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Support many data types of several operators (#5731)

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* Support many data types of several operators

* SeqConv only support float/double

* Revert adagrad
release/0.11.0
Yu Yang 7 years ago committed by GitHub
parent f2ca07e88a
commit a5e73f9eaf
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
13 changed files with 68 additions and 74 deletions
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90
paddle/operators/activation_op.cc
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3
paddle/operators/adadelta_op.cc
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@ -109,4 +109,5 @@ paramOut = param + paramUpdate$$
namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT(adadelta, ops::AdadeltaOp, ops::AdadeltaOpMaker);
REGISTER_OP_CPU_KERNEL(
adadelta, ops::AdadeltaOpKernel<paddle::platform::CPUPlace, float>);
adadelta, ops::AdadeltaOpKernel<paddle::platform::CPUPlace, float>,
ops::AdadeltaOpKernel<paddle::platform::CPUPlace, double>);

3
paddle/operators/adadelta_op.cu
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@ -17,4 +17,5 @@
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(
adadelta, ops::AdadeltaOpKernel<paddle::platform::GPUPlace, float>);
adadelta, ops::AdadeltaOpKernel<paddle::platform::GPUPlace, float>,
ops::AdadeltaOpKernel<paddle::platform::GPUPlace, double>);

4
paddle/operators/adadelta_op.h
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@ -33,8 +33,8 @@ class AdadeltaOpKernel : public framework::OpKernel<T> {
avg_squared_grad_out_tensor->mutable_data<T>(ctx.GetPlace());
avg_squared_update_out_tensor->mutable_data<T>(ctx.GetPlace());
float rho = ctx.Attr<float>("rho");
float epsilon = ctx.Attr<float>("epsilon");
T rho = static_cast<T>(ctx.Attr<float>("rho"));
T epsilon = static_cast<T>(ctx.Attr<float>("epsilon"));
auto param = framework::EigenVector<T>::Flatten(
*ctx.Input<framework::Tensor>("Param"));

6
paddle/operators/adagrad_op.cu
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@ -14,8 +14,8 @@
#define EIGEN_USE_GPU
#include "paddle/operators/adagrad_op.h"
#include "paddle/operators/math/selected_rows_functor.h"
#include "paddle/operators/math/math_function.h"
#include "paddle/operators/math/selected_rows_functor.h"
#include "paddle/platform/cuda_helper.h"
namespace paddle {
@ -134,8 +134,8 @@ struct SparseAdagradFunctor<platform::GPUPlace, T> {
T, 256><<<grid2, threads, 0,
reinterpret_cast<const platform::CUDADeviceContext&>(context)
.stream()>>>(grad_merge_data, grad_merge->rows().data(),
lr, param_data,
moment_data, grad_width, epsilon);
lr, param_data, moment_data, grad_width,
epsilon);
}
};

3
paddle/operators/adam_op.cc
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@ -127,4 +127,5 @@ paramOut = param - learningRate * moment_1/ ($\sqrt{(moment_2)} + \epsilon)$$
namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT(adam, ops::AdamOp, ops::AdamOpMaker);
REGISTER_OP_CPU_KERNEL(adam,
ops::AdamOpKernel<paddle::platform::CPUPlace, float>);
ops::AdamOpKernel<paddle::platform::CPUPlace, float>,
ops::AdamOpKernel<paddle::platform::CPUPlace, double>);

3
paddle/operators/adam_op.cu
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@ -17,4 +17,5 @@
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(adam,
ops::AdamOpKernel<paddle::platform::GPUPlace, float>);
ops::AdamOpKernel<paddle::platform::GPUPlace, float>,
ops::AdamOpKernel<paddle::platform::GPUPlace, double>);

