Remove nnvm namespace for FInferShape, FInferType, and FInferStorageType

cjolivier01 · Jun 25, 2017 · 8aedf05 · 8aedf05
1 parent bcf9676
commit 8aedf05
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Showing 28 changed files with 168 additions and 128 deletions.
diff --git a/include/mxnet/op_attr_types.h b/include/mxnet/op_attr_types.h
@@ -71,6 +71,46 @@ using FComputeEx = std::function<void (const nnvm::NodeAttrs& attrs,
                                      const std::vector<NDArray>& inputs,
                                      const std::vector<OpReqType>& req,
                                      const std::vector<NDArray>& outputs)>;
+
+/*!
+ * \brief Inference function of certain type.
+ * \tparam AttrType The type of the attribute to be infered.
+ * \return whether all attributes are inferred.
+ */
+template<typename AttrType>
+using FInferNodeEntryAttr = std::function<bool (const NodeAttrs& attrs,
+                                                std::vector<AttrType> *in_attrs,
+                                                std::vector<AttrType> *out_attrs)>;
+/*!
+ * \brief Shape inference function.
+ *  Update the shapes given the input shape information.
+ *  TShape.ndim() == 0 means the shape is still unknown.
+ *
+ * \note Register under "FInferShape",
+ *  by default do not update any shapes.
+ *
+ *  FInferShape is needed by shape inference
+ */
+using FInferShape = FInferNodeEntryAttr<TShape>;
+
+/*!
+ * \brief Type inference function.
+ *  Update the type given the known type information.
+ *
+ * \note Register under "FInferType",
+ *  by default set all the output types to 0.
+ */
+using FInferType = FInferNodeEntryAttr<int>;
+
+/*!
+ * \brief Storage type inference function.
+ *  Update the type given the known type information.
+ *
+ * \note Register under "FInferStorageType",
+ *  by default set all the output types to 1.
+ */
+using FInferStorageType = FInferNodeEntryAttr<int>;
+
 }  // namespace mxnet
 
 #endif  // MXNET_OP_ATTR_TYPES_H_
diff --git a/src/c_api/c_api_ndarray.cc b/src/c_api/c_api_ndarray.cc
@@ -133,9 +133,9 @@ void SetShapeType(const nnvm::Op* op,
                   std::vector<NDArray>* p_ndoutputs,
                   int* dispatch_stype) {
   std::vector<NDArray>& ndoutputs = *p_ndoutputs;
-  static auto& infershape = nnvm::Op::GetAttr<nnvm::FInferShape>("FInferShape");
-  static auto& infertype = nnvm::Op::GetAttr<nnvm::FInferType>("FInferType");
-  static auto& inferstorage = nnvm::Op::GetAttr<nnvm::FInferStorageType>("FInferStorageType");
+  static auto& infershape = nnvm::Op::GetAttr<FInferShape>("FInferShape");
+  static auto& infertype = nnvm::Op::GetAttr<FInferType>("FInferType");
+  static auto& inferstorage = nnvm::Op::GetAttr<FInferStorageType>("FInferStorageType");
   MXAPIThreadLocalEntry *ret = MXAPIThreadLocalStore::Get();
   // infer shape
   std::vector<TShape>& in_shapes  = ret->arg_shapes;

diff --git a/src/executor/infer_graph_attr_pass.cc b/src/executor/infer_graph_attr_pass.cc
@@ -28,7 +28,7 @@ nnvm::Graph InferAttr(nnvm::Graph &&ret,
 
   const IndexedGraph& idx = ret.indexed_graph();
   static auto& finfer_shape =
-      Op::GetAttr<nnvm::FInferNodeEntryAttr<AttrType> >(infer_name);
+      Op::GetAttr<FInferNodeEntryAttr<AttrType> >(infer_name);
   static auto& is_backward =
       Op::GetAttr<nnvm::TIsBackward>("TIsBackward");
   // gradient function, used to get node correspondence.

