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InfiniTensor
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style: fix style

This commit is contained in:
OdinaryWord 2023-12-14 11:32:07 +08:00
parent c29dcf1e6d
commit db8c3eec15
7 changed files with 86 additions and 75 deletions
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3
include/cuda/cuda_unary.h
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@ -15,7 +15,8 @@ template <typename T> void erf_kernel(T *input, T *output, size_t num);
template <typename T> void hard_sigmoid_kernel(T *input, T *output, size_t num); template <typename T> void hard_sigmoid_kernel(T *input, T *output, size_t num);
template <typename T> void hard_swish_kernel(T *input, T *output, size_t num); template <typename T> void hard_swish_kernel(T *input, T *output, size_t num);
template<typename INPUT, typename OUTPUT> void cast_kernel(INPUT *input, OUTPUT *output, size_t num); template <typename INPUT, typename OUTPUT>
void cast_kernel(INPUT *input, OUTPUT *output, size_t num);
void unary_kernel(const Operator &_op); void unary_kernel(const Operator &_op);

12
src/kernels/cuda/gather.cc
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@ -18,15 +18,13 @@ class GatherCuda : public CudaKernelWithoutConfig {
void *const inputData = (op->getInputs(0)->getRawDataPtr<void *>()); void *const inputData = (op->getInputs(0)->getRawDataPtr<void *>());
void *const outputData = (op->getOutput()->getRawDataPtr<void *>()); void *const outputData = (op->getOutput()->getRawDataPtr<void *>());
if (op->getDType() == DataType::Float32) { if (op->getDType() == DataType::Float32) {
gather_kernel<float>((float*)inputData, (float*)outputData, metaData, op->getOutput()->size()); gather_kernel<float>((float *)inputData, (float *)outputData,
metaData, op->getOutput()->size());
} else if (op->getDType() == DataType::Float32) {
gather_kernel<half>((half *)inputData, (half *)outputData, metaData,
op->getOutput()->size());
} }
else if(op->getDType() == DataType::Float32){
gather_kernel<half>((half*)inputData, (half*)outputData, metaData, op->getOutput()->size());
}
} }
}; };

9
src/kernels/cuda/gather.cu
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@ -50,7 +50,10 @@ void gather_kernel(T *in, T *out, GatherMetaData metaData, size_t num) {
_gather_kernel<T, int><<<gridSize, blockSize>>>(in, out, metaData, num); _gather_kernel<T, int><<<gridSize, blockSize>>>(in, out, metaData, num);
} }
} }
template void gather_kernel<float>(float *in, float *out, GatherMetaData metaData, size_t num); template void gather_kernel<float>(float *in, float *out,
template void gather_kernel<half>(half *in, half *out, GatherMetaData metaData, size_t num); GatherMetaData metaData, size_t num);
template void gather_kernel<int8_t>(int8_t *in, int8_t *out, GatherMetaData metaData, size_t num); template void gather_kernel<half>(half *in, half *out, GatherMetaData metaData,
size_t num);
template void gather_kernel<int8_t>(int8_t *in, int8_t *out,
GatherMetaData metaData, size_t num);
} // namespace infini } // namespace infini

46
src/kernels/cuda/unary.cc
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@ -22,28 +22,32 @@ class CastCuda : public CudaKernelWithoutConfig {
void *const inputData = (op->getInputs(0)->getRawDataPtr<void *>()); void *const inputData = (op->getInputs(0)->getRawDataPtr<void *>());
void *const outputData = (op->getOutput()->getRawDataPtr<void *>()); void *const outputData = (op->getOutput()->getRawDataPtr<void *>());
if (op->getType() == CastType::Float162Float) { if (op->getType() == CastType::Float162Float) {
IT_ASSERT(op->getInDType() == DataType::Float16 && op->getOutDType() == DataType::Float32); IT_ASSERT(op->getInDType() == DataType::Float16 &&
cast_kernel<half, float>((half *)inputData, (float*)outputData, num); op->getOutDType() == DataType::Float32);
} cast_kernel<half, float>((half *)inputData, (float *)outputData,
else if(op->getType() == CastType::Float2Float16){ num);
IT_ASSERT(op->getInDType() == DataType::Float32 && op->getOutDType() == DataType::Float16); } else if (op->getType() == CastType::Float2Float16) {
cast_kernel<float, half>((float*)inputData, (half *)outputData, num); IT_ASSERT(op->getInDType() == DataType::Float32 &&
} op->getOutDType() == DataType::Float16);
else if(op->getType() == CastType::Float2Int32){ cast_kernel<float, half>((float *)inputData, (half *)outputData,
IT_ASSERT(op->getInDType() == DataType::Float32 && op->getOutDType() == DataType::Int32); num);
cast_kernel<float, int32_t>((float*)inputData, (int32_t *)outputData, num); } else if (op->getType() == CastType::Float2Int32) {
} IT_ASSERT(op->getInDType() == DataType::Float32 &&
else if(op->getType() == CastType::Float2Int8){ op->getOutDType() == DataType::Int32);
IT_ASSERT(op->getInDType() == DataType::Float32 && op->getOutDType() == DataType::Int8); cast_kernel<float, int32_t>((float *)inputData,
cast_kernel<float, int8_t>((float*)inputData, (int8_t *)outputData, num); (int32_t *)outputData, num);
} } else if (op->getType() == CastType::Float2Int8) {
else if(op->getType() == CastType::Int82Float){ IT_ASSERT(op->getInDType() == DataType::Float32 &&
IT_ASSERT(op->getInDType() == DataType::Int8 && op->getOutDType() == DataType::Float32); op->getOutDType() == DataType::Int8);
cast_kernel<int8_t, float>((int8_t*)inputData, (float *)outputData, num); cast_kernel<float, int8_t>((float *)inputData, (int8_t *)outputData,
} num);
else{ } else if (op->getType() == CastType::Int82Float) {
IT_ASSERT(op->getInDType() == DataType::Int8 &&
op->getOutDType() == DataType::Float32);
cast_kernel<int8_t, float>((int8_t *)inputData, (float *)outputData,
num);
} else {
IT_ASSERT(false); IT_ASSERT(false);
} }
} }

