Improve createOpState for custom ops

example/extensions/lib_custom_op/gemm_lib.cc

@@ -204,6 +204,9 @@ class MyStatefulGemm : public CustomStatefulOp {
 };
 
 MXReturnValue createOpState(const std::unordered_map<std::string, std::string>& attrs,
+                            const MXContext& ctx,
+                            const std::vector<std::vector<unsigned int> >& in_shapes,
+                            const std::vector<int> in_types,
                             CustomStatefulOp** op_inst) {
   // testing passing of keyword arguments
   int count = attrs.count("test_kw") > 0 ? std::stoi(attrs.at("test_kw")) : 0;

example/extensions/lib_custom_op/relu_lib.cc

@@ -116,12 +116,18 @@ MXReturnValue MyStatefulReluGPU::Backward(std::vector<MXTensor>* inputs,
 
 
 MXReturnValue createOpStateCPU(const std::unordered_map<std::string, std::string>& attrs,
+                               const MXContext& ctx,
+                               const std::vector<std::vector<unsigned int> >& in_shapes,
+                               const std::vector<int> in_types,
                                CustomStatefulOp** op_inst) {
   *op_inst = new MyStatefulReluCPU(attrs);
   return MX_SUCCESS;
 }
 
 MXReturnValue createOpStateGPU(const std::unordered_map<std::string, std::string>& attrs,
+                               const MXContext& ctx,
+                               const std::vector<std::vector<unsigned int> >& in_shapes,
+                               const std::vector<int> in_types,
                                CustomStatefulOp** op_inst) {
   *op_inst = new MyStatefulReluGPU(attrs);
   return MX_SUCCESS;

example/extensions/lib_custom_op/test_gemm.py

@@ -47,36 +47,59 @@
 t = mx.sym.Variable('t')
 c = mx.sym.my_gemm(s,t)
 d = mx.sym.state_gemm(s,t,test_kw=200)
+e = mx.sym.linalg.gemm2(s,t)
 
-in_grad = [mx.nd.empty((2,3)),mx.nd.empty((3,1))]
-in_grad2 = [mx.nd.empty((2,3)),mx.nd.empty((3,1))]
-
-exe = c.bind(ctx=mx.cpu(),args={'s':a,'t':b},args_grad=in_grad)
-exe2 = d.bind(ctx=mx.cpu(),args={'s':a,'t':b},args_grad=in_grad2)
+out_grad = mx.nd.ones((2,1))
 
-out = exe.forward()
-print(out)
-print("-------")
+# stateless
+block = mx.gluon.nn.SymbolBlock(c,[s,t])
+with mx.autograd.record():
+    a_ = mx.nd.array([[1,2,3],[4,5,6]])
+    b_ = mx.nd.array([[7],[8],[9]])
+    a_.attach_grad()
+    b_.attach_grad()
+    # foward
+    out = block(a_,b_)
+    print(out)
+    print('+++++')
+    # backward
+    out.backward(out_grad)
+    print(a_.grad)
+    print(b_.grad)
+    print("-------")
 
-out2 = exe2.forward()
-out2 = exe2.forward()
+# stateful
+block2 = mx.gluon.nn.SymbolBlock(d,[s,t])
+block2.hybridize(static_alloc=True, static_shape=True)
+out2 = block2(a,b)
+out2 = block2(a,b)
 print(out2)
-print("-------")
+with mx.autograd.record():
+    a_ = mx.nd.array([[1,2,3],[4,5,6]])
+    b_ = mx.nd.array([[7],[8],[9]])
+    a_.attach_grad()
+    b_.attach_grad()
+    # forward
+    out2 = block2(a_,b_)
+    print('+++++')
+    # backward
+    out2.backward(out_grad)
+    print(a_.grad)
+    print(b_.grad)
+    print("-------")
 
