diff --git a/mindspore/nn/layer/basic.py b/mindspore/nn/layer/basic.py
index d688c6a2bdf..0309fc5552b 100644
--- a/mindspore/nn/layer/basic.py
+++ b/mindspore/nn/layer/basic.py
@@ -93,9 +93,7 @@ class Dropout(Cell):
         self.dropout_do_mask = P.DropoutDoMask()
         self.cast = P.Cast()
         self.is_gpu = context.get_context('device_target') in ["GPU"]
-
-        if self.is_gpu:
-            self.dropout = P.Dropout(keep_prob)
+        self.dropout = P.Dropout(keep_prob)
 
     def construct(self, x):
         if not self.training:
diff --git a/mindspore/nn/layer/embedding.py b/mindspore/nn/layer/embedding.py
index 83241239f3b..f5be4d9a258 100755
--- a/mindspore/nn/layer/embedding.py
+++ b/mindspore/nn/layer/embedding.py
@@ -128,8 +128,10 @@ class EmbeddingLookup(Cell):
         vocab_size (int): Size of the dictionary of embeddings.
         embedding_size (int): The size of each embedding vector.
         param_init (str): The initialize way of embedding table. Default: 'normal'.
-        target (str): Specify the target where the op is executed. Default: 'CPU'.
-        slice_mode (str): The slicing way in semi auto parallel/auto parallel. Default: 'batch_slice'.
+        target (str): Specify the target where the op is executed. The value should in
+        ['DEVICE', 'CPU']. Default: 'CPU'.
+        slice_mode (str): The slicing way in semi auto parallel/auto parallel. The value should get through
+        nn.EmbeddingLookUpSplitMode. Default: 'batch_slice'.
         manual_shapes (tuple): The accompaniment array in field slice mode.
 
     Inputs: