Add api doc code examples (#17285)

* Add api doc code examples

add or fix topk, squeeze, stack, StaticRNN,
StaticRNN memory in doc

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* Add squeeze md5.

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

* Add import package

test=develop
Signed-off-by: Nzhaoyuchen <zhaoyuchen01@baidu.com>

paddle/fluid/API.spec

@@ -120,7 +120,7 @@ paddle.fluid.layers.ctc_greedy_decoder (ArgSpec(args=['input', 'blank', 'name'],
 paddle.fluid.layers.edit_distance (ArgSpec(args=['input', 'label', 'normalized', 'ignored_tokens'], varargs=None, keywords=None, defaults=(True, None)), ('document', '97f0262f97602644c83142789d784571'))
 paddle.fluid.layers.l2_normalize (ArgSpec(args=['x', 'axis', 'epsilon', 'name'], varargs=None, keywords=None, defaults=(1e-12, None)), ('document', '35c6a241bcc1a1fc89508860d82ad62b'))
 paddle.fluid.layers.matmul (ArgSpec(args=['x', 'y', 'transpose_x', 'transpose_y', 'alpha', 'name'], varargs=None, keywords=None, defaults=(False, False, 1.0, None)), ('document', 'b4cbe1ac451005df6dad12e9ffdccca9'))
-paddle.fluid.layers.topk (ArgSpec(args=['input', 'k', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'd3570c02f71bcd78e60b3f31dc8f5b32'))
+paddle.fluid.layers.topk (ArgSpec(args=['input', 'k', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2a1e9ea041ff4d6a9948bb8d03b743ea'))
 paddle.fluid.layers.warpctc (ArgSpec(args=['input', 'label', 'blank', 'norm_by_times', 'use_cudnn'], varargs=None, keywords=None, defaults=(0, False, False)), ('document', 'aaba49c038ba927f0a8e45c0c9a686ab'))
 paddle.fluid.layers.sequence_reshape (ArgSpec(args=['input', 'new_dim'], varargs=None, keywords=None, defaults=None), ('document', 'a10ab9bf88d4a7e328882d411abb6fd1'))
 paddle.fluid.layers.transpose (ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'a1feac48b843d679db82312dc85885f4'))
@@ -139,7 +139,7 @@ paddle.fluid.layers.smooth_l1 (ArgSpec(args=['x', 'y', 'inside_weight', 'outside
 paddle.fluid.layers.one_hot (ArgSpec(args=['input', 'depth'], varargs=None, keywords=None, defaults=None), ('document', '960fc799549c202da1e85d626cb2c962'))
 paddle.fluid.layers.autoincreased_step_counter (ArgSpec(args=['counter_name', 'begin', 'step'], varargs=None, keywords=None, defaults=(None, 1, 1)), ('document', '67afefa80b6cc38801bd5b631fed8a4a'))
 paddle.fluid.layers.reshape (ArgSpec(args=['x', 'shape', 'actual_shape', 'act', 'inplace', 'name'], varargs=None, keywords=None, defaults=(None, None, False, None)), ('document', '323c019f257e55ddea4a824a362de62f'))
-paddle.fluid.layers.squeeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '3229d06517f794e86ca3da14c38b1465'))
+paddle.fluid.layers.squeeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '06588973f613e9dcd592724322864589'))
 paddle.fluid.layers.unsqueeze (ArgSpec(args=['input', 'axes', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'bbd62da391b1df984a1909d069a759b2'))
 paddle.fluid.layers.lod_reset (ArgSpec(args=['x', 'y', 'target_lod'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'f122194c562bd674f6ecdccf33785f99'))
