Go: Update generated wrapper functions for TensorFlow ops.

PiperOrigin-RevId: 216455250

1 files changed, 56 insertions, 55 deletions

diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index f35117084a..c6ecd75587 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -4562,6 +4562,59 @@ func CTCBeamSearchDecoder(scope *Scope, inputs tf.Output, sequence_length tf.Out
 	return decoded_indices, decoded_values, decoded_shape, log_probability
 }
 
+// CTCGreedyDecoderAttr is an optional argument to CTCGreedyDecoder.
+type CTCGreedyDecoderAttr func(optionalAttr)
+
+// CTCGreedyDecoderMergeRepeated sets the optional merge_repeated attribute to value.
+//
+// value: If True, merge repeated classes in output.
+// If not specified, defaults to false
+func CTCGreedyDecoderMergeRepeated(value bool) CTCGreedyDecoderAttr {
+	return func(m optionalAttr) {
+		m["merge_repeated"] = value
+	}
+}
+
+// Performs greedy decoding on the logits given in inputs.
+//
+// A note about the attribute merge_repeated: if enabled, when
+// consecutive logits' maximum indices are the same, only the first of
+// these is emitted.  Labeling the blank '*', the sequence "A B B * B B"
+// becomes "A B B" if merge_repeated = True and "A B B B B" if
+// merge_repeated = False.
+//
+// Regardless of the value of merge_repeated, if the maximum index of a given
+// time and batch corresponds to the blank, index `(num_classes - 1)`, no new
+// element is emitted.
+//
+// Arguments:
+//	inputs: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.
+//	sequence_length: A vector containing sequence lengths, size `(batch_size)`.
+//
+// Returns Indices matrix, size `(total_decoded_outputs x 2)`,
+// of a `SparseTensor<int64, 2>`.  The rows store: [batch, time].Values vector, size: `(total_decoded_outputs)`,
+// of a `SparseTensor<int64, 2>`.  The vector stores the decoded classes.Shape vector, size `(2)`, of the decoded SparseTensor.
+// Values are: `[batch_size, max_decoded_length]`.Matrix, size `(batch_size x 1)`, containing sequence
+// log-probabilities.
+func CTCGreedyDecoder(scope *Scope, inputs tf.Output, sequence_length tf.Output, optional ...CTCGreedyDecoderAttr) (decoded_indices tf.Output, decoded_values tf.Output, decoded_shape tf.Output, log_probability tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	attrs := map[string]interface{}{}
+	for _, a := range optional {
+		a(attrs)
+	}
+	opspec := tf.OpSpec{
+		Type: "CTCGreedyDecoder",
+		Input: []tf.Input{
+			inputs, sequence_length,
+		},
+		Attrs: attrs,
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0), op.Output(1), op.Output(2), op.Output(3)
+}
+
 // ResourceStridedSliceAssignAttr is an optional argument to ResourceStridedSliceAssign.
 type ResourceStridedSliceAssignAttr func(optionalAttr)
 
@@ -18904,10 +18957,11 @@ func MutableDenseHashTableV2MaxLoadFactor(value float32) MutableDenseHashTableV2
 // Arguments:
 //	empty_key: The key used to represent empty key buckets internally. Must not
 // be used in insert or lookup operations.
+//
 //	value_dtype: Type of the table values.
 //
 // Returns Handle to a table.
-func MutableDenseHashTableV2(scope *Scope, empty_key tf.Output, value_dtype tf.DataType, optional ...MutableDenseHashTableV2Attr) (table_handle tf.Output) {
+func MutableDenseHashTableV2(scope *Scope, empty_key tf.Output, deleted_key tf.Output, value_dtype tf.DataType, optional ...MutableDenseHashTableV2Attr) (table_handle tf.Output) {
 	if scope.Err() != nil {
 		return
 	}
@@ -18918,7 +18972,7 @@ func MutableDenseHashTableV2(scope *Scope, empty_key tf.Output, value_dtype tf.D
 	opspec := tf.OpSpec{
 		Type: "MutableDenseHashTableV2",
 		Input: []tf.Input{
-			empty_key,
+			empty_key, deleted_key,
 		},
 		Attrs: attrs,
 	}
@@ -33104,56 +33158,3 @@ func CTCLoss(scope *Scope, inputs tf.Output, labels_indices tf.Output, labels_va
 	op := scope.AddOperation(opspec)
 	return op.Output(0), op.Output(1)
 }
-
-// CTCGreedyDecoderAttr is an optional argument to CTCGreedyDecoder.
-type CTCGreedyDecoderAttr func(optionalAttr)
-
-// CTCGreedyDecoderMergeRepeated sets the optional merge_repeated attribute to value.
-//
-// value: If True, merge repeated classes in output.
-// If not specified, defaults to false
-func CTCGreedyDecoderMergeRepeated(value bool) CTCGreedyDecoderAttr {
-	return func(m optionalAttr) {
-		m["merge_repeated"] = value
-	}
-}
-
-// Performs greedy decoding on the logits given in inputs.
-//
-// A note about the attribute merge_repeated: if enabled, when
-// consecutive logits' maximum indices are the same, only the first of
-// these is emitted.  Labeling the blank '*', the sequence "A B B * B B"
-// becomes "A B B" if merge_repeated = True and "A B B B B" if
-// merge_repeated = False.
-//
-// Regardless of the value of merge_repeated, if the maximum index of a given
-// time and batch corresponds to the blank, index `(num_classes - 1)`, no new
-// element is emitted.
-//
-// Arguments:
-//	inputs: 3-D, shape: `(max_time x batch_size x num_classes)`, the logits.
-//	sequence_length: A vector containing sequence lengths, size `(batch_size)`.
-//
-// Returns Indices matrix, size `(total_decoded_outputs x 2)`,
-// of a `SparseTensor<int64, 2>`.  The rows store: [batch, time].Values vector, size: `(total_decoded_outputs)`,
-// of a `SparseTensor<int64, 2>`.  The vector stores the decoded classes.Shape vector, size `(2)`, of the decoded SparseTensor.
-// Values are: `[batch_size, max_decoded_length]`.Matrix, size `(batch_size x 1)`, containing sequence
-// log-probabilities.
-func CTCGreedyDecoder(scope *Scope, inputs tf.Output, sequence_length tf.Output, optional ...CTCGreedyDecoderAttr) (decoded_indices tf.Output, decoded_values tf.Output, decoded_shape tf.Output, log_probability tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	attrs := map[string]interface{}{}
-	for _, a := range optional {
-		a(attrs)
-	}
-	opspec := tf.OpSpec{
-		Type: "CTCGreedyDecoder",
-		Input: []tf.Input{
-			inputs, sequence_length,
-		},
-		Attrs: attrs,
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0), op.Output(1), op.Output(2), op.Output(3)
-}