Go: Update generated wrapper functions for TensorFlow ops.

PiperOrigin-RevId: 210950778

1 files changed, 24 insertions, 24 deletions

diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index 986f198c44..a9747d4104 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -3377,6 +3377,30 @@ func PopulationCount(scope *Scope, x tf.Output) (y tf.Output) {
 	return op.Output(0)
 }
 
+// Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior. Returns a boolean indicating whether to continue centering.
+//
+// Arguments:
+//	tree_ensemble_handle: Handle to the tree ensemble.
+//	mean_gradients: A tensor with shape=[logits_dimension] with mean of gradients for a first node.
+//	mean_hessians: A tensor with shape=[logits_dimension] mean of hessians for a first node.
+//	l1: l1 regularization factor on leaf weights, per instance based.
+//	l2: l2 regularization factor on leaf weights, per instance based.
+//
+// Returns Bool, whether to continue bias centering.
+func BoostedTreesCenterBias(scope *Scope, tree_ensemble_handle tf.Output, mean_gradients tf.Output, mean_hessians tf.Output, l1 tf.Output, l2 tf.Output) (continue_centering tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	opspec := tf.OpSpec{
+		Type: "BoostedTreesCenterBias",
+		Input: []tf.Input{
+			tree_ensemble_handle, mean_gradients, mean_hessians, l1, l2,
+		},
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0)
+}
+
 // Computes the mean along sparse segments of a tensor.
 //
 // Read @{$math_ops#Segmentation$the section on segmentation} for an explanation of
@@ -16650,30 +16674,6 @@ func OrderedMapUnstageNoKey(scope *Scope, indices tf.Output, dtypes []tf.DataTyp
 	return key, values
 }
 
-// Calculates the prior from the training data (the bias) and fills in the first node with the logits' prior. Returns a boolean indicating whether to continue centering.
-//
-// Arguments:
-//	tree_ensemble_handle: Handle to the tree ensemble.
-//	mean_gradients: A tensor with shape=[logits_dimension] with mean of gradients for a first node.
-//	mean_hessians: A tensor with shape=[logits_dimension] mean of hessians for a first node.
-//	l1: l1 regularization factor on leaf weights, per instance based.
-//	l2: l2 regularization factor on leaf weights, per instance based.
-//
-// Returns Bool, whether to continue bias centering.
-func BoostedTreesCenterBias(scope *Scope, tree_ensemble_handle tf.Output, mean_gradients tf.Output, mean_hessians tf.Output, l1 tf.Output, l2 tf.Output) (continue_centering tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	opspec := tf.OpSpec{
-		Type: "BoostedTreesCenterBias",
-		Input: []tf.Input{
-			tree_ensemble_handle, mean_gradients, mean_hessians, l1, l2,
-		},
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0)
-}
-
 // SerializeManySparseAttr is an optional argument to SerializeManySparse.
 type SerializeManySparseAttr func(optionalAttr)