提交 eef1ccbf 编写于 作者: L Liu Yiqun

Add the check of inputs and outputs in all operators.

上级 40fba4aa
...@@ -23,10 +23,15 @@ class AccuracyOp : public framework::OperatorWithKernel { ...@@ -23,10 +23,15 @@ class AccuracyOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Inference"), PADDLE_ENFORCE_NOT_NULL(
"Input of Inference must be initialized."); ctx.InputVar("Inference"),
"Input(Inference) of AccuracyOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Label"), PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Label"),
"Input of Inference must be initialized."); "Input(Label) of AccuracyOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Accuracy"),
"Output(Accuracy) of AccuracyOp should not be null.");
auto *inference = ctx.Input<framework::Tensor>("Inference"); auto *inference = ctx.Input<framework::Tensor>("Inference");
auto *label = ctx.Input<framework::Tensor>("Label"); auto *label = ctx.Input<framework::Tensor>("Label");
......
...@@ -23,6 +23,13 @@ class AddOp : public framework::OperatorWithKernel { ...@@ -23,6 +23,13 @@ class AddOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of AddOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"),
"Input(Y) of AddOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of AddOp should not be null.");
PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("X")->dims(), PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("X")->dims(),
ctx.Input<Tensor>("Y")->dims(), ctx.Input<Tensor>("Y")->dims(),
"Two input of Add Op's dimension must be same."); "Two input of Add Op's dimension must be same.");
......
...@@ -25,6 +25,9 @@ class ConcatOp : public framework::OperatorWithKernel { ...@@ -25,6 +25,9 @@ class ConcatOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of ConcatOp should not be null.");
auto ins = ctx.MultiInput<framework::Tensor>("X"); auto ins = ctx.MultiInput<framework::Tensor>("X");
auto *out = ctx.Output<framework::LoDTensor>("Out"); auto *out = ctx.Output<framework::LoDTensor>("Out");
size_t axis = static_cast<size_t>(ctx.Attr<int>("axis")); size_t axis = static_cast<size_t>(ctx.Attr<int>("axis"));
......
...@@ -33,7 +33,8 @@ using DDim = framework::DDim; ...@@ -33,7 +33,8 @@ using DDim = framework::DDim;
void CondOp::CreateScope(const Scope& scope) const { void CondOp::CreateScope(const Scope& scope) const {
auto sub_scopes_var = scope.FindVar("SubScopes"); auto sub_scopes_var = scope.FindVar("SubScopes");
PADDLE_ENFORCE(sub_scopes_var != nullptr, ""); PADDLE_ENFORCE_NOT_NULL(sub_scopes_var,
"Output(SubScopes) of CondOp should not be null.");
auto sub_scopes = sub_scopes_var->GetMutable<std::vector<Scope*>>(); auto sub_scopes = sub_scopes_var->GetMutable<std::vector<Scope*>>();
auto& sub_scope = scope.NewScope(); auto& sub_scope = scope.NewScope();
sub_scopes->push_back(&sub_scope); sub_scopes->push_back(&sub_scope);
...@@ -41,7 +42,8 @@ void CondOp::CreateScope(const Scope& scope) const { ...@@ -41,7 +42,8 @@ void CondOp::CreateScope(const Scope& scope) const {
void CondOp::CreateIndexTensor(const Scope& scope) const { void CondOp::CreateIndexTensor(const Scope& scope) const {
auto index_tensors_var = scope.FindVar("IndexTensors"); auto index_tensors_var = scope.FindVar("IndexTensors");
PADDLE_ENFORCE(index_tensors_var != nullptr, ""); PADDLE_ENFORCE_NOT_NULL(index_tensors_var,
"Output(IndexTensors) of CondOp should not be null.");
auto& index_tensors = auto& index_tensors =
*index_tensors_var->GetMutable<std::vector<LoDTensor>>(); *index_tensors_var->GetMutable<std::vector<LoDTensor>>();
index_tensors.push_back(LoDTensor()); index_tensors.push_back(LoDTensor());
...@@ -49,7 +51,8 @@ void CondOp::CreateIndexTensor(const Scope& scope) const { ...@@ -49,7 +51,8 @@ void CondOp::CreateIndexTensor(const Scope& scope) const {
void CondOp::InferShape(const Scope& scope) const { void CondOp::InferShape(const Scope& scope) const {
