diff --git a/python/paddle/fluid/data_feeder.py b/python/paddle/fluid/data_feeder.py
index 8a68ad9d54baf8f19a5d5abfad16b1bc664dd3f3..b2db00296bf95dff39e819595b71070ef1ef298f 100644
--- a/python/paddle/fluid/data_feeder.py
+++ b/python/paddle/fluid/data_feeder.py
@@ -26,31 +26,25 @@ from .framework import Variable, default_main_program, _current_expected_place,
 from .framework import _cpu_num, _cuda_ids
 __all__ = ['DataFeeder']
 
+_PADDLE_DTYPE_2_NUMPY_DTYPE = {
+    core.VarDesc.VarType.BOOL: 'bool',
+    core.VarDesc.VarType.FP16: 'float16',
+    core.VarDesc.VarType.FP32: 'float32',
+    core.VarDesc.VarType.FP64: 'float64',
+    core.VarDesc.VarType.INT8: 'int8',
+    core.VarDesc.VarType.INT16: 'int16',
+    core.VarDesc.VarType.INT32: 'int32',
+    core.VarDesc.VarType.INT64: 'int64',
+    core.VarDesc.VarType.UINT8: 'uint8',
+    core.VarDesc.VarType.COMPLEX64: 'complex64',
+    core.VarDesc.VarType.COMPLEX128: 'complex128',
+}
+
 
 def convert_dtype(dtype):
     if isinstance(dtype, core.VarDesc.VarType):
-        if dtype == core.VarDesc.VarType.BOOL:
-            return 'bool'
-        elif dtype == core.VarDesc.VarType.FP16:
-            return 'float16'
-        elif dtype == core.VarDesc.VarType.FP32:
-            return 'float32'
-        elif dtype == core.VarDesc.VarType.FP64:
-            return 'float64'
-        elif dtype == core.VarDesc.VarType.INT8:
-            return 'int8'
-        elif dtype == core.VarDesc.VarType.INT16:
-            return 'int16'
-        elif dtype == core.VarDesc.VarType.INT32:
-            return 'int32'
-        elif dtype == core.VarDesc.VarType.INT64:
-            return 'int64'
-        elif dtype == core.VarDesc.VarType.UINT8:
-            return 'uint8'
-        elif dtype == core.VarDesc.VarType.COMPLEX64:
-            return 'complex64'
-        elif dtype == core.VarDesc.VarType.COMPLEX128:
-            return 'complex128'
+        if dtype in _PADDLE_DTYPE_2_NUMPY_DTYPE:
+            return _PADDLE_DTYPE_2_NUMPY_DTYPE[dtype]
     elif isinstance(dtype, type):
         if dtype in [
                 np.bool, np.float16, np.float32, np.float64, np.int8, np.int16,
diff --git a/python/paddle/fluid/dygraph/varbase_patch_methods.py b/python/paddle/fluid/dygraph/varbase_patch_methods.py
index 7b0a3453b13efef2af0d20435e8808eeea54ef60..d3cf4d7bf3a3738b9acc87a5dece25541f8e7d22 100644
--- a/python/paddle/fluid/dygraph/varbase_patch_methods.py
+++ b/python/paddle/fluid/dygraph/varbase_patch_methods.py
@@ -23,6 +23,7 @@ from ..framework import Variable, Parameter, ParamBase
 from .base import switch_to_static_graph
 from .math_op_patch import monkey_patch_math_varbase
 from .parallel import scale_loss
+from paddle.fluid.data_feeder import convert_dtype, _PADDLE_DTYPE_2_NUMPY_DTYPE
 
 
 def monkey_patch_varbase():
@@ -319,5 +320,20 @@ def monkey_patch_varbase():
         ("__name__", "Tensor")):
         setattr(core.VarBase, method_name, method)
 
+    # NOTE(zhiqiu): pybind11 will set a default __str__ method of enum class.
+    # So, we need to overwrite it to a more readable one.
+    # See details in https://github.com/pybind/pybind11/issues/2537.
+    origin = getattr(core.VarDesc.VarType, "__repr__")
+
+    def dtype_str(dtype):
+        if dtype in _PADDLE_DTYPE_2_NUMPY_DTYPE:
+            prefix = 'paddle.'
+            return prefix + _PADDLE_DTYPE_2_NUMPY_DTYPE[dtype]
+        else:
+            # for example, paddle.fluid.core.VarDesc.VarType.LOD_TENSOR
+            return origin(dtype)
+
+    setattr(core.VarDesc.VarType, "__repr__", dtype_str)
+
     # patch math methods for varbase
     monkey_patch_math_varbase()
diff --git a/python/paddle/fluid/tests/unittests/test_var_base.py b/python/paddle/fluid/tests/unittests/test_var_base.py
index 2f4a9c8e37e59bfcca8a4db1c717ce5712f7e3ad..6c5458c1a2cb9fff356bf76941cdf27147f1722c 100644
--- a/python/paddle/fluid/tests/unittests/test_var_base.py
+++ b/python/paddle/fluid/tests/unittests/test_var_base.py
@@ -617,6 +617,16 @@ class TestVarBase(unittest.TestCase):
         self.assertEqual(a_str, expected)
         paddle.enable_static()
 
+    def test_print_tensor_dtype(self):
+        paddle.disable_static(paddle.CPUPlace())
+        a = paddle.rand([1])
+        a_str = str(a.dtype)
+
+        expected = 'paddle.float32'
+
+        self.assertEqual(a_str, expected)
+        paddle.enable_static()
+
 
 class TestVarBaseSetitem(unittest.TestCase):
     def setUp(self):