fix paddlepaddle API examples (#17306)

* API.spec test=develop

* update

* update test=develop

* update test=develop

* update

* update test=develop

* update test=develop

* update test=develop

* update test=develop

* update test=develop

* test=develop

* update

* update test=develop

* update test=develop

paddle/fluid/API.spec

@@ -104,11 +104,11 @@ paddle.fluid.layers.sequence_expand_as (ArgSpec(args=['x', 'y', 'name'], varargs
 paddle.fluid.layers.sequence_pad (ArgSpec(args=['x', 'pad_value', 'maxlen', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '6a1adf3067b20f6e4bcb354d71c19184'))
 paddle.fluid.layers.sequence_unpad (ArgSpec(args=['x', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd12803c903c99aa36ec03aaac5f0cc5b'))
 paddle.fluid.layers.lstm_unit (ArgSpec(args=['x_t', 'hidden_t_prev', 'cell_t_prev', 'forget_bias', 'param_attr', 'bias_attr', 'name'], varargs=None, keywords=None, defaults=(0.0, None, None, None)), ('document', '409d1c2ca874a22511258175649d2b7f'))
-paddle.fluid.layers.reduce_sum (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'b69998ce3ff4980fb21da0df05565f1b'))
-paddle.fluid.layers.reduce_mean (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'd4d80dd98a1a5839f41eeb3a0f85f370'))
-paddle.fluid.layers.reduce_max (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '66a622db727551761ce4eb73eaa7f6a4'))
-paddle.fluid.layers.reduce_min (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'd50ac552b5d131468ed466d08bb2d38c'))
-paddle.fluid.layers.reduce_prod (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'fcd8301a0ce15f219c7a4bcd0c1e8eca'))
+paddle.fluid.layers.reduce_sum (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'dd5f06fb7cf39ca06cbab4abd03e6893'))
+paddle.fluid.layers.reduce_mean (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'a3024789eba11a70c2ef27c358173400'))
+paddle.fluid.layers.reduce_max (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '10023caec4d7f78c3b901f023a1feaa7'))
+paddle.fluid.layers.reduce_min (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '1a1c91625ce3c32646f69ca10d4d1da7'))
+paddle.fluid.layers.reduce_prod (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'b386471f0476c80c61d8c8672278063d'))
 paddle.fluid.layers.reduce_all (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', '646ca4d4a2cc16084f59de44b6927eca'))
 paddle.fluid.layers.reduce_any (ArgSpec(args=['input', 'dim', 'keep_dim', 'name'], varargs=None, keywords=None, defaults=(None, False, None)), ('document', 'f36661060aeeaf6c6b1331e41b3726fa'))
 paddle.fluid.layers.sequence_first_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', '2b290d3d77882bfe9bb8d331cac8cdd3'))
@@ -183,15 +183,15 @@ paddle.fluid.layers.sequence_enumerate (ArgSpec(args=['input', 'win_size', 'pad_
 paddle.fluid.layers.expand (ArgSpec(args=['x', 'expand_times', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '117d3607d1ffa0571835bbaebc7857ff'))
 paddle.fluid.layers.sequence_concat (ArgSpec(args=['input', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b992616c1afbd6b0c2a897ac23036381'))
 paddle.fluid.layers.scale (ArgSpec(args=['x', 'scale', 'bias', 'bias_after_scale', 'act', 'name'], varargs=None, keywords=None, defaults=(1.0, 0.0, True, None, None)), ('document', '463e4713806e5adaa4d20a41e2218453'))
-paddle.fluid.layers.elementwise_add (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '210ee7e597f429f836a21b298991ef85'))
-paddle.fluid.layers.elementwise_div (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '9ce91719cf4a05de9a817e9ff2387ee8'))
-paddle.fluid.layers.elementwise_sub (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'c66c50b550bc547b6c61d15c1f3ee2ab'))
-paddle.fluid.layers.elementwise_mul (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'e6919013e5369c7b0d486b8604da6b2f'))
-paddle.fluid.layers.elementwise_max (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'f839de1318c794f26b9f5aafcd2ad92f'))
-paddle.fluid.layers.elementwise_min (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'c37aa719815585f2c20623f92e738d54'))
-paddle.fluid.layers.elementwise_pow (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '984e0e72db2a3b4241a694499f8d76c8'))
-paddle.fluid.layers.elementwise_mod (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '4aa6b682b8676a2f3adf9f58790e327d'))
-paddle.fluid.layers.elementwise_floordiv (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '638ca44932743bda05caf3fcc15f1f0d'))
+paddle.fluid.layers.elementwise_add (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '5c0fb7298aec32525f96d451ae4c2851'))
