Go: Update generated wrapper functions for TensorFlow ops.
PiperOrigin-RevId: 219882917
This commit is contained in:
A. Unique TensorFlower
TensorFlower Gardener
parent
09f82cbffd
commit
937617ed6a
@ -5475,6 +5475,78 @@ func OrderedMapUnstage(scope *Scope, key tf.Output, indices tf.Output, dtypes []
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return values
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}
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// OrderedMapPeekAttr is an optional argument to OrderedMapPeek.
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type OrderedMapPeekAttr func(optionalAttr)
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// OrderedMapPeekCapacity sets the optional capacity attribute to value.
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// If not specified, defaults to 0
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//
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// REQUIRES: value >= 0
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func OrderedMapPeekCapacity(value int64) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["capacity"] = value
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}
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}
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// OrderedMapPeekMemoryLimit sets the optional memory_limit attribute to value.
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// If not specified, defaults to 0
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//
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// REQUIRES: value >= 0
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func OrderedMapPeekMemoryLimit(value int64) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["memory_limit"] = value
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}
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}
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// OrderedMapPeekContainer sets the optional container attribute to value.
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// If not specified, defaults to ""
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func OrderedMapPeekContainer(value string) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["container"] = value
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}
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}
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// OrderedMapPeekSharedName sets the optional shared_name attribute to value.
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// If not specified, defaults to ""
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func OrderedMapPeekSharedName(value string) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["shared_name"] = value
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}
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}
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// Op peeks at the values at the specified key. If the
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//
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// underlying container does not contain this key
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// this op will block until it does. This Op is optimized for
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// performance.
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func OrderedMapPeek(scope *Scope, key tf.Output, indices tf.Output, dtypes []tf.DataType, optional ...OrderedMapPeekAttr) (values []tf.Output) {
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if scope.Err() != nil {
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return
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}
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attrs := map[string]interface{}{"dtypes": dtypes}
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for _, a := range optional {
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a(attrs)
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}
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opspec := tf.OpSpec{
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Type: "OrderedMapPeek",
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Input: []tf.Input{
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key, indices,
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},
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Attrs: attrs,
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}
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op := scope.AddOperation(opspec)
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if scope.Err() != nil {
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return
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}
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var idx int
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var err error
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if values, idx, err = makeOutputList(op, idx, "values"); err != nil {
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scope.UpdateErr("OrderedMapPeek", err)
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return
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}
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return values
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}
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// Returns the truth value of x OR y element-wise.
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//
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// *NOTE*: `LogicalOr` supports broadcasting. More about broadcasting
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@ -6994,6 +7066,36 @@ func Cast(scope *Scope, x tf.Output, DstT tf.DataType, optional ...CastAttr) (y
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return op.Output(0)
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}
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// Outputs a tensor containing the reduction across all input tensors.
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//
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// Outputs a tensor containing the reduction across all input tensors passed to ops
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// within the same `shared_name.
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//
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// The graph should be constructed so if one op runs with shared_name value `c`,
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// then `num_devices` ops will run with shared_name value `c`. Failure to do so
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// will cause the graph execution to fail to complete.
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//
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// input: the input to the reduction
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// data: the value of the reduction across all `num_devices` devices.
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// reduction: the reduction operation to perform.
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// num_devices: The number of devices participating in this reduction.
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// shared_name: Identifier that shared between ops of the same reduction.
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func NcclAllReduce(scope *Scope, input tf.Output, reduction string, num_devices int64, shared_name string) (data tf.Output) {
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if scope.Err() != nil {
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return
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}
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attrs := map[string]interface{}{"reduction": reduction, "num_devices": num_devices, "shared_name": shared_name}
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opspec := tf.OpSpec{
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Type: "NcclAllReduce",
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Input: []tf.Input{
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input,
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},
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Attrs: attrs,
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}
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op := scope.AddOperation(opspec)
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return op.Output(0)
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}
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// RegexReplaceAttr is an optional argument to RegexReplace.
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type RegexReplaceAttr func(optionalAttr)
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@ -8971,6 +9073,32 @@ func SparseFillEmptyRows(scope *Scope, indices tf.Output, values tf.Output, dens
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return op.Output(0), op.Output(1), op.Output(2), op.Output(3)
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}
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// Reduces `input` from `num_devices` using `reduction` to a single device.
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//
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// Reduces `input` from `num_devices` using `reduction` to a single device.
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//
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// The graph should be constructed so that all inputs have a valid device
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// assignment, and the op itself is assigned one of these devices.
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//
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// input: The input to the reduction.
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// data: the value of the reduction across all `num_devices` devices.
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// reduction: the reduction operation to perform.
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func NcclReduce(scope *Scope, input []tf.Output, reduction string) (data tf.Output) {
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if scope.Err() != nil {
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return
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}
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attrs := map[string]interface{}{"reduction": reduction}
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opspec := tf.OpSpec{
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Type: "NcclReduce",
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Input: []tf.Input{
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tf.OutputList(input),
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},
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Attrs: attrs,
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}
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op := scope.AddOperation(opspec)
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return op.Output(0)
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}
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// BiasAddGradAttr is an optional argument to BiasAddGrad.