auto sub_scopes_var = scope.FindVar("SubScopes"); auto sub_scopes_var = scope.FindVar("SubScopes");
PADDLE_ENFORCE_NOT_NULL(sub_scopes_var); PADDLE_ENFORCE_NOT_NULL(sub_scopes_var,
"Output(SubScopes) of CondOp should not be null.");
auto& sub_scopes = *sub_scopes_var->GetMutable<std::vector<Scope*>>(); auto& sub_scopes = *sub_scopes_var->GetMutable<std::vector<Scope*>>();
for (int i = 0; i < 2; ++i) { for (int i = 0; i < 2; ++i) {
...@@ -63,7 +66,8 @@ void CondOp::InferShape(const Scope& scope) const { ...@@ -63,7 +66,8 @@ void CondOp::InferShape(const Scope& scope) const {
// branch // branch
CreateIndexTensor(scope); CreateIndexTensor(scope);
PADDLE_ENFORCE(!Inputs("Xs").empty(), "Inputs can't be empty"); PADDLE_ENFORCE(!Inputs("Xs").empty(),
"Inputs(Xs) of CondOp can't be empty.");
for (auto& input : Inputs("Xs")) { for (auto& input : Inputs("Xs")) {
// Create a new tensor in sub-scope for input-type tensor // Create a new tensor in sub-scope for input-type tensor
Variable* v = sub_scopes[i]->NewVar(input); Variable* v = sub_scopes[i]->NewVar(input);
...@@ -108,13 +112,18 @@ void CondOp::InferShape(const Scope& scope) const { ...@@ -108,13 +112,18 @@ void CondOp::InferShape(const Scope& scope) const {
void CondOp::Run(const Scope& scope, void CondOp::Run(const Scope& scope,
const platform::DeviceContext& dev_ctx) const { const platform::DeviceContext& dev_ctx) const {
auto* sub_scopes_var = scope.FindVar("SubScopes"); auto* sub_scopes_var = scope.FindVar("SubScopes");
PADDLE_ENFORCE_NOT_NULL(sub_scopes_var,
"Output(SubScopes) of CondOp should not be null.");
auto sub_scopes = sub_scopes_var->Get<std::vector<Scope*>>(); auto sub_scopes = sub_scopes_var->Get<std::vector<Scope*>>();
auto* index_tensors_var = scope.FindVar("IndexTensors"); auto* index_tensors_var = scope.FindVar("IndexTensors");
PADDLE_ENFORCE_NOT_NULL(index_tensors_var,
"Output(IndexTensors) of CondOp should not be null.");
auto index_tensors = index_tensors_var->Get<std::vector<LoDTensor>>(); auto index_tensors = index_tensors_var->Get<std::vector<LoDTensor>>();
std::string cond_name = Input("Cond"); std::string cond_name = Input("Cond");
Variable* cond_var = scope.FindVar(cond_name); Variable* cond_var = scope.FindVar(cond_name);
PADDLE_ENFORCE_NOT_NULL(cond_var); PADDLE_ENFORCE_NOT_NULL(cond_var,
"Input(Cond) of CondOp should not be null.");
const LoDTensor* cond = cond_var->GetMutable<LoDTensor>(); const LoDTensor* cond = cond_var->GetMutable<LoDTensor>();
// Step 1: get the true/false index at runtime // Step 1: get the true/false index at runtime
...@@ -171,6 +180,8 @@ void CondOp::Run(const Scope& scope, ...@@ -171,6 +180,8 @@ void CondOp::Run(const Scope& scope,
} }
// Step 4: merge output results // Step 4: merge output results
PADDLE_ENFORCE(!Outputs("Outs").empty(),
"Outputs(Outs) of CondOp can't be empty.");
for (int i = 0; i < 2; ++i) { for (int i = 0; i < 2; ++i) {
// i= 0/i for True and False branches respectively // i= 0/i for True and False branches respectively
for (auto& output : Outputs("Outs")) { for (auto& output : Outputs("Outs")) {
......
...@@ -26,8 +26,16 @@ class CosSimOp : public framework::OperatorWithKernel { ...@@ -26,8 +26,16 @@ class CosSimOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
// notnull check // notnull check
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) must not be null."); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) must not be null."); "Input(X) of CosSimOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"),
"Input(Y) of CosSimOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of CosSimOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("XNorm"),
"Output(XNorm) of CosSimOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("YNorm"),
"Output(YNorm) of CosSimOp should not be null.");
// shape check // shape check
auto x_dims = ctx.Input<Tensor>("X")->dims(); auto x_dims = ctx.Input<Tensor>("X")->dims();
......