+paddle.fluid.layers.elementwise_div (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '1da49b7cda887dd84087ef8c060fcf6a'))
+paddle.fluid.layers.elementwise_sub (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '992559c8327c61babd2ed25fc9047fbf'))
+paddle.fluid.layers.elementwise_mul (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '213db11a61dcb0f31159d343cc35e2f5'))
+paddle.fluid.layers.elementwise_max (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '409167a1409ec31b0d3a2f8852a7943f'))
+paddle.fluid.layers.elementwise_min (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '4e1322836eb69473d5606bfe346c5375'))
+paddle.fluid.layers.elementwise_pow (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'b9e7e9fa1ca28d8b6f07cc59eadb4a02'))
+paddle.fluid.layers.elementwise_mod (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', '614984304f810f3ddae6b489ec01296b'))
+paddle.fluid.layers.elementwise_floordiv (ArgSpec(args=['x', 'y', 'axis', 'act', 'name'], varargs=None, keywords=None, defaults=(-1, None, None)), ('document', 'a8c4b26d899246378e878f169582c7a4'))
 paddle.fluid.layers.uniform_random_batch_size_like (ArgSpec(args=['input', 'shape', 'dtype', 'input_dim_idx', 'output_dim_idx', 'min', 'max', 'seed'], varargs=None, keywords=None, defaults=('float32', 0, 0, -1.0, 1.0, 0)), ('document', 'c8c7518358cfbb3822a019e6b5fbea52'))
 paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '8c78ccb77e291e4a0f0673d34823ce4b'))
 paddle.fluid.layers.sampling_id (ArgSpec(args=['x', 'min', 'max', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0, 'float32')), ('document', '35428949368cad5121dd37f8522ef8b0'))
@@ -259,8 +259,8 @@ paddle.fluid.layers.tensor_array_to_tensor (ArgSpec(args=['input', 'axis', 'name
 paddle.fluid.layers.concat (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'f9e905b48123914c78055a45fe23106a'))
 paddle.fluid.layers.sums (ArgSpec(args=['input', 'out'], varargs=None, keywords=None, defaults=(None,)), ('document', '5df743d578638cd2bbb9369499b44af4'))
 paddle.fluid.layers.assign (ArgSpec(args=['input', 'output'], varargs=None, keywords=None, defaults=(None,)), ('document', 'b690184f3537df5501e4d9d8f31152a5'))
-paddle.fluid.layers.fill_constant_batch_size_like (ArgSpec(args=['input', 'shape', 'dtype', 'value', 'input_dim_idx', 'output_dim_idx'], varargs=None, keywords=None, defaults=(0, 0)), ('document', 'd4059a2f5763036b07018d76429f9acb'))
-paddle.fluid.layers.fill_constant (ArgSpec(args=['shape', 'dtype', 'value', 'force_cpu', 'out'], varargs=None, keywords=None, defaults=(False, None)), ('document', '1d8b14729639fa38509c79b9784740fa'))
+paddle.fluid.layers.fill_constant_batch_size_like (ArgSpec(args=['input', 'shape', 'dtype', 'value', 'input_dim_idx', 'output_dim_idx'], varargs=None, keywords=None, defaults=(0, 0)), ('document', 'baf63a2f3b647a2d5da6ba8afb6135ac'))
+paddle.fluid.layers.fill_constant (ArgSpec(args=['shape', 'dtype', 'value', 'force_cpu', 'out'], varargs=None, keywords=None, defaults=(False, None)), ('document', 'd6b76c7d2c7129f8d713ca74f1c2c287'))
 paddle.fluid.layers.argmin (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '677c09cc0fd7381974bfc845c4d9f0f2'))
 paddle.fluid.layers.argmax (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', 'ef64ee883998e7e246a854a845e11e2c'))
 paddle.fluid.layers.argsort (ArgSpec(args=['input', 'axis', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '0a85a9a145d2e24e05958a3f1322d68a'))
@@ -286,7 +286,7 @@ paddle.fluid.layers.less_than (ArgSpec(args=['x', 'y', 'force_cpu', 'cond'], var
 paddle.fluid.layers.less_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd6b173ae1a149e0bdfe7b8bf69285957'))
 paddle.fluid.layers.greater_than (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '2c9bd414caa6c615539018d27001b44c'))
 paddle.fluid.layers.greater_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '62c667d24e7b07e166b47a53b61b2ff4'))
-paddle.fluid.layers.equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '80c29b1dc64718f0116de90d1ac88a77'))
+paddle.fluid.layers.equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '788aa651e8b9fec79d16931ef3a33e90'))
 paddle.fluid.layers.not_equal (ArgSpec(args=['x', 'y', 'cond'], varargs=None, keywords=None, defaults=(None,)), ('document', '56148fb1024687a08e96af79bdc5c929'))
 paddle.fluid.layers.array_read (ArgSpec(args=['array', 'i'], varargs=None, keywords=None, defaults=None), ('document', 'dd68bead34dfbaf6b0a163fc1cc3c385'))
 paddle.fluid.layers.array_length (ArgSpec(args=['array'], varargs=None, keywords=None, defaults=None), ('document', 'ffb8b9578ec66db565b223d313aa82a2'))

