FusedPadConv2d

public final class FusedPadConv2d

Performs a padding as a preprocess during a convolution.

Similar to FusedResizeAndPadConv2d, this op allows for an optimized implementation where the spatial padding transformation stage is fused with the im2col lookup, but in this case without the bilinear filtering required for resizing. Fusing the padding prevents the need to write out the intermediate results as whole tensors, reducing memory pressure, and we can get some latency gains by merging the transformation calculations. The data_format attribute for Conv2D isn't supported by this op, and 'NHWC' order is used instead. Internally this op uses a single per-graph scratch buffer, which means that it will block if multiple versions are being run in parallel. This is because this operator is primarily an optimization to minimize memory usage.

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> FusedPadConv2d<T>
create(Scope scope, Operand<T> input, Operand<TInt32> paddings, Operand<T> filter, String mode, List<Long> strides, String padding)
Factory method to create a class wrapping a new FusedPadConv2d operation.
Output<T>
output()

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "FusedPadConv2D"

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 FusedPadConv2d<T> create (Scope scope, Operand<T> input, Operand<TInt32> paddings, Operand<T> filter, String mode, List<Long> strides, String padding)

Factory method to create a class wrapping a new FusedPadConv2d operation.

Parameters
scope current scope
input 4-D with shape `[batch, in_height, in_width, in_channels]`.
paddings A two-column matrix specifying the padding sizes. The number of rows must be the same as the rank of `input`.
filter 4-D with shape `[filter_height, filter_width, in_channels, out_channels]`.
strides 1-D of length 4. The stride of the sliding window for each dimension of `input`. Must be in the same order as the dimension specified with format.
padding The type of padding algorithm to use.
Returns
  • a new instance of FusedPadConv2d

public Output<T> output ()