-# baseline forward
-e = mx.sym.linalg.gemm2(s,t)
-in_grad3 = [mx.nd.empty((2,3)),mx.nd.empty((3,1))]
-exe3 = e.bind(ctx=mx.cpu(),args={'s':a,'t':b},args_grad=in_grad3)
-out3 = exe3.forward()
-print(out3)
-
-print("--------start backward compute--------")
-out_grad = mx.nd.ones((2,1))
-exe.backward([out_grad])
-print(in_grad)
-print("-------")
-exe2.backward([out_grad])
-print(in_grad2)
-print("-------")
-exe3.backward([out_grad])
-print(in_grad3)
+# baseline
+block3 = mx.gluon.nn.SymbolBlock(e,[s,t])
+with mx.autograd.record():
+    a_ = mx.nd.array([[1,2,3],[4,5,6]])
+    b_ = mx.nd.array([[7],[8],[9]])
+    a_.attach_grad()
+    b_.attach_grad()
+    # forward
+    out3 = block3(a_,b_)
+    print(out3)
+    print('+++++')
+    # backward
+    out3.backward(out_grad)
+    print(a_.grad)
+    print(b_.grad)

example/extensions/lib_custom_op/test_relu.py

@@ -46,21 +46,39 @@
 d = mx.sym.Variable('d')
 e = mx.sym.my_relu(c)
 base = mx.sym.relu(d)
-in_grad = [mx.nd.empty((2,2), ctx=mx.gpu())]
-in_grad_base = [mx.nd.empty((2,2), ctx=mx.gpu())]
-exe = e.bind(ctx=mx.gpu(), args={'c':b}, args_grad=in_grad)
-exe_base = base.bind(ctx=mx.gpu(), args={'d':b}, args_grad=in_grad_base)
-out = exe.forward()
-out_base = exe_base.forward()
-print(out)
-print(out_base)
-
-print("--------backward compute--------")
+#in_grad = [mx.nd.empty((2,2), ctx=mx.gpu())]
+#in_grad_base = [mx.nd.empty((2,2), ctx=mx.gpu())]
 out_grad = mx.nd.ones((2,2), ctx=mx.gpu())
-exe.backward([out_grad])
-exe_base.backward([out_grad])
-print(in_grad)
-print(in_grad_base)
+#exe = e.bind(ctx=mx.gpu(), args={'c':b}, args_grad=in_grad)
+block = mx.gluon.nn.SymbolBlock(e,[c])
+#exe_base = base.bind(ctx=mx.gpu(), args={'d':b}, args_grad=in_grad_base)
+block_base = mx.gluon.nn.SymbolBlock(base,[d])
+
+# base
+with mx.autograd.record():
+    b_ = mx.nd.array([[-2,-1],[1,2]], ctx=mx.gpu())
+    b_.attach_grad()
+    # foward
+    out_base = block_base(b_)
+    print(out_base)
+    print('+++++')
+    # backward
+    out_base.backward(out_grad)
+    print(b_.grad)
+    print("-------")
+
+# custom relu
+with mx.autograd.record():
+    b_ = mx.nd.array([[-2,-1],[1,2]], ctx=mx.gpu())
+    b_.attach_grad()
+    # foward
+    out = block(b_)
+    print(out)
+    print('+++++')
+    # backward
+    out.backward(out_grad)
+    print(b_.grad)
+    print("-------")
 
 print("--------test ndarray with size of 1 million---------")
 b = mx.nd.uniform(shape=(100,100,100), ctx=mx.gpu())

example/extensions/lib_custom_op/transposecsr_lib.cc

@@ -176,6 +176,9 @@ class MyStatefulTransposeCSR : public CustomStatefulOp {
 };
 
 MXReturnValue createOpState(const std::unordered_map<std::string, std::string>& attrs,
+                            const MXContext& ctx,
+                            const std::vector<std::vector<unsigned int> >& in_shapes,
+                            const std::vector<int> in_types,
                             CustomStatefulOp** op_inst) {
   // testing passing of keyword arguments
   int count = attrs.count("test_kw") > 0 ? std::stoi(attrs.at("test_kw")) : 0;

example/extensions/lib_custom_op/transposerowsp_lib.cc

@@ -178,6 +178,9 @@ class MyStatefulTransposeRowSP : public CustomStatefulOp {
 };
 
