T - data type for output() output@Operator public final class Conv2D<T extends Number> extends PrimitiveOp implements Operand<T>
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]`.
| Modifier and Type | Class and Description |
|---|---|
static class |
Conv2D.Options
Optional attributes for
Conv2D |
operation| Modifier and Type | Method and Description |
|---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T extends Number> |
create(Scope scope,
Operand<T> input,
Operand<T> filter,
List<Long> strides,
String padding,
Conv2D.Options... options)
Factory method to create a class to wrap a new Conv2D operation to the graph.
|
static Conv2D.Options |
dataFormat(String dataFormat) |
static Conv2D.Options |
dilations(List<Long> dilations) |
Output<T> |
output()
A 4-D tensor.
|
static Conv2D.Options |
useCudnnOnGpu(Boolean useCudnnOnGpu) |
equals, hashCode, toStringpublic static <T extends Number> Conv2D<T> create(Scope scope, Operand<T> input, Operand<T> filter, List<Long> strides, String padding, Conv2D.Options... options)
scope - current graph scopeinput - 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 valuespublic static Conv2D.Options useCudnnOnGpu(Boolean useCudnnOnGpu)
useCudnnOnGpu - public static Conv2D.Options dataFormat(String dataFormat)
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)
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 Output<T> output()
public Output<T> asOutput()
OperandInputs 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.
asOutput in interface Operand<T extends Number>OperationBuilder.addInput(Output)Copyright © 2015–2019. All rights reserved.