...@@ -25,8 +25,14 @@ class ElementWiseMulOp : public framework::OperatorWithKernel { ...@@ -25,8 +25,14 @@ class ElementWiseMulOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) should not be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), "Input(Y) should not be null"); "Input(X) of ElementWiseMulOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"),
"Input(Y) of ElementWiseMulOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Out"),
"Output(Out) of ElementWiseMulOp should not be null.");
auto x_dim = ctx.Input<Tensor>("X")->dims(); auto x_dim = ctx.Input<Tensor>("X")->dims();
auto y_dim = ctx.Input<Tensor>("Y")->dims(); auto y_dim = ctx.Input<Tensor>("Y")->dims();
PADDLE_ENFORCE_GE(x_dim.size(), y_dim.size(), PADDLE_ENFORCE_GE(x_dim.size(), y_dim.size(),
......
...@@ -23,6 +23,13 @@ class FillZerosLikeOp : public framework::OperatorWithKernel { ...@@ -23,6 +23,13 @@ class FillZerosLikeOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(
ctx.InputVar("Src"),
"Input(Src) of FillZerosLikeOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Dst"),
"Output(Dst) of FillZerosLikeOp should not be null.");
ctx.Output<framework::LoDTensor>("Dst")->Resize( ctx.Output<framework::LoDTensor>("Dst")->Resize(
ctx.Input<framework::Tensor>("Src")->dims()); ctx.Input<framework::Tensor>("Src")->dims());
} }
......
...@@ -24,6 +24,13 @@ class GatherOp : public framework::OperatorWithKernel { ...@@ -24,6 +24,13 @@ class GatherOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of GatherOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Index"),
"Input(Index) of GatherOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of GatherOp should not be null.");
int batch_size = ctx.Input<Tensor>("Index")->dims()[0]; int batch_size = ctx.Input<Tensor>("Index")->dims()[0];
PADDLE_ENFORCE_GE(batch_size, 0, "Batch size must be >0"); PADDLE_ENFORCE_GE(batch_size, 0, "Batch size must be >0");
framework::DDim output_dims(ctx.Input<Tensor>("X")->dims()); framework::DDim output_dims(ctx.Input<Tensor>("X")->dims());
......
...@@ -43,8 +43,12 @@ class GaussianRandomOp : public framework::OperatorWithKernel { ...@@ -43,8 +43,12 @@ class GaussianRandomOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
protected: protected:
void InferShape(const framework::InferShapeContext& context) const override { void InferShape(const framework::InferShapeContext& ctx) const override {
auto* tensor = context.Output<framework::LoDTensor>("Out"); PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Out"),
"Output(Out) of GaussianRandomOp should not be null.");
auto* tensor = ctx.Output<framework::LoDTensor>("Out");
auto dims = Attr<std::vector<int>>("dims"); auto dims = Attr<std::vector<int>>("dims");
std::vector<int64_t> temp; std::vector<int64_t> temp;
temp.reserve(dims.size()); temp.reserve(dims.size());
......
...@@ -42,6 +42,11 @@ class IdentityOp : public NetOp { ...@@ -42,6 +42,11 @@ class IdentityOp : public NetOp {
const framework::VariableNameMap &outputs, const framework::VariableNameMap &outputs,
const framework::AttributeMap &attrs) const framework::AttributeMap &attrs)
: NetOp(type, inputs, outputs, attrs) { : NetOp(type, inputs, outputs, attrs) {
PADDLE_ENFORCE_NE(Input("X"), framework::kEmptyVarName,
"Input(X) of IdentityOp should not be null.");
PADDLE_ENFORCE_NE(Output("Out"), framework::kEmptyVarName,
"Output(Out) of IdentityOp should not be null.");
AppendOp(framework::OpRegistry::CreateOp( AppendOp(framework::OpRegistry::CreateOp(
"scale", {{"X", {Input("X")}}}, {{"Out", {Output("Out")}}}, "scale", {{"X", {Input("X")}}}, {{"Out", {Output("Out")}}},
{{"scale", static_cast<AttrType>(1)}})); {{"scale", static_cast<AttrType>(1)}}));
......
