[PASS] Add gradient pass (#28)

Author: tqchen

nnvm/example/src/operator.cc

@@ -15,6 +15,10 @@ using nnvm::FMutateInputs;
 using nnvm::FInferShape;
 using nnvm::FInferType;
 using nnvm::FInplaceOption;
+using nnvm::Node;
+using nnvm::NodePtr;
+using nnvm::NodeEntry;
+using nnvm::FGradient;
 using nnvm::NodeAttrs;
 using nnvm::TShape;
 using nnvm::array_view;
@@ -37,6 +41,17 @@ inline std::vector<std::pair<int, int> > InplaceIn0Out0(const NodeAttrs& attrs)
   return {{0, 0}};
 }
 
+// quick helper to make node
+inline NodeEntry MakeNode(const char* op_name,
+                          std::string node_name,
+                          std::vector<NodeEntry> inputs) {
+  NodePtr p = Node::Create();
+  p->op = nnvm::Op::Get(op_name);
+  p->attrs.name = std::move(node_name);
+  p->inputs = std::move(inputs);
+  return NodeEntry{p, 0, 0};
+}
+
 // simple demonstration of reshape.
 NNVM_REGISTER_OP(reshape)
 .describe("reshape source to target shape")
@@ -84,21 +99,67 @@ NNVM_REGISTER_OP(cast)
       return true;
     });
 
+NNVM_REGISTER_OP(exp)
+.describe("take exponential")
+.set_num_inputs(1)
+.attr<FInferShape>("FInferShape", SameShape)
+.attr<FGradient>(
+    "FGradient", [](const NodePtr& n,
+                    const std::vector<NodeEntry>& ograds) {
+      return std::vector<NodeEntry>{
+        MakeNode("mul", n->attrs.name + "_grad",
+                 {ograds[0], NodeEntry{n, 0, 0}})
+      };
+    });
+
+NNVM_REGISTER_OP(identity)
+.describe("identity function")
+.set_num_inputs(1)
+.attr<FInferShape>("FInferShape", SameShape)
+.attr<FGradient>(
+    "FGradient", [](const NodePtr& n,
+                    const std::vector<NodeEntry>& ograds) {
+      return std::vector<NodeEntry>{ograds[0]};
+    });
 
 NNVM_REGISTER_OP(add)
 .describe("add two data together")
 .set_num_inputs(2)
 .attr<FInferShape>("FInferShape", SameShape)
-.attr<FInplaceOption>("FInplaceOption", InplaceIn0Out0);
+.attr<FInplaceOption>("FInplaceOption", InplaceIn0Out0)
+.attr<FGradient>(
+    "FGradient", [](const NodePtr& n,
+                    const std::vector<NodeEntry>& ograds){
+      return std::vector<NodeEntry>{ograds[0], ograds[0]};
+    });
 
-NNVM_REGISTER_OP(__add_symbol__)
-.describe("Alias of add")
-.set_num_inputs(2);
+NNVM_REGISTER_OP(mul)
+.describe("multiply two data together")
+.set_num_inputs(2)
+.attr<FInferShape>("FInferShape", SameShape)
+.attr<FInplaceOption>("FInplaceOption", InplaceIn0Out0)
+.attr<FGradient>(
+    "FGradient", [](const NodePtr& n,
+                    const std::vector<NodeEntry>& ograds){
+      return std::vector<NodeEntry>{
+        MakeNode("mul", n->attrs.name + "_grad_0",
+                 {ograds[0], n->inputs[1]}),
+        MakeNode("mul", n->attrs.name + "_grad_1",
+                 {ograds[0], n->inputs[0]})
+      };
+    });
 
-NNVM_REGISTER_OP(exp)
-.describe("take exponential")
-.set_num_inputs(1)
-.attr<FInferShape>("FInferShape", SameShape);
+NNVM_REGISTER_OP(__ewise_sum__)
+.describe("elementwise sum")
+.set_num_inputs(nnvm::kVarg);
+
+NNVM_REGISTER_OP(__zero__)
+.describe("set output to zero")
+.set_num_inputs(0);
+
+NNVM_REGISTER_OP(__one__)
+.describe("set output to one")
+.set_num_inputs(0);
 
