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refine some grad op makers, test=develop (#21629)

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paddle_tiny_install
Zeng Jinle 5 years ago committed by GitHub
parent e2d849b989
commit 29f64c8c9e
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GPG Key ID: 4AEE18F83AFDEB23
6 changed files with 76 additions and 30 deletions
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4
paddle/fluid/op_use_default_grad_op_maker.spec
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@ -1,10 +1,7 @@
cos_sim
fsp
gru
lstm_unit
match_matrix_tensor
max_pool2d_with_index
max_pool3d_with_index
maxout
pool2d
pool3d
@ -15,6 +12,5 @@ reshape
rnn_memory_helper
sequence_softmax
spp
tensor_array_to_tensor
transpose
unsqueeze

29
paddle/fluid/operators/lstm_unit_op.cc
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@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/lstm_unit_op.h"
#include <memory>
namespace paddle {
namespace operators {
@ -94,14 +95,34 @@ class LstmUnitGradOp : public framework::OperatorWithKernel {
}
};
template <typename T>
class LstmUnitGradOpMaker : public framework::SingleGradOpMaker<T> {
public:
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
protected:
std::unique_ptr<T> Apply() const override {
std::unique_ptr<T> op(new T());
op->SetType("lstm_unit_grad");
op->SetInput("X", this->Input("X"));
op->SetInput("C_prev", this->Input("C_prev"));
op->SetInput("C", this->Output("C"));
op->SetInput(framework::GradVarName("H"), this->OutputGrad("H"));
op->SetInput(framework::GradVarName("C"), this->OutputGrad("C"));
op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
op->SetOutput(framework::GradVarName("C_prev"), this->InputGrad("C_prev"));
op->SetAttrMap(this->Attrs());
return op;
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(
lstm_unit, ops::LstmUnitOp, ops::LstmUnitOpMaker,
paddle::framework::DefaultGradOpMaker<paddle::framework::OpDesc, true>,
paddle::framework::DefaultGradOpMaker<paddle::imperative::OpBase, true>);
REGISTER_OPERATOR(lstm_unit, ops::LstmUnitOp, ops::LstmUnitOpMaker,
ops::LstmUnitGradOpMaker<paddle::framework::OpDesc>,
ops::LstmUnitGradOpMaker<paddle::imperative::OpBase>);
REGISTER_OPERATOR(lstm_unit_grad, ops::LstmUnitGradOp);
REGISTER_OP_CPU_KERNEL(lstm_unit,
ops::LstmUnitKernel<paddle::platform::CPUPlace, float>,

12
paddle/fluid/operators/lstm_unit_op.cu
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@ -62,9 +62,9 @@ __global__ void LSTMUnitKernel(const int nthreads, const int dim,
template <typename T>
__global__ void LSTMUnitGradientKernel(const int nthreads, const int dim,
const T* C_prev, const T* X, const T* C,
const T* H, const T* C_diff,
const T* H_diff, T* C_prev_diff,
T* X_diff, const T forget_bias) {
const T* C_diff, const T* H_diff,
T* C_prev_diff, T* X_diff,
const T forget_bias) {
CUDA_1D_KERNEL_LOOP(index, nthreads) {
const int n = index / dim;
const int d = index % dim;
@ -146,7 +146,6 @@ class LstmUnitGradOpCUDAKernel : public framework::OpKernel<T> {
auto* X = x_tensor->data<T>();
auto* C_prev = c_prev_tensor->data<T>();
auto* C = c_tensor->data<T>();
auto* H = h_tensor->data<T>();
auto* H_diff = hdiff_tensor->data<T>();
auto* C_diff = cdiff_tensor->data<T>();
@ -163,9 +162,8 @@ class LstmUnitGradOpCUDAKernel : public framework::OpKernel<T> {
int n = N * D;
int grid = (n + block - 1) / block;
LSTMUnitGradientKernel<T><<<grid, block>>>(n, D, C_prev, X, C, H, C_diff,
H_diff, C_prev_diff, X_diff,
forget_bias);
LSTMUnitGradientKernel<T><<<grid, block>>>(
n, D, C_prev, X, C, C_diff, H_diff, C_prev_diff, X_diff, forget_bias);
}
};

3
paddle/fluid/operators/lstm_unit_op.h
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@ -88,7 +88,6 @@ class LstmUnitGradKernel : public framework::OpKernel<T> {
auto x_tensor = ctx.Input<Tensor>("X");
auto c_prev_tensor = ctx.Input<Tensor>("C_prev");
auto c_tensor = ctx.Input<Tensor>("C");
auto h_tensor = ctx.Input<Tensor>("H");
auto hdiff_tensor = ctx.Input<Tensor>(framework::GradVarName("H"));
auto cdiff_tensor = ctx.Input<Tensor>(framework::GradVarName("C"));
@ -100,7 +99,6 @@ class LstmUnitGradKernel : public framework::OpKernel<T> {
auto* X = x_tensor->data<T>();
auto* C_prev = c_prev_tensor->data<T>();
auto* C = c_tensor->data<T>();
auto* H = h_tensor->data<T>();
auto* H_diff = hdiff_tensor->data<T>();
auto* C_diff = cdiff_tensor->data<T>();
@ -138,7 +136,6 @@ class LstmUnitGradKernel : public framework::OpKernel<T> {
C_prev += D;
X += 4 * D;
C += D;
H += D;
C_diff += D;
H_diff += D;
X_diff += 4 * D;

