Refine python api code example note: (#17369)

* fix:
1. infernce multi card occupy
2. facebox model inference occupy too much
test=develop

* refine python api comments: shuffle, while, scale, sampled_softmax_with_cross_entropy, scatter,
round, sin, sqrt, shape, split, soft_relu, slice, selu, ifelse, switch.
test=develodp

* fix conflict error.
test=develop

paddle/fluid/API.spec

@@ -115,7 +115,7 @@ paddle.fluid.layers.sequence_first_step (ArgSpec(args=['input'], varargs=None, k
 paddle.fluid.layers.sequence_last_step (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'c16a892f44f7fe71bfa5afc32d3f34ce'))
 paddle.fluid.layers.sequence_slice (ArgSpec(args=['input', 'offset', 'length', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'fdcea0e8b5bc7d8d4b1b072c521014e6'))
 paddle.fluid.layers.dropout (ArgSpec(args=['x', 'dropout_prob', 'is_test', 'seed', 'name', 'dropout_implementation'], varargs=None, keywords=None, defaults=(False, None, None, 'downgrade_in_infer')), ('document', 'f1dd22f7351f7f9853212958e0d8aa7a'))
-paddle.fluid.layers.split (ArgSpec(args=['input', 'num_or_sections', 'dim', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '652625345c2acb900029c78cc75f8aa6'))
+paddle.fluid.layers.split (ArgSpec(args=['input', 'num_or_sections', 'dim', 'name'], varargs=None, keywords=None, defaults=(-1, None)), ('document', '59b28903ce8fb6a7e3861ff355592eb4'))
 paddle.fluid.layers.ctc_greedy_decoder (ArgSpec(args=['input', 'blank', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '2bc3a59efa9d52b628a6255422d9f0e8'))
 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'))
@@ -126,7 +126,7 @@ paddle.fluid.layers.sequence_reshape (ArgSpec(args=['input', 'new_dim'], varargs
 paddle.fluid.layers.transpose (ArgSpec(args=['x', 'perm', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '8e72db173d4c082e27cb11f31d8c9bfa'))
 paddle.fluid.layers.im2sequence (ArgSpec(args=['input', 'filter_size', 'stride', 'padding', 'input_image_size', 'out_stride', 'name'], varargs=None, keywords=None, defaults=(1, 1, 0, None, 1, None)), ('document', '33134416fc27dd65a767e5f15116ee16'))
 paddle.fluid.layers.nce (ArgSpec(args=['input', 'label', 'num_total_classes', 'sample_weight', 'param_attr', 'bias_attr', 'num_neg_samples', 'name', 'sampler', 'custom_dist', 'seed', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, 'uniform', None, 0, False)), ('document', '32b3c442da0f3df682b5fcac10468116'))
-paddle.fluid.layers.sampled_softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'num_samples', 'num_true', 'remove_accidental_hits', 'use_customized_samples', 'customized_samples', 'customized_probabilities', 'seed'], varargs=None, keywords=None, defaults=(1, True, False, None, None, 0)), ('document', '5db30b8a74e8c93687943a3e8d221da0'))
+paddle.fluid.layers.sampled_softmax_with_cross_entropy (ArgSpec(args=['logits', 'label', 'num_samples', 'num_true', 'remove_accidental_hits', 'use_customized_samples', 'customized_samples', 'customized_probabilities', 'seed'], varargs=None, keywords=None, defaults=(1, True, False, None, None, 0)), ('document', '4521da36af223d5a95bb8f190b5c7add'))
 paddle.fluid.layers.hsigmoid (ArgSpec(args=['input', 'label', 'num_classes', 'param_attr', 'bias_attr', 'name', 'path_table', 'path_code', 'is_custom', 'is_sparse'], varargs=None, keywords=None, defaults=(None, None, None, None, None, False, False)), ('document', '80641ee6810b1cdc3fd6e14fc89ecc9d'))
 paddle.fluid.layers.beam_search (ArgSpec(args=['pre_ids', 'pre_scores', 'ids', 'scores', 'beam_size', 'end_id', 'level', 'is_accumulated', 'name', 'return_parent_idx'], varargs=None, keywords=None, defaults=(0, True, None, False)), ('document', '1270395ce97a4e1b556104abbb14f096'))
 paddle.fluid.layers.row_conv (ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None)), ('document', '17485788fffe4e2d36dc58c2ac8d174e'))
@@ -154,12 +154,12 @@ paddle.fluid.layers.image_resize_short (ArgSpec(args=['input', 'out_short_len',
 paddle.fluid.layers.resize_bilinear (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners', 'align_mode'], varargs=None, keywords=None, defaults=(None, None, None, None, True, 1)), ('document', '746bf58fdb1bd475f8c5f996b05b0e52'))
