diff --git a/paddle/fluid/framework/paddle2cinn/cinn_zero_tensor_trick_pass.cc b/paddle/fluid/framework/paddle2cinn/cinn_zero_tensor_trick_pass.cc
index 9c4e6192be424230cca1df798e520e280c48d3d1..de84742146cabbaf10c6f194d930cf7008f4c134 100644
--- a/paddle/fluid/framework/paddle2cinn/cinn_zero_tensor_trick_pass.cc
+++ b/paddle/fluid/framework/paddle2cinn/cinn_zero_tensor_trick_pass.cc
@@ -32,6 +32,32 @@ void CinnZeroTensorTrickPass::ApplyImpl(ir::Graph* graph) const {
                                                           "assign_value",
                                                           "gaussian_random",
                                                           "set_value"};
+  // NOTE: Hack squeeze2 0D-Tensor input
+  // If squeeze2 inputs 0D-Tensor and axes, The 0D-Tensor's shape will convert
+  // to 1D-Tensor, which could lead error. We hack squeeze2's axes attribute to
+  // resolve this. Change 0D-Tensor input to 1D-Tensor input and then make
+  // axes->axes[: -1]
+  for (const ir::Node* n : graph->Nodes()) {
+    if (n->IsOp() && n->Op()->Type() == "unsqueeze2") {
+      if (n->Op()->HasAttr("axes")) {
+        auto axes =
+            PADDLE_GET_CONST(std::vector<int32_t>, n->Op()->GetAttr("axes"));
+        for (const ir::Node* var : n->inputs) {
+          if (var->Var() &&
+              var->Var()->GetType() == proto::VarType::LOD_TENSOR) {
+            std::vector<int64_t> shape = var->Var()->GetShape();
+            if (shape.empty()) {
+              axes.pop_back();
+              n->Op()->SetAttr("axes", axes);
+              VLOG(4) << "unsqueeze2 axes dims is full, fix dim -> dim[:-1] to "
+                         "avoid 0D-Tensor input error";
+            }
+          }
+        }
+      }
+    }
+  }
+
   for (const ir::Node* n : graph->Nodes()) {
     if (n->IsOp() && op_cases_fix_attr.count(n->Op()->Type())) {
       if (n->Op()->HasAttr("shape")) {