Merge pull request #11369 from luotao1/refine_doc

refine docs of elementwise_op etc.
wangkuiyi-patch-1
Tao Luo 7 years ago committed by GitHub
commit ca4d528b35
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GPG Key ID: 4AEE18F83AFDEB23

@ -66,40 +66,41 @@ class ElementwiseOpMaker : public framework::OpProtoAndCheckerMaker {
.SetDefault(-1)
.EqualGreaterThan(-1);
AddComment(string::Sprintf(R"DOC(
Limited Elementwise %s Operator.
Limited Elementwise %s Operator
The equation is:
$$%s$$
$X$ is a tensor of any dimension and the dimensions of tensor $Y$ must be
smaller than or equal to the dimensions of $X$.
- $X$: a tensor of any dimension.
- $Y$: a tensor whose dimensions must be less than or equal to the dimensions of $X$.
There are two cases for this operator:
1. The shape of $Y$ is same with $X$;
2. The shape of $Y$ is a congiguous subsequencet of $X$. The trailing dimensions
of size 1 for $Y$ will be ignored for the consideration of subsequence.
1. The shape of $Y$ is the same with $X$.
2. The shape of $Y$ is a continuous subsequence of $X$.
For case 2:
$Y$ will be broadcasted to match the shape of $X$ and axis should be
set to index of the start dimension to broadcast $Y$ onto $X$.
1. Broadcast $Y$ to match the shape of $X$, where $axis$ is the start dimension index
for broadcasting $Y$ onto $X$.
2. If $axis$ is -1 (default), $axis = rank(X) - rank(Y)$.
3. The trailing dimensions of size 1 for $Y$ will be ignored for the consideration of
subsequence, such as shape(Y) = (2, 1) => (2).
If axis is -1, it is treated as axis=rank(X)-rank(Y).
For example:
For example
.. code-block:: python
shape(X) = (2, 3, 4, 5), shape(Y) = (,)
shape(X) = (2, 3, 4, 5), shape(Y) = (5,)
shape(X) = (2, 3, 4, 5), shape(Y) = (4, 5)
shape(X) = (2, 3, 4, 5), shape(Y) = (4, 5), with axis=-1(default) or axis=2
shape(X) = (2, 3, 4, 5), shape(Y) = (3, 4), with axis=1
shape(X) = (2, 3, 4, 5), shape(Y) = (2), with axis=0
shape(X) = (2, 3, 4, 5), shape(Y) = (2, 1), with axis=0
Either of the inputs $X$ and $Y$ or none can carry the LoD (Level of Details)
information. However, the output only shares the LoD information with input $X$.
The inputs $X$ and $Y$ can carry the different LoD information.
But the output only shares the LoD information with the input $X$.
)DOC",
GetName(), GetEquation()));

@ -1445,7 +1445,7 @@ def sequence_pool(input, pool_type):
def sequence_first_step(input):
"""
This funciton get the first step of sequence.
This function gets the first step of sequence.
.. code-block:: text
@ -1478,7 +1478,7 @@ def sequence_first_step(input):
def sequence_last_step(input):
"""
This funciton get the last step of sequence.
This function gets the last step of sequence.
.. code-block:: text

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