@Operator public final class TensorArraySplit extends PrimitiveOp implements Operand<Float>
Assuming that `lengths` takes on values
(n0, n1, ..., n(T-1))
and that `value` has shape
(n0 + n1 + ... + n(T-1) x d0 x d1 x ...)
,
this splits values into a TensorArray with T tensors.
TensorArray index t will be the subtensor of values with starting position
(n0 + n1 + ... + n(t-1), 0, 0, ...)
and having size
nt x d0 x d1 x ...
operation
Modifier and Type | Method and Description |
---|---|
Output<Float> |
asOutput()
Returns the symbolic handle of a tensor.
|
static <T> TensorArraySplit |
create(Scope scope,
Operand<?> handle,
Operand<T> value,
Operand<Long> lengths,
Operand<Float> flowIn)
Factory method to create a class wrapping a new TensorArraySplit operation.
|
Output<Float> |
flowOut()
A float scalar that enforces proper chaining of operations.
|
equals, hashCode, op, toString
public static <T> TensorArraySplit create(Scope scope, Operand<?> handle, Operand<T> value, Operand<Long> lengths, Operand<Float> flowIn)
scope
- current scopehandle
- The handle to a TensorArray.value
- The concatenated tensor to write to the TensorArray.lengths
- The vector of lengths, how to split the rows of value into the
TensorArray.flowIn
- A float scalar that enforces proper chaining of operations.public Output<Float> 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<Float>
OperationBuilder.addInput(Output)
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