T
- data type for output()
output@Operator(group="nn") public final class FusedResizeAndPadConv2d<T extends Number> extends PrimitiveOp implements Operand<T>
It's often possible to do spatial transformations more efficiently as part of the packing stage of a convolution, so this op allows for an optimized implementation where these stages are fused together. This 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 defaults to 'NHWC' order. 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.
Modifier and Type | Class and Description |
---|---|
static class |
FusedResizeAndPadConv2d.Options
Optional attributes for
FusedResizeAndPadConv2d |
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> size,
Operand<Integer> paddings,
Operand<T> filter,
String mode,
List<Long> strides,
String padding,
FusedResizeAndPadConv2d.Options... options)
Factory method to create a class wrapping a new FusedResizeAndPadConv2d operation.
|
Output<T> |
output() |
static FusedResizeAndPadConv2d.Options |
resizeAlignCorners(Boolean resizeAlignCorners) |
equals, hashCode, op, toString
public static <T extends Number> FusedResizeAndPadConv2d<T> create(Scope scope, Operand<T> input, Operand<Integer> size, Operand<Integer> paddings, Operand<T> filter, String mode, List<Long> strides, String padding, FusedResizeAndPadConv2d.Options... options)
scope
- current scopeinput
- 4-D with shape `[batch, in_height, in_width, in_channels]`.size
- A 1-D int32 Tensor of 2 elements: `new_height, new_width`. The
new size for the images.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]`.mode
- 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.options
- carries optional attributes valuespublic static FusedResizeAndPadConv2d.Options resizeAlignCorners(Boolean resizeAlignCorners)
resizeAlignCorners
- If true, the centers of the 4 corner pixels of the input and output tensors are
aligned, preserving the values at the corner pixels. Defaults to false.public Output<T> 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<T extends Number>
OperationBuilder.addInput(Output)
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