提交 a74db488 编写于 作者: C caoying03

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上级 ebe4425f
......@@ -467,7 +467,7 @@ lambda_cost
:noindex:
square_error_cost
--------
-----------------
.. autoclass:: paddle.v2.layer.square_error_cost
:noindex:
......@@ -533,7 +533,7 @@ Miscs
=====
dropout
--------------
--------
.. autoclass:: paddle.v2.layer.dropout
:noindex:
......
......@@ -19,17 +19,17 @@ dynamic_lstm
:noindex:
data
---------
----
.. autofunction:: paddle.v2.fluid.layers.data
:noindex:
mean
---------
----
.. autofunction:: paddle.v2.fluid.layers.mean
:noindex:
mul
---------
---
.. autofunction:: paddle.v2.fluid.layers.mul
:noindex:
......@@ -45,13 +45,13 @@ elementwise_div
dropout
---------
-------
.. autofunction:: paddle.v2.fluid.layers.dropout
:noindex:
reshape
---------
--------
.. autofunction:: paddle.v2.fluid.layers.reshape
:noindex:
......@@ -81,67 +81,67 @@ transpose
sigmoid_cross_entropy_with_logits
---------
---------------------------------
.. autofunction:: paddle.v2.fluid.layers.esigmoid_cross_entropy_with_logits
:noindex:
cast
---------
----
.. autofunction:: paddle.v2.fluid.layers.cast
:noindex:
concat
---------
-------
.. autofunction:: paddle.v2.fluid.layers.concat
:noindex:
sums
---------
----
.. autofunction:: paddle.v2.fluid.layers.sums
:noindex:
linear_chain_crf
---------
----------------
.. autofunction:: paddle.v2.fluid.layers.linear_chain_crf
:noindex:
assign
---------
-------
.. autofunction:: paddle.v2.fluid.layers.embedding
:noindex:
split_lod_tensor
---------
----------------
.. autofunction:: paddle.v2.fluid.layers.split_lod_tensor
:noindex:
merge_lod_tensor
---------
----------------
.. autofunction:: paddle.v2.fluid.layers.merge_lod_tensor
:noindex:
cos_sim
---------
--------
.. autofunction:: paddle.v2.fluid.layers.cos_sim
:noindex:
cross_entropy
---------
-------------
.. autofunction:: paddle.v2.fluid.layers.cross_entropy
:noindex:
square_error_cost
---------
-----------------
.. autofunction:: paddle.v2.fluid.layers.square_error_cost
:noindex:
......@@ -153,68 +153,68 @@ accuracy
sequence_conv
---------
-------------
.. autofunction:: paddle.v2.fluid.layers.sequence_conv
:noindex:
conv2d
---------
------
.. autofunction:: paddle.v2.fluid.layers.conv2d
:noindex:
sequence_pool
---------
-------------
.. autofunction:: paddle.v2.fluid.layers.sequence_pool
:noindex:
pool2d
---------
------
.. autofunction:: paddle.v2.fluid.layers.pool2d
:noindex:
batch_norm
---------
----------
.. autofunction:: paddle.v2.fluid.layers.batch_norm
:noindex:
beam_search_decode
---------
------------------
.. autofunction:: paddle.v2.fluid.layers.beam_search_decode
:noindex:
lod_rank_table
---------
--------------
.. autofunction:: paddle.v2.fluid.layers.lod_rank_table
:noindex:
max_sequence_len
---------
----------------
.. autofunction:: paddle.v2.fluid.layers.max_sequence_len
:noindex:
topk
---------
-----
.. autofunction:: paddle.v2.fluid.layers.topk
:noindex:
lod_tensor_to_array
---------
-------------------
.. autofunction:: paddle.v2.fluid.layers.lod_tensor_to_array
:noindex:
array_to_lod_tensor
---------
-------------------