 paddle.fluid.layers.lrn (ArgSpec(args=['input', 'n', 'k', 'alpha', 'beta', 'name'], varargs=None, keywords=None, defaults=(5, 1.0, 0.0001, 0.75, None)), ('document', '330241f0bc57e9d16973ec322a6aef71'))
@@ -176,7 +176,7 @@ paddle.fluid.layers.leaky_relu (ArgSpec(args=['x', 'alpha', 'name'], varargs=Non
 paddle.fluid.layers.soft_relu (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None)), ('document', '869adce548c342d6cc1bd88a948d83c9'))
 paddle.fluid.layers.flatten (ArgSpec(args=['x', 'axis', 'name'], varargs=None, keywords=None, defaults=(1, None)), ('document', 'cb295c13cb957db85cd9609269d7784d'))
 paddle.fluid.layers.sequence_mask (ArgSpec(args=['x', 'maxlen', 'dtype', 'name'], varargs=None, keywords=None, defaults=(None, 'int64', None)), ('document', 'f0dd6eddd3bff015a3c05269d82fcbd8'))
-paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '367cfbb642839beacb5d117e2d2b4041'))
+paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '43a9fef72d45df3bc58f52b93cdb61cb'))
 paddle.fluid.layers.pad2d (ArgSpec(args=['input', 'paddings', 'mode', 'pad_value', 'data_format', 'name'], varargs=None, keywords=None, defaults=([0, 0, 0, 0], 'constant', 0.0, 'NCHW', None)), ('document', '7f4d46320cc077ca2e8db600c35f4030'))
 paddle.fluid.layers.unstack (ArgSpec(args=['x', 'axis', 'num'], varargs=None, keywords=None, defaults=(0, None)), ('document', '98eb9d633116efcfc6f90c114bd44fd6'))
 paddle.fluid.layers.sequence_enumerate (ArgSpec(args=['input', 'win_size', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', 'f6028537085dc296103bbbd85fa7763d'))
@@ -303,7 +303,7 @@ paddle.fluid.layers.DynamicRNN.static_input (ArgSpec(args=['self', 'x'], varargs
 paddle.fluid.layers.DynamicRNN.step_input (ArgSpec(args=['self', 'x', 'level'], varargs=None, keywords=None, defaults=(0,)), ('document', '7568c5ac7622a10288d3307a94134655'))
 paddle.fluid.layers.DynamicRNN.update_memory (ArgSpec(args=['self', 'ex_mem', 'new_mem'], varargs=None, keywords=None, defaults=None), ('document', '5d83987da13b98363d6a807a52d8024f'))
 paddle.fluid.layers.StaticRNN.__init__ (ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.layers.StaticRNN.memory (ArgSpec(args=['self', 'init', 'shape', 'batch_ref', 'init_value', 'init_batch_dim_idx', 'ref_batch_dim_idx'], varargs=None, keywords=None, defaults=(None, None, None, 0.0, 0, 1)), ('document', '72530f299d6451a567cf4a12dc3fb1ff'))
+paddle.fluid.layers.StaticRNN.memory (ArgSpec(args=['self', 'init', 'shape', 'batch_ref', 'init_value', 'init_batch_dim_idx', 'ref_batch_dim_idx'], varargs=None, keywords=None, defaults=(None, None, None, 0.0, 0, 1)), ('document', 'f1b60dc4194d0bb714d6c6f5921b227f'))
 paddle.fluid.layers.StaticRNN.output (ArgSpec(args=['self'], varargs='outputs', keywords=None, defaults=None), ('document', 'df6ceab6e6c9bd31e97914d7e7538137'))
 paddle.fluid.layers.StaticRNN.step (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6d3e0a5d9aa519a9773a36e1620ea9b7'))
 paddle.fluid.layers.StaticRNN.step_input (ArgSpec(args=['self', 'x'], varargs=None, keywords=None, defaults=None), ('document', '903387ec11f3d0bf46821d31a68cffa5'))