python/paddle/fluid/layers/control_flow.py

@@ -1130,6 +1130,9 @@ def equal(x, y, cond=None):
     Examples:
         .. code-block:: python
 
+          import paddle.fluid as fluid
+          label = fluid.layers.data(name="label", shape=[3,10,32,32], dtype="float32")
+          limit = fluid.layers.data(name="limit", shape=[3,10,32,32], dtype="float32")
           less = fluid.layers.equal(x=label, y=limit)
     """
     helper = LayerHelper("equal", **locals())

python/paddle/fluid/layers/nn.py

@@ -4601,21 +4601,24 @@ def reduce_sum(input, dim=None, keep_dim=False, name=None):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid as fluid
             # x is a Tensor variable with following elements:
             #    [[0.2, 0.3, 0.5, 0.9]
             #     [0.1, 0.2, 0.6, 0.7]]
             # Each example is followed by the corresponding output tensor.
+            x = fluid.layers.data(name='x', shape=[4, 2], dtype='float32')
             fluid.layers.reduce_sum(x)  # [3.5]
             fluid.layers.reduce_sum(x, dim=0)  # [0.3, 0.5, 1.1, 1.6]
             fluid.layers.reduce_sum(x, dim=-1)  # [1.9, 1.6]
             fluid.layers.reduce_sum(x, dim=1, keep_dim=True)  # [[1.9], [1.6]]
 
-            # x is a Tensor variable with shape [2, 2, 2] and elements as below:
+            # y is a Tensor variable with shape [2, 2, 2] and elements as below:
             #      [[[1, 2], [3, 4]],
             #      [[5, 6], [7, 8]]]
             # Each example is followed by the corresponding output tensor.
-            fluid.layers.reduce_sum(x, dim=[1, 2]) # [10, 26]
-            fluid.layers.reduce_sum(x, dim=[0, 1]) # [16, 20]
+            y = fluid.layers.data(name='y', shape=[2, 2, 2], dtype='float32')
+            fluid.layers.reduce_sum(y, dim=[1, 2]) # [10, 26]
+            fluid.layers.reduce_sum(y, dim=[0, 1]) # [16, 20]
 
     """
     helper = LayerHelper('reduce_sum', **locals())
@@ -4658,22 +4661,24 @@ def reduce_mean(input, dim=None, keep_dim=False, name=None):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid as fluid
             # x is a Tensor variable with following elements:
             #    [[0.2, 0.3, 0.5, 0.9]
             #     [0.1, 0.2, 0.6, 0.7]]
             # Each example is followed by the correspending output tensor.
+            x = fluid.layers.data(name='x', shape=[4, 2], dtype='float32')
             fluid.layers.reduce_mean(x)  # [0.4375]
             fluid.layers.reduce_mean(x, dim=0)  # [0.15, 0.25, 0.55, 0.8]
             fluid.layers.reduce_mean(x, dim=-1)  # [0.475, 0.4]
-            fluid.layers.reduce_mean(
-                x, dim=1, keep_dim=True)  # [[0.475], [0.4]]
+            fluid.layers.reduce_mean(x, dim=1, keep_dim=True)  # [[0.475], [0.4]]
 
