Conv2d

public final class Conv2d

Computes a 2-D convolution given 4-D `input` and `filter` tensors.

Given an input tensor of shape `[batch, in_height, in_width, in_channels]` and a filter / kernel tensor of shape `[filter_height, filter_width, in_channels, out_channels]`, this op performs the following:

1. Flattens the filter to a 2-D matrix with shape `[filter_height * filter_width * in_channels, output_channels]`. 2. Extracts image patches from the input tensor to form a virtual tensor of shape `[batch, out_height, out_width, filter_height * filter_width * in_channels]`. 3. For each patch, right-multiplies the filter matrix and the image patch vector.

In detail, with the default NHWC format,

output[b, i, j, k] = sum_{di, dj, q} input[b, strides[1] * i + di, strides[2] * j + dj, q] * filter[di, dj, q, k]

Must have `strides[0] = strides[3] = 1`. For the most common case of the same horizontal and vertices strides, `strides = [1, stride, stride, 1]`.

Nested Classes

class

Conv2d.Options

Optional attributes for Conv2d

Constants

String

OP_NAME

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

Public Methods

Output<T>	asOutput() Returns the symbolic handle of the tensor.
static <T extends TNumber> Conv2d<T>	create(Scope scope, Operand<T> input, Operand<T> filter, List<Long> strides, String padding, Options... options) Factory method to create a class wrapping a new Conv2d operation.
static Conv2d.Options	dataFormat(String dataFormat)
static Conv2d.Options	dilations(List<Long> dilations)
static Conv2d.Options	explicitPaddings(List<Long> explicitPaddings)
Output<T>	output() A 4-D tensor.
static Conv2d.Options	useCudnnOnGpu(Boolean useCudnnOnGpu)

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.

From interface org.tensorflow.Operand

abstract Output<T>	asOutput() Returns the symbolic handle of the tensor.
abstract T	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<T>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

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

Constant Value: "Conv2D"

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static Conv2d<T> create (Scope scope, Operand<T> input, Operand<T> filter, List<Long> strides, String padding, Options... options)

Factory method to create a class wrapping a new Conv2d operation.

Parameters

scope	current scope
input	A 4-D tensor. The dimension order is interpreted according to the value of `data_format`, see below for details.
filter	A 4-D tensor of shape `[filter_height, filter_width, in_channels, out_channels]`
strides	1-D tensor of length 4. The stride of the sliding window for each dimension of `input`. The dimension order is determined by the value of `data_format`, see below for details.
padding	The type of padding algorithm to use.
options	carries optional attributes values

Returns

• a new instance of Conv2d

public static Conv2d.Options dataFormat (String dataFormat)

Parameters

dataFormat	Specify the data format of the input and output data. With the default format "NHWC", the data is stored in the order of: [batch, height, width, channels]. Alternatively, the format could be "NCHW", the data storage order of: [batch, channels, height, width].

public static Conv2d.Options dilations (List<Long> dilations)

Parameters

dilations	1-D tensor of length 4. The dilation factor for each dimension of `input`. If set to k > 1, there will be k-1 skipped cells between each filter element on that dimension. The dimension order is determined by the value of `data_format`, see above for details. Dilations in the batch and depth dimensions must be 1.

public static Conv2d.Options explicitPaddings (List<Long> explicitPaddings)

Parameters

explicitPaddings	If `padding` is `"EXPLICIT"`, the list of explicit padding amounts. For the ith dimension, the amount of padding inserted before and after the dimension is `explicit_paddings[2 * i]` and `explicit_paddings[2 * i + 1]`, respectively. If `padding` is not `"EXPLICIT"`, `explicit_paddings` must be empty.

public Output<T> output ()

A 4-D tensor. The dimension order is determined by the value of `data_format`, see below for details.

public static Conv2d.Options useCudnnOnGpu (Boolean useCudnnOnGpu)