6
paddle/operators/adam_op.h
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@ -31,9 +31,9 @@ class AdamOpKernel : public framework::OpKernel<T> {
moment1_out_tensor->mutable_data<T>(ctx.GetPlace());
moment2_out_tensor->mutable_data<T>(ctx.GetPlace());
float beta1 = ctx.Attr<float>("beta1");
float beta2 = ctx.Attr<float>("beta2");
float epsilon = ctx.Attr<float>("epsilon");
T beta1 = static_cast<T>(ctx.Attr<float>("beta1"));
T beta2 = static_cast<T>(ctx.Attr<float>("beta2"));
T epsilon = static_cast<T>(ctx.Attr<float>("epsilon"));
auto param = framework::EigenVector<T>::Flatten(
*ctx.Input<framework::Tensor>("Param"));

3
paddle/operators/adamax_op.cc
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@ -126,4 +126,5 @@ division by 0 error.
namespace ops = paddle::operators;
REGISTER_OP_WITHOUT_GRADIENT(adamax, ops::AdamaxOp, ops::AdamaxOpMaker);
REGISTER_OP_CPU_KERNEL(adamax,
ops::AdamaxOpKernel<paddle::platform::CPUPlace, float>);
ops::AdamaxOpKernel<paddle::platform::CPUPlace, float>,
ops::AdamaxOpKernel<paddle::platform::CPUPlace, double>);

3
paddle/operators/adamax_op.cu
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@ -17,4 +17,5 @@
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(adamax,
ops::AdamaxOpKernel<paddle::platform::GPUPlace, float>);
ops::AdamaxOpKernel<paddle::platform::GPUPlace, float>,
ops::AdamaxOpKernel<paddle::platform::GPUPlace, double>);

6
paddle/operators/adamax_op.h
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@ -31,9 +31,9 @@ class AdamaxOpKernel : public framework::OpKernel<T> {
moment_out_tensor->mutable_data<T>(ctx.GetPlace());
inf_norm_out_tensor->mutable_data<T>(ctx.GetPlace());
float beta1 = ctx.Attr<float>("beta1");
float beta2 = ctx.Attr<float>("beta2");
float epsilon = ctx.Attr<float>("epsilon");
T beta1 = static_cast<T>(ctx.Attr<float>("beta1"));
T beta2 = static_cast<T>(ctx.Attr<float>("beta2"));
T epsilon = static_cast<T>(ctx.Attr<float>("epsilon"));
auto param = framework::EigenVector<T>::Flatten(
*ctx.Input<framework::Tensor>("Param"));

6
paddle/operators/sequence_conv_op.cc
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@ -179,7 +179,9 @@ REGISTER_OP(sequence_conv, ops::SequenceConvOp, ops::SequenceConvOpMaker,
sequence_conv_grad, ops::SequenceConvGradOp);
REGISTER_OP_CPU_KERNEL(
sequence_conv, ops::SequenceConvKernel<paddle::platform::CPUPlace, float>);
sequence_conv, ops::SequenceConvKernel<paddle::platform::CPUPlace, float>,
ops::SequenceConvKernel<paddle::platform::CPUPlace, double>);
REGISTER_OP_CPU_KERNEL(
sequence_conv_grad,
ops::SequenceConvGradKernel<paddle::platform::CPUPlace, float>);
ops::SequenceConvGradKernel<paddle::platform::CPUPlace, float>,
ops::SequenceConvGradKernel<paddle::platform::CPUPlace, double>);

6
paddle/operators/sequence_conv_op.cu.cc
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@ -16,7 +16,9 @@
namespace ops = paddle::operators;
REGISTER_OP_GPU_KERNEL(
sequence_conv, ops::SequenceConvKernel<paddle::platform::GPUPlace, float>);
sequence_conv, ops::SequenceConvKernel<paddle::platform::GPUPlace, float>,
ops::SequenceConvKernel<paddle::platform::GPUPlace, double>);
REGISTER_OP_GPU_KERNEL(
sequence_conv_grad,
ops::SequenceConvGradKernel<paddle::platform::GPUPlace, float>);
ops::SequenceConvGradKernel<paddle::platform::GPUPlace, float>,
ops::SequenceConvGradKernel<paddle::platform::GPUPlace, double>);

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