diff --git a/src/io/image_io.cc b/src/io/image_io.cc
@@ -281,8 +281,8 @@ NNVM_REGISTER_OP(_cvimresize)
 .set_num_inputs(1)
 .set_num_outputs(1)
 .set_attr_parser(op::ParamParser<ResizeParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", ResizeShape)
-.set_attr<nnvm::FInferType>("FInferType", op::ElemwiseType<1, 1>)
+.set_attr<FInferShape>("FInferShape", ResizeShape)
+.set_attr<FInferType>("FInferType", op::ElemwiseType<1, 1>)
 .set_attr<FCompute>("FCompute<cpu>", Imresize)
 .add_argument("src", "NDArray", "source image")
 .add_arguments(ResizeParam::__FIELDS__());
@@ -292,8 +292,8 @@ NNVM_REGISTER_OP(_cvcopyMakeBorder)
 .set_num_inputs(1)
 .set_num_outputs(1)
 .set_attr_parser(op::ParamParser<MakeBorderParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", MakeBorderShape)
-.set_attr<nnvm::FInferType>("FInferType", op::ElemwiseType<1, 1>)
+.set_attr<FInferShape>("FInferShape", MakeBorderShape)
+.set_attr<FInferType>("FInferType", op::ElemwiseType<1, 1>)
 .set_attr<FCompute>("FCompute<cpu>", copyMakeBorder)
 .add_argument("src", "NDArray", "source image")
 .add_arguments(MakeBorderParam::__FIELDS__());

diff --git a/src/nnvm/legacy_op_util.cc b/src/nnvm/legacy_op_util.cc
@@ -323,8 +323,8 @@ void RegisterLegacyOpProp() {
     op.set_attr<nnvm::FListInputNames>("FListInputNames", OpPropListInputNames);
     op.set_attr<nnvm::FListOutputNames>("FListOutputNames", OpPropListOutputNames);
     op.set_attr<nnvm::FNumVisibleOutputs>("FNumVisibleOutputs", OpPropNumVisibleOutputs);
-    op.set_attr<nnvm::FInferShape>("FInferShape", OpPropInferShape);
-    op.set_attr<nnvm::FInferType>("FInferType", OpPropInferType);
+    op.set_attr<FInferShape>("FInferShape", OpPropInferShape);
+    op.set_attr<FInferType>("FInferType", OpPropInferType);
     op.set_attr<nnvm::FMutateInputs>("FMutateInputs", OpPropMutateInputs);
     op.set_attr<nnvm::FInplaceOption>("FInplaceOption", OpPropInplaceOption);
     op.set_attr<FResourceRequest>("FResourceRequest", OpPropResourceRequest);

diff --git a/src/operator/contrib/dequantize.cc b/src/operator/contrib/dequantize.cc
@@ -23,8 +23,8 @@ here `range(T) = numeric_limits<T>::max() - numeric_limits<T>::min()`
 .set_attr_parser(ParamParser<DequantizeParam>)
 .set_num_inputs(3)
 .set_num_outputs(1)
-.set_attr<nnvm::FInferShape>("FInferShape", DequantizeShape)
-.set_attr<nnvm::FInferType>("FInferType", DequantizeType)
+.set_attr<FInferShape>("FInferShape", DequantizeShape)
+.set_attr<FInferType>("FInferType", DequantizeType)
 .set_attr<FCompute>("FCompute<cpu>", DequantizeCompute<cpu>)
 .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseNone{"_dequantize"})
 .add_argument("input", "NDArray-or-Symbol", "A ndarray/symbol of type `uint8`")

