FractionalMaxPool

public final class FractionalMaxPool

Performs fractional max pooling on the input.

Fractional max pooling is slightly different than regular max pooling. In regular max pooling, you downsize an input set by taking the maximum value of smaller N x N subsections of the set (often 2x2), and try to reduce the set by a factor of N, where N is an integer. Fractional max pooling, as you might expect from the word "fractional", means that the overall reduction ratio N does not have to be an integer.

The sizes of the pooling regions are generated randomly but are fairly uniform. For example, let's look at the height dimension, and the constraints on the list of rows that will be pool boundaries.

First we define the following:

1. input_row_length : the number of rows from the input set 2. output_row_length : which will be smaller than the input 3. alpha = input_row_length / output_row_length : our reduction ratio 4. K = floor(alpha) 5. row_pooling_sequence : this is the result list of pool boundary rows

Then, row_pooling_sequence should satisfy:

1. a[0] = 0 : the first value of the sequence is 0 2. a[end] = input_row_length : the last value of the sequence is the size 3. K <= (a[i+1] - a[i]) <= K+1 : all intervals are K or K+1 size 4. length(row_pooling_sequence) = output_row_length+1

For more details on fractional max pooling, see this paper: [Benjamin Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071)

Nested Classes

class

FractionalMaxPool.Options

Optional attributes for FractionalMaxPool

Constants

String

OP_NAME

The name of this op, as known by TensorFlow core engine

Public Methods

Output<TInt64>	colPoolingSequence() column pooling sequence, needed to calculate gradient.
static <T extends TNumber> FractionalMaxPool<T>	create(Scope scope, Operand<T> value, List<Float> poolingRatio, Options... options) Factory method to create a class wrapping a new FractionalMaxPool operation.
static FractionalMaxPool.Options	deterministic(Boolean deterministic)
Output<T>	output() output tensor after fractional max pooling.
static FractionalMaxPool.Options	overlapping(Boolean overlapping)
static FractionalMaxPool.Options	pseudoRandom(Boolean pseudoRandom)
Output<TInt64>	rowPoolingSequence() row pooling sequence, needed to calculate gradient.
static FractionalMaxPool.Options	seed(Long seed)
static FractionalMaxPool.Options	seed2(Long seed2)

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single Operation.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single Operation.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "FractionalMaxPool"

Public Methods

public Output<TInt64> colPoolingSequence ()

column pooling sequence, needed to calculate gradient.

public static FractionalMaxPool<T> create (Scope scope, Operand<T> value, List<Float> poolingRatio, Options... options)

Factory method to create a class wrapping a new FractionalMaxPool operation.

Parameters

scope	current scope
value	4-D with shape `[batch, height, width, channels]`.
poolingRatio	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.
options	carries optional attributes values

Returns

• a new instance of FractionalMaxPool

public static FractionalMaxPool.Options deterministic (Boolean deterministic)

Parameters

deterministic	When set to True, a fixed pooling region will be used when iterating over a FractionalMaxPool node in the computation graph. Mainly used in unit test to make FractionalMaxPool deterministic.

public Output<T> output ()

output tensor after fractional max pooling.

public static FractionalMaxPool.Options overlapping (Boolean overlapping)

Parameters

overlapping	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 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 [20, 16] for fractional max pooling.

public static FractionalMaxPool.Options pseudoRandom (Boolean pseudoRandom)

Parameters

pseudoRandom	When set to True, generates the pooling sequence in a pseudorandom fashion, otherwise, in a random fashion. Check paper [Benjamin Graham, Fractional Max-Pooling](http://arxiv.org/abs/1412.6071) for difference between pseudorandom and random.

public Output<TInt64> rowPoolingSequence ()

row pooling sequence, needed to calculate gradient.

public static FractionalMaxPool.Options seed (Long seed)

Parameters

seed	If either seed or seed2 are set to be non-zero, the random number generator is seeded by the given seed. Otherwise, it is seeded by a random seed.

public static FractionalMaxPool.Options seed2 (Long seed2)

Parameters

seed2	An second seed to avoid seed collision.