You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
105 lines
3.9 KiB
105 lines
3.9 KiB
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License");
|
|
you may not use this file except in compliance with the License.
|
|
You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software
|
|
distributed under the License is distributed on an "AS IS" BASIS,
|
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
See the License for the specific language governing permissions and
|
|
limitations under the License. */
|
|
|
|
#include "paddle/fluid/framework/data_type_transform.h"
|
|
#include "paddle/fluid/framework/op_registry.h"
|
|
#include "paddle/fluid/operators/linspace_op.h"
|
|
#include "paddle/fluid/platform/cuda_primitives.h"
|
|
|
|
namespace paddle {
|
|
namespace operators {
|
|
|
|
using Tensor = framework::Tensor;
|
|
|
|
template <typename T>
|
|
__global__ void LinspaceKernel(T start, T stop, double step, int64_t size,
|
|
T* out) {
|
|
int64_t index = blockIdx.x * blockDim.x + threadIdx.x;
|
|
|
|
for (; index < size; index += blockDim.x * gridDim.x) {
|
|
if (index < size / 2) {
|
|
out[index] = static_cast<T>(start + step * index);
|
|
} else {
|
|
out[index] = static_cast<T>(stop - step * (size - index - 1));
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename T>
|
|
__global__ void LinspaceSpecialKernel(T start, T* out) {
|
|
out[0] = static_cast<T>(start);
|
|
}
|
|
|
|
template <typename T>
|
|
class CUDALinspaceKernel : public framework::OpKernel<T> {
|
|
public:
|
|
void Compute(const framework::ExecutionContext& context) const override {
|
|
auto* pre_start = context.Input<framework::Tensor>("Start");
|
|
auto* pre_stop = context.Input<framework::Tensor>("Stop");
|
|
auto* num_t = context.Input<framework::Tensor>("Num");
|
|
auto* out = context.Output<framework::Tensor>("Out");
|
|
auto dtype = static_cast<framework::proto::VarType::Type>(
|
|
context.Attr<int>("dtype"));
|
|
|
|
Tensor start_t;
|
|
Tensor stop_t;
|
|
auto start_dtype =
|
|
framework::OpKernelType(pre_start->type(), context.GetPlace());
|
|
auto stop_dtype =
|
|
framework::OpKernelType(pre_stop->type(), context.GetPlace());
|
|
auto out_dtype = framework::OpKernelType(dtype, context.GetPlace());
|
|
framework::TransDataType(start_dtype, out_dtype, *pre_start, &start_t);
|
|
framework::TransDataType(stop_dtype, out_dtype, *pre_stop, &stop_t);
|
|
|
|
framework::Tensor n_start;
|
|
framework::Tensor n_stop;
|
|
framework::Tensor n_num;
|
|
framework::TensorCopy(start_t, platform::CPUPlace(), &n_start);
|
|
T start = n_start.data<T>()[0];
|
|
framework::TensorCopy(stop_t, platform::CPUPlace(), &n_stop);
|
|
T stop = n_stop.data<T>()[0];
|
|
framework::TensorCopy(*num_t, platform::CPUPlace(), &n_num);
|
|
int64_t num = static_cast<int64_t>(n_num.data<int32_t>()[0]);
|
|
|
|
PADDLE_ENFORCE_GT(num, 0, platform::errors::InvalidArgument(
|
|
"The num of linspace op should be larger "
|
|
"than 0, but received num is %d",
|
|
num));
|
|
|
|
out->Resize(framework::make_ddim({num}));
|
|
T* out_data = out->mutable_data<T>(context.GetPlace());
|
|
|
|
double step = 0;
|
|
auto stream = context.cuda_device_context().stream();
|
|
int block = 512;
|
|
int grid = (num + block - 1) / block;
|
|
if (num != 1) {
|
|
step = (static_cast<double>(stop - start)) / (num - 1);
|
|
LinspaceKernel<T><<<grid, block, 0, stream>>>(start, stop, step, num,
|
|
out_data);
|
|
} else {
|
|
LinspaceSpecialKernel<T><<<grid, block, 0, stream>>>(start, out_data);
|
|
}
|
|
}
|
|
};
|
|
|
|
} // namespace operators
|
|
} // namespace paddle
|
|
|
|
namespace ops = paddle::operators;
|
|
REGISTER_OP_CUDA_KERNEL(linspace, ops::CUDALinspaceKernel<float>,
|
|
ops::CUDALinspaceKernel<int32_t>,
|
|
ops::CUDALinspaceKernel<int64_t>,
|
|
ops::CUDALinspaceKernel<double>);
|