...@@ -22,10 +22,17 @@ class LookupTableOp : public framework::OperatorWithKernel { ...@@ -22,10 +22,17 @@ class LookupTableOp : public framework::OperatorWithKernel {
using framework::OperatorWithKernel::OperatorWithKernel; using framework::OperatorWithKernel::OperatorWithKernel;
protected: protected:
void InferShape(const framework::InferShapeContext &context) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
auto table_t = context.Input<Tensor>("W"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("W"),
auto ids_t = context.Input<Tensor>("Ids"); "Input(W) of LookupTableOp should not be null.");
auto output_t = context.Output<framework::LoDTensor>("Out"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Ids"),
"Input(Ids) of LookupTableOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of LookupTableOp should not be null.");
auto table_t = ctx.Input<Tensor>("W");
auto ids_t = ctx.Input<Tensor>("Ids");
auto output_t = ctx.Output<framework::LoDTensor>("Out");
output_t->Resize({ids_t->dims()[0], table_t->dims()[1]}); output_t->Resize({ids_t->dims()[0], table_t->dims()[1]});
} }
......
...@@ -24,7 +24,9 @@ class MeanOp : public framework::OperatorWithKernel { ...@@ -24,7 +24,9 @@ class MeanOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input of MeanOp must be initialized."); "Input(X) of MeanOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of MeanOp should not be null.");
ctx.Output<framework::LoDTensor>("Out")->Resize({1}); ctx.Output<framework::LoDTensor>("Out")->Resize({1});
} }
}; };
......
...@@ -27,6 +27,13 @@ class MinusOp : public framework::OperatorWithKernel { ...@@ -27,6 +27,13 @@ class MinusOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of MinusOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"),
"Input(Y) of MinusOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of MinusOp should not be null.");
auto *left_tensor = ctx.Input<framework::Tensor>("X"); auto *left_tensor = ctx.Input<framework::Tensor>("X");
auto *right_tensor = ctx.Input<framework::Tensor>("Y"); auto *right_tensor = ctx.Input<framework::Tensor>("Y");
......
...@@ -26,6 +26,13 @@ class MulOp : public framework::OperatorWithKernel { ...@@ -26,6 +26,13 @@ class MulOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of MulOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"),
"Input(Y) of MulOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of MulOp should not be null.");
auto x_dims = ctx.Input<Tensor>("X")->dims(); auto x_dims = ctx.Input<Tensor>("X")->dims();
auto y_dims = ctx.Input<Tensor>("Y")->dims(); auto y_dims = ctx.Input<Tensor>("Y")->dims();
int x_num_col_dims = Attr<int>("x_num_col_dims"); int x_num_col_dims = Attr<int>("x_num_col_dims");
......
...@@ -23,6 +23,16 @@ class OnehotCrossEntropyOp : public framework::OperatorWithKernel { ...@@ -23,6 +23,16 @@ class OnehotCrossEntropyOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(
ctx.InputVar("X"),
"Input(X) of OnehotCrossEntropyOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(
ctx.InputVar("label"),
"Input(label) of OnehotCrossEntropyOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Y"),
"Output(Y) of OnehotCrossEntropyOp should not be null.");
auto *X = ctx.Input<Tensor>("X"); auto *X = ctx.Input<Tensor>("X");
auto *label = ctx.Input<Tensor>("label"); auto *label = ctx.Input<Tensor>("label");
......
...@@ -25,6 +25,11 @@ class PadOp : public framework::OperatorWithKernel { ...@@ -25,6 +25,11 @@ class PadOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of PadOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of PadOp should not be null.");
auto x_dim = ctx.Input<Tensor>("X")->dims(); auto x_dim = ctx.Input<Tensor>("X")->dims();
auto paddings = Attr<std::vector<int>>("paddings"); auto paddings = Attr<std::vector<int>>("paddings");
PADDLE_ENFORCE_EQ(x_dim.size() * 2, int64_t(paddings.size()), PADDLE_ENFORCE_EQ(x_dim.size() * 2, int64_t(paddings.size()),
......
