fix API en doc (#20261)

* test=develop,test=document_preview, test=document_fix

* test=develop,test=document_preview, test=document_fix

* fix API.spec, test=develop,test=document_preview, test=document_fix

paddle/fluid/API.spec

@@ -105,7 +105,7 @@ paddle.fluid.io.PipeReader.get_line (ArgSpec(args=['self', 'cut_lines', 'line_br
 paddle.fluid.io.multiprocess_reader (ArgSpec(args=['readers', 'use_pipe', 'queue_size'], varargs=None, keywords=None, defaults=(True, 1000)), ('document', '7d8b3a96e592107c893d5d51ce968ba0'))
 paddle.fluid.io.Fake ('paddle.reader.decorator.Fake', ('document', '0d8f4847b99bed6d456ade0d903202e1'))
 paddle.fluid.io.Fake.__init__ (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.initializer.ConstantInitializer ('paddle.fluid.initializer.ConstantInitializer', ('document', '798f1fd87cbe9798d001ffb6e616415d'))
+paddle.fluid.initializer.ConstantInitializer ('paddle.fluid.initializer.ConstantInitializer', ('document', '911263fc30c516c55e89cd72086a23f8'))
 paddle.fluid.initializer.ConstantInitializer.__init__ (ArgSpec(args=['self', 'value', 'force_cpu'], varargs=None, keywords=None, defaults=(0.0, False)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.initializer.UniformInitializer ('paddle.fluid.initializer.UniformInitializer', ('document', '587b7035cd1d56f76f2ded617b92521d'))
 paddle.fluid.initializer.UniformInitializer.__init__ (ArgSpec(args=['self', 'low', 'high', 'seed', 'diag_num', 'diag_step', 'diag_val'], varargs=None, keywords=None, defaults=(-1.0, 1.0, 0, 0, 0, 1.0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
@@ -115,9 +115,9 @@ paddle.fluid.initializer.TruncatedNormalInitializer ('paddle.fluid.initializer.T
 paddle.fluid.initializer.TruncatedNormalInitializer.__init__ (ArgSpec(args=['self', 'loc', 'scale', 'seed'], varargs=None, keywords=None, defaults=(0.0, 1.0, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
 paddle.fluid.initializer.XavierInitializer ('paddle.fluid.initializer.XavierInitializer', ('document', '3d5676f1a5414aa0c815d793a795ccb3'))
 paddle.fluid.initializer.XavierInitializer.__init__ (ArgSpec(args=['self', 'uniform', 'fan_in', 'fan_out', 'seed'], varargs=None, keywords=None, defaults=(True, None, None, 0)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
-paddle.fluid.initializer.BilinearInitializer ('paddle.fluid.initializer.BilinearInitializer', ('document', '8a40b54fe33c19c3edcf6624ffae5d03'))
+paddle.fluid.initializer.BilinearInitializer ('paddle.fluid.initializer.BilinearInitializer', ('document', '0abf3908cf6a520dcf822c481bd05767'))
 paddle.fluid.initializer.BilinearInitializer.__init__ (ArgSpec(args=['self'], varargs=None, keywords=None, defaults=None), ('document', 'd389912dc079cbef432335a00017cec0'))
-paddle.fluid.initializer.MSRAInitializer ('paddle.fluid.initializer.MSRAInitializer', ('document', 'b99e0ee95e2fd02640cb4b08a7ae80cc'))
+paddle.fluid.initializer.MSRAInitializer ('paddle.fluid.initializer.MSRAInitializer', ('document', '75c2699c9be56de9dd4e7fcc4c611f74'))
 paddle.fluid.initializer.MSRAInitializer.__init__ (ArgSpec(args=['self', 'uniform', 'fan_in', 'seed'], varargs=None, keywords=None, defaults=(True, None, 0)), ('document', '53c757bed9345f2ad3361902531e7cf5'))
 paddle.fluid.initializer.force_init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', '5f55553caf939d270c7fe8dc418084b2'))
 paddle.fluid.initializer.init_on_cpu (ArgSpec(args=[], varargs=None, keywords=None, defaults=None), ('document', 'eaa04fd68661a3af59abd0e19b3b6eda'))
@@ -185,7 +185,7 @@ paddle.fluid.layers.nce (ArgSpec(args=['input', 'label', 'num_total_classes', 's
 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', 'd4435a63d34203339831ee6a86ef9242'))
 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', 'b83e7dfa81059b39bb137922dc914f50'))
 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', '1d8a1c8b686b55631ba1b77805e4eacf'))
+paddle.fluid.layers.row_conv (ArgSpec(args=['input', 'future_context_size', 'param_attr', 'act'], varargs=None, keywords=None, defaults=(None, None)), ('document', 'a6477957b44907787b3c74157400b80c'))
 paddle.fluid.layers.multiplex (ArgSpec(args=['inputs', 'index'], varargs=None, keywords=None, defaults=None), ('document', '2c4d1ae83da6ed35e3b36ba1b3b51d23'))
 paddle.fluid.layers.layer_norm (ArgSpec(args=['input', 'scale', 'shift', 'begin_norm_axis', 'epsilon', 'param_attr', 'bias_attr', 'act', 'name'], varargs=None, keywords=None, defaults=(True, True, 1, 1e-05, None, None, None, None)), ('document', '79797f827d89ae72c77960e9696883a9'))
 paddle.fluid.layers.group_norm (ArgSpec(args=['input', 'groups', 'epsilon', 'param_attr', 'bias_attr', 'act', 'data_layout', 'name'], varargs=None, keywords=None, defaults=(1e-05, None, None, None, 'NCHW', None)), ('document', '87dd4b818f102bc1a780e1804c28bd38'))