11
src/kernels/cuda/unary.cu
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@ -2,8 +2,8 @@
#include "core/constants.h" #include "core/constants.h"
#include "cuda/cuda_common.h" #include "cuda/cuda_common.h"
#include "cuda/cuda_unary.h" #include "cuda/cuda_unary.h"
#include <math.h>
#include <cub/cub.cuh> #include <cub/cub.cuh>
#include <math.h>
using infini::E_CONSTANT; using infini::E_CONSTANT;
constexpr unsigned int num_threads() { return 32 * 4; } constexpr unsigned int num_threads() { return 32 * 4; }
@ -297,8 +297,11 @@ void cast_kernel(INPUT *input, OUTPUT *output, size_t num) {
template void cast_kernel<float, half>(float *input, half *output, size_t num); template void cast_kernel<float, half>(float *input, half *output, size_t num);
template void cast_kernel<half, float>(half *input, float *output, size_t num); template void cast_kernel<half, float>(half *input, float *output, size_t num);
template void cast_kernel<float, int32_t>(float *input, int32_t *output, size_t num); template void cast_kernel<float, int32_t>(float *input, int32_t *output,
template void cast_kernel<float, int8_t>(float *input, int8_t *output, size_t num); size_t num);
template void cast_kernel<int8_t, float>(int8_t *input, float *output, size_t num); template void cast_kernel<float, int8_t>(float *input, int8_t *output,
size_t num);
template void cast_kernel<int8_t, float>(int8_t *input, float *output,
size_t num);
}; // namespace infini }; // namespace infini

10
test/kernels/cuda/test_cuda_unary.cc
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@ -55,7 +55,8 @@ void testCast(const std::function<void(void *, size_t, DataType)> &generator,
// GPU // GPU
Graph cudaGraph = make_ref<GraphObj>(cudaRuntime); Graph cudaGraph = make_ref<GraphObj>(cudaRuntime);
auto inputGpu = cudaGraph->cloneTensor(inputCpu); auto inputGpu = cudaGraph->cloneTensor(inputCpu);
auto gpuOp = cudaGraph->addOp<T>(inputGpu, nullptr, CastType::Float2Float16); auto gpuOp =
cudaGraph->addOp<T>(inputGpu, nullptr, CastType::Float2Float16);
cudaGraph->dataMalloc(); cudaGraph->dataMalloc();
inputGpu->setData(generator); inputGpu->setData(generator);
cudaRuntime->run(cudaGraph); cudaRuntime->run(cudaGraph);
@ -69,8 +70,8 @@ void testCast(const std::function<void(void *, size_t, DataType)> &generator,
// GPU // GPU
// Graph cudaGraph2 = make_ref<GraphObj>(cudaRuntime); // Graph cudaGraph2 = make_ref<GraphObj>(cudaRuntime);
////auto inputGpu2 = cudaGraph2->cloneTensor(outputGpu2Cpu); ////auto inputGpu2 = cudaGraph2->cloneTensor(outputGpu2Cpu);
//auto gpuOp2 = cudaGraph2->addOp<T>(outputGpu, nullptr, CastType::Float162Float); // auto gpuOp2 = cudaGraph2->addOp<T>(outputGpu, nullptr,
//cudaGraph2->dataMalloc(); // CastType::Float162Float); cudaGraph2->dataMalloc();
////inputGpu2->setData(generator); ////inputGpu2->setData(generator);
// cudaRuntime->run(cudaGraph2); // cudaRuntime->run(cudaGraph2);
// auto outputGpu2 = gpuOp2->getOutput(); // auto outputGpu2 = gpuOp2->getOutput();
@ -100,7 +101,8 @@ TEST(cuDNN_Unary, run) {
// testUnary<GeluObj>(IncrementalGenerator(), Shape{1, 2}); // testUnary<GeluObj>(IncrementalGenerator(), Shape{1, 2});
// testUnary<GeluObj>(IncrementalGenerator(), Shape{1, 2, 2, 3}); // testUnary<GeluObj>(IncrementalGenerator(), Shape{1, 2, 2, 3});
testCast<CastObj>(IncrementalGenerator(), Shape{8, 1}, vector<float>{0, 1, 2, 3, 4, 5, 6, 7}); testCast<CastObj>(IncrementalGenerator(), Shape{8, 1},
vector<float>{0, 1, 2, 3, 4, 5, 6, 7});
} }
} // namespace infini } // namespace infini