* limitations under the License.
 */

package org.gradle.nativeplatform.fixtures.app

import org.gradle.integtests.fixtures.SourceFile

class CppSimpleUnitTest extends CppSourceElement {
    final sum = new CppSum()
    final sumTest = new CppSumTest()

    List<SourceFile> sourceFiles = [
        new SourceFile("cpp", "test.cpp", """
            int main(int argc, char **argv) {
              if (42 == 42) {

bool IsInLiftedFunc(Operation* op);

// Checks if the op is inside a StableHLO op with region.
// If the given op pointer is a nullptr, returns false.
bool IsInStableHloOpRegion(Operation* op);

// Checks if a given einsum op is supported for XlaDotV2 quantization.
bool IsEinsumSupportedByXlaDotV2(StringAttr equation_attr);

// Gets the quantization method from `op`. It is retrieved from the
// `kQuantizationMethodAttr` string attribute. Returns

    }

    IncrementalCppLib getLibrary() {
        return lib
    }

    class IncrementalCppLib extends IncrementalCppElement {
        final greeter = new CppGreeter()
        final sum = new CppSum()

        final List<IncrementalElement.Transform> incrementalChanges = [preserve(greeter.asLib()), preserve(sum.asLib())]
    }

    class IncrementalCppAppWithDep extends IncrementalCppElement implements AppElement {

  %0 = mhlo.constant dense<(1.000000e+00,-1.000000e+00)> : tensor<128x32x4xcomplex<f32>>
  %1 = mhlo.constant dense<(1.000000e+00,1.000000e+00)> : tensor<8x64x128xcomplex<f32>>
  %2 = "mhlo.einsum"(%1, %0) <{einsum_config = "abc,cde->abde"}> : (tensor<8x64x128xcomplex<f32>>, tensor<128x32x4xcomplex<f32>>) -> tensor<8x64x32x4xcomplex<f32>>
  return %2 : tensor<8x64x32x4xcomplex<f32>>
}

// -----

        // Check that each directory in hierarchy is present
        file.withInputStream { InputStream instr ->
            def dirs = [] as Set
            def zipStr = new ZipInputStream(instr)
            def entry
            while (entry = zipStr.getNextEntry()) {
                if (entry.directory) {
                    assertTrue("Duplicate directory '$entry.name'", dirs.add(entry.name))
                }

        settingsFile """
            include "dist"
            include "lib"
        """

        file("dist/build.gradle").text = """
            abstract class ZipSrc extends DefaultTask {
                @Internal
                int countResolved

                @Internal
                abstract DirectoryProperty getSources()

                @InputFiles

            tensor_spec.TensorSpec(
                shape=shape, dtype=dtypes.float32, name='input_tensor'
            )
        ),
    )
    return model

  # Prepares sample einsum input data shapes.
  # This function returns:
  # 1. Shape for input 1
  # 2. Shape for input 2
  # 3. Shape for bias
  # 4. Signature for input 1 (Could contain None dimension)

      }

      if (!is_weight_constant) {
        if (!function_name.contains("matmul") &&
            !function_name.contains("einsum")) {
          return absl::InternalError(
              "Non-constant weights are not supported at the moment,"
              " except matmul and einsum.");
        } else if (!quant_options_.enable_two_input_tensors() &&
                   !is_unitwise_quantization_enabled) {

          function_name.contains("and_bias")) {
        spec->biases_params[2] = {{0, 1},
                                  quant::GetUniformQuantizedTypeForBias};
      }
    } else if (function_name.contains("einsum")) {
      spec->coeff_op_quant_dim[1] = -1;
      if (function_name.contains("with_bias")) {
        spec->biases_params[2] = {{0, 1},
                                  quant::GetUniformQuantizedTypeForBias};
      }

#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"
#include "tensorflow/compiler/mlir/tensorflow/ir/tf_ops.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/einsum.h"

namespace mlir {
namespace quant {
namespace {

using ::tensorflow::quantization::OpSet;

class PrepareLiftingPass
    : public PassWrapper<PrepareLiftingPass, OperationPass<func::FuncOp>> {
 public: