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add GPU operator: abs and floor

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pull/3142/head
CaoJian 5 years ago
parent 7233d650f0
commit f3f9fc958a
4 changed files with 68 additions and 1 deletions
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43
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/unary_op_impl.cu
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@ -103,6 +103,35 @@ __global__ void ZeroslikeKernel(T *output, size_t count) {
return;
}
template <typename T>
__global__ void AbsKernel(T *input, T *output, size_t count) {
for (size_t i = blockIdx.x * blockDim.x + threadIdx.x; i < (count); i += blockDim.x * gridDim.x) {
output[i] = abs(input[i]);
}
return;
}
template <>
__global__ void AbsKernel(half *input, half *output, size_t count) {
half zero = 0.0;
for (size_t i = blockIdx.x * blockDim.x + threadIdx.x; i < (count); i += blockDim.x * gridDim.x) {
output[i] = input[i] < zero ? -input[i] : input[i];
}
return;
}
template <typename T>
__global__ void FloorKernel(T *input, T *output, size_t count) {
for (size_t i = blockIdx.x * blockDim.x + threadIdx.x; i < (count); i += blockDim.x * gridDim.x) {
output[i] = floor(input[i]);
}
return;
}
template <>
__global__ void FloorKernel(half *input, half *output, size_t count) {
for (size_t i = blockIdx.x * blockDim.x + threadIdx.x; i < (count); i += blockDim.x * gridDim.x) {
output[i] = hfloor(input[i]);
}
return;
}
template <typename T>
void Exponential(T *input, T *output, size_t count, cudaStream_t cuda_stream) {
ExponentialKernel<<<GET_BLOCKS(count), GET_THREADS, 0, cuda_stream>>>(input, output, count);
return;
@ -147,6 +176,16 @@ void Zeroslike(T *output, size_t count, cudaStream_t cuda_stream) {
ZeroslikeKernel<<<GET_BLOCKS(count), GET_THREADS, 0, cuda_stream>>>(output, count);
return;
}
template <typename T>
void Abs(T *input, T *output, size_t count, cudaStream_t cuda_stream) {
AbsKernel<<<GET_BLOCKS(count), GET_THREADS, 0, cuda_stream>>>(input, output, count);
return;
}
template <typename T>
void Floor(T *input, T *output, size_t count, cudaStream_t cuda_stream) {
FloorKernel<<<GET_BLOCKS(count), GET_THREADS, 0, cuda_stream>>>(input, output, count);
return;
}
template void Exponential<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
template void Logarithm<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
@ -156,6 +195,8 @@ template void Square<float>(float *input, float *output, size_t count, cudaStrea
template void Sqrt<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
template void Rsqrt<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
template void Zeroslike<float>(float *output, size_t count, cudaStream_t cuda_stream);
template void Abs<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
template void Floor<float>(float *input, float *output, size_t count, cudaStream_t cuda_stream);
template void Exponential<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);
template void Logarithm<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);
template void Negative<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);
@ -164,3 +205,5 @@ template void Square<half>(half *input, half *output, size_t count, cudaStream_t
template void Sqrt<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);
template void Rsqrt<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);
template void Zeroslike<half>(half *output, size_t count, cudaStream_t cuda_stream);
template void Abs<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);
template void Floor<half>(half *input, half *output, size_t count, cudaStream_t cuda_stream);

4
mindspore/ccsrc/backend/kernel_compiler/gpu/cuda_impl/unary_op_impl.cuh
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@ -34,5 +34,9 @@ template <typename T>
void Rsqrt(T *input, T *output, size_t count, cudaStream_t cuda_stream);
template <typename T>
void Zeroslike(T *output, size_t count, cudaStream_t cuda_stream);
template <typename T>
void Abs(T *input, T *output, size_t count, cudaStream_t cuda_stream);
template <typename T>
void Floor(T *input, T *output, size_t count, cudaStream_t cuda_stream);
#endif // MINDSPORE_CCSRC_KERNEL_GPU_CUDA_IMPL_UNARYOPIMPL_H_

8
mindspore/ccsrc/backend/kernel_compiler/gpu/math/unary_op_gpu_kernel.cc
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@ -46,5 +46,13 @@ MS_REG_GPU_KERNEL_ONE(Sqrt, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOut
UnaryOpGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(Rsqrt, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
UnaryOpGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(Abs, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
UnaryOpGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(Abs, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
UnaryOpGpuKernel, half)
MS_REG_GPU_KERNEL_ONE(Floor, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
UnaryOpGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(Floor, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
UnaryOpGpuKernel, half)
} // namespace kernel
} // namespace mindspore

14
mindspore/ccsrc/backend/kernel_compiler/gpu/math/unary_op_gpu_kernel.h
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@ -36,6 +36,8 @@ enum UnaryOptype {
UNARY_OP_SQUARE,
UNARY_OP_SQRT,
UNARY_OP_RSQRT,
UNARY_OP_ABS,
UNARY_OP_FLOOR,
UNARY_OP_INVALID_TYPE = 255
};
static const std::map<std::string, UnaryOptype> kUnaryOpTypeMap = {{"Exp", UNARY_OP_EXP},
@ -45,7 +47,9 @@ static const std::map<std::string, UnaryOptype> kUnaryOpTypeMap = {{"Exp", UNARY
{"ZerosLike", UNARY_OP_ZEROSLIKE},
{"Square", UNARY_OP_SQUARE},
{"Sqrt", UNARY_OP_SQRT},
{"Rsqrt", UNARY_OP_RSQRT}};
{"Rsqrt", UNARY_OP_RSQRT},
{"Abs", UNARY_OP_ABS},
{"Floor", UNARY_OP_FLOOR}};
template <typename T>
class UnaryOpGpuKernel : public GpuKernel {
public:
@ -100,6 +104,14 @@ class UnaryOpGpuKernel : public GpuKernel {
Zeroslike(output_addr, output_size_ / sizeof(T), reinterpret_cast<cudaStream_t>(stream_ptr));
return true;
}
case UNARY_OP_ABS: {
Abs(input_addr, output_addr, inputs[0]->size / sizeof(T), reinterpret_cast<cudaStream_t>(stream_ptr));
break;
}
case UNARY_OP_FLOOR: {
Floor(input_addr, output_addr, inputs[0]->size / sizeof(T), reinterpret_cast<cudaStream_t>(stream_ptr));
break;
}
default: {
MS_LOG(EXCEPTION) << "Unary operation " << unary_op_type_ << " is not supported.";
}

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