Caffe2 - C++ API
A deep learning, cross platform ML framework
Data Structures | Public Types | Static Public Member Functions | Static Public Attributes
caffe2::AbstractSortedSegmentRangeDef< T, SIndex, Context, ReducerDef > Struct Template Reference

Data Structures

struct  GetGradient
 

Public Types

using OpDef = ReducerDef
 
using ForwardOp = AbstractSortedSegmentRangeOp< T, SIndex, Context, typename ReducerDef::template Reducer< T, Context >>
 
using BackwardOp = AbstractSortedSegmentRangeGradientOp< T, SIndex, Context, typename ReducerDef::template ReducerGradient< T, Context >>
 

Static Public Member Functions

static void PopulateSchema (OpSchema &schema)
 

Static Public Attributes

static constexpr const char * basename = "SortedSegmentRange"
 
static constexpr const char * doc
 

Detailed Description

template<typename T, typename SIndex, typename Context, typename ReducerDef>
struct caffe2::AbstractSortedSegmentRangeDef< T, SIndex, Context, ReducerDef >

Definition at line 211 of file segment_reduction_op.h.

Field Documentation

template<typename T , typename SIndex , typename Context , typename ReducerDef >
constexpr const char* caffe2::AbstractSortedSegmentRangeDef< T, SIndex, Context, ReducerDef >::doc
static
Initial value:
= R"DOC(
Applies '{op}' to each segment of input tensor. In order to allow for more
efficient implementation of '{op}', the input segments have to be contiguous
and non-empty.
SEGMENT_IDS is a vector that maps each of the first dimension slices of the
DATA to a particular group (segment). Values belonging to the same segment are
aggregated together.
The first dimension of the output is equal to the number of input segments,
i.e. `SEGMENT_IDS[-1]+1`. Other dimensions are inherited from the input tensor.
{op_doc}
)DOC"

Definition at line 214 of file segment_reduction_op.h.


The documentation for this struct was generated from the following file: