fix diff from en and cn

doc/fluid/api_cn/layers_cn/multiclass_nms_cn.rst

@@ -62,9 +62,9 @@ multiclass_nms
 ..  code-block:: python
 
     import paddle.fluid as fluid
-    boxes = fluid.layers.data(name='bboxes', shape=[81, 4],
+    boxes = fluid.data(name='bboxes', shape=[None, 81, 4],
                               dtype='float32', lod_level=1)
-    scores = fluid.layers.data(name='scores', shape=[81],
+    scores = fluid.data(name='scores', shape=[None, 81],
                               dtype='float32', lod_level=1)
     out = fluid.layers.multiclass_nms(bboxes=boxes,
                                       scores=scores,

doc/fluid/api_cn/layers_cn/noam_decay_cn.rst

@@ -37,12 +37,10 @@ noam衰减的numpy实现如下：
 .. code-block:: python
 
         import paddle.fluid as fluid
+        d_model = 0.01
         warmup_steps = 100
         learning_rate = 0.01
-        lr = fluid.layers.learning_rate_scheduler.noam_decay(
-                       1/(warmup_steps *(learning_rate ** 2)),
-                       warmup_steps)
-
+        lr = fluid.layers.noam_decay(d_model, warmup_steps, learning_rate)
 
 
 

doc/fluid/api_cn/layers_cn/yolo_box_cn.rst

@@ -57,8 +57,8 @@ yolo_box
 .. code-block:: python
 
     import paddle.fluid as fluid
-    x = fluid.layers.data(name='x', shape=[255, 13, 13], dtype='float32')
-    img_size = fluid.layers.data(name='img_size',shape=[2],dtype='int64')
+    x = fluid.data(name='x', shape=[None, 255, 13, 13], dtype='float32')
+    img_size = fluid.data(name='img_size',shape=[None, 2],dtype='int64')
     anchors = [10, 13, 16, 30, 33, 23]
     boxes, scores = fluid.layers.yolo_box(x=x, img_size=img_size, class_num=80, anchors=anchors,
                                     conf_thresh=0.01, downsample_ratio=32)

doc/fluid/api_cn/layers_cn/yolov3_loss_cn.rst

@@ -85,10 +85,10 @@ yolov3 loss前的网络输出形状为[N，C，H，W]，H和W应该相同，用
 .. code-block:: python
 
     import paddle.fluid as fluid
-    x = fluid.layers.data(name='x', shape=[255, 13, 13], dtype='float32')
-    gt_box = fluid.layers.data(name='gt_box', shape=[6, 4], dtype='float32')
-    gt_label = fluid.layers.data(name='gt_label', shape=[6], dtype='int32')
-    gt_score = fluid.layers.data(name='gt_score', shape=[6], dtype='float32')
+    x = fluid.data(name='x', shape=[None, 255, 13, 13], dtype='float32')
+    gt_box = fluid.data(name='gt_box', shape=[None, 6, 4], dtype='float32')
+    gt_label = fluid.data(name='gt_label', shape=[None, 6], dtype='int32')
+    gt_score = fluid.data(name='gt_score', shape=[None, 6], dtype='float32')
     anchors = [10, 13, 16, 30, 33, 23, 30, 61, 62, 45, 59, 119, 116, 90, 156, 198, 373, 326]
     anchor_mask = [0, 1, 2]
     loss = fluid.layers.yolov3_loss(x=x, gt_box=gt_box, gt_label=gt_label,