// RUN: tf-opt %s --tf-decompose-optionals --split-input-file | FileCheck %s

// CHECK-LABEL: @from_value
func.func @from_value(%arg0: tensor<f32>) {
  // CHECK-NOT: Optional
  %0 = "tf.OptionalFromValue"(%arg0) : (tensor<f32>) -> tensor<!tf_type.variant<tensor<f32>>>
  return
}

// -----

// CHECK-LABEL: @get_value
func.func @get_value(%arg0: tensor<!tf_type.variant<tensor<f32>>>) {
  // CHECK-NOT: Optional

  REGISTER_KERNEL_BUILDER(Name("OptionalNone").Device(DEVICE),                 \
                          data::OptionalNoneOp);                               \
  REGISTER_KERNEL_BUILDER(Name("OptionalFromValue").Device(DEVICE),            \
                          data::OptionalFromValueOp);                          \
  REGISTER_KERNEL_BUILDER(                                                     \

    raw_ostream* os = nullptr);

// Moves TPUCompileMlir ops as far to the front as possible.
std::unique_ptr<OperationPass<func::FuncOp>> CreateMoveTpuCompileToFrontPass();

// Decomposes OptionalFromValue, OptionalGetValue, OptionalNone,
// and OptionalHasValue
std::unique_ptr<OperationPass<ModuleOp>> CreateDecomposeOptionalsPass();

//===----------------------------------------------------------------------===//

  let summary = "Decomposes ops of the 'Optional' family";
  let description = [{
    Turns OptionalFromValue, OptionalGetValue, OptionalNone,
    and OptionalHasValue into identities.

    For example, if we have:

      %1 = "tf.OptionalFromValue"(%0) : (tensor<f32>) -> !tf_type.variant
      %2 = "tf.OptionalGetValue"(%1) : (tensor<!tf_type.variant>) -> tensor<f32>

    DefaultValuedOptionalAttr<StrArrayAttr, "{}">:$optimization_configs
  );

  let results = (outs
    TF_VariantTensor:$handle
  );
}

def TF_OptionalFromValueOp : TF_Op<"OptionalFromValue", [Pure]> {
  let summary = "Constructs an Optional variant from a tuple of tensors.";

  let arguments = (ins
    Variadic<TF_Tensor>:$components
  );

  let results = (outs