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chengduo
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Set the right shape of selected_rows (#13723)
* set the right shape of selected_rows test=develop * enhance check * fix activation_op * remove cast * use ShareDimInfo replace SetDim and ShareLod * use ShareDimAndLod test=develop * follow comment test=develop * check whether the input has lod test=develop * Split ShareDimAndLod test=develop * checkout clip.py test=develop
1 parent 2a36f0a commit e176170

19 files changed

+158
-25
lines changed

‎.gitignore

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@@ -25,5 +25,6 @@ third_party/
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bazel-*
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third_party/
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build_*
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# clion workspace.
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cmake-build-*

‎paddle/fluid/framework/op_desc.cc

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@@ -50,6 +50,27 @@ class CompileTimeInferShapeContext : public InferShapeContext {
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const std::vector<std::string> &Outputs(
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const std::string &name) const override;
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53+
void ShareDim(const std::string &in, const std::string &out, size_t i = 0,
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size_t j = 0) override {
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PADDLE_ENFORCE_LT(i, Inputs(in).size());
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PADDLE_ENFORCE_LT(j, Outputs(out).size());
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const std::string &input_n = Inputs(in)[i];
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const std::string &output_n = Outputs(out)[j];
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PADDLE_ENFORCE(input_n != framework::kEmptyVarName, "The %s[%d] is @EMPTY@",
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in, i);
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PADDLE_ENFORCE(output_n != framework::kEmptyVarName,
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"The %s[%d] is @EMPTY@", out, j);
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auto *in_var = block_.FindVarRecursive(input_n);
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auto *out_var = block_.FindVarRecursive(output_n);
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PADDLE_ENFORCE(in_var->GetType() == out_var->GetType(),
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"The type of %s and %s is not the same.", input_n, output_n);
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SetDim(output_n, GetDim(input_n));
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}
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void ShareLoD(const std::string &in, const std::string &out, size_t i = 0,
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size_t j = 0) const override {
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PADDLE_ENFORCE_LT(i, Inputs(in).size());

‎paddle/fluid/framework/operator.cc

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@@ -542,6 +542,36 @@ class RuntimeInferShapeContext : public InferShapeContext {
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return op_.Outputs(name);
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}
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void ShareDim(const std::string& in, const std::string& out, size_t i = 0,
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size_t j = 0) override {
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PADDLE_ENFORCE_LT(i, Inputs(in).size());
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PADDLE_ENFORCE_LT(j, Outputs(out).size());
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const std::string& input_n = Inputs(in)[i];
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const std::string& output_n = Outputs(out)[j];
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Variable* in_var = scope_.FindVar(input_n);
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Variable* out_var = scope_.FindVar(output_n);
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PADDLE_ENFORCE(in_var->Type() == out_var->Type(),
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"The type of %s and %s is not the same.", output_n,
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GetDim(input_n));
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558+
if (in_var->IsType<framework::SelectedRows>()) {
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auto& in_sele_rows = in_var->Get<framework::SelectedRows>();
560+
auto out_sele_rows = out_var->GetMutable<framework::SelectedRows>();
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out_sele_rows->mutable_value()->Resize(in_sele_rows.value().dims());
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out_sele_rows->set_rows(in_sele_rows.rows());
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out_sele_rows->set_height(in_sele_rows.height());
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} else if (in_var->IsType<framework::LoDTensor>()) {
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auto& in_lod_tensor = in_var->Get<framework::LoDTensor>();
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auto* out_lod_tensor = out_var->GetMutable<framework::LoDTensor>();
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out_lod_tensor->Resize(in_lod_tensor.dims());
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} else {
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PADDLE_THROW(
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"Currently, the input type of ShareDim only can be LoDTensor "
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"or SelectedRows.");
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}
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}
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void ShareLoD(const std::string& in, const std::string& out, size_t i = 0,
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size_t j = 0) const override {
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const std::vector<std::string>& inputs = Inputs(in);

