[Docathon] Fix NO.51-64 API Label

python/paddle/nn/functional/pooling.py

@@ -887,7 +887,7 @@ def max_unpool2d(
 ):
     r"""
     This API implements max unpooling 2d opereation.
-    See more details in :ref:`api_nn_pooling_MaxUnPool2D` .
+    See more details in :ref:`api_paddle_nn_MaxUnPool2D` .
 
 
     Args:
@@ -1347,8 +1347,8 @@ def max_pool3d(
     name=None,
 ):
     """
-    This API implements max pooling 2d operation.
-    See more details in :ref:`api_nn_pooling_MaxPool3d` .
+    This API implements max pooling 3d operation.
+    See more details in :ref:`api_paddle_nn_MaxPool3D` .
 
     Args:
         x (Tensor): The input tensor of pooling operator, which is a 5-D tensor with

python/paddle/nn/functional/vision.py

@@ -461,7 +461,7 @@ def pixel_unshuffle(x, downscale_factor, data_format="NCHW", name=None):
 def channel_shuffle(x, groups, data_format="NCHW", name=None):
     """
     This API implements channel shuffle operation.
-    See more details in :ref:`api_nn_vision_ChannelShuffle`.
+    See more details in :ref:`api_paddle_nn_ChannelShuffle`.
 
     Parameters:
         x (Tensor): 4-D tensor, the data type should be float32 or float64.

python/paddle/sparse/nn/functional/pooling.py

@@ -30,7 +30,7 @@ def max_pool3d(
 ):
     """
     Implements sparse max pooling 3d operation.
-    See more details in :ref:`api_sparse_pooling_MaxPool3d` .
+    See more details in :ref:`api_paddle_sparse_nn_MaxPool3D` .
 
     Args:
         x (Tensor): The input SparseCooTensor of pooling operator, which is a 5-D tensor with

python/paddle/static/nn/sequence_lod.py

@@ -167,7 +167,7 @@ def sequence_softmax(input, use_cudnn=False, name=None):
     r"""
 
     Note:
-        The input type of the OP must be Tensor. For Tensor, use:** :ref:`api_static_nn_softmax`
+        The input type of the OP must be Tensor. For Tensor, use:** :ref:`api_paddle_nn_functional_softmax`
 
     A LoD-tensor can be regarded as several sequences, and this op apply softmax algo on each sequence.
     The shape of input Tensor can be :math:`[N, 1]` or :math:`[N]`, where :math:`N`
@@ -254,7 +254,7 @@ def sequence_pool(input, pool_type, is_test=False, pad_value=0.0):
     r"""
 
     Note:
-        Only receives Tensor as input. If your input is Tensor, please use pool2d Op.(static.nn.** :ref:`api_static_nn_pool2d` ).
+        Only receives Tensor as input. If your input is Tensor, please use pool2d Op.(static.nn.** :ref:`api_paddle_static_nn_sequence_pool` ).
 
     This operator only supports Tensor as input. It will apply specified pooling
     operation on the input Tensor. It pools features of all time-steps of each
@@ -372,7 +372,7 @@ def sequence_concat(input, name=None):
     """
 
     Note:
-        Only receives Tensor as input. If your input is Tensor, please use concat Op.(static.nn.** :ref:`api_static_nn_concat` ).
+        Only receives Tensor as input. If your input is Tensor, please use concat Op.(static.nn.** :ref:`api_paddle_concat` ).
 
     This operator only supports Tensor as input. It concatenates the multiple Tensor from input by the LoD information,
     and outputs the concatenated Tensor.
@@ -921,7 +921,7 @@ def sequence_pad(x, pad_value, maxlen=None, name=None):
         to ``maxlen``). The padding value is defined by ``pad_value``, and will be
         appended to the tail of sequences. The result is a Python tuple ``(Out, Length)``:
         the Tensor ``Out`` is the padded sequences, and Tensor ``Length`` is
-        the length information of input sequences. For removing padding data (unpadding operation), See :ref:`api_static_static_sequence_unpad`.
+        the length information of input sequences. For removing padding data (unpadding operation), See :ref:`api_paddle_static_nn_sequence_unpad`.
 
     Note:
         Please note that the input ``x`` should be Tensor.
@@ -1039,7 +1039,7 @@ def sequence_unpad(x, length, name=None):
     """
 
     Note:
-        The input of the OP is Tensor and the output is Tensor.  For padding operation, See:**  :ref:`api_static_nn_sequence_pad`
+        The input of the OP is Tensor and the output is Tensor.  For padding operation, See:**  :ref:`api_paddle_static_nn_sequence_pad`
 
     Remove the padding data from the input based on the length information and returns a Tensor.
 
@@ -1123,7 +1123,7 @@ def sequence_reshape(input, new_dim):
     """
 
     Note:
-        Only receives Tensor as input. If your input is Tensor, please use reshape Op.(static.nn.** :ref:`api_static_nn_reshape` ).
+        Only receives Tensor as input. If your input is Tensor, please use reshape Op.(static.nn.** :ref:`api_paddle_reshape` ).
 
     Only supports Tensor as input. Given :attr:`new_dim` ,
     it will compute new shape according to original length of each sequence,
@@ -1420,7 +1420,7 @@ def sequence_mask(x, maxlen=None, dtype='int64', name=None):
 def sequence_reverse(x, name=None):
     """
     Note:
-        Only receives Tensor as input. If your input is Tensor, please use reverse Op.(static.nn.** :ref:`api_static_nn_reverse` ).
+        Only receives Tensor as input. If your input is Tensor, please use reverse Op.(static.nn.** :ref:`api_paddle_static_nn_sequence_reverse` ).
 
     Only supports Tensor as input. It will reverse each sequence for input Tensor.
     Currently it only supports 1-level Tensor. This operator is very useful when building a

python/paddle/tensor/manipulation.py

@@ -1630,7 +1630,7 @@ def flatten(x, start_axis=0, stop_axis=-1, name=None):
 def flatten_(x, start_axis=0, stop_axis=-1, name=None):
     """
     Inplace version of ``flatten`` API, the output Tensor will be inplaced with input ``x``.
-    Please refer to :ref:`api_tensor_flatten`.
+    Please refer to :ref:`api_paddle_flatten`.
     """
     if not (isinstance(x, Variable)):
         raise ValueError("The input x should be a Tensor")
@@ -4723,7 +4723,7 @@ def put_along_axis(arr, indices, values, axis, reduce='assign'):
 def put_along_axis_(arr, indices, values, axis, reduce='assign'):
     r"""
     Inplace version of ``put_along_axis`` API, the output Tensor will be inplaced with input ``arr``.
-    Please refer to :ref:`api_tensor_put_along_axis`.
+    Please refer to :ref:`api_paddle_put_along_axis`.
     """
     if len(arr.shape) != len(indices.shape):
         raise ValueError(

python/paddle/tensor/random.py

@@ -684,7 +684,7 @@ def uniform_(x, min=-1.0, max=1.0, seed=0, name=None):
     """
     This is the inplace version of OP ``uniform``, which returns a Tensor filled
     with random values sampled from a uniform distribution. The output Tensor will
-    be inplaced with input ``x``. Please refer to :ref:`api_tensor_uniform`.
+    be inplaced with input ``x``. Please refer to :ref:`api_paddle_uniform`.
 
     Args:
         x(Tensor): The input tensor to be filled with random values.