[NNVM][OP] Allow two input tensors with different type in reshape_like op (#2052)

nnvm/python/nnvm/frontend/mxnet.py

@@ -290,7 +290,8 @@ _identity_list = ['__add_scalar__', '__add_symbol__', '__div_scalar__',
                   'elemwise_div', 'elemwise_mul', 'elemwise_sub', 'exp',
                   'flatten', 'log', 'log_softmax', 'max', 'min', 'negative',
                   'ones_like', 'relu', 'sigmoid', 'slice_like', 'softmax',
-                  'sum', 'tanh', 'transpose', 'zeros_like', 'gather_nd']
+                  'sum', 'tanh', 'transpose', 'zeros_like', 'gather_nd',
+                  'reshape_like']
 
 _convert_map = {
     '_copy'         : _rename('copy'),

nnvm/src/top/tensor/transform.cc

@@ -631,6 +631,15 @@ The significance of each is explained below:
 })
 .set_support_level(3);
 
+inline bool ReshapeLikeInferType(const NodeAttrs &attrs,
+                                 std::vector<int> *in_attrs,
+                                 std::vector<int> *out_attrs) {
+  CHECK_EQ(in_attrs->size(), 2U);
+  CHECK_EQ(out_attrs->size(), 1U);
+  NNVM_ASSIGN_OUTPUT_TYPE(attrs, *out_attrs, 0, (*in_attrs)[0]);
+  return true;
+}
+
 NNVM_REGISTER_OP(reshape_like)
   .describe(R"code(Reshapes the input array by the size of another array.
 For an input array with shape ``(d1, d2, ..., dk)``, `reshape_like` operation reshapes
@@ -651,7 +660,7 @@ the input array into an output array with the same shape as the second input arr
     NNVM_ASSIGN_OUTPUT_SHAPE(attrs, *out_attrs, 0, in_attrs->at(1));
     return true;
 })
-.set_attr<FInferType>("FInferType", ElemwiseType<2, 1>)
+.set_attr<FInferType>("FInferType", ReshapeLikeInferType)
 // never transform layout of the second input array.
 .set_attr<FCorrectLayout>("FCorrectLayout", ElemwiseFixedLayoutUnknownOut<1, 1>)
 .set_attr<FGradient>(