 paddle.fluid.layers.resize_nearest (ArgSpec(args=['input', 'out_shape', 'scale', 'name', 'actual_shape', 'align_corners'], varargs=None, keywords=None, defaults=(None, None, None, None, True)), ('document', '9baf9288c862161ff850d45228047a5e'))
 paddle.fluid.layers.gather (ArgSpec(args=['input', 'index'], varargs=None, keywords=None, defaults=None), ('document', '01a198d6fff38d5f0d8180a40b228085'))
-paddle.fluid.layers.scatter (ArgSpec(args=['input', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '65f8e9d8ddfd0b412f940579c4faa342'))
+paddle.fluid.layers.scatter (ArgSpec(args=['input', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '846a53fd2991bdaab3a8134008eef0c7'))
 paddle.fluid.layers.sequence_scatter (ArgSpec(args=['input', 'index', 'updates', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '71df5136cf03b06c65027b692fe78f1a'))
 paddle.fluid.layers.random_crop (ArgSpec(args=['x', 'shape', 'seed'], varargs=None, keywords=None, defaults=(None,)), ('document', 'c9ab9e460ef0a1823249935a30e82c66'))
 paddle.fluid.layers.mean_iou (ArgSpec(args=['input', 'label', 'num_classes'], varargs=None, keywords=None, defaults=None), ('document', 'e3b6630ba43cb13dfeeb1601cb64d671'))
 paddle.fluid.layers.relu (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', 'bf1676268df8ef100b8ab01d51336b25'))
-paddle.fluid.layers.selu (ArgSpec(args=['x', 'scale', 'alpha', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', '9044c7fe667b76cb2d9264f2db11f417'))
+paddle.fluid.layers.selu (ArgSpec(args=['x', 'scale', 'alpha', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'f93c61f5b0bf933cd425a64dca2c4fdd'))
 paddle.fluid.layers.log (ArgSpec(args=['x', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '056af2c0e6e22d94e8df7fc39677707f'))
 paddle.fluid.layers.crop (ArgSpec(args=['x', 'shape', 'offsets', 'name'], varargs=None, keywords=None, defaults=(None, None, None)), ('document', 'ddf9837ee83e549119210a3d714d5f44'))
 paddle.fluid.layers.rank_loss (ArgSpec(args=['label', 'left', 'right', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '1098b7a70c7696cc7437d6d57b5d89ed'))
@@ -173,7 +173,7 @@ paddle.fluid.layers.swish (ArgSpec(args=['x', 'beta', 'name'], varargs=None, key
 paddle.fluid.layers.prelu (ArgSpec(args=['x', 'mode', 'param_attr', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'f6acef7ff7d887e49ff499fbb1dad4a9'))
 paddle.fluid.layers.brelu (ArgSpec(args=['x', 't_min', 't_max', 'name'], varargs=None, keywords=None, defaults=(0.0, 24.0, None)), ('document', '3db337c195e156e6ef2b8b4a57113600'))
 paddle.fluid.layers.leaky_relu (ArgSpec(args=['x', 'alpha', 'name'], varargs=None, keywords=None, defaults=(0.02, None)), ('document', 'f878486c82b576938151daad0de995a0'))
-paddle.fluid.layers.soft_relu (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None)), ('document', '869adce548c342d6cc1bd88a948d83c9'))
+paddle.fluid.layers.soft_relu (ArgSpec(args=['x', 'threshold', 'name'], varargs=None, keywords=None, defaults=(40.0, None)), ('document', '3490ed5c9835ae039a82979daf3918a4'))
 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', '767cea598dee8e2b94f04110fa6b7e67'))
 paddle.fluid.layers.stack (ArgSpec(args=['x', 'axis'], varargs=None, keywords=None, defaults=(0,)), ('document', '43a9fef72d45df3bc58f52b93cdb61cb'))
@@ -182,7 +182,7 @@ paddle.fluid.layers.unstack (ArgSpec(args=['x', 'axis', 'num'], varargs=None, ke
 paddle.fluid.layers.sequence_enumerate (ArgSpec(args=['input', 'win_size', 'pad_value', 'name'], varargs=None, keywords=None, defaults=(0, None)), ('document', '2e49e97069beb57ee89d54ed088ae2da'))
 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', '30190413b2fa442e7466d6cf2ce5ea07'))
+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'))
@@ -197,8 +197,8 @@ paddle.fluid.layers.gaussian_random (ArgSpec(args=['shape', 'mean', 'std', 'seed
 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'))
 paddle.fluid.layers.gaussian_random_batch_size_like (ArgSpec(args=['input', 'shape', 'input_dim_idx', 'output_dim_idx', 'mean', 'std', 'seed', 'dtype'], varargs=None, keywords=None, defaults=(0, 0, 0.0, 1.0, 0, 'float32')), ('document', '9e520987168f8ddb7dd71ffd68aa352c'))
