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"exported scatter to python" #9038

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Mar 15, 2018
Merged

"exported scatter to python" #9038

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38745a6
"exported scatter to python"
dzhwinter Mar 14, 2018
9898114
Revert ""exported scatter to python""
dzhwinter Mar 14, 2018
38bbce8
"polish scatter and export to python"
dzhwinter Mar 14, 2018
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35 changes: 17 additions & 18 deletions paddle/fluid/operators/scatter_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -23,24 +23,24 @@ class ScatterOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel;

void InferShape(framework::InferShapeContext* ctx) const override {
PADDLE_ENFORCE(ctx->HasInput("Ref"),
"Input(Ref) of ScatterOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Index"),
"Input(Index) of ScatterOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("X"),
"Input(X) of ScatterOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Ids"),
"Input(Ids) of ScatterOp should not be null.");
PADDLE_ENFORCE(ctx->HasInput("Updates"),
"Input(Updates) of ScatterOp should not be null.");
PADDLE_ENFORCE(ctx->HasOutput("Out"),
"Output(Out) of ScatterOp should not be null.");

auto updates_dims = ctx->GetInputDim("Updates");
auto ref_dims = ctx->GetInputDim("Ref");
PADDLE_ENFORCE_EQ(ctx->GetInputDim("Index").size(), 1,
"Update Index should be 1-D.");
auto ref_dims = ctx->GetInputDim("X");
PADDLE_ENFORCE_EQ(ctx->GetInputDim("Ids").size(), 1,
"Update Ids should be 1-D.");
PADDLE_ENFORCE_EQ(ref_dims.size(), updates_dims.size(),
"Reference and Updates should have the same shape size");
"Xerence and Updates should have the same shape size");
PADDLE_ENFORCE_EQ(ctx->GetInputDim("Updates")[0],
ctx->GetInputDim("Index")[0],
"Updates and Index should have same batch-size.");
ctx->GetInputDim("Ids")[0],
"Updates and Ids should have same batch-size.");
framework::DDim data_dim(updates_dims);
for (int i = 1; i < data_dim.size(); ++i) {
PADDLE_ENFORCE_EQ(data_dim[i], updates_dims[i]);
Expand All @@ -52,7 +52,7 @@ class ScatterOp : public framework::OperatorWithKernel {
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
return framework::OpKernelType(
framework::ToDataType(ctx.Input<Tensor>("Ref")->type()),
framework::ToDataType(ctx.Input<Tensor>("X")->type()),
ctx.device_context());
}
};
Expand All @@ -64,14 +64,14 @@ class ScatterGradOp : public framework::OperatorWithKernel {
void InferShape(framework::InferShapeContext* ctx) const override {
ctx->SetOutputDim(framework::GradVarName("Updates"),
ctx->GetInputDim("Updates"));
ctx->SetOutputDim(framework::GradVarName("Ref"), ctx->GetInputDim("Ref"));
ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("X"));
}

protected:
framework::OpKernelType GetExpectedKernelType(
const framework::ExecutionContext& ctx) const override {
return framework::OpKernelType(
framework::ToDataType(ctx.Input<Tensor>("Ref")->type()),
framework::ToDataType(ctx.Input<Tensor>("X")->type()),
ctx.device_context());
}
};
Expand All @@ -80,9 +80,8 @@ class ScatterOpMaker : public framework::OpProtoAndCheckerMaker {
public:
ScatterOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("Ref", "The source input of scatter op");
AddInput("Index",
"The index input of scatter op where Ref will be updated");
AddInput("X", "The source input of scatter op");
AddInput("Ids", "The index input of scatter op where X will be updated");
AddInput("Updates", "The updated value of updates op");
AddOutput("Out", "The output of add op");
AddComment(R"DOC(
Expand All @@ -91,8 +90,8 @@ Scatter Operator.
This operator obtains output by updating the input on selected indices on the first axis:

$$
Out = Ref \\
Out[Index] = Ref[Index] + Updates
Out = X \\
Out[Ids] = X[Ids] + Updates
$$

)DOC");
Expand Down
20 changes: 10 additions & 10 deletions paddle/fluid/operators/scatter_op.cu
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Original file line number Diff line number Diff line change
Expand Up @@ -25,14 +25,14 @@ class ScatterOpCUDAKernel : public framework::OpKernel<T> {
void Compute(const framework::ExecutionContext &ctx) const override {
PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
"This kernel only runs on GPU device.");
auto *Ref = ctx.Input<Tensor>("Ref");
auto *Index = ctx.Input<Tensor>("Index");
auto *X = ctx.Input<Tensor>("X");
auto *Ids = ctx.Input<Tensor>("Ids");
auto *Updates = ctx.Input<Tensor>("Updates");
auto *Out = ctx.Output<Tensor>("Out");

Out->ShareDataWith(*Ref);
Out->ShareDataWith(*X);

GPUScatterAssign<T>(ctx.device_context(), *Updates, *Index, Out);
GPUScatterAssign<T>(ctx.device_context(), *Updates, *Ids, Out);
}
};