diff --git a/src/operator/contrib/quantize.cc b/src/operator/contrib/quantize.cc
@@ -23,8 +23,8 @@ here `range(T) = numeric_limits<T>::max() - numeric_limits<T>::min()`
 .set_attr_parser(ParamParser<QuantizeParam>)
 .set_num_inputs(3)
 .set_num_outputs(3)
-.set_attr<nnvm::FInferShape>("FInferShape", QuantizeShape)
-.set_attr<nnvm::FInferType>("FInferType", QuantizeType)
+.set_attr<FInferShape>("FInferShape", QuantizeShape)
+.set_attr<FInferType>("FInferType", QuantizeType)
 .set_attr<FCompute>("FCompute<cpu>", QuantizeCompute<cpu>)
 .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseNone{"_quantize"})
 .add_argument("input", "NDArray-or-Symbol", "A ndarray/symbol of type `float32`")

diff --git a/src/operator/loss_binary_op.cc b/src/operator/loss_binary_op.cc
@@ -40,8 +40,8 @@ Example::
 )code" ADD_FILELINE)
 .set_num_inputs(2)
 .set_num_outputs(1)
-.set_attr<nnvm::FInferShape>("FInferShape", SoftmaxCrossEntropyShape)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<2, 1>)
+.set_attr<FInferShape>("FInferShape", SoftmaxCrossEntropyShape)
+.set_attr<FInferType>("FInferType", ElemwiseType<2, 1>)
 .set_attr<FResourceRequest>("FResourceRequest",
   [](const NodeAttrs& attrs) {
     return std::vector<ResourceRequest>{ResourceRequest::kTempSpace};

diff --git a/src/operator/nn/cast_storage.cc b/src/operator/nn/cast_storage.cc
@@ -19,9 +19,9 @@ NNVM_REGISTER_OP(cast_storage)
 .set_num_inputs(1)
 .set_num_outputs(1)
 .set_attr_parser(ParamParser<CastStorageParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<1, 1>)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>)
-.set_attr<nnvm::FInferStorageType>("FInferStorageType", CastStorageInferStorageType)
+.set_attr<FInferShape>("FInferShape", ElemwiseShape<1, 1>)
+.set_attr<FInferType>("FInferType", ElemwiseType<1, 1>)
+.set_attr<FInferStorageType>("FInferStorageType", CastStorageInferStorageType)
 .set_attr<FCompute>("FCompute<cpu>", IdentityCompute<cpu>)
 .set_attr<FComputeEx>("FComputeEx<cpu>", CastStorageComputeEx<cpu>)
 .add_argument("data", "NDArray-or-Symbol", "The input.")

