diff --git a/python/paddle/fluid/imperative/learning_rate_scheduler.py b/python/paddle/fluid/dygraph/learning_rate_scheduler.py
similarity index 100%
rename from python/paddle/fluid/imperative/learning_rate_scheduler.py
rename to python/paddle/fluid/dygraph/learning_rate_scheduler.py
diff --git a/python/paddle/fluid/layers/learning_rate_scheduler.py b/python/paddle/fluid/layers/learning_rate_scheduler.py
index 9c642712d2acda2b61b815ef0ece26223cb9a988..18ebab8ad683df73b12541f83fb4d4787e2d3b1f 100644
--- a/python/paddle/fluid/layers/learning_rate_scheduler.py
+++ b/python/paddle/fluid/layers/learning_rate_scheduler.py
@@ -30,8 +30,8 @@ from . import ops
 from . import tensor
 from ..initializer import init_on_cpu
 from ..framework import default_main_program, Parameter, unique_name, name_scope
-from ..imperative import base as imperative_base
-from ..imperative import learning_rate_scheduler as imperate_lr
+from ..dygraph import base as imperative_base
+from ..dygraph import learning_rate_scheduler as imperate_lr
 
 __all__ = [
     'exponential_decay', 'natural_exp_decay', 'inverse_time_decay',
@@ -350,7 +350,7 @@ def cosine_decay(learning_rate, step_each_epoch, epochs):
     following cosine decay strategy.
 
     decayed_lr = learning_rate * 0.5 * (math.cos(epoch * math.pi / epochs) + 1)
-    
+
     Args:
         learning_rate(Variable|float): The initial learning rate.
         step_each_epoch(int): the number of steps in an epoch.
diff --git a/python/paddle/fluid/tests/unittests/test_imperative_mnist.py b/python/paddle/fluid/tests/unittests/test_imperative_mnist.py
index 5b3c250501386a7854313218f5ea338281824252..5ab01839fbc20bbd3c242878c4ea23a00f7b0dca 100644
--- a/python/paddle/fluid/tests/unittests/test_imperative_mnist.py
+++ b/python/paddle/fluid/tests/unittests/test_imperative_mnist.py
@@ -23,12 +23,12 @@ import paddle
 import paddle.fluid as fluid
 from paddle.fluid import core
 from paddle.fluid.optimizer import SGDOptimizer
-from paddle.fluid.imperative.nn import Conv2D, Pool2D, FC
-from paddle.fluid.imperative.base import to_variable
+from paddle.fluid.dygraph.nn import Conv2D, Pool2D, FC
+from paddle.fluid.dygraph.base import to_variable
 from test_imperative_base import new_program_scope
 
 
-class SimpleImgConvPool(fluid.imperative.Layer):
+class SimpleImgConvPool(fluid.dygraph.Layer):
     def __init__(self,
                  name_scope,
                  num_channels,
@@ -77,7 +77,7 @@ class SimpleImgConvPool(fluid.imperative.Layer):
         return x
 
 
-class MNIST(fluid.imperative.Layer):
+class MNIST(fluid.dygraph.Layer):
     def __init__(self, name_scope):
         super(MNIST, self).__init__(name_scope)
 
@@ -108,7 +108,7 @@ class TestImperativeMnist(unittest.TestCase):
     def test_mnist_float32(self):
         seed = 90
         epoch_num = 1
-        with fluid.imperative.guard():
+        with fluid.dygraph.guard():
             fluid.default_startup_program().random_seed = seed
             fluid.default_main_program().random_seed = seed