Struct caffe2op_lppool::LpPoolFunctor
source · pub struct LpPoolFunctor {}Expand description
| LpPool consumes an input blob and
| applies max pooling across the the blob
| according to kernel sizes, stride sizes,
| pad lengths and dilation. $L_p$ pooling
| consists of taking the $L_p$ norm of
| a subset of the input tensor according
| to the kernel size and downsampling
| the data into the output blob for further
| processing.
|
| Pooling layers reduce the spatial dimensionality
| of the input blob. Each of the output
| blob’s dimensions will reduce according
| to:
|
| $$dim_{out}=\frac{dim_{in}-kernel+2*pad}{stride}+1$$
|
| Github Links: - https://github.com/pytorch/pytorch/blob/master/caffe2/operators/lp_pool_op.cc
|
Trait Implementations§
source§impl Default for LpPoolFunctor
impl Default for LpPoolFunctor
source§fn default() -> LpPoolFunctor
fn default() -> LpPoolFunctor
Returns the “default value” for a type. Read more
Auto Trait Implementations§
impl RefUnwindSafe for LpPoolFunctor
impl Send for LpPoolFunctor
impl Sync for LpPoolFunctor
impl Unpin for LpPoolFunctor
impl UnwindSafe for LpPoolFunctor
Blanket Implementations§
§impl<T> Pointable for T
impl<T> Pointable for T
§impl<SS, SP> SupersetOf<SS> for SPwhere
SS: SubsetOf<SP>,
impl<SS, SP> SupersetOf<SS> for SPwhere SS: SubsetOf<SP>,
§fn to_subset(&self) -> Option<SS>
fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct
self from the equivalent element of its
superset. Read more§fn is_in_subset(&self) -> bool
fn is_in_subset(&self) -> bool
Checks if
self is actually part of its subset T (and can be converted to it).§fn to_subset_unchecked(&self) -> SS
fn to_subset_unchecked(&self) -> SS
Use with care! Same as
self.to_subset but without any property checks. Always succeeds.§fn from_subset(element: &SS) -> SP
fn from_subset(element: &SS) -> SP
The inclusion map: converts
self to the equivalent element of its superset.