diff --git a/src/operator/optimizer_op.cc b/src/operator/optimizer_op.cc
@@ -29,8 +29,8 @@ update is applied only to rows whose gradient has non-zero entries.
 .set_num_inputs(2)
 .set_num_outputs(1)
 .set_attr_parser(ParamParser<SGDParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<2, 1>)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<2, 1>)
+.set_attr<FInferShape>("FInferShape", ElemwiseShape<2, 1>)
+.set_attr<FInferType>("FInferType", ElemwiseType<2, 1>)
 .set_attr<FCompute>("FCompute<cpu>", SGDUpdate<cpu>)
 .set_attr<FComputeEx>("FComputeEx<cpu>", SGDUpdateEx<cpu>)
 .add_argument("weight", "NDArray-or-Symbol", "Weight")
@@ -63,8 +63,8 @@ only rows whose gradients contain non-zero entries are updated (for both weight
 .set_num_inputs(3)
 .set_num_outputs(1)
 .set_attr_parser(ParamParser<SGDMomParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<3, 1>)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<3, 1>)
+.set_attr<FInferShape>("FInferShape", ElemwiseShape<3, 1>)
+.set_attr<FInferType>("FInferType", ElemwiseType<3, 1>)
 .set_attr<nnvm::FMutateInputs>("FMutateInputs",
   [](const nnvm::NodeAttrs& attrs) {
     return std::vector<uint32_t>{2};
@@ -100,8 +100,8 @@ It updates the weights using::
 .set_num_inputs(4)
 .set_num_outputs(1)
 .set_attr_parser(ParamParser<AdamParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<4, 1>)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<4, 1>)
+.set_attr<FInferShape>("FInferShape", ElemwiseShape<4, 1>)
+.set_attr<FInferType>("FInferType", ElemwiseType<4, 1>)
 .set_attr<nnvm::FMutateInputs>("FMutateInputs",
   [](const nnvm::NodeAttrs& attrs) {
     return std::vector<uint32_t>{2, 3};
@@ -152,8 +152,8 @@ Hinton suggests the momentum term :math:`\gamma` to be 0.9 and the learning rate
 .set_num_inputs(3)
 .set_num_outputs(1)
 .set_attr_parser(ParamParser<RMSPropParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<3, 1>)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<3, 1>)
+.set_attr<FInferShape>("FInferShape", ElemwiseShape<3, 1>)
+.set_attr<FInferType>("FInferType", ElemwiseType<3, 1>)
 .set_attr<nnvm::FMutateInputs>("FMutateInputs",
   [](const nnvm::NodeAttrs &attrs) {
     return std::vector<uint32_t>{2};
@@ -191,8 +191,8 @@ to be 0.9 and the learning rate :math:`\eta` to be 0.0001.
 .set_num_inputs(5)
 .set_num_outputs(1)
 .set_attr_parser(ParamParser<RMSPropAlexParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<5, 1>)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<5, 1>)
+.set_attr<FInferShape>("FInferShape", ElemwiseShape<5, 1>)
+.set_attr<FInferType>("FInferType", ElemwiseType<5, 1>)
 .set_attr<nnvm::FMutateInputs>("FMutateInputs",
   [](const nnvm::NodeAttrs& attrs) {
     return std::vector<uint32_t>{2, 3, 4};

diff --git a/src/operator/random/multisample_op.cc b/src/operator/random/multisample_op.cc
@@ -131,8 +131,8 @@ DMLC_REGISTER_PARAMETER(MultiSampleParam);
     [](const NodeAttrs& attrs) { \
       std::vector<std::string> v = {input_name_1, input_name_2}; v.resize(num_inputs); return v; \
     }) \
-  .set_attr<nnvm::FInferShape>("FInferShape", MultiSampleOpShape) \
-  .set_attr<nnvm::FInferType>("FInferType", MultiSampleOpType) \
+  .set_attr<FInferShape>("FInferShape", MultiSampleOpShape) \
+  .set_attr<FInferType>("FInferType", MultiSampleOpType) \
   .set_attr<FResourceRequest>("FResourceRequest", [](const NodeAttrs& attrs) { \
       return std::vector<ResourceRequest>(1, ResourceRequest::kRandom); \
     }) \

diff --git a/src/operator/random/sample_multinomial_op.cc b/src/operator/random/sample_multinomial_op.cc
@@ -47,8 +47,8 @@ Examples::
     return param.get_prob ? 2U : 1U;
   })
 .set_attr_parser(ParamParser<SampleMultinomialParam>)
-.set_attr<nnvm::FInferShape>("FInferShape", SampleMultinomialOpShape)
-.set_attr<nnvm::FInferType>("FInferType", SampleMultinomialOpType)
+.set_attr<FInferShape>("FInferShape", SampleMultinomialOpShape)
+.set_attr<FInferType>("FInferType", SampleMultinomialOpType)
 .set_attr<FResourceRequest>("FResourceRequest",
   [](const nnvm::NodeAttrs& attrs) {
       return std::vector<ResourceRequest>{

