| Modifier and Type | Class and Description |
|---|---|
static class |
Conv3DBackpropFilterV2.Options
Optional attributes for
Conv3DBackpropFilterV2 |
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<Integer> filterSizes,
Operand<T> outBackprop,
List<Long> strides,
String padding,
Conv3DBackpropFilterV2.Options... options)
Factory method to create a class to wrap a new Conv3DBackpropFilterV2 operation to the graph.
|
static Conv3DBackpropFilterV2.Options |
dataFormat(String dataFormat) |
static Conv3DBackpropFilterV2.Options |
dilations(List<Long> dilations) |
Output<T> |
output() |
equals, hashCode, toStringpublic static <T extends Number> Conv3DBackpropFilterV2<T> create(Scope scope, Operand<T> input, Operand<Integer> filterSizes, Operand<T> outBackprop, List<Long> strides, String padding, Conv3DBackpropFilterV2.Options... options)
scope - current graph scopeinput - Shape `[batch, depth, rows, cols, in_channels]`.filterSizes - An integer vector representing the tensor shape of `filter`,
where `filter` is a 5-D
`[filter_depth, filter_height, filter_width, in_channels, out_channels]`
tensor.outBackprop - Backprop signal of shape `[batch, out_depth, out_rows, out_cols,
out_channels]`.strides - 1-D tensor of length 5. The stride of the sliding window for each
dimension of `input`. Must have `strides[0] = strides[4] = 1`.padding - The type of padding algorithm to use.options - carries optional attributes valuespublic static Conv3DBackpropFilterV2.Options dataFormat(String dataFormat)
dataFormat - The data format of the input and output data. With the
default format "NDHWC", the data is stored in the order of:
[batch, in_depth, in_height, in_width, in_channels].
Alternatively, the format could be "NCDHW", the data storage order is:
[batch, in_channels, in_depth, in_height, in_width].public static Conv3DBackpropFilterV2.Options dilations(List<Long> dilations)
dilations - 1-D tensor of length 5. 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> 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.