[Fix Bug]fix the bug of tensorflow frontend when parsing Range layer (#…

…9999)

Co-authored-by: wangjiuyang <wang.jiuyang@intellif.com>

python/tvm/relay/frontend/tensorflow_ops.py

@@ -2454,16 +2454,16 @@ def _impl(inputs, attr, params, mod):
                 delta = inputs[2]
 
         # if all attributes are constant, evalute the range function and return relay.const
+        dtype = attr["Tidx"].name if "Tidx" in attr else str(start.dtype)
         if all(
             [
                 isinstance(start, (np.int32, np.int64, int, np.float32, np.float64, float)),
                 isinstance(limit, (np.int32, np.int64, int, np.float32, np.float64, float)),
                 isinstance(delta, (np.int32, np.int64, int, np.float32, np.float64, float)),
             ]
         ):
-            return tvm.relay.const(list(range(int(start), int(limit), int(delta))))
+            return tvm.relay.const(list(range(int(start), int(limit), int(delta))), dtype=dtype)
 
-        dtype = attr["Tidx"].name if "Tidx" in attr else str(start.dtype)
         if isinstance(start, (np.int32, np.int64, int, np.float32, np.float64, float)):
             start = _expr.const(start, dtype=dtype)
         if isinstance(limit, (np.int32, np.int64, int, np.float32, np.float64, float)):