tf.nn.fractional_avg_pool(
value,
pooling_ratio,
pseudo_random=False,
overlapping=False,
deterministic=False,
seed=0,
seed2=0,
name=None
)
Defined in tensorflow/python/ops/nn_ops.py.
Performs fractional average pooling on the input. (deprecated)
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: ATensor. 4-D with shape[batch, height, width, channels].pooling_ratio: A list offloatsthat has length >= 4. Pooling ratio for each dimension ofvalue, 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 optionalbool. Defaults toFalse. When set toTrue, generates the pooling sequence in a pseudorandom fashion, otherwise, in a random fashion. Check paper Benjamin Graham, Fractional Max-Pooling for difference between pseudorandom and random.overlapping: An optionalbool. Defaults toFalse. When set toTrue, 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 7If 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 optionalbool. Deprecated; usefractional_avg_pool_v2instead.seed: An optionalint. Defaults to0. 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 optionalint. Deprecated; usefractional_avg_pool_v2instead.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.