37
paddle/fluid/operators/pool_with_index_op.cc
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@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/pool_with_index_op.h"
#include <memory>
namespace paddle {
namespace operators {
@ -283,16 +284,33 @@ Example:
}
};
template <typename T>
class MaxPoolWithIndexGradOpMaker : public framework::SingleGradOpMaker<T> {
public:
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
protected:
std::unique_ptr<T> Apply() const override {
std::unique_ptr<T> op(new T());
op->SetType(this->ForwardOpType() + "_grad");
op->SetAttrMap(this->Attrs());
op->SetInput("X", this->Input("X"));
op->SetInput("Mask", this->Output("Mask"));
op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
return op;
}
};
} // namespace operators
} // namespace paddle
namespace ops = paddle::operators;
REGISTER_OPERATOR(
max_pool2d_with_index, ops::MaxPoolWithIndexOp,
ops::MaxPool2dWithIndexOpMaker,
paddle::framework::DefaultGradOpMaker<paddle::framework::OpDesc, true>,
paddle::framework::DefaultGradOpMaker<paddle::imperative::OpBase, true>);
REGISTER_OPERATOR(max_pool2d_with_index, ops::MaxPoolWithIndexOp,
ops::MaxPool2dWithIndexOpMaker,
ops::MaxPoolWithIndexGradOpMaker<paddle::framework::OpDesc>,
ops::MaxPoolWithIndexGradOpMaker<paddle::imperative::OpBase>);
REGISTER_OPERATOR(max_pool2d_with_index_grad, ops::MaxPoolWithIndexOpGrad);
REGISTER_OP_CPU_KERNEL(
@ -307,11 +325,10 @@ REGISTER_OP_CPU_KERNEL(
ops::MaxPoolWithIndexGradKernel<paddle::platform::CPUDeviceContext, double,
int>);
REGISTER_OPERATOR(
max_pool3d_with_index, ops::MaxPoolWithIndexOp,
ops::MaxPool3dWithIndexOpMaker,
paddle::framework::DefaultGradOpMaker<paddle::framework::OpDesc, true>,
paddle::framework::DefaultGradOpMaker<paddle::imperative::OpBase, true>);
REGISTER_OPERATOR(max_pool3d_with_index, ops::MaxPoolWithIndexOp,
ops::MaxPool3dWithIndexOpMaker,
ops::MaxPoolWithIndexGradOpMaker<paddle::framework::OpDesc>,
ops::MaxPoolWithIndexGradOpMaker<paddle::imperative::OpBase>);
REGISTER_OPERATOR(max_pool3d_with_index_grad, ops::MaxPoolWithIndexOpGrad);
REGISTER_OP_CPU_KERNEL(

21
paddle/fluid/operators/tensor_array_to_tensor_op.cc
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@ -273,6 +273,23 @@ class LoDTensorArray2TensorGradOp : public framework::OperatorBase {
}
};
template <typename T>
class TensorArrayToTensorGradOpMaker : public framework::SingleGradOpMaker<T> {
public:
using framework::SingleGradOpMaker<T>::SingleGradOpMaker;
protected:
std::unique_ptr<T> Apply() const override {
std::unique_ptr<T> op(new T());
op->SetType("tensor_array_to_tensor_grad");
op->SetAttrMap(this->Attrs());
op->SetInput("X", this->Input("X"));
op->SetInput(framework::GradVarName("Out"), this->OutputGrad("Out"));
op->SetOutput(framework::GradVarName("X"), this->InputGrad("X"));
return op;
}
};
} // namespace operators
} // namespace paddle
USE_OP(concat);
@ -281,8 +298,8 @@ namespace ops = paddle::operators;
REGISTER_OPERATOR(
tensor_array_to_tensor, ops::LoDTensorArray2TensorOp,
ops::LoDTensorArray2TensorOpMaker, ops::LoDTensorArray2TensorOpInferShape,
paddle::framework::DefaultGradOpMaker<paddle::framework::OpDesc, true>,
paddle::framework::DefaultGradOpMaker<paddle::imperative::OpBase, true>);
ops::TensorArrayToTensorGradOpMaker<paddle::framework::OpDesc>,
ops::TensorArrayToTensorGradOpMaker<paddle::imperative::OpBase>);
REGISTER_OPERATOR(tensor_array_to_tensor_grad, ops::LoDTensorArray2TensorGradOp,
ops::LoDTensorArray2TensorGradInferShape,
ops::LoDTensorArray2TensorGradInferVarType);

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