T
- data type for output()
output@Operator public final class ParallelConcat<T> extends PrimitiveOp implements Operand<T>
The input tensors are all required to have size 1 in the first dimension.
For example:
# 'x' is [[1, 4]]
# 'y' is [[2, 5]]
# 'z' is [[3, 6]]
parallel_concat([x, y, z]) => [[1, 4], [2, 5], [3, 6]] # Pack along first dim.
The difference between concat and parallel_concat is that concat requires all
of the inputs be computed before the operation will begin but doesn't require
that the input shapes be known during graph construction. Parallel concat
will copy pieces of the input into the output as they become available, in
some situations this can provide a performance benefit.operation
Modifier and Type | Method and Description |
---|---|
Output<T> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T> ParallelConcat<T> |
create(Scope scope,
Iterable<Operand<T>> values,
Shape shape)
Factory method to create a class wrapping a new ParallelConcat operation.
|
Output<T> |
output()
The concatenated tensor.
|
equals, hashCode, op, toString
public static <T> ParallelConcat<T> create(Scope scope, Iterable<Operand<T>> values, Shape shape)
scope
- current scopevalues
- Tensors to be concatenated. All must have size 1 in the first dimension
and same shape.shape
- the final shape of the result; should be equal to the shapes of any input
but with the number of input values in the first dimension.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>
OperationBuilder.addInput(Output)
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