This is a deprecated version of fractional_avg_pool.
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.
Args
value
A Tensor. 4-D with shape [batch, height, width, channels].
pooling_ratio
A list of floats that has length >= 4. Pooling ratio for
each dimension of 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.
pseudo_random
An optional bool. Defaults to False. When set to True,
generates the pooling sequence in a pseudorandom fashion, otherwise, in a
random fashion. Check paper (Graham, 2015) for difference between
pseudorandom and random.
overlapping
An optional bool. Defaults to False. When set to True,
it means when pooling, the values at the boundary of adjacent pooling
cells are used by both cells. For example:
index 0 1 2 3 4value 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 [20, 16] for fractional avg pooling.
deterministic
An optional bool. Deprecated; use fractional_avg_pool_v2
instead.
seed
An optional int. Defaults to 0. If set to be non-zero, the
random number generator is seeded by the given seed. Otherwise it is
seeded by a random seed.
seed2
An optional int. Deprecated; use fractional_avg_pool_v2 instead.
name
A name for the operation (optional).
Returns
A tuple of Tensor objects (output, row_pooling_sequence,
col_pooling_sequence).
output: Output Tensor after fractional avg pooling. Has the same type as
value.
row_pooling_sequence: A Tensor of type int64.
col_pooling_sequence: A Tensor of type int64.