Conv3dBackpropInput

public final class Conv3dBackpropInput

Computes the gradients of 3-D convolution with respect to the input.

Nested Classes

class Conv3dBackpropInput.Options Optional attributes for Conv3dBackpropInput  

Constants

String OP_NAME The name of this op, as known by TensorFlow core engine

Public Methods

Output<U>
asOutput()
Returns the symbolic handle of the tensor.
static <U extends TNumber> Conv3dBackpropInput<U>
create(Scope scope, Operand<? extends TNumber> inputSizes, Operand<U> filter, Operand<U> outBackprop, List<Long> strides, String padding, 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()

Inherited Methods

org.tensorflow.op.RawOp
final boolean
equals(Object obj)
final int
hashCode()
Operation
op()
Return this unit of computation as a single Operation.
final String
toString()
boolean
equals(Object arg0)
final Class<?>
getClass()
int
hashCode()
final void
notify()
final void
notifyAll()
String
toString()
final void
wait(long arg0, int arg1)
final void
wait(long arg0)
final void
wait()
org.tensorflow.op.Op
abstract ExecutionEnvironment
env()
Return the execution environment this op was created in.
abstract Operation
op()
Return this unit of computation as a single Operation.
org.tensorflow.Operand
abstract Output<U extends TNumber>
asOutput()
Returns the symbolic handle of the tensor.
abstract U extends TNumber
asTensor()
Returns the tensor at this operand.
abstract Shape
shape()
Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<U extends TNumber>
type()
Returns the tensor type of this operand
org.tensorflow.ndarray.Shaped
abstract int
rank()
abstract Shape
shape()
abstract long
size()
Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "Conv3DBackpropInputV2"

Public Methods

public Output<U> 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 Conv3dBackpropInput<U> create (Scope scope, Operand<? extends TNumber> inputSizes, Operand<U> filter, Operand<U> outBackprop, List<Long> strides, String padding, Options... options)

Factory method to create a class wrapping a new Conv3dBackpropInput operation.

Parameters
scope current scope
inputSizes 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 values
Returns
  • a new instance of Conv3dBackpropInput

public static Conv3dBackpropInput.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].

public static Conv3dBackpropInput.Options dilations (List<Long> dilations)

Parameters
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> output ()