Go: Update generated wrapper functions for TensorFlow ops.

PiperOrigin-RevId: 214176089

1 files changed, 203 insertions, 203 deletions

diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index 1d72bcd2b6..e6e07c8437 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -3770,6 +3770,68 @@ func BoostedTreesMakeStatsSummary(scope *Scope, node_ids tf.Output, gradients tf
 	return op.Output(0)
 }
 
+// Retrieves the tree ensemble resource stamp token, number of trees and growing statistics.
+//
+// Arguments:
+//	tree_ensemble_handle: Handle to the tree ensemble.
+//
+// Returns Stamp token of the tree ensemble resource.The number of trees in the tree ensemble resource.The number of trees that were finished successfully.The number of layers we attempted to build (but not necessarily succeeded).Rank size 2 tensor that contains start and end ids of the nodes in the latest
+// layer.
+func BoostedTreesGetEnsembleStates(scope *Scope, tree_ensemble_handle tf.Output) (stamp_token tf.Output, num_trees tf.Output, num_finalized_trees tf.Output, num_attempted_layers tf.Output, last_layer_nodes_range tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	opspec := tf.OpSpec{
+		Type: "BoostedTreesGetEnsembleStates",
+		Input: []tf.Input{
+			tree_ensemble_handle,
+		},
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0), op.Output(1), op.Output(2), op.Output(3), op.Output(4)
+}
+
+// Creates a tree ensemble model and returns a handle to it.
+//
+// Arguments:
+//	tree_ensemble_handle: Handle to the tree ensemble resource to be created.
+//	stamp_token: Token to use as the initial value of the resource stamp.
+//	tree_ensemble_serialized: Serialized proto of the tree ensemble.
+//
+// Returns the created operation.
+func BoostedTreesCreateEnsemble(scope *Scope, tree_ensemble_handle tf.Output, stamp_token tf.Output, tree_ensemble_serialized tf.Output) (o *tf.Operation) {
+	if scope.Err() != nil {
+		return
+	}
+	opspec := tf.OpSpec{
+		Type: "BoostedTreesCreateEnsemble",
+		Input: []tf.Input{
+			tree_ensemble_handle, stamp_token, tree_ensemble_serialized,
+		},
+	}
+	return scope.AddOperation(opspec)
+}
+
+// Checks whether a tree ensemble has been initialized.
+//
+// Arguments:
+//	tree_ensemble_handle: Handle to the tree ensemble resouce.
+//
+// Returns output boolean on whether it is initialized or not.
+func IsBoostedTreesEnsembleInitialized(scope *Scope, tree_ensemble_handle tf.Output) (is_initialized tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	opspec := tf.OpSpec{
+		Type: "IsBoostedTreesEnsembleInitialized",
+		Input: []tf.Input{
+			tree_ensemble_handle,
+		},
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0)
+}
+
 // Computes the sum along sparse segments of a tensor.
 //
 // Read
@@ -5755,26 +5817,6 @@ func LogicalAnd(scope *Scope, x tf.Output, y tf.Output) (z tf.Output) {
 	return op.Output(0)
 }
 
-// Checks whether a tree ensemble has been initialized.
-//
-// Arguments:
-//	tree_ensemble_handle: Handle to the tree ensemble resouce.
-//
-// Returns output boolean on whether it is initialized or not.
-func IsBoostedTreesEnsembleInitialized(scope *Scope, tree_ensemble_handle tf.Output) (is_initialized tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	opspec := tf.OpSpec{
-		Type: "IsBoostedTreesEnsembleInitialized",
-		Input: []tf.Input{
-			tree_ensemble_handle,
-		},
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0)
-}
-
 // CastAttr is an optional argument to Cast.
 type CastAttr func(optionalAttr)
 
@@ -19714,27 +19756,6 @@ func OptimizeDataset(scope *Scope, input_dataset tf.Output, optimizations tf.Out
 	return op.Output(0)
 }
 
-// Retrieves the tree ensemble resource stamp token, number of trees and growing statistics.
-//
-// Arguments:
-//	tree_ensemble_handle: Handle to the tree ensemble.
-//
-// Returns Stamp token of the tree ensemble resource.The number of trees in the tree ensemble resource.The number of trees that were finished successfully.The number of layers we attempted to build (but not necessarily succeeded).Rank size 2 tensor that contains start and end ids of the nodes in the latest
-// layer.
-func BoostedTreesGetEnsembleStates(scope *Scope, tree_ensemble_handle tf.Output) (stamp_token tf.Output, num_trees tf.Output, num_finalized_trees tf.Output, num_attempted_layers tf.Output, last_layer_nodes_range tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	opspec := tf.OpSpec{
-		Type: "BoostedTreesGetEnsembleStates",
-		Input: []tf.Input{
-			tree_ensemble_handle,
-		},
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0), op.Output(1), op.Output(2), op.Output(3), op.Output(4)
-}
-
 // Returns the element-wise min of two SparseTensors.
 //
 // Assumes the two SparseTensors have the same shape, i.e., no broadcasting.
@@ -21078,6 +21099,147 @@ func SparseSegmentMean(scope *Scope, data tf.Output, indices tf.Output, segment_
 	return op.Output(0)
 }
 
