update example (#1483)

doc/fluid/api_cn/layers_cn/anchor_generator_cn.rst

@@ -33,7 +33,7 @@ anchor_generator
 .. code-block:: python
 
     import paddle.fluid as fluid
-    conv1 = fluid.layers.data(name='conv1', shape=[48, 16, 16], dtype='float32')
+    conv1 = fluid.data(name='conv1', shape=[None, 48, 16, 16], dtype='float32')
     anchor, var = fluid.layers.anchor_generator(
     input=conv1,
     anchor_sizes=[64, 128, 256, 512],

doc/fluid/api_cn/layers_cn/bipartite_match_cn.rst

@@ -34,7 +34,7 @@ bipartite_match
 ..  code-block:: python
 
          import paddle.fluid as fluid
-         x = fluid.layers.data(name='x', shape=[4], dtype='float32')
-         y = fluid.layers.data(name='y', shape=[4], dtype='float32')
+         x = fluid.data(name='x', shape=[None, 4], dtype='float32')
+         y = fluid.data(name='y', shape=[None, 4], dtype='float32')
          iou = fluid.layers.iou_similarity(x=x, y=y)
          matched_indices, matched_dist = fluid.layers.bipartite_match(iou)

doc/fluid/api_cn/layers_cn/box_clip_cn.rst

@@ -37,8 +37,8 @@ box_clip
 ..  code-block:: python
 
     import paddle.fluid as fluid
-    boxes = fluid.layers.data(
-        name='boxes', shape=[8, 4], dtype='float32', lod_level=1)
-    im_info = fluid.layers.data(name='im_info', shape=[3])
+    boxes = fluid.data(
+        name='boxes', shape=[None, 8, 4], dtype='float32', lod_level=1)
+    im_info = fluid.data(name='im_info', shape=[None, 3])
     out = fluid.layers.box_clip(
         input=boxes, im_info=im_info)

doc/fluid/api_cn/layers_cn/box_coder_cn.rst

@@ -65,27 +65,23 @@ Bounding Box Coder
 
     import paddle.fluid as fluid
     # For encode
-    prior_box_encode = fluid.layers.data(name='prior_box_encode',
+    prior_box_encode = fluid.data(name='prior_box_encode',
                                   shape=[512, 4],
-                                  dtype='float32',
-                                  append_batch_size=False)
-    target_box_encode = fluid.layers.data(name='target_box_encode',
+                                  dtype='float32')
+    target_box_encode = fluid.data(name='target_box_encode',
                                    shape=[81,4],
-                                   dtype='float32',
-                                   append_batch_size=False)
+                                   dtype='float32')
     output_encode = fluid.layers.box_coder(prior_box=prior_box_encode,
                                     prior_box_var=[0.1,0.1,0.2,0.2],
                                     target_box=target_box_encode,
                                     code_type="encode_center_size")
     # For decode
-    prior_box_decode = fluid.layers.data(name='prior_box_decode',
+    prior_box_decode = fluid.data(name='prior_box_decode',
                                   shape=[512, 4],
-                                  dtype='float32',
-                                  append_batch_size=False)
-    target_box_decode = fluid.layers.data(name='target_box_decode',
+                                  dtype='float32')
+    target_box_decode = fluid.data(name='target_box_decode',
                                    shape=[512,81,4],
-                                   dtype='float32',
-                                   append_batch_size=False)
+                                   dtype='float32')
     output_decode = fluid.layers.box_coder(prior_box=prior_box_decode,
                                     prior_box_var=[0.1,0.1,0.2,0.2],
                                     target_box=target_box_decode,

doc/fluid/api_cn/layers_cn/box_decoder_and_assign_cn.rst

@@ -49,14 +49,14 @@ box decode过程得出decode_box，然后分配方案如下所述：
 .. code-block:: python
 
     import paddle.fluid as fluid
-    pb = fluid.layers.data(
-        name='prior_box', shape=[4], dtype='float32')
-    pbv = fluid.layers.data(
-        name='prior_box_var', shape=[4], dtype='float32', append_batch_size=False))
-    loc = fluid.layers.data(
-        name='target_box', shape=[4*81], dtype='float32')
-    scores = fluid.layers.data(
-        name='scores', shape=[81], dtype='float32')
+    pb = fluid.data(
+        name='prior_box', shape=[None, 4], dtype='float32')
+    pbv = fluid.data(
+        name='prior_box_var', shape=[4], dtype='float32')
+    loc = fluid.data(
+        name='target_box', shape=[None, 4*81], dtype='float32')
+    scores = fluid.data(
+        name='scores', shape=[None, 81], dtype='float32')
     decoded_box, output_assign_box = fluid.layers.box_decoder_and_assign(
         pb, pbv, loc, scores, 4.135)
 

