Go: Update generated wrapper functions for TensorFlow ops.
PiperOrigin-RevId: 239214941
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@ -7652,6 +7652,17 @@ func OptionalFromValue(scope *Scope, components []tf.Output) (optional tf.Output
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return op.Output(0)
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}
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// OptimizeDatasetAttr is an optional argument to OptimizeDataset.
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type OptimizeDatasetAttr func(optionalAttr)
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// OptimizeDatasetOptimizationConfigs sets the optional optimization_configs attribute to value.
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// If not specified, defaults to <>
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func OptimizeDatasetOptimizationConfigs(value []string) OptimizeDatasetAttr {
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return func(m optionalAttr) {
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m["optimization_configs"] = value
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}
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}
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// Creates a dataset by applying optimizations to `input_dataset`.
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//
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// Creates a dataset by applying optimizations to `input_dataset`.
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@ -7661,11 +7672,14 @@ func OptionalFromValue(scope *Scope, components []tf.Output) (optional tf.Output
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// optimizations: A `tf.string` vector `tf.Tensor` identifying optimizations to use.
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//
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//
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func OptimizeDataset(scope *Scope, input_dataset tf.Output, optimizations tf.Output, output_types []tf.DataType, output_shapes []tf.Shape) (handle tf.Output) {
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func OptimizeDataset(scope *Scope, input_dataset tf.Output, optimizations tf.Output, output_types []tf.DataType, output_shapes []tf.Shape, optional ...OptimizeDatasetAttr) (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: "OptimizeDataset",
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Input: []tf.Input{
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