‎paddle/fluid/framework/shape_inference.h

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@@ -56,6 +56,9 @@ class InferShapeContext {
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virtual const std::vector<std::string> &Outputs(
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const std::string &name) const = 0;
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59+
virtual void ShareDim(const std::string &in, const std::string &out,
60+
size_t i = 0, size_t j = 0) = 0;
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virtual void ShareLoD(const std::string &in, const std::string &out,
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size_t i = 0, size_t j = 0) const = 0;
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‎paddle/fluid/operators/activation_op.cc

Lines changed: 18 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -80,7 +80,7 @@ class ActivationOp : public framework::OperatorWithKernel {
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using framework::OperatorWithKernel::OperatorWithKernel;
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void InferShape(framework::InferShapeContext* ctx) const override {
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ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
83+
ctx->ShareDim("X", /*->*/ "Out");
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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@@ -91,12 +91,26 @@ class ActivationOp : public framework::OperatorWithKernel {
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}
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};
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94+
class ActivationOpInferVarType : public framework::VarTypeInference {
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public:
96+
void operator()(const framework::OpDesc& op_desc,
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framework::BlockDesc* block) const override {
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auto x_name = op_desc.Input("X")[0];
99+
auto out_name = op_desc.Output("Out")[0];
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auto& x = block->FindRecursiveOrCreateVar(x_name);
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auto& out = block->FindRecursiveOrCreateVar(out_name);
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out.SetType(x.GetType());
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out.SetDataType(x.GetDataType());
104+
}
105+
};
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class ActivationOpGrad : public framework::OperatorWithKernel {
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public:
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using framework::OperatorWithKernel::OperatorWithKernel;
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98111
void InferShape(framework::InferShapeContext* ctx) const override {
99-
ctx->SetOutputDim(framework::GradVarName("X"), ctx->GetInputDim("Out"));
112+
ctx->ShareDim("Out", framework::GradVarName("X"));
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ctx->ShareLoD("Out", framework::GradVarName("X"));
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}
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protected:
@@ -525,12 +539,14 @@ namespace ops = paddle::operators;
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#define REGISTER_INPLACE_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
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REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
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::paddle::operators::OP_NAME##OpMaker, \
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::paddle::operators::ActivationOpInferVarType, \
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::paddle::operators::OP_NAME##GradMaker); \
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REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
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531546
#define REGISTER_ACTIVATION_OP(OP_NAME, KERNEL_TYPE) \
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REGISTER_OPERATOR(KERNEL_TYPE, ::paddle::operators::ActivationOp, \
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::paddle::operators::OP_NAME##OpMaker, \
549+
::paddle::operators::ActivationOpInferVarType, \
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::paddle::framework::DefaultGradOpDescMaker<true>); \
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REGISTER_OPERATOR(KERNEL_TYPE##_grad, ::paddle::operators::ActivationOpGrad)
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‎paddle/fluid/operators/argsort_op.cc

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@@ -42,8 +42,8 @@ class ArgsortOp : public framework::OperatorWithKernel {
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"-rank(Input(X)) (%d).",
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axis, num_dims);
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45-
ctx->SetOutputDim("Out", in_dims);
46-
ctx->SetOutputDim("Indices", in_dims);
45+
ctx->ShareDim("X", "Out");
46+
ctx->ShareDim("X", "Indices");
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ctx->ShareLoD("X", "Out");
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ctx->ShareLoD("X", "Indices");
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}

‎paddle/fluid/operators/conv_shift_op.cc

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@@ -44,7 +44,7 @@ class ConvShiftOp : public framework::OperatorWithKernel {
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PADDLE_ENFORCE_LE(y_dims[1], x_dims[1],
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"The 2nd dimension of Input(Y) should be less than or "
4646
"equal to the 2nd dimension of Input(X).");
47-
ctx->SetOutputDim("Out", x_dims);
47+
ctx->ShareDim("X", /*->*/ "Out");
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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};

