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

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)