diff --git a/assignment/assignment1.ipynb b/assignment/assignment1.ipynb
index fddf1e4..120fff0 100644
--- a/assignment/assignment1.ipynb
+++ b/assignment/assignment1.ipynb
@@ -206,7 +206,7 @@
     "\n",
     "def emit_te_example():\n",
     "    bb = relax.BlockBuilder()\n",
-    "    x = relax.Var(\"x\", (128, 128), relax.DynTensorType(2, \"float32\"))\n",
+    "    x = relax.Var(\"x\", relax.TensorStructInfo((128, 128), \"float32\"))\n",
     "    with bb.function(\"main\", [x]):\n",
     "        with bb.dataflow():\n",
     "            lv0 = bb.emit_te(relu, x)\n",
@@ -253,7 +253,7 @@
    "source": [
     "def create_model_via_emit_te():\n",
     "    bb = relax.BlockBuilder()\n",
-    "    x = relax.Var(\"x\", input_shape, relax.DynTensorType(batch_size, \"float32\"))\n",
+    "    x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
     "\n",
     "    conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
     "    conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",
@@ -272,7 +272,7 @@
     "\n",
     "\n",
     "def build_mod(mod):\n",
-    "    exec = relax.vm.build(mod, \"llvm\")\n",
+    "    exec = relax.build(mod, \"llvm\")\n",
     "    dev = tvm.cpu()\n",
     "    vm = relax.VirtualMachine(exec, dev)\n",
     "    return vm\n",
@@ -362,7 +362,7 @@
     "def create_model_with_torch_func():\n",
     "    bb = relax.BlockBuilder()\n",
     "\n",
-    "    x = relax.Var(\"x\", input_shape, relax.DynTensorType(4, \"float32\"))\n",
+    "    x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
     "\n",
     "    conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
     "    conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",
diff --git a/assignment/assignment1_zh.ipynb b/assignment/assignment1_zh.ipynb
index d0b022d..4324de5 100644
--- a/assignment/assignment1_zh.ipynb
+++ b/assignment/assignment1_zh.ipynb
@@ -205,7 +205,7 @@
     "\n",
     "def emit_te_example():\n",
     "    bb = relax.BlockBuilder()\n",
-    "    x = relax.Var(\"x\", (128, 128), relax.DynTensorType(2, \"float32\"))\n",
+    "    x = relax.Var(\"x\", relax.TensorStructInfo((128, 128), \"float32\"))\n",
     "    with bb.function(\"main\", [x]):\n",
     "        with bb.dataflow():\n",
     "            lv0 = bb.emit_te(relu, x)\n",
@@ -252,7 +252,7 @@
    "source": [
     "def create_model_via_emit_te():\n",
     "    bb = relax.BlockBuilder()\n",
-    "    x = relax.Var(\"x\", input_shape, relax.DynTensorType(batch_size, \"float32\"))\n",
+    "    x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
     "\n",
     "    conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
     "    conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",
@@ -271,7 +271,7 @@
     "\n",
     "\n",
     "def build_mod(mod):\n",
-    "    exec = relax.vm.build(mod, \"llvm\")\n",
+    "    exec = relax.build(mod, \"llvm\")\n",
     "    dev = tvm.cpu()\n",
     "    vm = relax.VirtualMachine(exec, dev)\n",
     "    return vm\n",
@@ -362,7 +362,7 @@
     "def create_model_with_torch_func():\n",
     "    bb = relax.BlockBuilder()\n",
     "\n",
-    "    x = relax.Var(\"x\", input_shape, relax.DynTensorType(4, \"float32\"))\n",
+    "    x = relax.Var(\"x\", relax.TensorStructInfo(input_shape, \"float32\"))\n",
     "\n",
     "    conv2d_weight = relax.const(weight_map[\"conv2d_weight\"], \"float32\")\n",
     "    conv2d_bias = relax.const(weight_map[\"conv2d_bias\"].reshape(1, 32, 1, 1), \"float32\")\n",