Go: Update generated wrapper functions for TensorFlow ops.

PiperOrigin-RevId: 201150427

1 files changed, 111 insertions, 111 deletions

diff --git a/tensorflow/go/op/wrappers.go b/tensorflow/go/op/wrappers.go
index a443879df2..bff2264c29 100644
--- a/tensorflow/go/op/wrappers.go
+++ b/tensorflow/go/op/wrappers.go
@@ -3015,40 +3015,6 @@ func Concat(scope *Scope, concat_dim tf.Output, values []tf.Output) (output tf.O
 	return op.Output(0)
 }
 
-// Creates a sequence of numbers.
-//
-// This operation creates a sequence of numbers that begins at `start` and
-// extends by increments of `delta` up to but not including `limit`.
-//
-// For example:
-//
-// ```
-// # 'start' is 3
-// # 'limit' is 18
-// # 'delta' is 3
-// tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
-// ```
-//
-// Arguments:
-//	start: 0-D (scalar). First entry in the sequence.
-//	limit: 0-D (scalar). Upper limit of sequence, exclusive.
-//	delta: 0-D (scalar). Optional. Default is 1. Number that increments `start`.
-//
-// Returns 1-D.
-func Range(scope *Scope, start tf.Output, limit tf.Output, delta tf.Output) (output tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	opspec := tf.OpSpec{
-		Type: "Range",
-		Input: []tf.Input{
-			start, limit, delta,
-		},
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0)
-}
-
 // Computes gradients for SparseSegmentSqrtN.
 //
 // Returns tensor "output" with same shape as grad, except for dimension 0 whose
@@ -8309,6 +8275,83 @@ func DataFormatVecPermute(scope *Scope, x tf.Output, optional ...DataFormatVecPe
 	return op.Output(0)
 }
 
+// Converts each string in the input Tensor to its hash mod by a number of buckets.
+//
+// The hash function is deterministic on the content of the string within the
+// process.
+//
+// Note that the hash function may change from time to time.
+// This functionality will be deprecated and it's recommended to use
+// `tf.string_to_hash_bucket_fast()` or `tf.string_to_hash_bucket_strong()`.
+//
+// Arguments:
+//
+//	num_buckets: The number of buckets.
+//
+// Returns A Tensor of the same shape as the input `string_tensor`.
+func StringToHashBucket(scope *Scope, string_tensor tf.Output, num_buckets int64) (output tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	attrs := map[string]interface{}{"num_buckets": num_buckets}
+	opspec := tf.OpSpec{
+		Type: "StringToHashBucket",
+		Input: []tf.Input{
+			string_tensor,
+		},
+		Attrs: attrs,
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0)
+}
+
+// Computes gradients for the exponential linear (Elu) operation.
+//
+// Arguments:
+//	gradients: The backpropagated gradients to the corresponding Elu operation.
+//	outputs: The outputs of the corresponding Elu operation.
+//
+// Returns The gradients: `gradients * (outputs + 1)` if outputs < 0,
+// `gradients` otherwise.
+func EluGrad(scope *Scope, gradients tf.Output, outputs tf.Output) (backprops tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	opspec := tf.OpSpec{
+		Type: "EluGrad",
+		Input: []tf.Input{
+			gradients, outputs,
+		},
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0)
+}
+
+// Creates a dataset that contains `count` elements from the `input_dataset`.
+//
+// Arguments:
+//
+//	count: A scalar representing the number of elements from the `input_dataset`
+// that should be taken. A value of `-1` indicates that all of `input_dataset`
+// is taken.
+//
+//
+func TakeDataset(scope *Scope, input_dataset tf.Output, count tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	attrs := map[string]interface{}{"output_types": output_types, "output_shapes": output_shapes}
+	opspec := tf.OpSpec{
+		Type: "TakeDataset",
+		Input: []tf.Input{
+			input_dataset, count,
+		},
+		Attrs: attrs,
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0)
+}
+
 // Reads the value of a variable.
 //
 // The tensor returned by this operation is immutable.
@@ -9918,83 +9961,6 @@ func FixedLengthRecordReaderV2(scope *Scope, record_bytes int64, optional ...Fix
 	return op.Output(0)
 }
 
