Performs 3D average pooling on the input.
Each entry in `output` is the mean of the corresponding size `ksize` window in `value`.
Nested Classes
class | AvgPool3d.Options | Optional attributes for AvgPool3d
|
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> AvgPool3d<T> |
create(Scope scope, Operand<T> input, List<Long> ksize, List<Long> strides, String padding, Options... options)
Factory method to create a class wrapping a new AvgPool3d operation.
|
static AvgPool3d.Options |
dataFormat(String dataFormat)
|
Output<T> |
output()
The average pooled output tensor.
|
Inherited Methods
Constants
public static final String OP_NAME
The name of this op, as known by TensorFlow core engine
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 AvgPool3d<T> create (Scope scope, Operand<T> input, List<Long> ksize, List<Long> strides, String padding, Options... options)
Factory method to create a class wrapping a new AvgPool3d operation.
Parameters
scope | current scope |
---|---|
input | Shape `[batch, depth, rows, cols, channels]` tensor to pool over. |
ksize | 1-D tensor of length 5. The size of the window for each dimension of the input tensor. Must have `ksize[0] = ksize[4] = 1`. |
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 values |
Returns
- a new instance of AvgPool3d
public static AvgPool3d.Options dataFormat (String dataFormat)
Parameters
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]. |
---|