Expand All @@ -42,16 +42,16 @@ class ScatterGradOpCUDAKernel : public framework::OpKernel<T> {
void Compute(const framework::ExecutionContext &ctx) const override {
PADDLE_ENFORCE(platform::is_gpu_place(ctx.GetPlace()),
"This kernel only runs on GPU device.");
auto *dRef = ctx.Output<Tensor>(framework::GradVarName("Ref"));
auto *dX = ctx.Output<Tensor>(framework::GradVarName("X"));
auto *dUpdates = ctx.Output<Tensor>(framework::GradVarName("Updates"));
auto *Index = ctx.Input<Tensor>("Index");
auto *Ids = ctx.Input<Tensor>("Ids");
auto *dOut = ctx.Input<Tensor>(framework::GradVarName("Out"));

// In place gradient: dRef = dO
dRef->ShareDataWith(*dOut);
// In place gradient: dX = dO
dX->ShareDataWith(*dOut);
dUpdates->mutable_data<T>(ctx.GetPlace());
// Gradient by Gather: dUpdates = dO[Index]
GPUGather<T>(ctx.device_context(), *dOut, *Index, dUpdates);
// Gradient by Gather: dUpdates = dO[Ids]
GPUGather<T>(ctx.device_context(), *dOut, *Ids, dUpdates);
}
};

Expand Down
22 changes: 11 additions & 11 deletions paddle/fluid/operators/scatter_op.h
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Original file line number Diff line number Diff line change
Expand Up @@ -29,15 +29,15 @@ class ScatterOpKernel : public framework::OpKernel<T> {
void Compute(const framework::ExecutionContext &ctx) const override {
PADDLE_ENFORCE(platform::is_cpu_place(ctx.GetPlace()),
"This kernel only runs on CPU.");
auto *Ref = ctx.Input<Tensor>("Ref");
auto *Index = ctx.Input<Tensor>("Index");
auto *X = ctx.Input<Tensor>("X");
auto *Ids = ctx.Input<Tensor>("Ids");
auto *Updates = ctx.Input<Tensor>("Updates");
auto *Out = ctx.Output<Tensor>("Out");

// In place output: Out = Ref, Out[Index] += Updates
Out->ShareDataWith(*Ref);
// In place output: Out = X, Out[Ids] += Updates
Out->ShareDataWith(*X);
// Apply ScatterUpdate: Out[index] += Updates[:]
ScatterAssign<T>(ctx.device_context(), *Updates, *Index, Out);
ScatterAssign<T>(ctx.device_context(), *Updates, *Ids, Out);
}
};

Expand All @@ -47,16 +47,16 @@ class ScatterGradientOpKernel : public framework::OpKernel<T> {
void Compute(const framework::ExecutionContext &ctx) const override {
PADDLE_ENFORCE(platform::is_cpu_place(ctx.GetPlace()),
"This kernel only runs on CPU.");
auto *dRef = ctx.Output<Tensor>(framework::GradVarName("Ref"));
auto *dX = ctx.Output<Tensor>(framework::GradVarName("X"));
auto *dUpdates = ctx.Output<Tensor>(framework::GradVarName("Updates"));
auto *Index = ctx.Input<Tensor>("Index");
auto *Ids = ctx.Input<Tensor>("Ids");
auto *dOut = ctx.Input<Tensor>(framework::GradVarName("Out"));

// In place gradient: dRef = dO
dRef->ShareDataWith(*dOut);
// In place gradient: dX = dO
dX->ShareDataWith(*dOut);
dUpdates->mutable_data<T>(ctx.GetPlace());
// Gradient by Gather: dUpdates += dO[Index]
CPUGather<T>(ctx.device_context(), *dOut, *Index, dUpdates);
// Gradient by Gather: dUpdates += dO[Ids]
CPUGather<T>(ctx.device_context(), *dOut, *Ids, dUpdates);
}
};

Expand Down
32 changes: 7 additions & 25 deletions python/paddle/fluid/layers/ops.py
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Original file line number Diff line number Diff line change
Expand Up @@ -45,31 +45,13 @@
]

__all__ = [
'mean',
'mul',
'reshape',
'scale',
'sigmoid_cross_entropy_with_logits',
'elementwise_add',
'elementwise_div',
'elementwise_sub',
'elementwise_mul',
'elementwise_max',
'elementwise_min',
'elementwise_pow',
'clip',
'clip_by_norm',
'softmax',
'sequence_softmax',
'logical_and',
'logical_or',
'logical_xor',
'logical_not',
'uniform_random',
'uniform_random_batch_size_like',
'gaussian_random',
'gaussian_random_batch_size_like',
'cumsum',
'mean', 'mul', 'reshape', 'scale', 'sigmoid_cross_entropy_with_logits',
'elementwise_add', 'elementwise_div', 'elementwise_sub', 'elementwise_mul',
'elementwise_max', 'elementwise_min', 'elementwise_pow', 'clip',
'clip_by_norm', 'softmax', 'sequence_softmax', 'logical_and', 'logical_or',
'logical_xor', 'logical_not', 'uniform_random',
'uniform_random_batch_size_like', 'gaussian_random',
'gaussian_random_batch_size_like', 'cumsum', 'scatter'
] + __activations__

for _OP in set(__all__):
Expand Down
2 changes: 1 addition & 1 deletion python/paddle/fluid/tests/unittests/test_scatter_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ def setUp(self):
updates_np = np.random.random((2, 3)).astype("float32")
output_np = np.copy(ref_np)
output_np[index_np] = updates_np
self.inputs = {'Ref': ref_np, 'Index': index_np, 'Updates': updates_np}
self.inputs = {'X': ref_np, 'Ids': index_np, 'Updates': updates_np}
self.outputs = {'Out': output_np}

def test_check_output(self):
Expand Down