+// Deserializes a serialized tree ensemble config and replaces current tree
+//
+// ensemble.
+//
+// Arguments:
+//	tree_ensemble_handle: Handle to the tree ensemble.
+//	stamp_token: Token to use as the new value of the resource stamp.
+//	tree_ensemble_serialized: Serialized proto of the ensemble.
+//
+// Returns the created operation.
+func BoostedTreesDeserializeEnsemble(scope *Scope, tree_ensemble_handle tf.Output, stamp_token tf.Output, tree_ensemble_serialized tf.Output) (o *tf.Operation) {
+	if scope.Err() != nil {
+		return
+	}
+	opspec := tf.OpSpec{
+		Type: "BoostedTreesDeserializeEnsemble",
+		Input: []tf.Input{
+			tree_ensemble_handle, stamp_token, tree_ensemble_serialized,
+		},
+	}
+	return scope.AddOperation(opspec)
+}
+
+// Transforms a tf.Example proto (as a string) into typed tensors.
+//
+// Arguments:
+//	serialized: A vector containing a batch of binary serialized Example protos.
+//	dense_defaults: A list of Tensors (some may be empty), whose length matches
+// the length of `dense_keys`. dense_defaults[j] provides default values
+// when the example's feature_map lacks dense_key[j].  If an empty Tensor is
+// provided for dense_defaults[j], then the Feature dense_keys[j] is required.
+// The input type is inferred from dense_defaults[j], even when it's empty.
+// If dense_defaults[j] is not empty, and dense_shapes[j] is fully defined,
+// then the shape of dense_defaults[j] must match that of dense_shapes[j].
+// If dense_shapes[j] has an undefined major dimension (variable strides dense
+// feature), dense_defaults[j] must contain a single element:
+// the padding element.
+//	num_sparse: The number of sparse features to be parsed from the example. This
+// must match the lengths of `sparse_keys` and `sparse_types`.
+//	sparse_keys: A list of `num_sparse` strings.
+// The keys expected in the Examples' features associated with sparse values.
+//	dense_keys: The keys expected in the Examples' features associated with dense
+// values.
+//	sparse_types: A list of `num_sparse` types; the data types of data in each
+// Feature given in sparse_keys.
+// Currently the ParseSingleExample op supports DT_FLOAT (FloatList),
+// DT_INT64 (Int64List), and DT_STRING (BytesList).
+//	dense_shapes: The shapes of data in each Feature given in dense_keys.
+// The length of this list must match the length of `dense_keys`.  The
+// number of elements in the Feature corresponding to dense_key[j] must
+// always equal dense_shapes[j].NumEntries().  If dense_shapes[j] ==
+// (D0, D1, ..., DN) then the shape of output Tensor dense_values[j]
+// will be (D0, D1, ..., DN): In the case dense_shapes[j] = (-1, D1,
+// ..., DN), the shape of the output Tensor dense_values[j] will be (M,
+// D1, .., DN), where M is the number of blocks of elements of length
+// D1 * .... * DN, in the input.
+func ParseSingleExample(scope *Scope, serialized tf.Output, dense_defaults []tf.Output, num_sparse int64, sparse_keys []string, dense_keys []string, sparse_types []tf.DataType, dense_shapes []tf.Shape) (sparse_indices []tf.Output, sparse_values []tf.Output, sparse_shapes []tf.Output, dense_values []tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	attrs := map[string]interface{}{"num_sparse": num_sparse, "sparse_keys": sparse_keys, "dense_keys": dense_keys, "sparse_types": sparse_types, "dense_shapes": dense_shapes}
+	opspec := tf.OpSpec{
+		Type: "ParseSingleExample",
+		Input: []tf.Input{
+			serialized, tf.OutputList(dense_defaults),
+		},
+		Attrs: attrs,
+	}
+	op := scope.AddOperation(opspec)
+	if scope.Err() != nil {
+		return
+	}
+	var idx int
+	var err error
+	if sparse_indices, idx, err = makeOutputList(op, idx, "sparse_indices"); err != nil {
+		scope.UpdateErr("ParseSingleExample", err)
+		return
+	}
+	if sparse_values, idx, err = makeOutputList(op, idx, "sparse_values"); err != nil {
+		scope.UpdateErr("ParseSingleExample", err)
+		return
+	}
+	if sparse_shapes, idx, err = makeOutputList(op, idx, "sparse_shapes"); err != nil {
+		scope.UpdateErr("ParseSingleExample", err)
+		return
+	}
+	if dense_values, idx, err = makeOutputList(op, idx, "dense_values"); err != nil {
+		scope.UpdateErr("ParseSingleExample", err)
+		return
+	}
+	return sparse_indices, sparse_values, sparse_shapes, dense_values
+}
+
+// WholeFileReaderV2Attr is an optional argument to WholeFileReaderV2.
+type WholeFileReaderV2Attr func(optionalAttr)
+
+// WholeFileReaderV2Container sets the optional container attribute to value.
+//
+// value: If non-empty, this reader is placed in the given container.
+// Otherwise, a default container is used.
+// If not specified, defaults to ""
+func WholeFileReaderV2Container(value string) WholeFileReaderV2Attr {
+	return func(m optionalAttr) {
+		m["container"] = value
+	}
+}
+
+// WholeFileReaderV2SharedName sets the optional shared_name attribute to value.
+//
+// value: If non-empty, this reader is named in the given bucket
+// with this shared_name. Otherwise, the node name is used instead.
+// If not specified, defaults to ""
+func WholeFileReaderV2SharedName(value string) WholeFileReaderV2Attr {
+	return func(m optionalAttr) {
+		m["shared_name"] = value
+	}
+}
+
+// A Reader that outputs the entire contents of a file as a value.
+//
+// To use, enqueue filenames in a Queue.  The output of ReaderRead will
+// be a filename (key) and the contents of that file (value).
+//
+// Returns The handle to reference the Reader.
+func WholeFileReaderV2(scope *Scope, optional ...WholeFileReaderV2Attr) (reader_handle tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	attrs := map[string]interface{}{}
+	for _, a := range optional {
+		a(attrs)
+	}
+	opspec := tf.OpSpec{
+		Type: "WholeFileReaderV2",
+
+		Attrs: attrs,
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0)
+}
+
 // Pop the element at the top of the stack.
 //
 // Arguments:
@@ -30734,27 +30896,6 @@ func TensorArrayScatterV2(scope *Scope, handle tf.Output, indices tf.Output, val
 	return op.Output(0)
 }
 