 paddle.fluid.layers.sum (ArgSpec(args=['x'], varargs=None, keywords=None, defaults=None), ('document', 'a418e3ccb5e2ac21bd60f5cc221d5860'))
-paddle.fluid.layers.slice (ArgSpec(args=['input', 'axes', 'starts', 'ends'], varargs=None, keywords=None, defaults=None), ('document', '01dbb91e7c74cb11336cd531013de51a'))
-paddle.fluid.layers.shape (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', '17db0f814eb7bb5a3fac1ca6e60e16d8'))
+paddle.fluid.layers.slice (ArgSpec(args=['input', 'axes', 'starts', 'ends'], varargs=None, keywords=None, defaults=None), ('document', 'bcb6380dbcf288058f8c1e14b82cbe0d'))
+paddle.fluid.layers.shape (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'bf61c8f79d795a8371bdb3b5468aa82b'))
 paddle.fluid.layers.rank (ArgSpec(args=['input'], varargs=None, keywords=None, defaults=None), ('document', 'ee1386c42ecc8f424fe3fb21862fefc2'))
 paddle.fluid.layers.logical_and (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'cdcf20c494c92060d10feb9374532f42'))
 paddle.fluid.layers.logical_or (ArgSpec(args=['x', 'y', 'out', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', '0eae3f726a4afe590757552fa3ced012'))
@@ -240,7 +240,7 @@ paddle.fluid.layers.sign (ArgSpec(args=['x'], varargs=None, keywords=None, defau
 paddle.fluid.layers.data (ArgSpec(args=['name', 'shape', 'append_batch_size', 'dtype', 'lod_level', 'type', 'stop_gradient'], varargs=None, keywords=None, defaults=(True, 'float32', 0, VarType.LOD_TENSOR, True)), ('document', 'adf285346e23316097f7789b572491e9'))
 paddle.fluid.layers.open_files (ArgSpec(args=['filenames', 'shapes', 'lod_levels', 'dtypes', 'thread_num', 'buffer_size', 'pass_num', 'is_test'], varargs=None, keywords=None, defaults=(None, None, 1, None)), ('document', 'dce69a78638da8f7ad80b1fc00ed2029'))
 paddle.fluid.layers.read_file (ArgSpec(args=['reader'], varargs=None, keywords=None, defaults=None), ('document', '32181f6037e387fb6e68a5beaafe33b6'))
-paddle.fluid.layers.shuffle (ArgSpec(args=['reader', 'buffer_size'], varargs=None, keywords=None, defaults=None), ('document', 'f967a73426db26f970bc70bfb03cffca'))
+paddle.fluid.layers.shuffle (ArgSpec(args=['reader', 'buffer_size'], varargs=None, keywords=None, defaults=None), ('document', 'f29d7d159e114f73fc988d9a86805841'))
 paddle.fluid.layers.batch (ArgSpec(args=['reader', 'batch_size'], varargs=None, keywords=None, defaults=None), ('document', 'fcb24383c6eef2ca040ee824c26e22fd'))
 paddle.fluid.layers.double_buffer (ArgSpec(args=['reader', 'place', 'name'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'c13b8a8521bea5f8123b925ae2a5d5db'))
 paddle.fluid.layers.random_data_generator (ArgSpec(args=['low', 'high', 'shapes', 'lod_levels', 'for_parallel'], varargs=None, keywords=None, defaults=(True,)), ('document', '9b7f0f86ec24bbc97643cadcb6499cff'))
@@ -277,8 +277,8 @@ paddle.fluid.layers.diag (ArgSpec(args=['diagonal'], varargs=None, keywords=None
 paddle.fluid.layers.While.__init__ (ArgSpec(args=['self', 'cond', 'is_test', 'name'], varargs=None, keywords=None, defaults=(False, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.layers.While.block (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.layers.Switch.__init__ (ArgSpec(args=['self', 'name'], varargs=None, keywords=None, defaults=(None,)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.layers.Switch.case (ArgSpec(args=['self', 'condition'], varargs=None, keywords=None, defaults=None), ('document', 'f7c7160014c1b46cfeda9dd5808d1789'))
-paddle.fluid.layers.Switch.default (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '50853ae884df03d9c36703bb46d9ef07'))
+paddle.fluid.layers.Switch.case (ArgSpec(args=['self', 'condition'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
+paddle.fluid.layers.Switch.default (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.layers.increment (ArgSpec(args=['x', 'value', 'in_place'], varargs=None, keywords=None, defaults=(1.0, True)), ('document', '73bb96ec4783ec1a11e760e8851b0e77'))
 paddle.fluid.layers.array_write (ArgSpec(args=['x', 'i', 'array'], varargs=None, keywords=None, defaults=(None,)), ('document', '40b6d15f4c86b2b09df340d7778ad713'))
 paddle.fluid.layers.create_array (ArgSpec(args=['dtype'], varargs=None, keywords=None, defaults=None), ('document', '2d4f20087080ba5105b55205ad5c5b6a'))