‎paddle/fluid/operators/elementwise_op.h

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@@ -41,7 +41,8 @@ class ElementwiseOp : public framework::OperatorWithKernel {
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auto y_dim = ctx->GetInputDim("Y");
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PADDLE_ENFORCE_GE(x_dim.size(), y_dim.size(),
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"Rank of first input must >= rank of second input.");
44-
ctx->SetOutputDim("Out", x_dim);
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45+
ctx->ShareDim("X", /*->*/ "Out");
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ctx->ShareLoD("X", /*->*/ "Out");
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}
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@@ -70,6 +71,7 @@ class ElementwiseOpInferVarType : public framework::VarTypeInference {
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auto& x = block->FindRecursiveOrCreateVar(x_name);
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auto& out = block->FindRecursiveOrCreateVar(out_name);
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out.SetType(x.GetType());
74+
out.SetDataType(x.GetDataType());
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}
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};
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@@ -157,10 +159,12 @@ class ElementwiseOpGrad : public framework::OperatorWithKernel {
157159
auto x_grad_name = framework::GradVarName("X");
158160
auto y_grad_name = framework::GradVarName("Y");
159161
if (ctx->HasOutput(x_grad_name)) {
160-
ctx->SetOutputDim(x_grad_name, x_dims);
162+
ctx->ShareDim("X", /*->*/ x_grad_name);
163+
ctx->ShareLoD("X", /*->*/ x_grad_name);
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}
162165
if (ctx->HasOutput(y_grad_name)) {
163-
ctx->SetOutputDim(y_grad_name, y_dims);
166+
ctx->ShareDim("Y", /*->*/ y_grad_name);
167+
ctx->ShareLoD("Y", /*->*/ y_grad_name);
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}
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}
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@@ -193,14 +197,15 @@ class ElementwiseOpExplicitGrad : public ElementwiseOpGrad {
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194198
auto x_grad_name = framework::GradVarName("X");
195199
if (ctx->HasOutput(x_grad_name)) {
196-
auto out_dims = ctx->GetInputDim(framework::GradVarName("Out"));
197-
ctx->SetOutputDim(x_grad_name, out_dims);
200+
ctx->ShareDim(framework::GradVarName("Out"), /*->*/ x_grad_name);
201+
ctx->ShareLoD(framework::GradVarName("Out"), /*->*/ x_grad_name);
198202
}
199203
auto y_grad_name = framework::GradVarName("Y");
200204
if (ctx->HasOutput(y_grad_name)) {
201205
PADDLE_ENFORCE(ctx->HasInput("Y"), "Input(Y) should not be null");
202-
auto y_dims = ctx->GetInputDim("Y");
203-
ctx->SetOutputDim(y_grad_name, y_dims);
206+
207+
ctx->ShareDim("Y", /*->*/ y_grad_name);
208+
ctx->ShareLoD("Y", /*->*/ y_grad_name);
204209
}
205210
}
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};

‎paddle/fluid/operators/fake_dequantize_op.cc

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@@ -48,7 +48,8 @@ class FakeDequantizeMaxAbsOp : public framework::OperatorWithKernel {
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"Input(X) of FakeDequantizeMaxAbsOp should not be null.");
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PADDLE_ENFORCE(ctx->HasOutput("Out"),
5050
"Output(Out) of FakeDequantizeMaxAbsOp should not be null.");
51-
ctx->SetOutputDim("Out", ctx->GetInputDim("X"));
51+
52+
ctx->ShareDim("X", /*->*/ "Out");
5253
ctx->ShareLoD("X", /*->*/ "Out");
5354
}
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};

‎paddle/fluid/operators/lookup_table_op.cc

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@@ -137,6 +137,7 @@ class LookupTableOpGradVarTypeInference : public framework::VarTypeInference {
137137
<< " is set to LoDTensor";
138138
block->Var(out_var_name)->SetType(framework::proto::VarType::LOD_TENSOR);
139139
}
140+
block->Var(out_var_name)->SetDataType(block->Var("W")->GetDataType());
140141
}
141142
};
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