.. autofunction:: paddle.v2.fluid.layers.array_to_lod_tensor
:noindex:
......@@ -222,26 +222,26 @@ array_to_lod_tensor
fill_constant
---------
-------------
.. autofunction:: paddle.v2.fluid.layers.fill_constant
:noindex:
fill_constant_batch_size_like
---------
-----------------------------
.. autofunction:: paddle.v2.fluid.layers.fill_constant_batch_size_like
:noindex:
ones
---------
----
.. autofunction:: paddle.v2.fluid.layers.ones
:noindex:
zeros
---------
-----
.. autofunction:: paddle.v2.fluid.layers.zeros
:noindex:
......@@ -253,14 +253,14 @@ increment
array_write
---------
-----------
.. autofunction:: paddle.v2.fluid.layers.array_write
:noindex:
create_array
---------
------------
.. autofunction:: paddle.v2.fluid.layers.create_array
:noindex:
......@@ -272,31 +272,31 @@ less_than
array_read
---------
----------
.. autofunction:: paddle.v2.fluid.layers.array_read
:noindex:
shrink_memory
---------
--------------
.. autofunction:: paddle.v2.fluid.layers.shrink_memory
:noindex:
array_length
---------
-------------
.. autofunction:: paddle.v2.fluid.layers.array_length
:noindex:
conv2d_transpose
---------
----------------
.. autofunction:: paddle.v2.fluid.layers.conv2d_transpose
:noindex:
sequence_expand
---------
---------------
.. autofunction:: paddle.v2.fluid.layers.sequence_expand
:noindex:
......@@ -308,13 +308,13 @@ lstm_unit
sequence_softmax
---------
----------------
.. autofunction:: paddle.v2.fluid.layers.sequence_softmax
:noindex:
reduce_sum
---------
----------
.. autofunction:: paddle.v2.fluid.layers.reduce_sum
:noindex:
......@@ -3,19 +3,19 @@ Nets
===========
simple_img_conv_pool
-----------
--------------------
.. autofunction:: paddle.v2.fluid.nets.simple_img_conv_pool
:noindex:
img_conv_group
-----------
---------------
.. autofunction:: paddle.v2.fluid.nets.img_conv_group
:noindex:
sequence_conv_pool
-----------
------------------
.. autofunction:: paddle.v2.fluid.nets.sequence_conv_pool
:noindex:
......
......@@ -18,7 +18,7 @@ SGDOptimizer
MomentumOptimizer
-----------
-----------------
.. automodule:: paddle.v2.fluid.optimizer
:members: MomentumOptimizer
:noindex:
......@@ -26,14 +26,14 @@ MomentumOptimizer
AdagradOptimizer
-----------
----------------
.. automodule:: paddle.v2.fluid.optimizer
:members: AdagradOptimizer
:noindex:
AdamOptimizer
-----------
-------------
.. automodule:: paddle.v2.fluid.optimizer
:members: AdamOptimizer
:noindex:
......@@ -47,7 +47,7 @@ AdamaxOptimizer
DecayedAdagradOptimizer
-----------
-----------------------
.. automodule:: paddle.v2.fluid.optimizer
:members: DecayedAdagradOptimizer
:noindex:
......
......@@ -3,14 +3,14 @@ Regularizer
===========
WeightDecayRegularizer
-----------
----------------------
.. automodule:: paddle.v2.fluid.regularizer
:members: WeightDecayRegularizer
:noindex:
L2DecayRegularizer
-----------
------------------
.. automodule:: paddle.v2.fluid.regularizer
:members: L2DecayRegularizer
:noindex:
......@@ -18,7 +18,7 @@ L2DecayRegularizer
L1DecayRegularizer
-----------
-------------------
.. automodule:: paddle.v2.fluid.regularizer
:members: L1DecayRegularizer
......