diff --git a/src/operator/random/sample_op.cc b/src/operator/random/sample_op.cc
@@ -21,8 +21,8 @@ DMLC_REGISTER_PARAMETER(SampleGenNegBinomialParam);
   .set_num_inputs(0)                                                    \
   .set_num_outputs(1)                                                   \
   .set_attr_parser(ParamParser<ParamType>)                              \
-  .set_attr<nnvm::FInferShape>("FInferShape", InitShape<ParamType>)     \
-  .set_attr<nnvm::FInferType>("FInferType", SampleOpType<ParamType>)    \
+  .set_attr<FInferShape>("FInferShape", InitShape<ParamType>)     \
+  .set_attr<FInferType>("FInferType", SampleOpType<ParamType>)    \
   .set_attr<FResourceRequest>("FResourceRequest", SampleResource)       \
   .add_arguments(ParamType::__FIELDS__())
 

diff --git a/src/operator/tensor/broadcast_reduce_op.h b/src/operator/tensor/broadcast_reduce_op.h
@@ -663,8 +663,8 @@ void PickOpBackward(const nnvm::NodeAttrs& attrs,
   .set_num_inputs(1)                                            \
   .set_num_outputs(1)                                           \
   .set_attr_parser(ParamParser<ReduceAxisParam>)                \
-  .set_attr<nnvm::FInferShape>("FInferShape", ReduceAxisShape)  \
-  .set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>) \
+  .set_attr<FInferShape>("FInferShape", ReduceAxisShape)  \
+  .set_attr<FInferType>("FInferType", ElemwiseType<1, 1>) \
   .add_argument("data", "NDArray-or-Symbol", "The input")       \
   .add_arguments(ReduceAxisParam::__FIELDS__())
 
@@ -673,8 +673,8 @@ void PickOpBackward(const nnvm::NodeAttrs& attrs,
   .set_num_inputs(1)                                            \
   .set_num_outputs(1)                                           \
   .set_attr_parser(AxesParamParser<ReduceAxesParam>)            \
-  .set_attr<nnvm::FInferShape>("FInferShape", ReduceAxesShape)  \
-  .set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>) \
+  .set_attr<FInferShape>("FInferShape", ReduceAxesShape)  \
+  .set_attr<FInferType>("FInferType", ElemwiseType<1, 1>) \
   .add_argument("data", "NDArray-or-Symbol", "The input")       \
   .add_arguments(ReduceAxesParam::__FIELDS__())
 
@@ -688,7 +688,7 @@ void PickOpBackward(const nnvm::NodeAttrs& attrs,
   NNVM_REGISTER_OP(name)                                        \
   .set_num_inputs(1)                                            \
   .set_num_outputs(1)                                           \
-  .set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>) \
+  .set_attr<FInferType>("FInferType", ElemwiseType<1, 1>) \
   .set_attr<nnvm::FGradient>("FGradient",                       \
     [](const nnvm::NodePtr& n,                                  \
        const std::vector<nnvm::NodeEntry>& ograds) {            \

diff --git a/src/operator/tensor/broadcast_reduce_op_index.cc b/src/operator/tensor/broadcast_reduce_op_index.cc
@@ -84,8 +84,8 @@ Examples::
     param.keepdims = false;
     attrs->parsed = param;
   })
-.set_attr<nnvm::FInferShape>("FInferShape", ReduceAxisShape)
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>)
+.set_attr<FInferShape>("FInferShape", ReduceAxisShape)
+.set_attr<FInferType>("FInferType", ElemwiseType<1, 1>)
 .set_attr<FCompute>("FCompute<cpu>", SearchAxisCompute<cpu, mshadow::red::maximum>)
 .add_argument("data", "NDArray-or-Symbol", "The input array");
 