-// Creates a tree ensemble model and returns a handle to it.
-//
-// Arguments:
-//	tree_ensemble_handle: Handle to the tree ensemble resource to be created.
-//	stamp_token: Token to use as the initial value of the resource stamp.
-//	tree_ensemble_serialized: Serialized proto of the tree ensemble.
-//
-// Returns the created operation.
-func BoostedTreesCreateEnsemble(scope *Scope, tree_ensemble_handle tf.Output, stamp_token tf.Output, tree_ensemble_serialized tf.Output) (o *tf.Operation) {
-	if scope.Err() != nil {
-		return
-	}
-	opspec := tf.OpSpec{
-		Type: "BoostedTreesCreateEnsemble",
-		Input: []tf.Input{
-			tree_ensemble_handle, stamp_token, tree_ensemble_serialized,
-		},
-	}
-	return scope.AddOperation(opspec)
-}
-
 // Applies sparse addition to `input` using individual values or slices
 //
 // from `updates` according to indices `indices`.  The updates are non-aliasing:
@@ -32575,144 +32716,3 @@ func FixedUnigramCandidateSampler(scope *Scope, true_classes tf.Output, num_true
 	op := scope.AddOperation(opspec)
 	return op.Output(0), op.Output(1), op.Output(2)
 }
-
-// Transforms a tf.Example proto (as a string) into typed tensors.
-//
-// Arguments:
-//	serialized: A vector containing a batch of binary serialized Example protos.
-//	dense_defaults: A list of Tensors (some may be empty), whose length matches
-// the length of `dense_keys`. dense_defaults[j] provides default values
-// when the example's feature_map lacks dense_key[j].  If an empty Tensor is
-// provided for dense_defaults[j], then the Feature dense_keys[j] is required.
-// The input type is inferred from dense_defaults[j], even when it's empty.
-// If dense_defaults[j] is not empty, and dense_shapes[j] is fully defined,
-// then the shape of dense_defaults[j] must match that of dense_shapes[j].
-// If dense_shapes[j] has an undefined major dimension (variable strides dense
-// feature), dense_defaults[j] must contain a single element:
-// the padding element.
-//	num_sparse: The number of sparse features to be parsed from the example. This
-// must match the lengths of `sparse_keys` and `sparse_types`.
-//	sparse_keys: A list of `num_sparse` strings.
-// The keys expected in the Examples' features associated with sparse values.
-//	dense_keys: The keys expected in the Examples' features associated with dense
-// values.
-//	sparse_types: A list of `num_sparse` types; the data types of data in each
-// Feature given in sparse_keys.
-// Currently the ParseSingleExample op supports DT_FLOAT (FloatList),
-// DT_INT64 (Int64List), and DT_STRING (BytesList).
-//	dense_shapes: The shapes of data in each Feature given in dense_keys.
-// The length of this list must match the length of `dense_keys`.  The
-// number of elements in the Feature corresponding to dense_key[j] must
-// always equal dense_shapes[j].NumEntries().  If dense_shapes[j] ==
-// (D0, D1, ..., DN) then the shape of output Tensor dense_values[j]
-// will be (D0, D1, ..., DN): In the case dense_shapes[j] = (-1, D1,
-// ..., DN), the shape of the output Tensor dense_values[j] will be (M,
-// D1, .., DN), where M is the number of blocks of elements of length
-// D1 * .... * DN, in the input.
