Performs fractional average pooling on the input.
Fractional average pooling is similar to Fractional max pooling in the pooling region generation step. The only difference is that after pooling regions are generated, a mean operation is performed instead of a max operation in each pooling region.
[batch, height, width, channels].
value, currently only supports row and col dimension and should be >= 1.0. For example, a valid pooling ratio looks like [1.0, 1.44, 1.73, 1.0]. The first and last elements must be 1.0 because we don't allow pooling on batch and channels dimensions. 1.44 and 1.73 are pooling ratio on height and width dimensions respectively.
Optional attributes (see
index 0 1 2 3 4
value 20 5 16 3 7
If the pooling sequence is [0, 2, 4], then 16, at index 2 will be used twice. The result would be [41/3, 26/3] for fractional avg pooling.
Outputoutput: output tensor after fractional avg pooling.
Outputrow_pooling_sequence: row pooling sequence, needed to calculate gradient.
Outputcol_pooling_sequence: column pooling sequence, needed to calculate gradient.
|Constructors and Destructors|
|Public static functions|
Optional attribute setters for FractionalAvgPool.
FractionalAvgPool( const ::tensorflow::Scope & scope, ::tensorflow::Input value, const gtl::ArraySlice< float > & pooling_ratio )
FractionalAvgPool( const ::tensorflow::Scope & scope, ::tensorflow::Input value, const gtl::ArraySlice< float > & pooling_ratio, const FractionalAvgPool::Attrs & attrs )
Attrs Deterministic( bool x )
Attrs Overlapping( bool x )
Attrs PseudoRandom( bool x )
Attrs Seed( int64 x )
Attrs Seed2( int64 x )
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.