t.Errorf("missing value = %q, want empty string", g)
	}

	assertMem := func(n string, fd multipart.File) {
		if _, ok := fd.(*os.File); ok {
			t.Error(n, " is *os.File, should not be")
		}
	}
	fda := testMultipartFile(t, req, "filea", "filea.txt", fileaContents)
	defer fda.Close()
	assertMem("filea", fda)
	fdb := testMultipartFile(t, req, "fileb", "fileb.txt", filebContents)

  StreamExecutor* executor = GetExecutor(0);
  const DeviceDescription& description = executor->GetDeviceDescription();
  ASSERT_EQ(description.name(), "TestName");
  ASSERT_EQ(description.device_vendor(), "TestVendor");
  ASSERT_EQ(description.pci_bus_id(), "TestPCIBusId");
  ASSERT_EQ(description.numa_node(), 123);
  ASSERT_EQ(description.memory_bandwidth(), 54);
}

TEST_F(StreamExecutorTest, DeviceDescriptionNumaNodeNotSet) {

  Set_TF_Status_from_Status(s, cc_status);
  ASSERT_EQ(TSL_INVALID_ARGUMENT, TSL_GetCode(s));
  ASSERT_EQ(std::string("some error"), TSL_Message(s));

  absl::Status another_cc_status(StatusFromTF_Status(s));
  ASSERT_FALSE(another_cc_status.ok());
  ASSERT_EQ(std::string("some error"), another_cc_status.message());
  ASSERT_EQ(error::INVALID_ARGUMENT, another_cc_status.code());

  TF_Operation* a = Placeholder(graph, s, "A");
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  TF_Operation* b = Placeholder(graph, s, "B");
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  TF_Operation* two = ScalarConst(2, graph, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  TF_Operation* plus2 = Add(a, two, graph, s, "plus2");
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  std::stringstream stream;
  stream << x;
  ASSERT_EQ(stream.str(), "42");
}

TEST(OStreamTest, TestFloat32) {
  Float32 x(0.375);  // Exactly representable as a float.
  std::stringstream stream;
  stream << x;
  ASSERT_EQ(stream.str(), "0.375");
}

TEST(OStreamTest, TestString) {
  String s("foo");
  std::stringstream stream;
  stream << s;
  ASSERT_EQ(stream.str(), "foo");
}

          tensorflow::unwrap(saved_model));
  tensorflow::Variable* uninitialized_variable;
  ASSERT_EQ(absl::OkStatus(), model_api->GetVariable("uninitialized_variable",
                                                     &uninitialized_variable));
  ASSERT_EQ(tensorflow::DT_FLOAT, uninitialized_variable->dtype());

  ASSERT_EQ(absl::OkStatus(),
            model_api->GetVariable("sub_module.uninitialized_variable",

  ASSERT_EQ(status, kTfLiteOk);

  const uint8_t* buffer = builder.GetBufferPointer();
  const Model* output_model = GetModel(buffer);
  ASSERT_TRUE(output_model);

  ASSERT_EQ(output_model->subgraphs()->size(), model_->subgraphs()->size());
  const auto quantized_graph = output_model->subgraphs()->Get(0);
  // A dequantize op should be added.
  ASSERT_EQ(quantized_graph->operators()->size(),

  (*module_ref)->setAttr("tf.devices", device_dict);

  mlir::TF::RuntimeDevices devices;
  EXPECT_TRUE(mlir::succeeded(GetDevicesFromOp(*module_ref, &devices)));

  ASSERT_EQ(devices.NumDevices(), 1);
  ASSERT_EQ(devices.device_names().size(), 1);
  ASSERT_EQ(DeviceNameUtils::ParsedNameToString(devices.device_names()[0]),
            "/job:worker/replica:0/task:0/device:CPU:0");
}

TEST(DeviceUtilTest, GetGpuDeviceMetadata) {

  EXPECT_EQ(xla_device_assignment->computation_count(), 2);
  ASSERT_EQ(xla_device_assignment->computation_devices_size(), 2);
  const auto& computation_device_0 =
      xla_device_assignment->computation_devices(0);
  ASSERT_EQ(computation_device_0.replica_device_ids_size(), 4);
  const auto& computation_device_1 =
      xla_device_assignment->computation_devices(1);
  ASSERT_EQ(computation_device_1.replica_device_ids_size(), 4);

	_interface    *_type
	concrete      *_type
	asserted      *_type
	missingMethod string // one method needed by Interface, missing from Concrete
}

func (*TypeAssertionError) RuntimeError() {}

func (e *TypeAssertionError) Error() string {
	inter := "interface"
	if e._interface != nil {
		inter = toRType(e._interface).string()
	}
	as := toRType(e.asserted).string()
	if e.concrete == nil {