 MXReturnValue createOpState(const std::unordered_map<std::string, std::string>& attrs,
+                            const MXContext& ctx,
+                            const std::vector<std::vector<unsigned int> >& in_shapes,
+                            const std::vector<int> in_types,
                             CustomStatefulOp** op_inst) {
   // testing passing of keyword arguments
   int count = attrs.count("test_kw") > 0 ? std::stoi(attrs.at("test_kw")) : 0;

example/extensions/lib_subgraph/subgraph_lib.cc

@@ -156,6 +156,9 @@ class MyStatefulOp : public CustomStatefulOp {
 };
 
 MXReturnValue createOpState(const std::unordered_map<std::string, std::string>& attrs,
+                            const MXContext& ctx,
+                            const std::vector<std::vector<unsigned int> >& in_shapes,
+                            const std::vector<int> in_types,
                             CustomStatefulOp** op_inst) {
   std::string serialized_subgraph = "[empty]";
   // MXNet subgraph is stored as Symbol in operator node attrs subgraphs field

include/mxnet/lib_api.h

@@ -732,6 +732,9 @@ typedef MXReturnValue (*mutateInputs_t)(const std::unordered_map<std::string,
                                         std::vector<int>* input_indices);
 typedef MXReturnValue (*createOpState_t)(const std::unordered_map<std::string,
                                          std::string>& attributes,
+                                         const MXContext& ctx,
+                                         const std::vector<std::vector<unsigned int> >& in_shapes,
+                                         const std::vector<int> in_types,
                                          CustomStatefulOp**);
 
 /*!
@@ -1000,8 +1003,9 @@ typedef int (*opCallMutateInputs_t)(mutateInputs_t mutate, const char* const* ke
 
 #define MXLIB_OPCALLCREATEOPSTATE_STR "_opCallCreateOpState"
 typedef int (*opCallCreateOpState_t)(createOpState_t create_op, const char* const* keys,
-                                     const char* const* vals, int num,
-                                     void** state_op);
+                                     const char* const* vals, int num, const char* dev_type,
+                                     int dev_id, unsigned int** inshapes, int* indims,
+                                     int num_in, const int* intypes, void** state_op);
 
 #define MXLIB_OPCALLFSTATEFULCOMP_STR "_opCallFStatefulCompute"
 typedef int (*opCallFStatefulComp_t)(int is_forward, void* state_op,
@@ -1190,8 +1194,9 @@ extern "C" {
 
   /*! \brief returns status of calling createStatefulOp function for operator from library */
   MX_INT_RET _opCallCreateOpState(mxnet::ext::createOpState_t create_op, const char* const* keys,
-                                  const char* const* vals, int num,
-                                  void** state_op);
+                                  const char* const* vals, int num, const char* dev_type,
+                                  int dev_id, unsigned int** inshapes, int* indims,
+                                  int num_in, const int* intypes, void** state_op);
 
   /*! \brief returns status of calling Stateful Forward/Backward for operator from library */
   MX_INT_RET _opCallFStatefulCompute(int is_forward, void* state_op, const int64_t** inshapes,

src/c_api/c_api.cc

@@ -1093,6 +1093,28 @@ void registerOperators(void *lib, int verbose, mxnet::ext::msgSize_t msgSize,
         attr_vals.push_back(kv.second.c_str());
       }
 
