SparseFillEmptyRows

public final class SparseFillEmptyRows

Fills empty rows in the input 2-D `SparseTensor` with a default value.

The input `SparseTensor` is represented via the tuple of inputs (`indices`, `values`, `dense_shape`). The output `SparseTensor` has the same `dense_shape` but with indices `output_indices` and values `output_values`.

This op inserts a single entry for every row that doesn't have any values. The index is created as `[row, 0, ..., 0]` and the inserted value is `default_value`.

For example, suppose `sp_input` has shape `[5, 6]` and non-empty values:

[0, 1]: a [0, 3]: b [2, 0]: c [3, 1]: d

Rows 1 and 4 are empty, so the output will be of shape `[5, 6]` with values:

[0, 1]: a [0, 3]: b [1, 0]: default_value [2, 0]: c [3, 1]: d [4, 0]: default_value

The output `SparseTensor` will be in row-major order and will have the same shape as the input.

This op also returns an indicator vector shaped `[dense_shape[0]]` such that

empty_row_indicator[i] = True iff row i was an empty row.

And a reverse index map vector shaped `[indices.shape[0]]` that is used during backpropagation,

reverse_index_map[j] = out_j s.t. indices[j, :] == output_indices[out_j, :]

Constants

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

Public Methods

static <T extends TType> SparseFillEmptyRows<T>
create(Scope scope, Operand<TInt64> indices, Operand<T> values, Operand<TInt64> denseShape, Operand<T> defaultValue)
Factory method to create a class wrapping a new SparseFillEmptyRows operation.
Output<TBool>
Output<TInt64>
Output<T>
outputValues()
1-D.
Output<TInt64>

Inherited Methods

Constants

public static final String OP_NAME

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

Constant Value: "SparseFillEmptyRows"

Public Methods

public static SparseFillEmptyRows<T> create (Scope scope, Operand<TInt64> indices, Operand<T> values, Operand<TInt64> denseShape, Operand<T> defaultValue)

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

Parameters
scope current scope
indices 2-D. the indices of the sparse tensor.
values 1-D. the values of the sparse tensor.
denseShape 1-D. the shape of the sparse tensor.
defaultValue 0-D. default value to insert into location `[row, 0, ..., 0]` for rows missing from the input sparse tensor. output indices: 2-D. the indices of the filled sparse tensor.
Returns
  • a new instance of SparseFillEmptyRows

public Output<TBool> emptyRowIndicator ()

1-D. whether the dense row was missing in the input sparse tensor.

public Output<TInt64> outputIndices ()

public Output<T> outputValues ()

1-D. the values of the filled sparse tensor.

public Output<TInt64> reverseIndexMap ()

1-D. a map from the input indices to the output indices.