Modifier and Type | Class and Description |
---|---|
static class |
Conv3dBackpropInput.Options
Optional attributes for
Conv3dBackpropInput |
operation
Modifier and Type | Method and Description |
---|---|
Output<U> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <U extends Number,T extends Number> |
create(Scope scope,
Operand<T> inputSizes,
Operand<U> filter,
Operand<U> outBackprop,
List<Long> strides,
String padding,
Conv3dBackpropInput.Options... options)
Factory method to create a class wrapping a new Conv3dBackpropInput operation.
|
static Conv3dBackpropInput.Options |
dataFormat(String dataFormat) |
static Conv3dBackpropInput.Options |
dilations(List<Long> dilations) |
Output<U> |
output() |
equals, hashCode, op, toString
public static <U extends Number,T extends Number> Conv3dBackpropInput<U> create(Scope scope, Operand<T> inputSizes, Operand<U> filter, Operand<U> outBackprop, List<Long> strides, String padding, Conv3dBackpropInput.Options... options)
scope
- current scopeinputSizes
- An integer vector representing the tensor shape of `input`,
where `input` is a 5-D
`[batch, depth, rows, cols, in_channels]` tensor.filter
- Shape `[depth, rows, cols, in_channels, out_channels]`.
`in_channels` must match between `input` and `filter`.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 Conv3dBackpropInput.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 Conv3dBackpropInput.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<U> asOutput()
Operand
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.
asOutput
in interface Operand<U extends Number>
OperationBuilder.addInput(Output)
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