Go: Update generated wrapper functions for TensorFlow ops.
PiperOrigin-RevId: 245289270
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@ -23501,6 +23501,17 @@ func Range(scope *Scope, start tf.Output, limit tf.Output, delta tf.Output) (out
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return op.Output(0)
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}
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// ShardDatasetAttr is an optional argument to ShardDataset.
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type ShardDatasetAttr func(optionalAttr)
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// ShardDatasetRequireNonEmpty sets the optional require_non_empty attribute to value.
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// If not specified, defaults to false
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func ShardDatasetRequireNonEmpty(value bool) ShardDatasetAttr {
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return func(m optionalAttr) {
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m["require_non_empty"] = value
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}
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}
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// Creates a `Dataset` that includes only 1/`num_shards` of this dataset.
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//
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// Arguments:
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@ -23509,11 +23520,14 @@ func Range(scope *Scope, start tf.Output, limit tf.Output, delta tf.Output) (out
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// index: An integer representing the current worker index.
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//
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//
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func ShardDataset(scope *Scope, input_dataset tf.Output, num_shards tf.Output, index tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) {
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func ShardDataset(scope *Scope, input_dataset tf.Output, num_shards tf.Output, index tf.Output, output_types []tf.DataType, output_shapes []tf.Shape, optional ...ShardDatasetAttr) (handle 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{}{"output_types": output_types, "output_shapes": output_shapes}
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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: "ShardDataset",
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Input: []tf.Input{
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