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!15698 告警清理 

From: @he-botao
Reviewed-by: @wuxuejian,@c_34
Signed-off-by: @wuxuejian
This commit is contained in:
mindspore-ci-bot 2021-04-27 09:21:38 +08:00 committed by Gitee
parent a20b631858 4ee7560ece
commit 40cf487413
4 changed files with 9 additions and 35 deletions
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38
mindspore/ccsrc/backend/kernel_compiler/cpu/elu_grad_cpu_kernel.cc
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@ -21,14 +21,6 @@
namespace mindspore {
namespace kernel {
template <typename T>
void EluGradCPUKernel::EluGrad(const T *input0, const T *input1, T *out, size_t start, size_t end) {
const T alpha = static_cast<T>(1);
for (size_t i = start; i < end; i++) {
out[i] = (input1[i] < static_cast<T>(0)) ? input0[i] * (input1[i] + alpha) : input0[i];
}
}
void EluGradCPUKernel::InitKernel(const CNodePtr &kernel_node) {
MS_EXCEPTION_IF_NULL(kernel_node);
dtype_ = AnfAlgo::GetPrevNodeOutputInferDataType(kernel_node, 0);
@ -57,29 +49,13 @@ void EluGradCPUKernel::LaunchKernel(const std::vector<AddressPtr> &inputs, const
T *output = reinterpret_cast<T *>(outputs[0]->addr);
size_t lens = outputs[0]->size > 0 ? static_cast<size_t>(outputs[0]->size / sizeof(T)) : 1;
auto max_thread_num = std::thread::hardware_concurrency();
size_t thread_num = lens < 128 * max_thread_num ? std::ceil(lens / 128.0) : max_thread_num;
MS_LOG(INFO) << "Lens=" << lens << "; use thread_num=" << thread_num << "; max_thread_num: " << max_thread_num;
std::vector<std::thread> threads;
if (thread_num < 1) {
MS_LOG(ERROR) << "Invalid value: thread_num " << thread_num;
return;
}
threads.reserve(thread_num);
size_t start = 0;
size_t once_compute_size = (lens + thread_num - 1) / thread_num;
if (once_compute_size < 1) {
MS_LOG(ERROR) << "Invalid value: once_compute_size " << once_compute_size;
return;
}
while (start < lens) {
size_t end = (start + once_compute_size) > lens ? lens : (start + once_compute_size);
threads.emplace_back(std::thread(&EluGradCPUKernel::EluGrad<T>, this, input0, input1, output, start, end));
start += once_compute_size;
}
for (size_t i = 0; i < threads.size(); ++i) {
threads[i].join();
}
auto task = [input0, input1, output](const size_t start, const size_t end) {
const T alpha = T(1);
for (size_t i = start; i < end; i++) {
output[i] = (input1[i] < static_cast<T>(0)) ? input0[i] * (input1[i] + alpha) : input0[i];
}
};
CPUKernelUtils::ParallelFor(task, lens);
}
} // namespace kernel
} // namespace mindspore

2
mindspore/ccsrc/backend/kernel_compiler/cpu/elu_grad_cpu_kernel.h
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@ -35,8 +35,6 @@ class EluGradCPUKernel : public CPUKernel {
void LaunchKernel(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &outputs);
private:
template <typename T>
void EluGrad(const T *input1, const T *input2, T *out, size_t start, size_t end);
TypeId dtype_{kTypeUnknown};
};

2
mindspore/ccsrc/backend/kernel_compiler/cpu/select_cpu_kernel.cc
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@ -37,7 +37,7 @@ void SelectCPUKernel<T>::InitKernel(const CNodePtr &kernel_node) {
}
template <typename T>
bool SelectCPUKernel<T>::Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
bool SelectCPUKernel<T>::Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &,
const std::vector<AddressPtr> &outputs) {
auto input_cond = reinterpret_cast<bool *>(inputs[0]->addr);
auto input_x = reinterpret_cast<T *>(inputs[1]->addr);

2
mindspore/ccsrc/backend/kernel_compiler/cpu/select_cpu_kernel.h
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@ -28,7 +28,7 @@ class SelectCPUKernel : public CPUKernel {
SelectCPUKernel() = default;
~SelectCPUKernel() override = default;
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &workspace,
bool Launch(const std::vector<AddressPtr> &inputs, const std::vector<AddressPtr> &,
const std::vector<AddressPtr> &outputs) override;
void InitKernel(const CNodePtr &kernel_node) override;