diff --git a/official/cv/lenet/src/dataset.py b/official/cv/lenet/src/dataset.py
index df9eecda1fe327a405057be7993e401c5ae08187..cbe6918b6c0a637049aa742ea1fe24294465e0c1 100644
--- a/official/cv/lenet/src/dataset.py
+++ b/official/cv/lenet/src/dataset.py
@@ -33,27 +33,23 @@ def create_dataset(data_path, batch_size=32, repeat_size=1,
 
     resize_height, resize_width = 32, 32
     rescale = 1.0 / 255.0
-    shift = 0.0
     rescale_nml = 1 / 0.3081
     shift_nml = -1 * 0.1307 / 0.3081
 
     # define map operations
     resize_op = CV.Resize((resize_height, resize_width), interpolation=Inter.LINEAR)  # Bilinear mode
-    rescale_nml_op = CV.Rescale(rescale_nml, shift_nml)
-    rescale_op = CV.Rescale(rescale, shift)
+    rescale_nml_op = CV.Rescale(rescale_nml * rescale, shift_nml)
     hwc2chw_op = CV.HWC2CHW()
     type_cast_op = C.TypeCast(mstype.int32)
 
     # apply map operations on images
     mnist_ds = mnist_ds.map(operations=type_cast_op, input_columns="label", num_parallel_workers=num_parallel_workers)
     mnist_ds = mnist_ds.map(operations=resize_op, input_columns="image", num_parallel_workers=num_parallel_workers)
-    mnist_ds = mnist_ds.map(operations=rescale_op, input_columns="image", num_parallel_workers=num_parallel_workers)
     mnist_ds = mnist_ds.map(operations=rescale_nml_op, input_columns="image", num_parallel_workers=num_parallel_workers)
     mnist_ds = mnist_ds.map(operations=hwc2chw_op, input_columns="image", num_parallel_workers=num_parallel_workers)
 
     # apply DatasetOps
-    buffer_size = 10000
-    mnist_ds = mnist_ds.shuffle(buffer_size=buffer_size)  # 10000 as in LeNet train script
+    mnist_ds = mnist_ds.shuffle(buffer_size=1024)
     mnist_ds = mnist_ds.batch(batch_size, drop_remainder=True)
     mnist_ds = mnist_ds.repeat(repeat_size)
 
diff --git a/official/nlp/gnmt_v2/src/gnmt_model/dynamic_rnn.py b/official/nlp/gnmt_v2/src/gnmt_model/dynamic_rnn.py
index 48ca08c3024128e1f3588ceec25169c72ae21230..7f4c91ab3486f85e24ccf1a7d15d1aadf166b38b 100644
--- a/official/nlp/gnmt_v2/src/gnmt_model/dynamic_rnn.py
+++ b/official/nlp/gnmt_v2/src/gnmt_model/dynamic_rnn.py
@@ -68,7 +68,7 @@ class DynamicRNNCell(nn.Cell):
                                 num_layers=1,
                                 has_bias=True,
                                 batch_first=False,
-                                dropout=0,
+                                dropout=0.0,
                                 bidirectional=False)
 
     def construct(self, x, init_h=None, init_c=None):