-            # x is a Tensor variable with shape [2, 2, 2] and elements as below:
+            # y is a Tensor variable with shape [2, 2, 2] and elements as below:
             #      [[[1.0, 2.0], [3.0, 4.0]],
             #      [[5.0, 6.0], [7.0, 8.0]]]
             # Each example is followed by the correspending output tensor.
-            fluid.layers.reduce_mean(x, dim=[1, 2]) # [2.5, 6.5]
-            fluid.layers.reduce_mean(x, dim=[0, 1]) # [4.0, 5.0]
+            y = fluid.layers.data(name='y', shape=[2, 2, 2], dtype='float32')
+            fluid.layers.reduce_mean(y, dim=[1, 2]) # [2.5, 6.5]
+            fluid.layers.reduce_mean(y, dim=[0, 1]) # [4.0, 5.0]
     """
     helper = LayerHelper('reduce_mean', **locals())
     out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
@@ -4714,21 +4719,24 @@ def reduce_max(input, dim=None, keep_dim=False, name=None):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid as fluid
             # x is a Tensor variable with following elements:
             #    [[0.2, 0.3, 0.5, 0.9]
             #     [0.1, 0.2, 0.6, 0.7]]
             # Each example is followed by the correspending output tensor.
+            x = fluid.layers.data(name='x', shape=[4, 2], dtype='float32')
             fluid.layers.reduce_max(x)  # [0.9]
             fluid.layers.reduce_max(x, dim=0)  # [0.2, 0.3, 0.6, 0.9]
             fluid.layers.reduce_max(x, dim=-1)  # [0.9, 0.7]
             fluid.layers.reduce_max(x, dim=1, keep_dim=True)  # [[0.9], [0.7]]
 
-            # x is a Tensor variable with shape [2, 2, 2] and elements as below:
+            # y is a Tensor variable with shape [2, 2, 2] and elements as below:
             #      [[[1.0, 2.0], [3.0, 4.0]],
             #      [[5.0, 6.0], [7.0, 8.0]]]
             # Each example is followed by the correspending output tensor.
-            fluid.layers.reduce_max(x, dim=[1, 2]) # [4.0, 8.0]
-            fluid.layers.reduce_max(x, dim=[0, 1]) # [7.0, 8.0]
+            y = fluid.layers.data(name='y', shape=[2, 2, 2], dtype='float32')
+            fluid.layers.reduce_max(y, dim=[1, 2]) # [4.0, 8.0]
+            fluid.layers.reduce_max(y, dim=[0, 1]) # [7.0, 8.0]
     """
     helper = LayerHelper('reduce_max', **locals())
     out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
@@ -4769,21 +4777,24 @@ def reduce_min(input, dim=None, keep_dim=False, name=None):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid as fluid
             # x is a Tensor variable with following elements:
             #    [[0.2, 0.3, 0.5, 0.9]
             #     [0.1, 0.2, 0.6, 0.7]]
             # Each example is followed by the correspending output tensor.
+            x = fluid.layers.data(name='x', shape=[4, 2], dtype='float32')
             fluid.layers.reduce_min(x)  # [0.1]
             fluid.layers.reduce_min(x, dim=0)  # [0.1, 0.2, 0.5, 0.7]
             fluid.layers.reduce_min(x, dim=-1)  # [0.2, 0.1]
             fluid.layers.reduce_min(x, dim=1, keep_dim=True)  # [[0.2], [0.1]]
 
-            # x is a Tensor variable with shape [2, 2, 2] and elements as below:
+            # y is a Tensor variable with shape [2, 2, 2] and elements as below:
             #      [[[1.0, 2.0], [3.0, 4.0]],
             #      [[5.0, 6.0], [7.0, 8.0]]]
             # Each example is followed by the correspending output tensor.
-            fluid.layers.reduce_min(x, dim=[1, 2]) # [1.0, 5.0]
-            fluid.layers.reduce_min(x, dim=[0, 1]) # [1.0, 2.0]
+            y = fluid.layers.data(name='y', shape=[2, 2, 2], dtype='float32')
+            fluid.layers.reduce_min(y, dim=[1, 2]) # [1.0, 5.0]
+            fluid.layers.reduce_min(y, dim=[0, 1]) # [1.0, 2.0]
     """
     helper = LayerHelper('reduce_min', **locals())
     out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
@@ -4824,22 +4835,25 @@ def reduce_prod(input, dim=None, keep_dim=False, name=None):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid as fluid
             # x is a Tensor variable with following elements:
             #    [[0.2, 0.3, 0.5, 0.9]
             #     [0.1, 0.2, 0.6, 0.7]]
             # Each example is followed by the correspending output tensor.
+            x = fluid.layers.data(name='x', shape=[4, 2], dtype='float32')
             fluid.layers.reduce_prod(x)  # [0.0002268]
             fluid.layers.reduce_prod(x, dim=0)  # [0.02, 0.06, 0.3, 0.63]
             fluid.layers.reduce_prod(x, dim=-1)  # [0.027, 0.0084]
             fluid.layers.reduce_prod(x, dim=1,
                                      keep_dim=True)  # [[0.027], [0.0084]]
 