python/paddle/fluid/layers/control_flow.py

@@ -276,27 +276,29 @@ class StaticRNN(object):
     the same. And the meaning of each axis of input and output are the same.**
 
     Examples:
-        >>> import paddle.fluid as fluid
-        >>> import paddle.fluid.layers as layers
-        >>>
-        >>> vocab_size, hidden_size=10000, 200
-        >>> x = layers.data(name="x", shape=[-1, 1, 1], dtype='int64')
-        >>> x_emb = layers.embedding(
-        >>>         input=x,
-        >>>         size=[vocab_size, hidden_size],
-        >>>         dtype='float32',
-        >>>         is_sparse=False)
-        >>> x_emb = layers.transpose(x_emb, perm=[1, 0, 2])
-        >>>
-        >>> rnn = fluid.layers.StaticRNN()
-        >>> with rnn.step():
-        >>>    word = rnn.step_input(x_emb)
-        >>>    prev = rnn.memory(shape=[-1, hidden_size], batch_ref = word)
-        >>>    hidden = fluid.layers.fc(input=[word, prev], size=hidden_size, act='relu')
-        >>>    rnn.update_memory(prev, hidden)  # set prev to hidden
-        >>>    rnn.step_output(hidden)
-        >>>
-        >>> result = rnn()
+        .. code-block:: python
+
+            import paddle.fluid as fluid
+            import paddle.fluid.layers as layers
+
+            vocab_size, hidden_size=10000, 200
+            x = layers.data(name="x", shape=[-1, 1, 1], dtype='int64')
+            x_emb = layers.embedding(
+                input=x,
+                size=[vocab_size, hidden_size],
+                dtype='float32',
+                is_sparse=False)
+            x_emb = layers.transpose(x_emb, perm=[1, 0, 2])
+
+            rnn = fluid.layers.StaticRNN()
+            with rnn.step():
+                word = rnn.step_input(x_emb)
+                prev = rnn.memory(shape=[-1, hidden_size], batch_ref = word)
+                hidden = fluid.layers.fc(input=[word, prev], size=hidden_size, act='relu')
+                rnn.update_memory(prev, hidden)  # set prev to hidden
+                rnn.step_output(hidden)
+
+            result = rnn()
 
     The StaticRNN will unfold sequence into time steps. Users need to define
     how to process each time step during the :code:`with` step.
@@ -361,6 +363,27 @@ class StaticRNN(object):
 
         Returns:
             The memory variable.
+        Examples:
+            .. code-block:: python
+
+                import paddle.fluid as fluid
+                import paddle.fluid.layers as layers
+
+                vocab_size, hidden_size=10000, 200
+                x = layers.data(name="x", shape=[-1, 1, 1], dtype='int64')
+                x_emb = layers.embedding(
+                    input=x,
+                    size=[vocab_size, hidden_size],
+                    dtype='float32',
+                    is_sparse=False)
+                x_emb = layers.transpose(x_emb, perm=[1, 0, 2])
+
+                rnn = fluid.layers.StaticRNN()
+                with rnn.step():
+                    word = rnn.step_input(x_emb)
+                    prev = rnn.memory(shape=[-1, hidden_size], batch_ref = word)
+                    hidden = fluid.layers.fc(input=[word, prev], size=hidden_size, act='relu')
+                    rnn.update_memory(prev, hidden)
         """
         self._assert_in_rnn_block_('memory')
         if init is None:

python/paddle/fluid/layers/nn.py

@@ -5158,6 +5158,8 @@ def topk(input, k, name=None):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid.layers as layers
+            input = layers.data(name="input", shape=[13, 11], dtype='float32')
             top5_values, top5_indices = layers.topk(input, k=5)
     """
     helper = LayerHelper("top_k", **locals())
@@ -6648,8 +6650,9 @@ def squeeze(input, axes, name=None):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid.layers as layers
             x = layers.data(name='x', shape=[5, 1, 10])
-            y = layers.sequeeze(input=x, axes=[1])
+            y = layers.squeeze(input=x, axes=[1])
     """
     assert not in_dygraph_mode(), (
         "squeeze layer is not supported in dygraph mode yet.")
@@ -9048,6 +9051,14 @@ def stack(x, axis=0):
     Returns:
         Variable: The stacked variable.
 
+    Examples:
+        .. code-block:: python
+
+            import paddle.fluid.layers as layers
+            x1 = layers.data(name='x1', shape[1, 2], dtype='int32')
+            x2 = layers.data(name='x2', shape[1, 2], dtype='int32')
+            data = layers.stack([x1,x2])
+
     """
 
     helper = LayerHelper('stack', **locals())