QuantizedAvgPool

public final class QuantizedAvgPool

Produces the average pool of the input tensor for quantized types.

Constants

String

OP_NAME

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

Public Methods

static <T extends TType> QuantizedAvgPool<T>	create(Scope scope, Operand<T> input, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, List<Long> ksize, List<Long> strides, String padding) Factory method to create a class wrapping a new QuantizedAvgPool operation.
Output<TFloat32>	maxOutput() The float value that the highest quantized output value represents.
Output<TFloat32>	minOutput() The float value that the lowest quantized output value represents.
Output<T>	output()

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: "QuantizedAvgPool"

Public Methods

public static QuantizedAvgPool<T> create (Scope scope, Operand<T> input, Operand<TFloat32> minInput, Operand<TFloat32> maxInput, List<Long> ksize, List<Long> strides, String padding)

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

Parameters

scope	current scope
input	4-D with shape `[batch, height, width, channels]`.
minInput	The float value that the lowest quantized input value represents.
maxInput	The float value that the highest quantized input value represents.
ksize	The size of the window for each dimension of the input tensor. The length must be 4 to match the number of dimensions of the input.
strides	The stride of the sliding window for each dimension of the input tensor. The length must be 4 to match the number of dimensions of the input.
padding	The type of padding algorithm to use.

Returns

• a new instance of QuantizedAvgPool

public Output<TFloat32> maxOutput ()

The float value that the highest quantized output value represents.

public Output<TFloat32> minOutput ()

The float value that the lowest quantized output value represents.

public Output<T> output ()