public static class Conv2dBackpropInput.Options extends Object
Conv2dBackpropInput
Modifier and Type | Method and Description |
---|---|
Conv2dBackpropInput.Options |
dataFormat(String dataFormat) |
Conv2dBackpropInput.Options |
dilations(List<Long> dilations) |
Conv2dBackpropInput.Options |
explicitPaddings(List<Long> explicitPaddings) |
Conv2dBackpropInput.Options |
useCudnnOnGpu(Boolean useCudnnOnGpu) |
public Conv2dBackpropInput.Options useCudnnOnGpu(Boolean useCudnnOnGpu)
useCudnnOnGpu
- public Conv2dBackpropInput.Options explicitPaddings(List<Long> explicitPaddings)
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 Conv2dBackpropInput.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, in_height, in_width, in_channels].
Alternatively, the format could be "NCHW", the data storage order of:
[batch, in_channels, in_height, in_width].public Conv2dBackpropInput.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.Copyright © 2022. All rights reserved.