...@@ -28,7 +28,11 @@ class ReshapeOp : public framework::OperatorWithKernel { ...@@ -28,7 +28,11 @@ class ReshapeOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
// input check // input check
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), "Input(X) shouldn't be null"); PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of ReshapeOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of ReshapeOp should not be null.");
auto shape = ctx.Attr<std::vector<int>>("shape"); auto shape = ctx.Attr<std::vector<int>>("shape");
PADDLE_ENFORCE(shape.size() > 0, "Attr(shape) shouldn't be empty."); PADDLE_ENFORCE(shape.size() > 0, "Attr(shape) shouldn't be empty.");
for (auto dim : shape) { for (auto dim : shape) {
......
...@@ -25,6 +25,13 @@ class RowwiseAddOp : public framework::OperatorWithKernel { ...@@ -25,6 +25,13 @@ class RowwiseAddOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of RowwiseAddOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("b"),
"Input(b) of RowwiseAddOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of RowwiseAddOp should not be null.");
auto x_dims = ctx.Input<Tensor>("X")->dims(); auto x_dims = ctx.Input<Tensor>("X")->dims();
auto b_dims = ctx.Input<Tensor>("b")->dims(); auto b_dims = ctx.Input<Tensor>("b")->dims();
PADDLE_ENFORCE_GT( PADDLE_ENFORCE_GT(
......
...@@ -27,6 +27,11 @@ class ScaleOp : public framework::OperatorWithKernel { ...@@ -27,6 +27,11 @@ class ScaleOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of ScaleOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of ScaleOp should not be null.");
auto *in = ctx.Input<framework::Tensor>("X"); auto *in = ctx.Input<framework::Tensor>("X");
auto *out = ctx.Output<framework::LoDTensor>("Out"); auto *out = ctx.Output<framework::LoDTensor>("Out");
out->Resize(in->dims()); out->Resize(in->dims());
......
...@@ -24,6 +24,15 @@ class ScatterOp : public framework::OperatorWithKernel { ...@@ -24,6 +24,15 @@ class ScatterOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Ref"),
"Input(Ref) of ScatterOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Index"),
"Input(Index) of ScatterOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Updates"),
"Input(Updates) of ScatterOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of ScatterOp should not be null.");
PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Index")->dims().size(), 1, PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Index")->dims().size(), 1,
"Update Index should be 1-D."); "Update Index should be 1-D.");
PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Ref")->dims().size(), PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("Ref")->dims().size(),
......
...@@ -23,9 +23,12 @@ class SequenceAvgPoolOp : public framework::OperatorWithKernel { ...@@ -23,9 +23,12 @@ class SequenceAvgPoolOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext& ctx) const override { void InferShape(const framework::InferShapeContext& ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), PADDLE_ENFORCE_NOT_NULL(
"Input of SequenceAvgPoolOp" ctx.InputVar("X"), "Input(X) of SequenceAvgPoolOp should not be null.");
"must be initialized."); PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Out"),
"Output(Out) of SequenceAvgPoolOp should not be null.");
auto* x = ctx.Input<framework::LoDTensor>("X"); auto* x = ctx.Input<framework::LoDTensor>("X");
auto dims = x->dims(); auto dims = x->dims();
auto lod = x->lod(); auto lod = x->lod();
......
...@@ -23,6 +23,13 @@ class SGDOp : public framework::OperatorWithKernel { ...@@ -23,6 +23,13 @@ class SGDOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("param"),
"Input(param) of SGDOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("grad"),
"Input(grad) of SGDOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("param_out"),
"Output(param_out) of SGDOp should not be null.");
PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("param")->dims(), PADDLE_ENFORCE_EQ(ctx.Input<Tensor>("param")->dims(),
ctx.Input<Tensor>("grad")->dims(), ctx.Input<Tensor>("grad")->dims(),
"Two input of SGD Op's dimension must be same."); "Two input of SGD Op's dimension must be same.");
......
...@@ -23,6 +23,11 @@ class SigmoidOp : public framework::OperatorWithKernel { ...@@ -23,6 +23,11 @@ class SigmoidOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of SigmoidOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Y"),
"Output(Y) of SigmoidOp should not be null.");
ctx.Output<framework::LoDTensor>("Y")->Resize( ctx.Output<framework::LoDTensor>("Y")->Resize(
ctx.Input<Tensor>("X")->dims()); ctx.Input<Tensor>("X")->dims());
} }
......