paddle/fluid/operators/row_conv_op.cc

@@ -89,10 +89,8 @@ class RowConvOpMaker : public framework::OpProtoAndCheckerMaker {
              "future_context is the future context length and N is the data "
              "dimension.");
     AddOutput("Out",
-              "the output(Out) is a LodTensor, which supports "
-              "variable time-length input sequences. The underlying tensor "
-              "in this LodTensor is a matrix with shape T x N, i.e., the "
-              "same shape as X.");
+              "the output(Out) is a LodTensor or Tensor, which has same type"
+              " and same shape as X.");
     AddComment(R"DOC(
 :strong:`Row-convolution operator`
 

python/paddle/fluid/initializer.py

@@ -130,13 +130,13 @@ class ConstantInitializer(Initializer):
     """Implements the constant initializer
 
     Args:
-        value (float): constant value to initialize the variable
+        value (float32): constant value to initialize the variable 
 
     Examples:
         .. code-block:: python
 
     	    import paddle.fluid as fluid
-            x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
+            x = fluid.data(name="data", shape=[8, 32, 32], dtype="float32")
 	    fc = fluid.layers.fc(input=x, size=10,
     		param_attr=fluid.initializer.Constant(value=2.0))
 
@@ -627,9 +627,9 @@ class MSRAInitializer(Initializer):
 
     Args:
         uniform (bool): whether to use uniform or normal distribution
-        fan_in (float): fan_in for MSRAInitializer. If None, it is\
-        inferred from the variable.
-        seed (int): random seed
+        fan_in (float32|None): fan_in for MSRAInitializer. If None, it is\
+        inferred from the variable. default is None.
+        seed (int32): random seed
 
     Note:
         It is recommended to set fan_in to None for most cases.
@@ -638,7 +638,7 @@ class MSRAInitializer(Initializer):
         .. code-block:: python
 
             import paddle.fluid as fluid
-            x = fluid.layers.data(name="data", shape=[32, 32], dtype="float32")
+            x = fluid.data(name="data", shape=[8, 32, 32], dtype="float32")
             fc = fluid.layers.fc(input=x, size=10,
                 param_attr=fluid.initializer.MSRA(uniform=False))
 
@@ -744,11 +744,13 @@ class BilinearInitializer(Initializer):
             import paddle.fluid as fluid
             factor = 2
             C = 2
+            B = 8
+            H = W = 32
             w_attr = fluid.param_attr.ParamAttr(
                 learning_rate=0., 
                 regularizer=fluid.regularizer.L2Decay(0.),
                 initializer=fluid.initializer.Bilinear())
-            x = fluid.layers.data(name="data", shape=[3, 32, 32], 
+            x = fluid.data(name="data", shape=[B, 3, H, W], 
                                   dtype="float32")
             conv_up = fluid.layers.conv2d_transpose(
                 input=x,

python/paddle/fluid/layers/nn.py

@@ -7422,10 +7422,14 @@ def row_conv(input, future_context_size, param_attr=None, act=None):
         ${out_comment}.
 
     Examples:
+        >>>  # for LodTensor inputs
         >>> import paddle.fluid as fluid
-        >>> x = fluid.layers.data(name='x', shape=[16],
+        >>> x = fluid.data(name='x', shape=[9, 16],
         >>>                        dtype='float32', lod_level=1)
         >>> out = fluid.layers.row_conv(input=x, future_context_size=2)
+        >>> # for Tensor inputs
+        >>> x = fluid.data(name='x', shape=[9, 4, 16], dtype='float32')
+        >>> out = fluid.layers.row_conv(input=x, future_context_size=2)
     """
     helper = LayerHelper('row_conv', **locals())
     dtype = helper.input_dtype()