-// Converts each string in the input Tensor to its hash mod by a number of buckets.
-//
-// The hash function is deterministic on the content of the string within the
-// process.
-//
-// Note that the hash function may change from time to time.
-// This functionality will be deprecated and it's recommended to use
-// `tf.string_to_hash_bucket_fast()` or `tf.string_to_hash_bucket_strong()`.
-//
-// Arguments:
-//
-//	num_buckets: The number of buckets.
-//
-// Returns A Tensor of the same shape as the input `string_tensor`.
-func StringToHashBucket(scope *Scope, string_tensor tf.Output, num_buckets int64) (output tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	attrs := map[string]interface{}{"num_buckets": num_buckets}
-	opspec := tf.OpSpec{
-		Type: "StringToHashBucket",
-		Input: []tf.Input{
-			string_tensor,
-		},
-		Attrs: attrs,
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0)
-}
-
-// Computes gradients for the exponential linear (Elu) operation.
-//
-// Arguments:
-//	gradients: The backpropagated gradients to the corresponding Elu operation.
-//	outputs: The outputs of the corresponding Elu operation.
-//
-// Returns The gradients: `gradients * (outputs + 1)` if outputs < 0,
-// `gradients` otherwise.
-func EluGrad(scope *Scope, gradients tf.Output, outputs tf.Output) (backprops tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	opspec := tf.OpSpec{
-		Type: "EluGrad",
-		Input: []tf.Input{
-			gradients, outputs,
-		},
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0)
-}
-
-// Creates a dataset that contains `count` elements from the `input_dataset`.
-//
-// Arguments:
-//
-//	count: A scalar representing the number of elements from the `input_dataset`
-// that should be taken. A value of `-1` indicates that all of `input_dataset`
-// is taken.
-//
-//
-func TakeDataset(scope *Scope, input_dataset tf.Output, count tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) {
-	if scope.Err() != nil {
-		return
-	}
-	attrs := map[string]interface{}{"output_types": output_types, "output_shapes": output_shapes}
-	opspec := tf.OpSpec{
-		Type: "TakeDataset",
-		Input: []tf.Input{
-			input_dataset, count,
-		},
-		Attrs: attrs,
-	}
-	op := scope.AddOperation(opspec)
-	return op.Output(0)
-}
-
 // The gradient operator for the SparseAdd op.
 //
 // The SparseAdd op calculates A + B, where A, B, and the sum are all represented
@@ -19440,6 +19406,40 @@ func OrderedMapIncompleteSize(scope *Scope, dtypes []tf.DataType, optional ...Or
 	return op.Output(0)
 }
 
+// Creates a sequence of numbers.
+//
+// This operation creates a sequence of numbers that begins at `start` and
+// extends by increments of `delta` up to but not including `limit`.
+//
+// For example:
+//
+// ```
+// # 'start' is 3
+// # 'limit' is 18
+// # 'delta' is 3
+// tf.range(start, limit, delta) ==> [3, 6, 9, 12, 15]
+// ```
+//
+// Arguments:
+//	start: 0-D (scalar). First entry in the sequence.
+//	limit: 0-D (scalar). Upper limit of sequence, exclusive.
+//	delta: 0-D (scalar). Optional. Default is 1. Number that increments `start`.
+//
+// Returns 1-D.
+func Range(scope *Scope, start tf.Output, limit tf.Output, delta tf.Output) (output tf.Output) {
+	if scope.Err() != nil {
+		return
+	}
+	opspec := tf.OpSpec{
+		Type: "Range",
+		Input: []tf.Input{
+			start, limit, delta,
+		},
+	}
+	op := scope.AddOperation(opspec)
+	return op.Output(0)
+}
+
 // DestroyResourceOpAttr is an optional argument to DestroyResourceOp.
 type DestroyResourceOpAttr func(optionalAttr)