...@@ -23,6 +23,11 @@ class SoftmaxOp : public framework::OperatorWithKernel { ...@@ -23,6 +23,11 @@ class SoftmaxOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input(X) of SoftmaxOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Y"),
"Output(Y) of SoftmaxOp should not be null.");
PADDLE_ENFORCE(ctx.Input<Tensor>("X")->dims().size() == 2UL, PADDLE_ENFORCE(ctx.Input<Tensor>("X")->dims().size() == 2UL,
"The input of softmax op must be a matrix."); "The input of softmax op must be a matrix.");
ctx.Output<framework::LoDTensor>("Y")->Resize( ctx.Output<framework::LoDTensor>("Y")->Resize(
......
...@@ -23,12 +23,18 @@ class SquaredL2DistanceOp : public framework::OperatorWithKernel { ...@@ -23,12 +23,18 @@ class SquaredL2DistanceOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext& ctx) const override { void InferShape(const framework::InferShapeContext& ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), PADDLE_ENFORCE_NOT_NULL(
"Input of SquaredL2DistanceOp " ctx.InputVar("X"),
"must be initialized."); "Input(X) of SquaredL2DistanceOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("Y"), PADDLE_ENFORCE_NOT_NULL(
"Target of SquaredL2DistanceOp " ctx.InputVar("Y"),
"must be initialized."); "Input(Y) of SquaredL2DistanceOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("sub_result"),
"Output(sub_result) of SquaredL2DistanceOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Out"),
"Output(Out) of SquaredL2DistanceOp should not be null.");
auto* x = ctx.Input<Tensor>("X"); auto* x = ctx.Input<Tensor>("X");
auto x_dims = x->dims(); auto x_dims = x->dims();
......
...@@ -22,6 +22,11 @@ class SumOp : public framework::OperatorWithKernel { ...@@ -22,6 +22,11 @@ class SumOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE(!ctx.MultiInputVar("X").empty(),
"Input(X) of SumOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of SumOp should not be null.");
auto ins = ctx.MultiInput<framework::Tensor>("X"); auto ins = ctx.MultiInput<framework::Tensor>("X");
auto *out = ctx.Output<framework::LoDTensor>("Out"); auto *out = ctx.Output<framework::LoDTensor>("Out");
int N = ins.size(); int N = ins.size();
......
...@@ -24,7 +24,12 @@ class TopkOp : public framework::OperatorWithKernel { ...@@ -24,7 +24,12 @@ class TopkOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext &ctx) const override { void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"), PADDLE_ENFORCE_NOT_NULL(ctx.InputVar("X"),
"Input of TopkOP must be initialized."); "Input(X) of TopkOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Out"),
"Output(Out) of TopkOp should not be null.");
PADDLE_ENFORCE_NOT_NULL(ctx.OutputVar("Indices"),
"Output(Indices) of TopkOp should not be null.");
auto *input = ctx.Input<framework::Tensor>("X"); auto *input = ctx.Input<framework::Tensor>("X");
const int k = static_cast<int>(ctx.Attr<int>("k")); const int k = static_cast<int>(ctx.Attr<int>("k"));
......
...@@ -48,6 +48,10 @@ class UniformRandomOp : public framework::OperatorWithKernel { ...@@ -48,6 +48,10 @@ class UniformRandomOp : public framework::OperatorWithKernel {
protected: protected:
void InferShape(const framework::InferShapeContext& ctx) const override { void InferShape(const framework::InferShapeContext& ctx) const override {
PADDLE_ENFORCE_NOT_NULL(
ctx.OutputVar("Out"),
"Output(Out) of UniformRandomOp should not be null.");
PADDLE_ENFORCE(Attr<float>("min") < Attr<float>("max"), PADDLE_ENFORCE(Attr<float>("min") < Attr<float>("max"),
"uniform_random's min must less then max"); "uniform_random's min must less then max");
auto* tensor = ctx.Output<framework::LoDTensor>("Out"); auto* tensor = ctx.Output<framework::LoDTensor>("Out");
......
