enable shape inference with hint func (#84)

nnvm/src/pass/infer_shape_type.cc

@@ -58,7 +58,7 @@ Graph InferAttr(Graph &&ret,
   std::vector<AttrType> ishape, oshape;
 
   // inference step function for nid
-  auto infer_step = [&](uint32_t nid) {
+  auto infer_step = [&](uint32_t nid, bool last_iter) {
     const auto& inode = idx[nid];
     const uint32_t num_inputs = inode.inputs.size();
     const uint32_t num_outputs = inode.source->num_outputs();
@@ -113,16 +113,20 @@ Graph InferAttr(Graph &&ret,
         oshape[i] = rshape[idx.entry_id(nid, i)];
         if (fis_none(oshape[i])) forward_known = false;
       }
+      auto finfer = finfer_shape.get(inode.source->op(), fdefault);
       if (!forward_known) {
-        auto finfer = finfer_shape.get(inode.source->op(), fdefault);
-        CHECK(finfer != nullptr)
-          << "Attribute " << infer_name
-          << " is not registed by op " << inode.source->op()->name;
-        // Call inference function of the operator.
-        try {
-          forward_known = finfer(inode.source->attrs, &ishape, &oshape);
-        } catch (const std::exception& e) {
-          throw dmlc::Error(e.what() + std::string(" with ") + inode.source->attrs.name);
+        if (finfer != nullptr) {
+          // Call inference function of the operator.
+          try {
+            forward_known = finfer(inode.source->attrs, &ishape, &oshape);
+          } catch (const std::exception& e) {
+            throw dmlc::Error(e.what() + std::string(" with ") + inode.source->attrs.name);
+          }
+        } else {
+          CHECK(!last_iter)
+              << "Attribute " << infer_name
+              << " is not registed by op " << inode.source->op()->name
+              << " we are not able to complete the inference because of this";
         }
       }
       // Save to the result map.
@@ -140,12 +144,12 @@ Graph InferAttr(Graph &&ret,
   for (int i = 0; i < kMaxStep; ++i) {
     if (i % 2 == 0) {
       for (uint32_t nid = 0; nid < idx.num_nodes(); ++nid) {
-        infer_step(nid);
+        infer_step(nid, i + 1 == kMaxStep);
       }
     } else {
       // backward inference
       for (uint32_t i = idx.num_nodes(); i != 0; --i) {
-        infer_step(i - 1);
+        infer_step(i - 1, i + 1 == kMaxStep);
       }
     }
     num_unknown = 0;