python/paddle/fluid/layers/control_flow.py

@@ -629,18 +629,20 @@ class While(object):
 
     Examples:
           .. code-block:: python
-
-            d0 = layers.data("d0", shape=[10], dtype='float32')
-            data_array = layers.array_write(x=d0, i=i)
-            array_len = layers.fill_constant(shape=[1],dtype='int64', value=3)
-
-            cond = layers.less_than(x=i, y=array_len)
-            while_op = layers.While(cond=cond)
+            
+            import paddle.fluid as fluid
+            
+            i = fluid.layers.fill_constant(shape=[1], dtype='int64', value=0)
+            d0 = fluid.layers.data("d0", shape=[10], dtype='float32')
+            data_array = fluid.layers.array_write(x=d0, i=i)
+            array_len = fluid.layers.fill_constant(shape=[1],dtype='int64', value=3)
+
+            cond = fluid.layers.less_than(x=i, y=array_len)
+            while_op = fluid.layers.While(cond=cond)
             with while_op.block():
-                d = layers.array_read(array=data_array, i=i)
-                i = layers.increment(x=i, in_place=True)
-                layers.array_write(result, i=i, array=d)
-                layers.less_than(x=i, y=array_len, cond=cond)
+                d = fluid.layers.array_read(array=data_array, i=i)
+                i = fluid.layers.increment(x=i, value=1, in_place=True)
+                fluid.layers.less_than(x=i, y=array_len, cond=cond)            
     """
 
     BEFORE_WHILE_BLOCK = 0
@@ -1409,23 +1411,30 @@ class Switch(object):
 
     Examples:
         .. code-block:: python
+            
+            import paddle.fluid as fluid
 
-            lr = fluid.layers.tensor.create_global_var(
+            lr = fluid.layers.create_global_var(
                 shape=[1],
                 value=0.0,
                 dtype='float32',
                 persistable=True,
                 name="learning_rate")
-            one_var = tensor.fill_constant(
+            zero_var = fluid.layers.fill_constant(
+                 shape=[1], dtype='float32', value=0.0)
+            one_var = fluid.layers.fill_constant(
                 shape=[1], dtype='float32', value=1.0)
-            two_var = tensor.fill_constant(
-                shape=[1], dtype='float32', value=2.0)
+            two_var = fluid.layers.fill_constant(
+                shape=[1], dtype='float32', value=2.0) 
+
+            global_step = fluid.layers.autoincreased_step_counter(
+                   counter_name='@LR_DECAY_COUNTER@', begin=0, step=1)
 
             with fluid.layers.control_flow.Switch() as switch:
                 with switch.case(global_step == zero_var):
-                    fluid.layers.tensor.assign(input=one_var, output=lr)
+                    fluid.layers.assign(input=one_var, output=lr)
                 with switch.default():
-                    fluid.layers.tensor.assign(input=two_var, output=lr)
+                    fluid.layers.assign(input=two_var, output=lr)
 