...@@ -4,7 +4,7 @@ from paddle.v2.framework.op import Operator ...@@ -4,7 +4,7 @@ from paddle.v2.framework.op import Operator
import numpy import numpy
class GaussianRandomTest(unittest.TestCase): class TestGaussianRandomOp(unittest.TestCase):
def test_cpu(self): def test_cpu(self):
self.gaussian_random_test(place=core.CPUPlace()) self.gaussian_random_test(place=core.CPUPlace())
......
import unittest
import numpy as np
from op_test import OpTest
class TestIdentityOp(OpTest):
def setUp(self):
self.op_type = "identity"
self.inputs = {'X': np.random.random((10, 10)).astype("float32")}
self.outputs = {'Out': self.inputs['X']}
def test_check_output(self):
self.check_output()
def test_check_grad(self):
self.check_grad(['X'], 'Out')
if __name__ == "__main__":
unittest.main()
...@@ -3,7 +3,7 @@ import numpy as np ...@@ -3,7 +3,7 @@ import numpy as np
from op_test import OpTest from op_test import OpTest
class MinusOpTest(OpTest): class TestMinusOp(OpTest):
def setUp(self): def setUp(self):
self.op_type = "minus" self.op_type = "minus"
self.inputs = { self.inputs = {
......
...@@ -3,7 +3,7 @@ import numpy ...@@ -3,7 +3,7 @@ import numpy
from op_test import OpTest from op_test import OpTest
class TestCrossEntropy(OpTest): class TestOnehotCrossEntropyOp(OpTest):
def setUp(self): def setUp(self):
self.op_type = "onehot_cross_entropy" self.op_type = "onehot_cross_entropy"
batch_size = 30 batch_size = 30
......
...@@ -3,20 +3,7 @@ import numpy as np ...@@ -3,20 +3,7 @@ import numpy as np
from op_test import OpTest from op_test import OpTest
class IdentityTest(OpTest): class TestScaleOp(OpTest):
def setUp(self):
self.op_type = "identity"
self.inputs = {'X': np.random.random((10, 10)).astype("float32")}
self.outputs = {'Out': self.inputs['X']}
def test_check_output(self):
self.check_output()
def test_check_grad(self):
self.check_grad(['X'], 'Out')
class ScaleTest(OpTest):
def setUp(self): def setUp(self):
self.op_type = "scale" self.op_type = "scale"
self.inputs = {'X': np.random.random((10, 10)).astype("float32")} self.inputs = {'X': np.random.random((10, 10)).astype("float32")}
......
...@@ -3,7 +3,7 @@ import numpy as np ...@@ -3,7 +3,7 @@ import numpy as np
from op_test import OpTest from op_test import OpTest
class TestSGD(OpTest): class TestSGDOp(OpTest):
def setUp(self): def setUp(self):
self.op_type = "sgd" self.op_type = "sgd"
w = np.random.random((102, 105)).astype("float32") w = np.random.random((102, 105)).astype("float32")
......
...@@ -3,7 +3,7 @@ import numpy as np ...@@ -3,7 +3,7 @@ import numpy as np
from op_test import OpTest from op_test import OpTest
class TestSigmoid(OpTest): class TestSigmoidOp(OpTest):
def setUp(self): def setUp(self):
self.op_type = "sigmoid" self.op_type = "sigmoid"
self.inputs = { self.inputs = {
......
...@@ -21,6 +21,9 @@ class TestTopkOp(OpTest): ...@@ -21,6 +21,9 @@ class TestTopkOp(OpTest):
self.outputs = {'Out': output, 'Indices': indices} self.outputs = {'Out': output, 'Indices': indices}
def test_check_output(self):
self.check_output()
class TestTopkOp3d(OpTest): class TestTopkOp3d(OpTest):
def setUp(self): def setUp(self):
...@@ -42,6 +45,9 @@ class TestTopkOp3d(OpTest): ...@@ -42,6 +45,9 @@ class TestTopkOp3d(OpTest):
self.outputs = {'Out': output, 'Indices': indices} self.outputs = {'Out': output, 'Indices': indices}
def test_check_output(self):
self.check_output()
if __name__ == "__main__": if __name__ == "__main__":
unittest.main() unittest.main()
...@@ -4,7 +4,7 @@ import paddle.v2.framework.core as core ...@@ -4,7 +4,7 @@ import paddle.v2.framework.core as core
import numpy import numpy
class UniformRandomTest(unittest.TestCase): class TestUniformRandomOp(unittest.TestCase):
def test_uniform_random_cpu(self): def test_uniform_random_cpu(self):
self.uniform_random_test(place=core.CPUPlace()) self.uniform_random_test(place=core.CPUPlace())
......
Markdown is supported
0% .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑!
想要评论请 注册