EXPECT_EQ(tf2xla_fallback_count, 322);
  EXPECT_EQ(non_categorized_count, 428);
}

// Just a counter test to see which ops have duplicate lowerings. This isn't a
// correctness test versus a test to easily ensure the op registry is kept
// in sync.
TEST_F(LegalizationOpConfigTest, CountTypesWhichHaveBothMlirAndTf2xlaFallback) {
  int double_lowering_count = 0;

  DialectRegistry dialect_registry;

  Env* env_;
  std::string test_dir_;
  std::string test_group_name_;
};

TEST_F(LowerClusterToRuntimeOpsTest, SanityCheck) {
  TF_ASSERT_OK(CreateMlirModule("empty_func.mlir"));

  TF_EXPECT_OK(RunLowerClusterToRuntimeOpsPassPipeline(
      *mlir_module_, DeviceType(DEVICE_TPU_XLA_JIT)));
}

TEST_F(LowerClusterToRuntimeOpsTest, LowersClusterOpsTPU) {
  TF_ASSERT_OK(CreateMlirModule("basic_cluster.mlir"));

    }
    return absl::OkStatus();
  }

  DialectRegistry registry_;
  MLIRContext context_;
  OwningOpRef<mlir::ModuleOp> mlir_module_;
};

TEST_F(FunctionClusterTensorflowDialectTest, ClustersTfReplicatedBridge) {
  CellReader<int64_t> compilation_status(kCompilationStreamz);

  TF_ASSERT_OK(CreateMlirModule("empty_func.mlir"));

#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/protobuf/meta_graph.pb.h"

namespace mlir::quant {
namespace {

using ::tensorflow::AssetFileDef;
using ::testing::Eq;
using ::testing::IsEmpty;
using ::testing::IsNull;
using ::testing::NotNull;
using ::testing::SizeIs;

class ConvertAssetArgsTest : public ::testing::Test {
 protected:
  ConvertAssetArgsTest() {

    return tsl::io::JoinPath(
        getenv("TEST_UNDECLARED_OUTPUTS_DIR"),
        absl::StrCat(test_info->test_suite_name(), ".", test_info->name()));
  }
};

TEST_F(InitPassManagerTest, CrashReproducer) {
  converter::DebugOptions debug_options;
  *debug_options.mutable_ir_dump_dir() = path_;

  mlir::PassManager pm(&context_);
  InitPassManager(pm, debug_options);

    }
    return absl::OkStatus();
  }

  DialectRegistry registry_;
  MLIRContext context_;
  OwningOpRef<mlir::ModuleOp> mlir_module_;
};

TEST_F(TensorflowDialectToExecutorTest, ConvertsToExecutor) {
  CellReader<int64_t> compilation_status(kExportStreamzName);

  TF_ASSERT_OK(CreateMlirModule("empty_func.mlir"));

    func.func @main(%arg0: tensor<1x4x4x3xf32>) -> tensor<1x4x4x3xf32> attributes {_from_xla_call_module} {
      %cst_0 = arith.constant dense<1.0> : tensor<3x1x1x3xf32>
      %cst_1 = arith.constant dense<2.0> : tensor<3xf32>

      &device_tensor, "", device_.get(), &dest_cpu_tensor));

  tensorflow::test::ExpectClose(origin_cpu_tensor, dest_cpu_tensor);
  device_context->Unref();
}

TEST_F(XlaHostSendRecvDeviceContextTest, CopyCPUTensorToDevice) {
  SetDevice("GPU");
  Tensor origin_cpu_tensor(host_allocator_, DT_FLOAT, TensorShape({2, 2}));
  test::FillValues<float>(&origin_cpu_tensor, {1.2, 2.3, 3.4, 4.5});

package org.gradle.api.plugins.quality.codenarc

import org.gradle.test.fixtures.file.TestFile


trait CodeNarcTestFixture {
    def goodCode() {
        file("src/main/groovy/org/gradle/class1.java") << "package org.gradle; class class1 { }"
        file("src/test/groovy/org/gradle/testclass1.java") << "package org.gradle; public class testclass1 { @org.junit.Test public void test1() { } }"

    }
    return absl::OkStatus();
  }

  DialectRegistry registry_;
  MLIRContext context_;
  OwningOpRef<mlir::ModuleOp> mlir_module_;
};

TEST_F(SessionClusterTensorflowDialectTest, ClustersTf) {
  CellReader<int64_t> compilation_status(kCompilationStreamz);

  TF_ASSERT_OK(CreateMlirModule("empty_func.mlir"));

  TF_EXPECT_OK(