<phi::GPUContext>().stream();
if (d_x != nullptr) {
KernelDataNormBP<<<GET_BLOCKS(C * N),
PADDLE_CUDA_NUM_THREADS,
0,
stream>>>(N,
C,
d_y->data<T>(),
scales->data<T>(),
d_x->mutable_data<T>(ctx.GetPlace()));
stream>>>(
N,
C,
d_y->template data<T>(),
scales->template data<T>(),
d_x->template mutable_data<T>(ctx.GetPlace()));
}

KernelDataNormBPStat<<<GET_BLOCKS(C), PADDLE_CUDA_NUM_THREADS, 0, stream>>>(
N,
C,
x->data<T>(),
means->data<T>(),
x->template data<T>(),
means->template data<T>(),
epsilon,
d_batch_size,
d_batch_sum,
Expand Down Expand Up @@ -306,11 +310,11 @@ class DataNormGradKernel<T, phi::GPUContext> : public framework::OpKernel<T> {
}

T *batch_size_data = ctx.Output<phi::DenseTensor>("BatchSize")
->mutable_data<T>(ctx.GetPlace());
->template mutable_data<T>(ctx.GetPlace());
T *batch_sum_data = ctx.Output<phi::DenseTensor>("BatchSum")
->mutable_data<T>(ctx.GetPlace());
->template mutable_data<T>(ctx.GetPlace());
T *batch_square_sum_data = ctx.Output<phi::DenseTensor>("BatchSquareSum")
->mutable_data<T>(ctx.GetPlace());
->template mutable_data<T>(ctx.GetPlace());
KernelUpdateParam<<<GET_BLOCKS(C), PADDLE_CUDA_NUM_THREADS, 0, stream>>>(
C,
d_batch_size,
Expand Down
2 changes: 1 addition & 1 deletion paddle/fluid/operators/isfinite_op.h
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Original file line number Diff line number Diff line change
Expand Up @@ -162,7 +162,7 @@ class OverflowKernel : public framework::OpKernel<T> {
virtual void Compute(const framework::ExecutionContext& ctx) const {
auto* x = ctx.InputVar("X");
auto* out = ctx.Output<phi::DenseTensor>("Out");
out->mutable_data<T>(ctx.GetPlace());
out->template mutable_data<T>(ctx.GetPlace());
Functor functor;
if (x->IsType<phi::DenseTensor>()) {
auto* in = ctx.Input<phi::DenseTensor>("X");
Expand Down
8 changes: 4 additions & 4 deletions paddle/fluid/operators/pull_gpups_sparse_op.h
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Expand Up @@ -36,10 +36,10 @@ static void PullGpuPSSparseFunctor(const framework::ExecutionContext &ctx) {
for (size_t i = 0; i < slot_size; i++) {
const auto *slot = inputs[i];
const uint64_t *single_slot_keys =
reinterpret_cast<const uint64_t *>(slot->data<int64_t>());
reinterpret_cast<const uint64_t *>(slot->template data<int64_t>());
all_keys[i] = single_slot_keys;
slot_lengths[i] = slot->numel();
auto *output = outputs[i]->mutable_data<T>(ctx.GetPlace());
auto *output = outputs[i]->template mutable_data<T>(ctx.GetPlace());
// double type is not fully supported now
all_values[i] = reinterpret_cast<float *>(output);
}
Expand Down Expand Up @@ -68,7 +68,7 @@ static void PushGpuPSSparseFunctor(const framework::ExecutionContext &ctx) {
for (size_t i = 0; i < slot_size; i++) {
const auto *slot = inputs[i];
const uint64_t *single_slot_keys =
reinterpret_cast<const uint64_t *>(slot->data<int64_t>());
reinterpret_cast<const uint64_t *>(slot->template data<int64_t>());
all_keys[i] = single_slot_keys;
slot_lengths[i] = slot->numel();
int cur_batch_size =
Expand All @@ -82,7 +82,7 @@ static void PushGpuPSSparseFunctor(const framework::ExecutionContext &ctx) {
"The batch size of all input slots should be same, "
"please check"));
}
const float *grad_value = d_output[i]->data<float>();
const float *grad_value = d_output[i]->template data<float>();
all_grad_values[i] = grad_value;
}
#ifdef PADDLE_WITH_HETERPS
Expand Down
2 changes: 1 addition & 1 deletion test/cpp/fluid/framework/data_device_transform_test.cu
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Expand Up @@ -73,7 +73,7 @@ class TestKernel : public OpKernel<float> {
std::cout << "input place:" << input->place() << std::endl;
auto* output = ctx.Output<phi::DenseTensor>("output");
output->Resize(input->dims());
output->mutable_data<T>(ctx.GetPlace());
output->template mutable_data<T>(ctx.GetPlace());

phi::funcs::TransformFunctor<AddFunctor<T>, T, DeviceContext> functor(
*input,
Expand Down
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