diff --git a/src/opr/impl/misc.cpp b/src/opr/impl/misc.cpp
index 26bc0a333809cd21a9298ded5632784231c6fda0..ed35b122dac4be6832f4cd7722af3f1334aed3c0 100644
--- a/src/opr/impl/misc.cpp
+++ b/src/opr/impl/misc.cpp
@@ -166,23 +166,11 @@ MGB_DYN_TYPE_OBJ_FINAL_IMPL(NvOf);
 
 NvOf::NvOf(VarNode* opr, const Param& param, const OperatorNodeConfig& config)
         : Super{opr->owner_graph(), config, "NvOf", {opr}}, m_param{param} {
-    constexpr size_t NDIM = 5;
     mgb_assert(opr->dtype() == dtype::Uint8());
     add_input({opr});
     //! NvOf hava only one output
     add_output(None);
-
     mgb_log_debug("init nvof engine with precision: %u", m_param.precision);
-    auto input_shape = this->input()[0]->shape();
-
-    //! nvof input format: nthwc4
-    mgb_assert(input_shape.ndim == NDIM);
-    //! now only support RGBA format channel data
-    mgb_assert(input_shape[4] == 4);
-
-    for (size_t i = 0; i < NDIM; i++) {
-        vshape.push_back(input_shape[i]);
-    }
 }
 
 void NvOf::init_output_dtype() {
@@ -195,6 +183,10 @@ SymbolVar NvOf::make(SymbolVar opr, const Param& param,
 }
 
 void NvOf::scn_do_execute() {
+    auto input_shape = this->input()[0]->shape();
+    for (size_t i = 0; i < 5; i++) {
+        vshape.push_back(input_shape[i]);
+    }
     auto c = this->comp_node();
     //! comp_node may init on CUDA or CPU, eg: lar with --cpu
     //! if ON CUDA, need sync, caused by we use different stream
@@ -229,6 +221,10 @@ void NvOf::init_output_static_infer_desc() {
     using namespace cg::static_infer;
     auto infer_shape = [](TensorShape& dest, const InpVal& iv) {
         auto ishp = iv.val.at(0).shape();
+        //! nvof input format: nthwc4
+        mgb_assert(ishp.ndim == 5);
+        //! now only support RGBA format channel data
+        mgb_assert(ishp[4] == 4);
         SmallVector<size_t> tv;
         tv.push_back(ishp[0]);
         tv.push_back(ishp[1] - 1);