 NNVM_REGISTER_OP(cross_device_copy)
 .describe("Copy data across device.")

nnvm/include/dmlc/base.h

@@ -58,6 +58,11 @@
                         __cplusplus >= 201103L || defined(_MSC_VER))
 #endif
 
+/*! \brief strict CXX11 support */
+#ifndef DMLC_STRICT_CXX11
+#define DMLC_STRICT_CXX11 (__cplusplus >= 201103L || defined(_MSC_VER))
+#endif
+
 /// check if g++ is before 4.6
 #if DMLC_USE_CXX11 && defined(__GNUC__) && !defined(__clang_version__)
 #if __GNUC__ == 4 && __GNUC_MINOR__ < 6
@@ -69,6 +74,7 @@
 #endif
 #endif
 
+
 /*!
  * \brief Enable std::thread related modules,
  *  Used to disable some module in mingw compile.
@@ -82,6 +88,13 @@
 #define DMLC_USE_REGEX (__cplusplus >= 201103L || defined(_MSC_VER))
 #endif
 
+/*! \brief helper macro to supress unused warning */
+#if defined(__GNUC__)
+#define DMLC_ATTRIBUTE_UNUSED __attribute__((unused))
+#else
+#define DMLC_ATTRIBUTE_UNUSED
+#endif
+
 /*! \brief helper macro to generate string concat */
 #define DMLC_STR_CONCAT_(__x, __y) __x##__y
 #define DMLC_STR_CONCAT(__x, __y) DMLC_STR_CONCAT_(__x, __y)

nnvm/include/dmlc/json.h

@@ -25,7 +25,9 @@
 #include <typeindex>
 #include <typeinfo>
 #include <unordered_map>
+#if DMLC_STRICT_CXX11
 #include "./any.h"
+#endif  // DMLC_STRICT_CXX11
 #endif  // DMLC_USE_CXX11
 
 namespace dmlc {
@@ -320,7 +322,8 @@ class JSONObjectReadHelper {
 };
 
 #define DMLC_JSON_ENABLE_ANY_VAR_DEF(KeyName)                  \
-  static ::dmlc::json::AnyJSONManager&  __make_AnyJSONType ## _ ## KeyName ## __
+  static DMLC_ATTRIBUTE_UNUSED ::dmlc::json::AnyJSONManager&   \
+  __make_AnyJSONType ## _ ## KeyName ## __
 
 /*!
  * \def DMLC_JSON_ENABLE_ANY
@@ -475,7 +478,7 @@ struct Handler {
   }
 };
 
-#if DMLC_USE_CXX11
+#if DMLC_STRICT_CXX11
 // Manager to store json serialization strategy.
 class AnyJSONManager {
  public:
@@ -561,7 +564,7 @@ struct Handler<any> {
     CHECK(!reader->NextArrayItem()) << "invalid any json format";
   }
 };
-#endif  // DMLC_USE_CXX11
+#endif  // DMLC_STRICT_CXX11
 
 }  // namespace json
 

nnvm/include/dmlc/parameter.h

@@ -251,7 +251,8 @@ struct Parameter {
     static ::dmlc::parameter::ParamManagerSingleton<PType> inst(#PType); \
     return &inst.manager;                                               \
   }                                                                     \
-  static ::dmlc::parameter::ParamManager &__make__ ## PType ## ParamManager__ = \
+  static DMLC_ATTRIBUTE_UNUSED ::dmlc::parameter::ParamManager&         \
+  __make__ ## PType ## ParamManager__ =                                 \
       (*PType::__MANAGER__())                                           \
 
 //! \endcond

nnvm/include/dmlc/registry.h

@@ -216,7 +216,7 @@ class FunctionRegEntryBase {
  * \sa FactoryRegistryEntryBase
  */
 #define DMLC_REGISTRY_REGISTER(EntryType, EntryTypeName, Name)          \
-  static EntryType & __make_ ## EntryTypeName ## _ ## Name ## __ =      \
+  static DMLC_ATTRIBUTE_UNUSED EntryType & __make_ ## EntryTypeName ## _ ## Name ## __ = \
       ::dmlc::Registry<EntryType>::Get()->__REGISTER__(#Name)           \
 