-            # x is a Tensor variable with shape [2, 2, 2] and elements as below:
+            # y is a Tensor variable with shape [2, 2, 2] and elements as below:
             #      [[[1.0, 2.0], [3.0, 4.0]],
             #      [[5.0, 6.0], [7.0, 8.0]]]
             # Each example is followed by the correspending output tensor.
-            fluid.layers.reduce_prod(x, dim=[1, 2]) # [24.0, 1680.0]
-            fluid.layers.reduce_prod(x, dim=[0, 1]) # [105.0, 384.0]
+            y = fluid.layers.data(name='y', shape=[2, 2, 2], dtype='float32')
+            fluid.layers.reduce_prod(y, dim=[1, 2]) # [24.0, 1680.0]
+            fluid.layers.reduce_prod(y, dim=[0, 1]) # [105.0, 384.0]
     """
     helper = LayerHelper('reduce_prod', **locals())
     out = helper.create_variable_for_type_inference(dtype=helper.input_dtype())
@@ -9752,6 +9766,43 @@ for func in [
             "act (basestring|None): Activation applied to the output.",
             "name (basestring|None): Name of the output."
         ])
+    func.__doc__ = func.__doc__ + """
+
+Examples:
+  .. code-block:: python
+    
+    import paddle.fluid as fluid
+    # example 1: shape(x) = (2, 3, 4, 5), shape(y) = (2, 3, 4, 5)
+    x0 = fluid.layers.data(name="x0", shape=[2, 3, 4, 5], dtype='float32')
+    y0 = fluid.layers.data(name="y0", shape=[2, 3, 4, 5], dtype='float32')
+    z0 = fluid.layers.%s(x0, y0)
+
+    # example 2: shape(X) = (2, 3, 4, 5), shape(Y) = (5)
+    x1 = fluid.layers.data(name="x1", shape=[2, 3, 4, 5], dtype='float32')
+    y1 = fluid.layers.data(name="y1", shape=[5], dtype='float32')
+    z1 = fluid.layers.%s(x1, y1)
+
+    # example 3: shape(X) = (2, 3, 4, 5), shape(Y) = (4, 5), with axis=-1(default) or axis=2
+    x2 = fluid.layers.data(name="x2", shape=[2, 3, 4, 5], dtype='float32')
+    y2 = fluid.layers.data(name="y2", shape=[4, 5], dtype='float32')
+    z2 = fluid.layers.%s(x2, y2, axis=2)
+
+    # example 4: shape(X) = (2, 3, 4, 5), shape(Y) = (3, 4), with axis=1
+    x3 = fluid.layers.data(name="x3", shape=[2, 3, 4, 5], dtype='float32')
+    y3 = fluid.layers.data(name="y3", shape=[3, 4], dtype='float32')
+    z3 = fluid.layers.%s(x3, y3, axis=1)
+
+    # example 5: shape(X) = (2, 3, 4, 5), shape(Y) = (2), with axis=0
+    x4 = fluid.layers.data(name="x4", shape=[2, 3, 4, 5], dtype='float32')
+    y4 = fluid.layers.data(name="y4", shape=[2], dtype='float32')
+    z4 = fluid.layers.%s(x4, y4, axis=0)
+
+    # example 6: shape(X) = (2, 3, 4, 5), shape(Y) = (2, 1), with axis=0
+    x5 = fluid.layers.data(name="x5", shape=[2, 3, 4, 5], dtype='float32')
+    y5 = fluid.layers.data(name="y5", shape=[2], dtype='float32')
+    z5 = fluid.layers.%s(x5, y5, axis=0)
+    """ % (func.__name__, func.__name__, func.__name__, func.__name__,
+           func.__name__, func.__name__)
 
 
 def _logical_op(op_name, x, y, out=None, name=None, binary_op=True):

python/paddle/fluid/layers/tensor.py

@@ -385,6 +385,7 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None):
     Examples:
         .. code-block:: python
 
+          import paddle.fluid as fluid
           data = fluid.layers.fill_constant(shape=[1], value=0, dtype='int64')
     """
 
@@ -438,7 +439,9 @@ def fill_constant_batch_size_like(input,
 
         .. code-block:: python
 
-             data = fluid.layers.fill_constant_batch_size_like(
+             import paddle.fluid as fluid
+             like = fluid.layers.data(name='like', shape=[1], dtype='float32')
+             data = fluid.lgyers.fill_constant_batch_size_like(
                          input=like, shape=[1], value=0, dtype='int64')
 
     """