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type BiasAddGradAttr func(optionalAttr)
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@ -10738,6 +10866,31 @@ func NonMaxSuppressionV2(scope *Scope, boxes tf.Output, scores tf.Output, max_ou
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return op.Output(0)
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}
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// Converts a `RaggedTensor` into a `SparseTensor` with the same values.
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//
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// input=ragged.from_nested_row_splits(rt_dense_values, rt_nested_splits)
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// output=SparseTensor(indices=sparse_indices, values=sparse_values,
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// dense_shape=sparse_dense_shape)
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//
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// Arguments:
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// rt_nested_splits: The `row_splits` for the `RaggedTensor`.
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// rt_dense_values: The `inner_values` for the `RaggedTensor`.
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//
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// Returns The indices for the `SparseTensor`.The values of the `SparseTensor`.`sparse_dense_shape` is a tight bounding box of the input `RaggedTensor`.
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func RaggedTensorToSparse(scope *Scope, rt_nested_splits []tf.Output, rt_dense_values tf.Output) (sparse_indices tf.Output, sparse_values tf.Output, sparse_dense_shape tf.Output) {
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if scope.Err() != nil {
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return
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}
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opspec := tf.OpSpec{
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Type: "RaggedTensorToSparse",
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Input: []tf.Input{
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tf.OutputList(rt_nested_splits), rt_dense_values,
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},
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}
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op := scope.AddOperation(opspec)
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return op.Output(0), op.Output(1), op.Output(2)
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}
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// Check if the input matches the regex pattern.
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//
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// The input is a string tensor of any shape. The pattern is a scalar
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@ -15397,78 +15550,6 @@ func SparseAdd(scope *Scope, a_indices tf.Output, a_values tf.Output, a_shape tf
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return op.Output(0), op.Output(1), op.Output(2)
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}
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// OrderedMapPeekAttr is an optional argument to OrderedMapPeek.
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type OrderedMapPeekAttr func(optionalAttr)
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// OrderedMapPeekCapacity sets the optional capacity attribute to value.
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// If not specified, defaults to 0
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//
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// REQUIRES: value >= 0
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func OrderedMapPeekCapacity(value int64) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["capacity"] = value
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}
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}
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// OrderedMapPeekMemoryLimit sets the optional memory_limit attribute to value.
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// If not specified, defaults to 0
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//
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// REQUIRES: value >= 0
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func OrderedMapPeekMemoryLimit(value int64) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["memory_limit"] = value
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}
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}
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// OrderedMapPeekContainer sets the optional container attribute to value.
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// If not specified, defaults to ""
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func OrderedMapPeekContainer(value string) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["container"] = value
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}
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}
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// OrderedMapPeekSharedName sets the optional shared_name attribute to value.
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// If not specified, defaults to ""
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func OrderedMapPeekSharedName(value string) OrderedMapPeekAttr {
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return func(m optionalAttr) {
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m["shared_name"] = value
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}
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}
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// Op peeks at the values at the specified key. If the
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//
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// underlying container does not contain this key
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// this op will block until it does. This Op is optimized for
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// performance.
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func OrderedMapPeek(scope *Scope, key tf.Output, indices tf.Output, dtypes []tf.DataType, optional ...OrderedMapPeekAttr) (values []tf.Output) {
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if scope.Err() != nil {
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return
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}
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attrs := map[string]interface{}{"dtypes": dtypes}
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for _, a := range optional {
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a(attrs)
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}
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opspec := tf.OpSpec{
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Type: "OrderedMapPeek",
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Input: []tf.Input{
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key, indices,
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},
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Attrs: attrs,
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}
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op := scope.AddOperation(opspec)
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if scope.Err() != nil {
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return
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}
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var idx int
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var err error
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if values, idx, err = makeOutputList(op, idx, "values"); err != nil {
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scope.UpdateErr("OrderedMapPeek", err)
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return
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}
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return values
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}
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// LRNAttr is an optional argument to LRN.
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type LRNAttr func(optionalAttr)
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@ -22120,6 +22201,108 @@ func MatrixTriangularSolve(scope *Scope, matrix tf.Output, rhs tf.Output, option
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return op.Output(0)
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}
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// UnicodeTranscodeAttr is an optional argument to UnicodeTranscode.
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type UnicodeTranscodeAttr func(optionalAttr)
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// UnicodeTranscodeErrors sets the optional errors attribute to value.
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//
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// value: Error handling policy when there is invalid formatting found in the input.
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// The value of 'strict' will cause the operation to produce a InvalidArgument
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// error on any invalid input formatting. A value of 'replace' (the default) will
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// cause the operation to replace any invalid formatting in the input with the
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// `replacement_char` codepoint. A value of 'ignore' will cause the operation to
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// skip any invalid formatting in the input and produce no corresponding output
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// character.
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// If not specified, defaults to "replace"
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func UnicodeTranscodeErrors(value string) UnicodeTranscodeAttr {
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return func(m optionalAttr) {
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m["errors"] = value
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}
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}
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// UnicodeTranscodeReplacementChar sets the optional replacement_char attribute to value.