 /*!
@@ -272,6 +272,7 @@ class FunctionRegEntryBase {
  */
 #define DMLC_REGISTRY_LINK_TAG(UniqueTag)                                \
   int __dmlc_registry_file_tag_ ## UniqueTag ## __();                   \
-  static int __reg_file_tag_ ## UniqueTag ## __ = __dmlc_registry_file_tag_ ## UniqueTag ## __();
+  static int DMLC_ATTRIBUTE_UNUSED __reg_file_tag_ ## UniqueTag ## __ = \
+      __dmlc_registry_file_tag_ ## UniqueTag ## __();
 }  // namespace dmlc
 #endif  // DMLC_REGISTRY_H_

nnvm/include/nnvm/c_api.h

@@ -260,6 +260,7 @@ NNVM_DLL int NNGraphFree(GraphHandle handle);
  * \return 0 when success, -1 when failure happens
  */
 NNVM_DLL int NNGraphGetSymbol(GraphHandle graph, SymbolHandle *symbol);
+
 /*!
  * \brief Get Set a attribute in json format.
  * This feature allows pass graph attributes back and forth in reasonable speed.
@@ -273,6 +274,7 @@ NNVM_DLL int NNGraphGetSymbol(GraphHandle graph, SymbolHandle *symbol);
 NNVM_DLL int NNGraphSetJSONAttr(GraphHandle handle,
                                 const char* key,
                                 const char* json_value);
+
 /*!
  * \brief Get a serialized attrirbute from graph.
  * This feature allows pass graph attributes back and forth in reasonable speed.
@@ -289,6 +291,21 @@ NNVM_DLL int NNGraphGetJSONAttr(SymbolHandle handle,
                                 const char* key,
                                 const char** json_out,
                                 int *success);
+
+/*!
+ * \brief Set a attribute whose type is std::vector<NodeEntry> in c++
+ * This feature allows pass List of symbolic variables for gradient request.
+ *
+ * \note This is beta feature only used for test purpos
+ *
+ * \param handle The graph handle.
+ * \param key The key to the attribute.
+ * \param list The symbol whose outputs represents the list of NodeEntry to be passed.
+ * \return 0 when success, -1 when failure happens
+ */
+NNVM_DLL int NNGraphSetNodeEntryListAttr_(GraphHandle handle,
+                                          const char* key,
+                                          SymbolHandle list);
 /*!
  * \brief Apply pass on the src graph.
  * \param src The source graph handle.

nnvm/include/nnvm/op.h

@@ -279,10 +279,8 @@ class OpMap {
 };
 
 // internal macros to make
-#define NNVM_STR_CONCAT_(__x, __y) __x##__y
-#define NNVM_STR_CONCAT(__x, __y) NNVM_STR_CONCAT_(__x, __y)
 #define NNVM_REGISTER_VAR_DEF(OpName)                              \
-  static ::nnvm::Op & __make_ ## NnvmOp ## _ ## OpName
+  static DMLC_ATTRIBUTE_UNUSED ::nnvm::Op & __make_ ## NnvmOp ## _ ## OpName
 
 /*!
  * \def NNVM_REGISTER_OP
@@ -300,7 +298,7 @@ class OpMap {
  * \endcode
  */
 #define NNVM_REGISTER_OP(OpName)                                     \
-  NNVM_STR_CONCAT(NNVM_REGISTER_VAR_DEF(OpName), __COUNTER__) =   \
+  DMLC_STR_CONCAT(NNVM_REGISTER_VAR_DEF(OpName), __COUNTER__) =         \
       ::dmlc::Registry<::nnvm::Op>::Get()->__REGISTER_OR_GET__(#OpName)
 
 // implementations of template functions after this.

