diff --git a/docs/langref/relay_op.rst b/docs/langref/relay_op.rst
index 5c3ab8b1ffda..f053165470fe 100644
--- a/docs/langref/relay_op.rst
+++ b/docs/langref/relay_op.rst
@@ -133,6 +133,9 @@ This level enables additional math and transform operators.
    :nosignatures:
 
    tvm.relay.image.resize
+   tvm.relay.vision.multibox_prior
+   tvm.relay.vision.multibox_transform_loc
+   tvm.relay.vision.nms
 
 
 **Level 10: Temporary Operators**
@@ -160,6 +163,7 @@ Level 1 Definitions
 .. autofunction:: tvm.relay.mod
 .. autofunction:: tvm.relay.tanh
 .. autofunction:: tvm.relay.concatenate
+.. autofunction:: tvm.relay.expand_dims
 .. autofunction:: tvm.relay.nn.softmax
 .. autofunction:: tvm.relay.nn.log_softmax
 .. autofunction:: tvm.relay.nn.relu
@@ -236,6 +240,9 @@ Level 4 Definitions
 Level 5 Definitions
 -------------------
 .. autofunction:: tvm.relay.image.resize
+.. autofunction:: tvm.relay.vision.multibox_prior
+.. autofunction:: tvm.relay.vision.multibox_transform_loc
+.. autofunction:: tvm.relay.vision.nms
 
 
 Level 10 Definitions
diff --git a/include/tvm/runtime/packed_func.h b/include/tvm/runtime/packed_func.h
index 0aeb7f2b1513..1e5265c07959 100644
--- a/include/tvm/runtime/packed_func.h
+++ b/include/tvm/runtime/packed_func.h
@@ -946,9 +946,11 @@ inline TVMType String2TVMType(std::string s) {
   char* xdelim;  // emulate sscanf("%ux%u", bits, lanes)
   uint8_t bits = static_cast<uint8_t>(strtoul(scan, &xdelim, 10));
   if (bits != 0) t.bits = bits;
+  char* endpt = xdelim;
   if (*xdelim == 'x') {
-    t.lanes = static_cast<uint16_t>(strtoul(xdelim + 1, nullptr, 10));
+    t.lanes = static_cast<uint16_t>(strtoul(xdelim + 1, &endpt, 10));
   }
+  CHECK(endpt == s.c_str() + s.length()) << "unknown type " << s;
   return t;
 }
 
diff --git a/python/tvm/relay/expr.py b/python/tvm/relay/expr.py
index 4725c0a7a07d..4e0852f1f7bb 100644
--- a/python/tvm/relay/expr.py
+++ b/python/tvm/relay/expr.py
@@ -49,7 +49,7 @@ def astype(self, dtype):
         result : tvm.relay.Expr
             The result expression.
         """
-        return _make.dtype_cast(self, dtype)
+        return _make.cast(self, dtype)
 
     def __add__(self, other):
         if isinstance(other, Expr):
diff --git a/python/tvm/relay/op/transform.py b/python/tvm/relay/op/transform.py
index 2791eaf7d9db..bc0a42d6ab30 100644
--- a/python/tvm/relay/op/transform.py
+++ b/python/tvm/relay/op/transform.py
@@ -4,6 +4,26 @@
 from ..expr import TupleWrapper
 
 
+def cast(data, dtype):
+    """Cast input tensor to data type.
+
+    Parameters
+    ----------
+    data : relay.Expr
+        The input data to the operator.
+
+    dtype: str
+        The target data type
+
+    Returns
+    -------
+    result : relay.Expr
+        The casted result.
+    """
+    from .. import _make as _relay_make
+    return _relay_make.cast(data, dtype)
+
+
 def expand_dims(data, axis, num_newaxis=1):
     """Insert `num_newaxis` axises at the position given by `axis`.
 
diff --git a/src/relay/op/tensor/transform.cc b/src/relay/op/tensor/transform.cc
index eb8b4f13fb3f..704324533185 100644
--- a/src/relay/op/tensor/transform.cc
+++ b/src/relay/op/tensor/transform.cc
@@ -61,7 +61,7 @@ Expr MakeCast(Expr data,
   return CallNode::make(op, {data}, Attrs(attrs), {});
 }
 
-TVM_REGISTER_API("relay._make.dtype_cast")
+TVM_REGISTER_API("relay._make.cast")
 .set_body([](const TVMArgs& args, TVMRetValue* rv) {
     runtime::detail::unpack_call<Expr, 2>(MakeCast, args, rv);
 });
diff --git a/tests/python/relay/test_op_level3.py b/tests/python/relay/test_op_level3.py
index 0731ecfef40a..31e87ef04856 100644
--- a/tests/python/relay/test_op_level3.py
+++ b/tests/python/relay/test_op_level3.py
@@ -46,6 +46,11 @@ def test_cast():
     assert "dtype=" in yy.astext()
     assert yy.checked_type == relay.TensorType((8, 9, 4), "int32")
 
+    x = relay.var("x", relay.TensorType((8, 9, 4), "float32"))
+    y = relay.cast(x, "int32")
+    yy = relay.ir_pass.infer_type(y)
+    assert "dtype=" in yy.astext()
+    assert yy.checked_type == relay.TensorType((8, 9, 4), "int32")
 
 def test_clip():
     a = relay.var("a", relay.TensorType((10, 4), "float32"))