org.tensorflow.op.core

Class QuantizedAvgPool<T>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.QuantizedAvgPool<T>

Type Parameters:

T - data type for output() output

All Implemented Interfaces:

Op

@Operator
public final class QuantizedAvgPool<T>
extends PrimitiveOp

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

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
static <T> QuantizedAvgPool<T>	create(Scope scope, Operand<T> input, Operand<Float> minInput, Operand<Float> maxInput, List<Long> ksize, List<Long> strides, String padding) Factory method to create a class to wrap a new QuantizedAvgPool operation to the graph.
Output<Float>	maxOutput() The float value that the highest quantized output value represents.
Output<Float>	minOutput() The float value that the lowest quantized output value represents.
Output<T>	output()

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Method Detail

create

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

Factory method to create a class to wrap a new QuantizedAvgPool operation to the graph.

Parameters:

scope - current graph 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

output

public Output<T> output()

minOutput

public Output<Float> minOutput()

The float value that the lowest quantized output value represents.

maxOutput

public Output<Float> maxOutput()

The float value that the highest quantized output value represents.