[incubator-mxnet] 02/02: upgrade enum according to updated tvm

[li...@apache.org]

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liuyizhi pushed a commit to branch tvm_sync
in repository https://gitbox.apache.org/repos/asf/incubator-mxnet.git

commit 2ef7de0ec0072828e788976d1ec44e9438b96383
Author: Yizhi Liu <li...@apache.org>
AuthorDate: Fri Jan 24 22:17:50 2020 -0800

    upgrade enum according to updated tvm
---
 src/nnvm/plan_memory.cc                              | 2 --
 src/nnvm/tvm_bridge.cc                               | 4 ++--
 src/operator/numpy/np_elemwise_broadcast_logic_op.cc | 6 +++---
 src/operator/tensor/elemwise_unary_op_pow.cc         | 4 ++--
 src/operator/tvmop/op_module.cc                      | 2 +-
 5 files changed, 8 insertions(+), 10 deletions(-)

diff --git a/src/nnvm/plan_memory.cc b/src/nnvm/plan_memory.cc
index c89eefc..e061dab 100644
--- a/src/nnvm/plan_memory.cc
+++ b/src/nnvm/plan_memory.cc
@@ -26,7 +26,6 @@
 #include <nnvm/pass.h>
 #include <nnvm/graph_attr_types.h>
 #include <nnvm/op_attr_types.h>
-#include <nnvm/top/tensor.h>
 #include <mxnet/base.h>
 #include <memory>
 #include "graph_algorithm.h"
@@ -36,7 +35,6 @@ namespace nnvm {
 namespace pass {
 
 namespace {
-  using namespace nnvm::top;
 // Return bytes of data flag.
 static int MXGetDTypeSize(int type_flag) {
   switch (type_flag) {
diff --git a/src/nnvm/tvm_bridge.cc b/src/nnvm/tvm_bridge.cc
index 0692998..17e05e3 100644
--- a/src/nnvm/tvm_bridge.cc
+++ b/src/nnvm/tvm_bridge.cc
@@ -73,7 +73,7 @@ class TVMFunctor {
         const NDArray& nd =
             static_cast<NDArray*>(args.values[i].v_handle)[0];
         // We cannot set the value until
-        type_codes_[i] = kArrayHandle;
+        type_codes_[i] = kTVMDLTensorHandle;
         array_data_.push_back(nd);
         array_loc_.push_back(i);
         // check if there is read or mutate
@@ -86,7 +86,7 @@ class TVMFunctor {
           mutate_vars->push_back(nd.var());
         }
       } else {
-        CHECK_LT(args.type_codes[i], kTVMType)
+        CHECK_LT(args.type_codes[i], kTVMDataType)
             << "Only allow POD type in mxnet async call";
       }
     }
diff --git a/src/operator/numpy/np_elemwise_broadcast_logic_op.cc b/src/operator/numpy/np_elemwise_broadcast_logic_op.cc
index 7e8951a..8395caf 100644
--- a/src/operator/numpy/np_elemwise_broadcast_logic_op.cc
+++ b/src/operator/numpy/np_elemwise_broadcast_logic_op.cc
@@ -95,7 +95,7 @@ struct TVMBinaryBroadcastCompute {
     values.resize(num_args);
     for (size_t i = 0; i < num_args; ++i) {
       tblobs[i] = PrependAxes(tblobs[i], ondim);
-      type_codes[i] = kArrayHandle;
+      type_codes[i] = kTVMDLTensorHandle;
       values[i].v_handle = const_cast<DLTensor*>(&(tblobs[i].dltensor()));
     }
     tvm::runtime::TVMArgs tvm_args(&values[0], &type_codes[0], tblobs.size());
@@ -200,7 +200,7 @@ struct TVMBinaryBroadcastScalarCompute {
     values.resize(num_args);
 
     // input tensor setup
-    type_codes[0] = kArrayHandle;
+    type_codes[0] = kTVMDLTensorHandle;
     values[0].v_handle = const_cast<DLTensor*>(&(tblobs[0].dltensor()));
 
     // scalar param
@@ -208,7 +208,7 @@ struct TVMBinaryBroadcastScalarCompute {
     values[1].v_float64 = nnvm::get<double>(attrs.parsed);
 
     // output tensor
-    type_codes[2] = kArrayHandle;
+    type_codes[2] = kTVMDLTensorHandle;
     values[2].v_handle = const_cast<DLTensor*>(&(tblobs[1].dltensor()));
 
     tvm::runtime::TVMArgs tvm_args(&values[0], &type_codes[0], 3);
diff --git a/src/operator/tensor/elemwise_unary_op_pow.cc b/src/operator/tensor/elemwise_unary_op_pow.cc
index b4d3a4a..914cb820 100644
--- a/src/operator/tensor/elemwise_unary_op_pow.cc
+++ b/src/operator/tensor/elemwise_unary_op_pow.cc
@@ -224,7 +224,7 @@ The storage type of ``rsqrt`` output is always dense
 MXNET_OPERATOR_REGISTER_BINARY_WITH_SPARSE_CPU_DR(
   _backward_rsqrt, unary_bwd<mshadow_op::reciprocal_square_root_grad>)
 .set_attr<nnvm::FGradient>("FGradient",
-  [](const nnvm::NodePtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
+  [](const nnvm::ObjectPtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
       // NodeEntry{n} : y_grad * f'(x)
       // n->inputs[0] : y_grad
       // n->inputs[1] : x
@@ -329,7 +329,7 @@ MXNET_OPERATOR_REGISTER_BINARY(_backward_rcbrt)
                     ElemwiseBinaryOp::Compute<cpu,
                       unary_bwd<mshadow_op::reciprocal_cube_root_grad>>)
 .set_attr<nnvm::FGradient>("FGradient",
-  [](const nnvm::NodePtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
+  [](const nnvm::ObjectPtr& n, const std::vector<nnvm::NodeEntry>& ograds) {
       // NodeEntry{n} : y_grad * f'(x)
       // n->inputs[0] : y_grad
       // n->inputs[1] : x
diff --git a/src/operator/tvmop/op_module.cc b/src/operator/tvmop/op_module.cc
index b45df5d..cdd7321 100644
--- a/src/operator/tvmop/op_module.cc
+++ b/src/operator/tvmop/op_module.cc
@@ -94,7 +94,7 @@ void TVMOpModule::Call(const std::string &func_name,
   type_codes.resize(args.size());
   values.resize(args.size());
   for (size_t i = 0; i < args.size(); ++i) {
-    type_codes[i] = kArrayHandle;
+    type_codes[i] = kTVMDLTensorHandle;
     values[i].v_handle = const_cast<DLTensor *>(&(args[i].dltensor()));
   }