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//
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// value: The replacement character codepoint to be used in place of any invalid
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// formatting in the input when `errors='replace'`. Any valid unicode codepoint may
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// be used. The default value is the default unicode replacement character is
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// 0xFFFD or U+65533.)
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//
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// Note that for UTF-8, passing a replacement character expressible in 1 byte, such
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// as ' ', will preserve string alignment to the source since invalid bytes will be
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// replaced with a 1-byte replacement. For UTF-16-BE and UTF-16-LE, any 1 or 2 byte
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// replacement character will preserve byte alignment to the source.
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// If not specified, defaults to 65533
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func UnicodeTranscodeReplacementChar(value int64) UnicodeTranscodeAttr {
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return func(m optionalAttr) {
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m["replacement_char"] = value
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}
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}
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// UnicodeTranscodeReplaceControlCharacters sets the optional replace_control_characters attribute to value.
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//
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// value: Whether to replace the C0 control characters (00-1F) with the
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// `replacement_char`. Default is false.
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// If not specified, defaults to false
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func UnicodeTranscodeReplaceControlCharacters(value bool) UnicodeTranscodeAttr {
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return func(m optionalAttr) {
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m["replace_control_characters"] = value
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}
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}
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// Transcode the input text from a source encoding to a destination encoding.
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//
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// The input is a string tensor of any shape. The output is a string tensor of
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// the same shape containing the transcoded strings. Output strings are always
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// valid unicode. If the input contains invalid encoding positions, the
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// `errors` attribute sets the policy for how to deal with them. If the default
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// error-handling policy is used, invalid formatting will be substituted in the
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// output by the `replacement_char`. If the errors policy is to `ignore`, any
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// invalid encoding positions in the input are skipped and not included in the
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// output. If it set to `strict` then any invalid formatting will result in an
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// InvalidArgument error.
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//
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// This operation can be used with `output_encoding = input_encoding` to enforce
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// correct formatting for inputs even if they are already in the desired encoding.
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//
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// If the input is prefixed by a Byte Order Mark needed to determine encoding
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// (e.g. if the encoding is UTF-16 and the BOM indicates big-endian), then that
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// BOM will be consumed and not emitted into the output. If the input encoding
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// is marked with an explicit endianness (e.g. UTF-16-BE), then the BOM is
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// interpreted as a non-breaking-space and is preserved in the output (including
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// always for UTF-8).
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//
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// The end result is that if the input is marked as an explicit endianness the
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// transcoding is faithful to all codepoints in the source. If it is not marked
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// with an explicit endianness, the BOM is not considered part of the string itself
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// but as metadata, and so is not preserved in the output.
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//
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// Arguments:
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// input: The text to be processed. Can have any shape.
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// input_encoding: Text encoding of the input strings. This is any of the encodings supported
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// by ICU ucnv algorithmic converters. Examples: `"UTF-16", "US ASCII", "UTF-8"`.
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// output_encoding: The unicode encoding to use in the output. Must be one of
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// `"UTF-8", "UTF-16-BE", "UTF-32-BE"`. Multi-byte encodings will be big-endian.
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//
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// Returns A string tensor containing unicode text encoded using `output_encoding`.
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func UnicodeTranscode(scope *Scope, input tf.Output, input_encoding string, output_encoding string, optional ...UnicodeTranscodeAttr) (output tf.Output) {
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if scope.Err() != nil {
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return
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}
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attrs := map[string]interface{}{"input_encoding": input_encoding, "output_encoding": output_encoding}
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for _, a := range optional {
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a(attrs)
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}
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opspec := tf.OpSpec{
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Type: "UnicodeTranscode",
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Input: []tf.Input{
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input,
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},
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Attrs: attrs,
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}
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op := scope.AddOperation(opspec)
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return op.Output(0)
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}
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// Computes inverse hyperbolic sine of x element-wise.
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func Asinh(scope *Scope, x tf.Output) (y tf.Output) {
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if scope.Err() != nil {
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@ -24464,6 +24647,33 @@ func Real(scope *Scope, input tf.Output, optional ...RealAttr) (output tf.Output
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return op.Output(0)
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}
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// Sends `input` to all devices that are connected to the output.
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//
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// Sends `input` to all devices that are connected to the output.
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//
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// The graph should be constructed so that all ops connected to the output have a
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// valid device assignment, and the op itself is assigned one of these devices.
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//
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// input: The input to the broadcast.
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// output: The same as input.
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// shape: The shape of the input tensor.
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//
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func NcclBroadcast(scope *Scope, input tf.Output, shape tf.Shape) (output tf.Output) {
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if scope.Err() != nil {
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return
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}
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attrs := map[string]interface{}{"shape": shape}
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opspec := tf.OpSpec{
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Type: "NcclBroadcast",
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Input: []tf.Input{
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input,
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},
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Attrs: attrs,
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}
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op := scope.AddOperation(opspec)
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return op.Output(0)
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}
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// ResizeAreaAttr is an optional argument to ResizeArea.
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type ResizeAreaAttr func(optionalAttr)
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