-func ParseSingleExample(scope *Scope, serialized tf.Output, dense_defaults []tf.Output, num_sparse int64, sparse_keys []string, dense_keys []string, sparse_types []tf.DataType, dense_shapes []tf.Shape) (sparse_indices []tf.Output, sparse_values []tf.Output, sparse_shapes []tf.Output, dense_values []tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	attrs := map[string]interface{}{"num_sparse": num_sparse, "sparse_keys": sparse_keys, "dense_keys": dense_keys, "sparse_types": sparse_types, "dense_shapes": dense_shapes}
-	opspec := tf.OpSpec{
-		Type: "ParseSingleExample",
-		Input: []tf.Input{
-			serialized, tf.OutputList(dense_defaults),
-		},
-		Attrs: attrs,
-	}
-	op := scope.AddOperation(opspec)
-	if scope.Err() != nil {
-		return
-	}
-	var idx int
-	var err error
-	if sparse_indices, idx, err = makeOutputList(op, idx, "sparse_indices"); err != nil {
-		scope.UpdateErr("ParseSingleExample", err)
-		return
-	}
-	if sparse_values, idx, err = makeOutputList(op, idx, "sparse_values"); err != nil {
-		scope.UpdateErr("ParseSingleExample", err)
-		return
-	}
-	if sparse_shapes, idx, err = makeOutputList(op, idx, "sparse_shapes"); err != nil {
-		scope.UpdateErr("ParseSingleExample", err)
-		return
-	}
-	if dense_values, idx, err = makeOutputList(op, idx, "dense_values"); err != nil {
-		scope.UpdateErr("ParseSingleExample", err)
-		return
-	}
-	return sparse_indices, sparse_values, sparse_shapes, dense_values
-}
-
-// WholeFileReaderV2Attr is an optional argument to WholeFileReaderV2.
-type WholeFileReaderV2Attr func(optionalAttr)
-
-// WholeFileReaderV2Container sets the optional container attribute to value.
-//
-// value: If non-empty, this reader is placed in the given container.
-// Otherwise, a default container is used.
-// If not specified, defaults to ""
-func WholeFileReaderV2Container(value string) WholeFileReaderV2Attr {
-	return func(m optionalAttr) {
-		m["container"] = value
-	}
-}
-
-// WholeFileReaderV2SharedName sets the optional shared_name attribute to value.
-//
-// value: If non-empty, this reader is named in the given bucket
-// with this shared_name. Otherwise, the node name is used instead.
-// If not specified, defaults to ""
-func WholeFileReaderV2SharedName(value string) WholeFileReaderV2Attr {
-	return func(m optionalAttr) {
-		m["shared_name"] = value
-	}
-}
-
-// A Reader that outputs the entire contents of a file as a value.
-//
-// To use, enqueue filenames in a Queue.  The output of ReaderRead will
-// be a filename (key) and the contents of that file (value).
-//
-// Returns The handle to reference the Reader.
-func WholeFileReaderV2(scope *Scope, optional ...WholeFileReaderV2Attr) (reader_handle tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	attrs := map[string]interface{}{}
-	for _, a := range optional {
-		a(attrs)
-	}
-	opspec := tf.OpSpec{
-		Type: "WholeFileReaderV2",
-
-		Attrs: attrs,
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0)
-}
-
-// Deserializes a serialized tree ensemble config and replaces current tree
-//
-// ensemble.
-//
-// Arguments:
-//	tree_ensemble_handle: Handle to the tree ensemble.
-//	stamp_token: Token to use as the new value of the resource stamp.
-//	tree_ensemble_serialized: Serialized proto of the ensemble.
-//
-// Returns the created operation.
-func BoostedTreesDeserializeEnsemble(scope *Scope, tree_ensemble_handle tf.Output, stamp_token tf.Output, tree_ensemble_serialized tf.Output) (o *tf.Operation) {
-	if scope.Err() != nil {
-		return
-	}
-	opspec := tf.OpSpec{
-		Type: "BoostedTreesDeserializeEnsemble",
-		Input: []tf.Input{
-			tree_ensemble_handle, stamp_token, tree_ensemble_serialized,
-		},
-	}
-	return scope.AddOperation(opspec)
-}