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>

def test_multiple_path():
    app = FastAPI()

    @app.get("/test1")
    @app.get("/test2")
    async def test(var: Annotated[str, Query()] = "bar"):
        return {"foo": var}

    client = TestClient(app)
    response = client.get("/test1")
    assert response.status_code == 200
    assert response.json() == {"foo": "bar"}

    response = client.get("/test1", params={"var": "baz"})
    assert response.status_code == 200

using ::tsl::testing::IsOk;

using QuantizationReportTest = ::mlir::quant::QuantizationTestBase;

TEST_F(QuantizationReportTest, GetQuantizationResultsReturnsEmptyResults) {
  QuantizationReport report{};

  const QuantizationResults& results = report.GetQuantizationResults();
  ASSERT_THAT(results.results(), IsEmpty());
}

TEST_F(QuantizationReportTest, AddQuantizationResult) {

  EXPECT_EQ(histogram.num(), 1);
  EXPECT_EQ(compilation_status.Delta("kOldBridgeNoMlirSuccess"), 1);
}

TEST_F(CompileTFGraphTest, SuccessfullyCompilesWithManualSharding) {
  // MLIR module from failing test.
  constexpr char kSupportedManualSharding[] = R"(

			hash,
			false,
		},
	}
	for _, test := range tests {
		updated := IsPodUpdated(test.pod, test.hash, test.templateGeneration)
		if updated != test.isUpdated {
			t.Errorf("%s: IsPodUpdated returned wrong value. Expected %t, got %t", test.test, test.isUpdated, updated)
		}
	}
}

func TestCreatePodTemplate(t *testing.T) {
	tests := []struct {
		templateGeneration *int64

      &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() { } }"

	}
	for _, test := range tl {
		if test.got != test.exp {
			t.Errorf("On %v, expected '%v', but got '%v'",
				test.name, test.exp, test.got)
		}
	}
}

func TestPrintDeployment(t *testing.T) {

	testDeployment := apps.Deployment{
		ObjectMeta: metav1.ObjectMeta{
			Name:              "test1",
			CreationTimestamp: metav1.Time{Time: time.Now().Add(1.9e9)},

    }
    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(

  OwningOpRef<mlir::ModuleOp> mlir_module_;
};

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

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

  TF_EXPECT_OK(ExportFromTensorflowDialectToExecutor(*mlir_module_));

  EXPECT_EQ(compilation_status.Delta("success"), 1);
}

TEST_F(TensorflowDialectToExecutorTest, ErrorsWhenCannotConvert) {