+      // string repr of supported context for custom library, currently only "cpu" and "gpu"
+      const char* ctx_str = ctx.dev_mask() == Context::kCPU ? "cpu" : "gpu";
+
+      std::vector<uint32_t*> inshapes(in_shapes.size());
+      std::vector<int> indims(in_shapes.size());
+
+      // determine amount of memory needed to store all the input shapes
+      size_t buff_size = 0;
+      for (size_t i = 0; i < in_shapes.size(); ++i)
+        buff_size += in_shapes[i].ndim();
+
+      // copy input shapes to raw memory layout
+      std::vector<uint32_t> inbuff(buff_size);
+      uint32_t *ptr = inbuff.data();
+      for (size_t i = 0; i < in_shapes.size(); ++i) {
+        inshapes[i] = ptr;
+        indims[i] = in_shapes[i].ndim();
+        for (int j = 0; j < in_shapes[i].ndim(); ++j, ++ptr) {
+          *ptr = static_cast<uint32_t>(in_shapes[i][j]);
+        }
+      }
+
       // convert subgraph symbol from node attributes to char*
       std::string subgraph_json;
       if (!attrs.subgraphs.empty()) {
@@ -1111,15 +1133,19 @@ void registerOperators(void *lib, int verbose, mxnet::ext::msgSize_t msgSize,
         CHECK(createop_map.count("cpu") > 0)
           << "CPU CreateOpState not implemented for '" << name_str << "'";
         int retval = callCreateOpState(createop_map.at("cpu"), attr_keys.data(), attr_vals.data(),
-                                       attr_keys.size(), &state_op_inst);
+                                       attr_keys.size(), ctx_str, ctx.real_dev_id(),
+                                       inshapes.data(), indims.data(),
+                                       in_shapes.size(), in_types.data(), &state_op_inst);
         std::string msgs = getExtensionMsgs(msgSize, msgGet);
         CHECK(retval) << "Error calling CreateOpState CPU for custom operator '" << name_str << "'"
                       << msgs;
       } else if (ctx.dev_mask() == Context::kGPU) {
         CHECK(createop_map.count("gpu") > 0)
           << "GPU CreateOpState not implemented for '" << name_str << "'";
         int retval = callCreateOpState(createop_map.at("gpu"), attr_keys.data(), attr_vals.data(),
-                                       attr_keys.size(), &state_op_inst);
+                                       attr_keys.size(), ctx_str, ctx.real_dev_id(),
+                                       inshapes.data(), indims.data(),
+                                       in_shapes.size(), in_types.data(), &state_op_inst);
         std::string msgs = getExtensionMsgs(msgSize, msgGet);
         CHECK(retval) << "Error calling CreateOpState GPU for custom operator '" << name_str << "'"
         << msgs;

src/lib_api.cc

@@ -1204,19 +1204,36 @@ MX_INT_RET _opCallMutateInputs(mxnet::ext::mutateInputs_t mutate, const char* co
 
 /*! \brief returns status of calling createStatefulOp function for operator from library */
 MX_INT_RET _opCallCreateOpState(mxnet::ext::createOpState_t create_op, const char* const* keys,
-                                const char* const* vals, int num,
-                                void** state_op) {
+                                     const char* const* vals, int num, const char* dev_type,
+                                     int dev_id, unsigned int** inshapes, int* indims,
+                                     int num_in, const int* intypes, void** state_op) {
   // create map of attributes from list
   std::unordered_map<std::string, std::string> attrs;
   for (int i = 0; i < num; i++) {
     attrs[std::string(keys[i])] = std::string(vals[i]);
   }
 
+  mxnet::ext::MXContext ctx(dev_type, dev_id);
+
+  // create a vector of shapes for inputs
+  std::vector<std::vector<unsigned int> > in_shapes(num_in);
+  for (int i = 0; i < num_in; i++) {
+    for (int j = 0; j < indims[i]; j++) {
+      in_shapes[i].push_back(inshapes[i][j]);
+    }
+  }
+
+  // create a vector of types for inputs
+  std::vector<int> in_types(num_in);
+  for (int i = 0; i < num_in; i++) {
+    in_types[i] = intypes[i];
+  }
+
   // void pointer to hold custom state op instance created in custom library
   // eventually state_op pointer is populated by instance from custom library
   mxnet::ext::CustomStatefulOp** op_ptr =
     reinterpret_cast<mxnet::ext::CustomStatefulOp**>(state_op);
-  return create_op(attrs, op_ptr);
+  return create_op(attrs, ctx, in_shapes, in_types, op_ptr);
 }
 
 /*! \brief returns status of calling Stateful Forward/Backward for operator from library */