     """
 
@@ -1435,8 +1444,6 @@ class Switch(object):
         self.pre_not_conditions = []
 
     def case(self, condition):
-        """create a new block for this condition
-        """
         if not self.inside_scope:
             raise ValueError("case should be called inside with")
 
@@ -1458,9 +1465,6 @@ class Switch(object):
         return ConditionalBlockGuard(cond_block)
 
     def default(self):
-        """
-        create a default case for this switch
-        """
         pre_cond_num = len(self.pre_not_conditions)
         if pre_cond_num == 0:
             raise ValueError("there should be at least one condition")
@@ -1529,8 +1533,12 @@ class IfElse(object):
     Examples:
           .. code-block:: python
 
+            import paddle.fluid as fluid
+
+            image = fluid.layers.data(name="X", shape=[2, 5, 5], dtype='float32')
+            label = fluid.layers.data(name='label', shape=[1], dtype='int64')
             limit = fluid.layers.fill_constant_batch_size_like(
-                input=label, dtype='int64', shape=[1], value=5.0)
+                 input=label, dtype='int64', shape=[1], value=5.0)
             cond = fluid.layers.less_than(x=label, y=limit)
             ie = fluid.layers.IfElse(cond)
             with ie.true_block():

python/paddle/fluid/layers/io.py

@@ -992,6 +992,19 @@ def shuffle(reader, buffer_size):
 
     Returns:
         callable: the new reader whose output is shuffled.
+
+    Examples:
+        .. code-block:: python
+
+            raw_reader = fluid.layers.io.open_files(filenames=['./data1.recordio',
+                                                           './data2.recordio'],
+                                                    shapes=[(3,224,224), (1,)],
+                                                    lod_levels=[0, 0],
+                                                    dtypes=['float32', 'int64'],
+                                                    thread_num=2,
+                                                    buffer_size=2)
+            batch_reader = fluid.layers.batch(reader=raw_reader, batch_size=5)
+            shuffle_reader = fluid.layers.shuffle(reader=batch_reader, buffer_size=5000)
     """
     return __create_unshared_decorated_reader__(
         'create_shuffle_reader', reader, {'buffer_size': int(buffer_size)})

python/paddle/fluid/layers/nn.py

@@ -4980,16 +4980,21 @@ def split(input, num_or_sections, dim=-1, name=None):
     Examples:
         .. code-block:: python
 
-            # x is a Tensor variable with shape [3, 9, 5]:
-            x0, x1, x2 = fluid.layers.split(x, num_or_sections=3, dim=1)
-            x0.shape  # [3, 3, 5]
-            x1.shape  # [3, 3, 5]
-            x2.shape  # [3, 3, 5]
-            x0, x1, x2 = fluid.layers.split(
-                x, num_or_sections=[2, 3, 4], dim=1)
-            x0.shape  # [3, 2, 5]
-            x1.shape  # [3, 3, 5]
-            x2.shape  # [3, 4, 5]
+            import paddle.fluid as fluid
+
+            # input is a variable which shape is [-1, 3, 9, 5]
+            input = fluid.layers.data(
+                 name="input", shape=[3, 9, 5], dtype="float32")
+
+            x0, x1, x2 = fluid.layers.split(x, num_or_sections=3, dim=2)
+            # x0.shape [-1, 3, 3, 5]
+            # x1.shape [-1, 3, 3, 5]
+            # x2.shape [-1, 3, 3, 5]
+
+            x0, x1, x2 = fluid.layers.split(input, num_or_sections=3, dim=2)
+            # x0.shape [-1, 3, 2, 5]
+            # x1.shape [-1, 3, 3, 5]
+            # x2.shape [-1, 3, 4, 5]
     """
     helper = LayerHelper('split', **locals())
     input_shape = input.shape
@@ -6406,11 +6411,13 @@ def sampled_softmax_with_cross_entropy(logits,
     Examples:
         .. code-block:: python
 