doc/fluid/api_cn/layers_cn/clip_by_norm_cn.rst

@@ -29,8 +29,8 @@ ClipByNorm算子
 .. code-block:: python
 
     import paddle.fluid as fluid
-    input = fluid.layers.data(
-        name='data', shape=[1], dtype='float32')
+    input = fluid.data(
+        name='data', shape=[None, 1], dtype='float32')
     reward = fluid.layers.clip_by_norm(x=input, max_norm=1.0)
 
 

doc/fluid/api_cn/layers_cn/collect_fpn_proposals_cn.rst

@@ -35,11 +35,11 @@ collect_fpn_proposals
     multi_rois = []
     multi_scores = []
     for i in range(4):
-        multi_rois.append(fluid.layers.data(
-            name='roi_'+str(i), shape=[4], dtype='float32', lod_level=1))
+        multi_rois.append(fluid.data(
+            name='roi_'+str(i), shape=[None, 4], dtype='float32', lod_level=1))
     for i in range(4):
-        multi_scores.append(fluid.layers.data(
-            name='score_'+str(i), shape=[1], dtype='float32', lod_level=1))
+        multi_scores.append(fluid.data(
+            name='score_'+str(i), shape=[None, 1], dtype='float32', lod_level=1))
 
     fpn_rois = fluid.layers.collect_fpn_proposals(
         multi_rois=multi_rois,

doc/fluid/api_cn/layers_cn/distribute_fpn_proposals_cn.rst

@@ -36,8 +36,8 @@ distribute_fpn_proposals
 .. code-block:: python
 
     import paddle.fluid as fluid
-    fpn_rois = fluid.layers.data(
-        name='data', shape=[4], dtype='float32', lod_level=1)
+    fpn_rois = fluid.data(
+        name='data', shape=[None, 4], dtype='float32', lod_level=1)
     multi_rois, restore_ind = fluid.layers.distribute_fpn_proposals(
         fpn_rois=fpn_rois,
         min_level=2,

doc/fluid/api_cn/layers_cn/maxout_cn.rst

@@ -38,8 +38,8 @@ maxout
 .. code-block:: python
 
     import paddle.fluid as fluid
-    input = fluid.layers.data(
+    input = fluid.data(
         name='data',
-        shape=[256, 32, 32],
+        shape=[None, 256, 32, 32],
         dtype='float32')
     out = fluid.layers.maxout(input, groups=2)

doc/fluid/api_cn/layers_cn/prelu_cn.rst

@@ -38,7 +38,7 @@ prelu
 
     import paddle.fluid as fluid
     from paddle.fluid.param_attr import ParamAttr
-    x = fluid.layers.data(name="x", shape=[5,10,10], dtype="float32")
+    x = fluid.data(name="x", shape=[None,5,10,10], dtype="float32")
     mode = 'channel'
     output = fluid.layers.prelu(
              x,mode,param_attr=ParamAttr(name='alpha'))

doc/fluid/api_cn/layers_cn/roi_align_cn.rst

@@ -35,10 +35,10 @@ Region of Interests align(直译：有意义、有价值选区对齐) 用于实
 ..  code-block:: python
 
     import paddle.fluid as fluid
-    x = fluid.layers.data(
-            name='data', shape=[256, 32, 32], dtype='float32')
-    rois = fluid.layers.data(
-            name='rois', shape=[4], dtype='float32')
+    x = fluid.data(
+            name='data', shape=[None, 256, 32, 32], dtype='float32')
+    rois = fluid.data(
+            name='rois', shape=[None, 4], dtype='float32')
     align_out = fluid.layers.roi_align(input=x,
                                        rois=rois,
                                        pooled_height=7,