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SparseSlice

public final class SparseSlice

Slice a `SparseTensor` based on the `start` and `size`.

For example, if the input is

input_tensor = shape = [2, 7] [ a d e ] [b c ]

Graphically the output tensors are:

sparse_slice([0, 0], [2, 4]) = shape = [2, 4] [ a ] [b c ]

sparse_slice([0, 4], [2, 3]) = shape = [2, 3] [ d e ] [ ]

Constants

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

Public Methods

static <T extends TType > SparseSlice <T>
create ( Scope scope, Operand < TInt64 > indices, Operand <T> values, Operand < TInt64 > shape, Operand < TInt64 > start, Operand < TInt64 > size)
Factory method to create a class wrapping a new SparseSlice operation.
Output < TInt64 >
Output < TInt64 >
outputShape ()
A list of 1-D tensors represents the shape of the output sparse tensors.
Output <T>
outputValues ()
A list of 1-D tensors represents the values of the output sparse tensors.

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "SparseSlice"

Public Methods

public static SparseSlice <T> create ( Scope scope, Operand < TInt64 > indices, Operand <T> values, Operand < TInt64 > shape, Operand < TInt64 > start, Operand < TInt64 > size)

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

Parameters
scope current scope
indices 2-D tensor represents the indices of the sparse tensor.
values 1-D tensor represents the values of the sparse tensor.
shape 1-D. tensor represents the shape of the sparse tensor.
start 1-D. tensor represents the start of the slice.
size 1-D. tensor represents the size of the slice. output indices: A list of 1-D tensors represents the indices of the output sparse tensors.
Returns
  • a new instance of SparseSlice

public Output < TInt64 > outputIndices ()

public Output < TInt64 > outputShape ()

A list of 1-D tensors represents the shape of the output sparse tensors.

public Output <T> outputValues ()

A list of 1-D tensors represents the values of the output sparse tensors.