-            logits = fluid.layers.data(name='data', shape=[256], dtype='float32')
+            import paddle.fluid as fluid
+
+            input = fluid.layers.data(name='data', shape=[256], dtype='float32')
             label = fluid.layers.data(name='label', shape=[5], dtype='int64')
-            fc = fluid.layers.fc(input=data, size=100)
+            fc = fluid.layers.fc(input=input, size=100)
             out = fluid.layers.sampled_softmax_with_cross_entropy(
-                logits=fc, label=label, num_samples=25)
+                      logits=fc, label=label, num_samples=25)
     """
     helper = LayerHelper('sample_logits', **locals())
     samples = helper.create_variable_for_type_inference(dtype='int64')
@@ -7862,8 +7869,13 @@ def scatter(input, index, updates, name=None):
 
         .. code-block:: python
 
-            output = fluid.layers.scatter(input, index, updates)
+            import paddle.fluid as fluid
+
+            input = fluid.layers.data(name='data', shape=[3, 5, 9], dtype='float32', append_batch_size=False)
+            index = fluid.layers.data(name='index', shape=[3], dtype='int64', append_batch_size=False)
+            updates = fluid.layers.data(name='update', shape=[3, 5, 9], dtype='float32', append_batch_size=False)
 
+            output = fluid.layers.scatter(input, index, updates)
     """
     helper = LayerHelper('scatter', **locals())
     dtype = helper.input_dtype()
@@ -8078,8 +8090,12 @@ def selu(x, scale=None, alpha=None, name=None):
     Examples:
 
         .. code-block:: python
-
-            output = fluid.layers.selu(x)
+             
+            import paddle.fluid as fluid
+          
+            input = fluid.layers.data(
+                 name="input", shape=[3, 9, 5], dtype="float32")
+            output = fluid.layers.selu(input)
     """
     helper = LayerHelper('selu', **locals())
     dtype = helper.input_dtype(input_param_name='x')
@@ -8904,9 +8920,11 @@ def soft_relu(x, threshold=40.0, name=None):
 
     Examples:
 
-        .. code-block:: python
-
-            x = fluid.layers.data(name="x", shape=[2,3,16,16], dtype="float32")
+        .. code-block:: python 
+ 
+            import paddle.fluid as fluid
+   
+            x = fluid.layers.data(name="x", shape=[3,16,16], dtype="float32")
             y = fluid.layers.soft_relu(x, threshold=20.0)
     """
     helper = LayerHelper('soft_relu', **locals())
@@ -9525,14 +9543,16 @@ def slice(input, axes, starts, ends):
     Examples:
         .. code-block:: python
 
+            import paddle.fluid as fluid
+ 
             starts = [1, 0, 2]
             ends = [3, 3, 4]
             axes = [0, 1, 2]
 
-            input = layers.data(
+            input = fluid.layers.data(
                 name="input", shape=[3, 4, 5, 6], dtype='float32')
 
-            out = layers.slice(input, axes=axes, starts=starts, ends=ends)
+            out = fluid.layers.slice(input, axes=axes, starts=starts, ends=ends)
     """
 
     helper = LayerHelper('slice', **locals())
@@ -9564,9 +9584,11 @@ def shape(input):
     Examples:
         .. code-block:: python
 
-            input = layers.data(
+            import paddle.fluid as fluid
+
+            input = fluid.layers.data(
                 name="input", shape=[3, 100, 100], dtype="float32")
-            out = layers.shape(input)
+            out = fluid.layers.shape(input)
     """
 
     helper = LayerHelper('shape', **locals())
@@ -9647,6 +9669,14 @@ def scale(x, scale=1.0, bias=0.0, bias_after_scale=True, act=None, name=None):
 
     Returns:
         out(${out_type}): ${out_comment}
+
+    Examples:
+        .. code-block:: python
+
+            import paddle.fluid as fluid
+
+            x = fluid.layers.data(name="X", shape=[1, 2, 5, 5], dtype='float32')
+            y = fluid.layers.scale(x, scale = 2.0, bias = 1.0)
     """
 
     helper = LayerHelper('scale', **locals())