@@ -131,8 +131,8 @@ Examples::
   [](const NodeAttrs& attrs) {
     return std::vector<std::string>{"data", "index"};
   })
-.set_attr<nnvm::FInferShape>("FInferShape", PickOpShape)
-.set_attr<nnvm::FInferType>("FInferType", PickOpType)
+.set_attr<FInferShape>("FInferShape", PickOpShape)
+.set_attr<FInferType>("FInferType", PickOpType)
 .set_attr<FCompute>("FCompute<cpu>", PickOpForward<cpu>)
 .set_attr<nnvm::FGradient>("FGradient",
   [](const nnvm::NodePtr& n, const std::vector<nnvm::NodeEntry>& ograds) {

diff --git a/src/operator/tensor/broadcast_reduce_op_value.cc b/src/operator/tensor/broadcast_reduce_op_value.cc
@@ -168,7 +168,7 @@ Example::
 )code" ADD_FILELINE)
 .set_attr_parser(ParamParser<BroadcastAxesParam>)
 .add_arguments(BroadcastAxesParam::__FIELDS__())
-.set_attr<nnvm::FInferShape>("FInferShape", BroadcastAxesShape)
+.set_attr<FInferShape>("FInferShape", BroadcastAxesShape)
 .set_attr<FCompute>("FCompute<cpu>", BroadcastCompute<cpu>);
 
 MXNET_OPERATOR_REGISTER_BROADCAST(broadcast_to)
@@ -192,7 +192,7 @@ So with `shape=(2,0)`, we will obtain the same result as in the above example.
 )code" ADD_FILELINE)
 .set_attr_parser(ParamParser<BroadcastToParam>)
 .add_arguments(BroadcastToParam::__FIELDS__())
-.set_attr<nnvm::FInferShape>("FInferShape", BroadcastToShape)
+.set_attr<FInferShape>("FInferShape", BroadcastToShape)
 .set_attr<FCompute>("FCompute<cpu>", BroadcastCompute<cpu>);
 
 // backward op for broadcast.
@@ -218,7 +218,7 @@ Examples::
 )code" ADD_FILELINE)
 .set_num_inputs(1)
 .set_num_outputs(1)
-.set_attr<nnvm::FInferShape>("FInferShape",
+.set_attr<FInferShape>("FInferShape",
   [](const nnvm::NodeAttrs& attrs,
      std::vector<TShape> *in_attrs,
      std::vector<TShape> *out_attrs) {
@@ -228,7 +228,7 @@ Examples::
     SHAPE_ASSIGN_CHECK(*out_attrs, 0, mshadow::Shape1(1));
     return true;
   })
-.set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>)
+.set_attr<FInferType>("FInferType", ElemwiseType<1, 1>)
 .set_attr<FCompute>("FCompute<cpu>", L2NormCompute<cpu>)
 .add_argument("data", "NDArray-or-Symbol", "Source input");
 

diff --git a/src/operator/tensor/control_flow_op.cc b/src/operator/tensor/control_flow_op.cc
@@ -25,8 +25,8 @@ NNVM_REGISTER_OP(where)
   [](const NodeAttrs& attrs) {
     return std::vector<std::string>{"condition", "x", "y"};
   })
-.set_attr<nnvm::FInferShape>("FInferShape", WhereOpShape)
-.set_attr<nnvm::FInferType>("FInferType", WhereOpType)
+.set_attr<FInferShape>("FInferShape", WhereOpShape)
+.set_attr<FInferType>("FInferType", WhereOpType)
 .set_attr<FCompute>("FCompute<cpu>", WhereOpForward<cpu>)
 .set_attr<nnvm::FGradient>("FGradient",
   // Use the following lambda function instead of ElemwiseGradUseIn

diff --git a/src/operator/tensor/elemwise_binary_broadcast_op.h b/src/operator/tensor/elemwise_binary_broadcast_op.h
@@ -227,8 +227,8 @@ void BinaryBroadcastBackwardUseIn(const nnvm::NodeAttrs& attrs,
     [](const NodeAttrs& attrs) {                                      \
       return std::vector<std::string>{"lhs", "rhs"};                  \
     })                                                                \
-  .set_attr<nnvm::FInferShape>("FInferShape", BinaryBroadcastShape)   \
-  .set_attr<nnvm::FInferType>("FInferType", ElemwiseType<2, 1>)       \
+  .set_attr<FInferShape>("FInferShape", BinaryBroadcastShape)   \
+  .set_attr<FInferType>("FInferType", ElemwiseType<2, 1>)       \
   .set_attr<nnvm::FInplaceOption>("FInplaceOption",                   \
     [](const NodeAttrs& attrs){                                       \
       return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};       \