nnvm/include/nnvm/op_attr_types.h

@@ -11,6 +11,7 @@
 #include <utility>
 #include <functional>
 #include "./base.h"
+#include "./node.h"
 #include "./tuple.h"
 
 namespace nnvm {
@@ -107,6 +108,19 @@ using TIsBackwardOp = bool;
 using FInplaceOption = std::function<
   std::vector<std::pair<int, int> > (const NodeAttrs& attrs)>;
 
+/*!
+ * \brief Get the gradient node of the op node
+ *  This function generates the backward graph of the node
+ * \param nodeptr The node to take gradient
+ * \param out_grads Gradient of current node's outputs
+ * \return gradients of the inputs
+ *
+ * \note Register under "FGradient"
+ */
+using FGradient = std::function<std::vector<NodeEntry>(
+    const NodePtr& nodeptr,
+    const std::vector<NodeEntry>& out_grads)>;
+
 }  // namespace nnvm
 
 #endif  // NNVM_OP_ATTR_TYPES_H_

nnvm/include/nnvm/pass_functions.h

@@ -109,6 +109,37 @@ inline Graph PlaceDevice(Graph graph,
   return ApplyPass(std::move(graph), {"PlaceDevice"});
 }
 
+/*!
+ * \brief Get the gradient graph whose outputs are gradients of xs wrt to ys.
+ * \param graph source graph
+ * \param ys The entries we want to take gradient from.
+ * \param xs The input to take gradient with respect to.
+ * \param ys_out_grad The symbol for additional gradient to be propagate back to y.
+ * \param aggregate_fun aggregation function applied to aggregate the inputs
+ * \param mirror_fun Optional mirror function to do mirror optimization and save memory.
+ * \return A new graph, whose outputs corresponds to inputs of xs.
+ */
+inline Graph Gradient(
+    Graph graph,
+    std::vector<NodeEntry> ys,
+    std::vector<NodeEntry> xs,
+    std::vector<NodeEntry> ys_out_grad,
+    std::function<NodeEntry(std::vector<NodeEntry>&& inputs)> aggregate_fun = nullptr,
+    std::function<int(const Node& node)> mirror_fun = nullptr) {
+  graph.attrs["grad_ys"] = std::make_shared<any>(std::move(ys));
+
+  graph.attrs["grad_xs"] = std::make_shared<any>(std::move(xs));
+  graph.attrs["grad_ys_out_grad"] = std::make_shared<any>(std::move(ys_out_grad));
+  if (aggregate_fun != nullptr) {
+    graph.attrs["grad_aggregate_fun"] = std::make_shared<any>(aggregate_fun);
+  }
+  if (mirror_fun != nullptr) {
+    graph.attrs["grad_mirror_fun"] = std::make_shared<any>(mirror_fun);
+  }
+
+  return ApplyPass(std::move(graph), {"Gradient"});
+}
+
 }  // namespace pass
 }  // namespace nnvm
 #endif  // NNVM_PASS_FUNCTIONS_H_

nnvm/python/nnvm/graph.py

@@ -10,7 +10,7 @@
 from ._base import c_array, c_str, nn_uint, py_str, string_types
 from ._base import GraphHandle, SymbolHandle
 from ._base import check_call
-from .symbol import Symbol
+from .symbol import Symbol, Group as _Group
 
 
 class Graph(object):
@@ -56,8 +56,27 @@ def json_attr(self, key):
         else:
             return None
 
+    def _set_symbol_list_attr(self, key, value):
+        """Set the attribute of the graph.
+
+        Parameters
+        ----------
+        key : string
+            The key of the attribute
+        value : value
+            The any type that can be dumped to json
+        type_name : string
+            The typename registered on c++ side.
+        """
+        if isinstance(value, list):
+            value = _Group(value)
+        if not isinstance(value, Symbol):
+            raise ValueError("value need to be grouped symbol")
+        check_call(_LIB.NNGraphSetNodeEntryListAttr_(
+            self.handle, c_str(key), value.handle))
+
     def _set_json_attr(self, key, value, type_name=None):
-        """Set the attribute of the symbol.
+        """Set the attribute of the graph.
 
         Parameters
         ----------