return op->emitError("expected exactly one called_computation");

    auto decomposition = mlir::cast<FlatSymbolRefAttr>(calledComputations[0]);

    auto composite = rewriter.create<mlir::stablehlo::CompositeOp>(
        op.getLoc(), op.getResultTypes(), op.getOperands(), name.str(), attrs,
        decomposition.getValue());
    rewriter.replaceOp(op, composite.getResults());
    return success();
  }
};

## RFC

This project is an alternative implementation of
[RFC:Standardizing composite ops in tensorflow to support efficient inference](https://github.com/tensorflow/community/blob/master/rfcs/20190610-standardizing-composite_ops.md).
This project doesn't rely on the tracing functionality provided by `tf.function`
to avoid all its pitfalls and it helps to build more general transformations in
the backends.

## Team

* Feng Liu

  auto c = Concat(root, {p[0], p[1]}, 0);
  TF_EXPECT_OK(root.status());
  Tensor out;
  test::GetTensor(root, c, &out);
  test::ExpectTensorEqual<int>(out, test::AsTensor<int>({1, 2}, {2, 1}));
}

TEST(CCOpTest, CompositeOp) {
  Scope root = Scope::NewRootScope();
  auto l = Linear(root.WithOpName("layer0"), {{10.0f, -3.0f}},
                  {{.8f, .5f}, {.1f, .6f}}, {-8.0f, 31.0f});
  TF_EXPECT_OK(root.status());

Translator::BuildVhloCompositeV1Op(mlir::vhlo::CompositeOpV1 composite_op,
                                   const std::vector<int32_t>& operands,
                                   const std::vector<int32_t>& results,
                                   std::string op_name) {
  uint32_t opcode_index =
      GetOpcodeIndex(op_name, tflite::BuiltinOperator_STABLEHLO_COMPOSITE);

  int32_t api_version = composite_op.getVersion()

// CHECK-NEXT:  %0:2 = "tfl.custom"(%arg0, %arg1, %arg2) <{custom_code = "my_composite_op", custom_option = #tfl<const_bytes : "0x6578616D706C655F6F7074696F6E006578616D706C655F737472000A76616C756520312E30310002281A0201020A120414042401">}> : (tensor<4x4xf32>,...