diff --git a/src/operator/tensor/elemwise_binary_op.h b/src/operator/tensor/elemwise_binary_op.h
@@ -361,8 +361,8 @@ void BinaryBackwardUseInWithHalf2(const nnvm::NodeAttrs& attrs,
     [](const NodeAttrs& attrs) {                                    \
       return std::vector<std::string>{"lhs", "rhs"};                \
     })                                                              \
-  .set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<2, 1>)  \
-  .set_attr<nnvm::FInferType>("FInferType", ElemwiseType<2, 1>)     \
+  .set_attr<FInferShape>("FInferShape", ElemwiseShape<2, 1>)  \
+  .set_attr<FInferType>("FInferType", ElemwiseType<2, 1>)     \
   .set_attr<nnvm::FInplaceOption>("FInplaceOption",                 \
     [](const NodeAttrs& attrs){                                     \
       return std::vector<std::pair<int, int> >{{0, 0}, {1, 0}};     \

diff --git a/src/operator/tensor/elemwise_binary_op_basic.cc b/src/operator/tensor/elemwise_binary_op_basic.cc
@@ -14,7 +14,7 @@ MXNET_OPERATOR_REGISTER_BINARY(elemwise_add)
 .set_attr<FCompute>("FCompute<cpu>", BinaryCompute<cpu, mshadow::op::plus>)
 .set_attr<FComputeEx>("FComputeEx<cpu>", BinaryComputeEx<cpu, mshadow::op::plus>)
 .set_attr<nnvm::FGradient>("FGradient", ElemwiseGradUseNone{"_backward_add"})
-.set_attr<nnvm::FInferStorageType>("FInferStorageType", ElemwiseStorageType<2, 1>);
+.set_attr<FInferStorageType>("FInferStorageType", ElemwiseStorageType<2, 1>);
 
 // specialized gradient add function to do add to optimization
 // this must differ from elemwise_add to prevent add to optimization in forward pass.
@@ -33,7 +33,7 @@ NNVM_REGISTER_OP(_backward_add)
                                                                 mshadow_op::identity>)
 .set_attr<FComputeEx>("FComputeEx<cpu>",
                       BinaryBackwardUseNoneEx<cpu, mshadow_op::identity, mshadow_op::identity>)
-.set_attr<nnvm::FInferStorageType>("FInferStorageType", ElemwiseStorageType<1, 2>);
+.set_attr<FInferStorageType>("FInferStorageType", ElemwiseStorageType<1, 2>);
 
 MXNET_OPERATOR_REGISTER_BINARY(_sub)
 .add_alias("_minus").add_alias("_Minus")

diff --git a/src/operator/tensor/elemwise_binary_scalar_op.h b/src/operator/tensor/elemwise_binary_scalar_op.h
@@ -56,8 +56,8 @@ void BinaryScalarBackward(const nnvm::NodeAttrs& attrs,
   .set_attr_parser([](NodeAttrs* attrs) {                           \
       attrs->parsed = std::stod(attrs->dict["scalar"]);             \
     })                                                              \
-  .set_attr<nnvm::FInferShape>("FInferShape", ElemwiseShape<1, 1>)  \
-  .set_attr<nnvm::FInferType>("FInferType", ElemwiseType<1, 1>)     \
+  .set_attr<FInferShape>("FInferShape", ElemwiseShape<1, 1>)  \
+  .set_attr<FInferType>("FInferType", ElemwiseType<1, 1>)     \
   .set_attr<nnvm::FInplaceOption>("FInplaceOption",                 \
     [](const NodeAttrs& attrs){                                     \
       return std::vector<std::pair<int, int> >{{0, 0}};             \