......@@ -73,36 +73,35 @@ class MulOpMaker : public framework::OpProtoAndCheckerMaker {
public:
MulOpMaker(OpProto* proto, OpAttrChecker* op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("X", "The first input tensor of the mul op.");
AddInput("Y", "The second input tensor of the mul op.");
AddOutput("Out", "The output tensor of the mul op.");
AddInput("X", "(Tensor), The first input tensor of mul op.");
AddInput("Y", "(Tensor), The second input tensor of mul op.");
AddOutput("Out", "(Tensor), The output tensor of mul op.");
AddAttr<int>(
"x_num_col_dims",
"(int, default 1) "
R"DOC(The mul_op can take tensors with more than two dimensions as its
inputs. If the input `X` is a tensor with more than two
dimensions, `X` will be flattened into a two-dimensional matrix
first. The flattening rule is: the first `num_col_dims` will be
flattened to form the first dimension of the final matrix (height
of the matrix), and the rest `rank(X) - num_col_dims` dimensions
are flattened to form the second dimension of the final matrix (
width of the matrix). As a result, height of the flattened matrix
is equal to the product of `X`'s first `x_num_col_dims` dimensions'
sizes, and width of the flattened matrix is equal to the product
of `X`'s last `rank(x) - num_col_dims` dimensions' size.
For example, suppose `X` is a 6-dimensional tensor with the shape
[2, 3, 4, 5, 6], and `x_num_col_dims` = 3. Then, the flattened
matrix will have a shape [2 x 3 x 4, 5 x 6] = [24, 30].
R"DOC((int, default 1), The mul_op can take tensors with more than two
dimensions as its inputs. If the input $X$ is a tensor with more
than two dimensions, $X$ will be flattened into a two-dimensional
matrix first. The flattening rule is: the first `num_col_dims`
will be flattened to form the first dimension of the final matrix
(the height of the matrix), and the rest `rank(X) - num_col_dims`
dimensions are flattened to form the second dimension of the final
matrix (the width of the matrix). As a result, height of the
flattened matrix is equal to the product of $X$'s first
`x_num_col_dims` dimensions' sizes, and width of the flattened
matrix is equal to the product of $X$'s last `rank(x) - num_col_dims`
dimensions' size. For example, suppose $X$ is a 6-dimensional
tensor with the shape [2, 3, 4, 5, 6], and `x_num_col_dims` = 3.
Thus, the flattened matrix will have a shape [2 x 3 x 4, 5 x 6] =
[24, 30].
)DOC")
.SetDefault(1)
.EqualGreaterThan(1);
AddAttr<int>(
"y_num_col_dims",
"(int, default 1) "
R"DOC(The mul_op can take tensors with more than two dimensions as its
inputs. If the input `Y` is a tensor with more than two
dimensions, `Y` will be flatten into a two-dimensional matrix
first. The attribute `y_num_col_dims` determines how `Y` is
R"DOC((int, default 1), The mul_op can take tensors with more than two,
dimensions as its inputs. If the input $Y$ is a tensor with more
than two dimensions, $Y$ will be flattened into a two-dimensional
matrix first. The attribute `y_num_col_dims` determines how $Y$ is
flattened. See comments of `x_num_col_dims` for more details.
)DOC")
.SetDefault(1)
......@@ -110,14 +109,14 @@ class MulOpMaker : public framework::OpProtoAndCheckerMaker {
AddComment(R"DOC(
Mul Operator.
This operator is used to perform matrix multiplication for input X and Y.
This operator is used to perform matrix multiplication for input $X$ and $Y$.
The equation is:
$$Out = X * Y$$
Both the input `X` and `Y` can carry the LoD (Level of Details) information,
or not. But the output only shares the LoD information with input `X`.
Both the input $X$ and $Y$ can carry the LoD (Level of Details) information,
or not. But the output only shares the LoD information with input $X$.
)DOC");
}
......
......@@ -40,7 +40,8 @@ def fc(input,
This process can be formulated as follows:
.. math::
Out = Act({\sum_{i=0}^{N-1}W_iX_i + b})
Out = Act\left({\sum_{i=0}^{N-1}W_iX_i + b}\right)
In the above equation:
......@@ -48,8 +49,8 @@ def fc(input,
* :math:`X_i`: The input tensor.
* :math:`W`: The weights created by this layer.
* :math:`b`: The bias parameter created by this layer (if needed).
* :math`Act`: The activation funtion.
* :math`Out`: The output tensor.
* :math:`Act`: The activation funtion.
* :math:`Out`: The output tensor.
Args:
input(Variable|list): The input tensor(s) to the fully connected layer.
......
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