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!6317 Add relu6 gpu 

Merge pull request !6317 from TuDouNi/relu6
This commit is contained in:
mindspore-ci-bot 2020-09-17 09:51:06 +08:00 committed by Gitee
parent 61c00fc4e7 d11239f70f
commit 0cbb4f6330
6 changed files with 25 additions and 3 deletions
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5
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.cc
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@ -23,6 +23,11 @@ MS_REG_GPU_KERNEL_ONE(ReLU, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOut
MS_REG_GPU_KERNEL_ONE(ReLU, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ActivationGpuFwdKernel, half)
MS_REG_GPU_KERNEL_ONE(ReLU6, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
ActivationGpuFwdKernel, float)
MS_REG_GPU_KERNEL_ONE(ReLU6, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ActivationGpuFwdKernel, half)
MS_REG_GPU_KERNEL_ONE(Tanh, KernelAttr().AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
ActivationGpuFwdKernel, float)
MS_REG_GPU_KERNEL_ONE(Tanh, KernelAttr().AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),

4
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_gpu_kernel.h
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@ -83,7 +83,8 @@ class ActivationGpuFwdKernel : public GpuKernel {
return true;
}
std::vector<int> shape;
CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_NOT_PROPAGATE_NAN, 0.0),
double coef = (mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) ? 6.0 : 0.0;
CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_NOT_PROPAGATE_NAN, coef),
"cudnnSetActivationDescriptor failed");
const int split_dim = 4;
@ -132,6 +133,7 @@ class ActivationGpuFwdKernel : public GpuKernel {
}
std::map<std::string, cudnnActivationMode_t> kernel_map = {{"ReLU", CUDNN_ACTIVATION_RELU},
{"ReLU6", CUDNN_ACTIVATION_CLIPPED_RELU},
{"Tanh", CUDNN_ACTIVATION_TANH},
{"ELU", CUDNN_ACTIVATION_ELU},
{"Sigmoid", CUDNN_ACTIVATION_SIGMOID}};

9
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.cc
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@ -27,6 +27,15 @@ MS_REG_GPU_KERNEL_ONE(
KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ActivationGradGpuKernel, half)
MS_REG_GPU_KERNEL_ONE(
ReLU6Grad,
KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),
ActivationGradGpuKernel, float)
MS_REG_GPU_KERNEL_ONE(
ReLU6Grad,
KernelAttr().AddInputAttr(kNumberTypeFloat16).AddInputAttr(kNumberTypeFloat16).AddOutputAttr(kNumberTypeFloat16),
ActivationGradGpuKernel, half)
MS_REG_GPU_KERNEL_ONE(
TanhGrad,
KernelAttr().AddInputAttr(kNumberTypeFloat32).AddInputAttr(kNumberTypeFloat32).AddOutputAttr(kNumberTypeFloat32),

6
mindspore/ccsrc/backend/kernel_compiler/gpu/nn/activation_grad_kernel.h
View File

@ -49,7 +49,7 @@ class ActivationGradGpuKernel : public GpuKernel {
}
T *dy = nullptr;
T *y = nullptr;
if (mode_ == CUDNN_ACTIVATION_RELU || mode_ == CUDNN_ACTIVATION_ELU) {
if (mode_ == CUDNN_ACTIVATION_RELU || mode_ == CUDNN_ACTIVATION_ELU || mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) {
dy = GetDeviceAddress<T>(inputs, 0);
y = GetDeviceAddress<T>(inputs, 1);
} else {
@ -90,7 +90,8 @@ class ActivationGradGpuKernel : public GpuKernel {
return true;
}
std::vector<int> shape;
CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_PROPAGATE_NAN, 0.0),
double coef = (mode_ == CUDNN_ACTIVATION_CLIPPED_RELU) ? 5.999999 : 0.0;
CHECK_CUDNN_RET_WITH_EXCEPT(cudnnSetActivationDescriptor(activation_desc_, mode_, CUDNN_PROPAGATE_NAN, coef),
"SetActivationDescriptor failed");
const int split_dim = 4;
@ -138,6 +139,7 @@ class ActivationGradGpuKernel : public GpuKernel {
}
std::map<std::string, cudnnActivationMode_t> kernel_map = {{"ReluGrad", CUDNN_ACTIVATION_RELU},
{"ReLU6Grad", CUDNN_ACTIVATION_CLIPPED_RELU},
{"TanhGrad", CUDNN_ACTIVATION_TANH},
{"ELUGrad", CUDNN_ACTIVATION_ELU},
{"SigmoidGrad", CUDNN_ACTIVATION_SIGMOID}};

2
mindspore/ccsrc/runtime/device/gpu/kernel_info_setter.h
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@ -54,6 +54,8 @@ static std::map<std::string, std::pair<std::vector<size_t>, std::vector<size_t>>
// Format insensitive.
{prim::kPrimRelu->name(), {{0}, {0}}},
{prim::kPrimReluGrad->name(), {{0, 1}, {0}}},
{prim::kPrimRelu6->name(), {{0}, {0}}},
{prim::kPrimRelu6Grad->name(), {{0, 1}, {0}}},
{kSliceOpName, {{0}, {0}}},
{kTensorAddOpName, {{0, 1}, {0}}},
{prim::kPrimConcat->name(), {{}, {0}}},

2
mindspore/core/base/core_ops.h
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@ -127,6 +127,7 @@ inline const PrimitivePtr kPrimFusedBatchNormGradEx = std::make_shared<Primitive
inline const PrimitivePtr kPrimBatchNorm = std::make_shared<Primitive>("BatchNorm");
inline const PrimitivePtr kPrimBatchNormGrad = std::make_shared<Primitive>("BatchNormGrad");
inline const PrimitivePtr kPrimReluGrad = std::make_shared<Primitive>("ReluGrad");
inline const PrimitivePtr kPrimRelu6Grad = std::make_shared<Primitive>("ReLU6Grad");
inline const PrimitivePtr kPrimConv2DBackpropInput = std::make_shared<Primitive>("Conv2DBackpropInput");
inline const PrimitivePtr kPrimConv2DBackpropFilter = std::make_shared<Primitive>("Conv2DBackpropFilter");
inline const PrimitivePtr kPrimDepthwiseConv2dNative = std::make_shared<Primitive>("DepthwiseConv2dNative");
@ -151,6 +152,7 @@ inline const PrimitivePtr kPrimOneHot = std::make_shared<Primitive>("OneHot");
inline const PrimitivePtr kPrimGelu = std::make_shared<Primitive>("Gelu");
inline const PrimitivePtr kPrimGeluGrad = std::make_shared<Primitive>("GeluGrad");
inline const PrimitivePtr kPrimRelu = std::make_shared<Primitive>("ReLU");
inline const PrimitivePtr kPrimRelu6 = std::make_shared<Primitive>("ReLU6");
inline const PrimitivePtr kPrimReluV2 = std::make_shared<Primitive>("ReLUV2");
inline const PrimitivePtr kPrimZerosLike = std::make_shared<Primitive>("ZerosLike");
inline const PrimitivePtr kPrimBpropCut = std::make_shared<Primitive>("bprop_cut");