// CHECK: "tf_device.launch"
// CHECK: device = "CORE_0"
// CHECK: "tf.opA"


// Tests devices are not remapped if device is not in replicate devices.
// CHECK-LABEL: func @no_override_device
func.func @no_override_device() {
  tf_executor.graph {
    %0 = tf_executor.island {
      tf_device.replicate {n = 2 : i32, devices = {CORE_0 = ["/CPU:0", "/GPU:1"]}} {
        "tf_device.launch"() ({
          "tf.opA"() : () -> ()

// which are managed by the devicemapper dm-1.
func (handler *deviceHandler) FindSlaveDevicesOnMultipath(dm string) []string {
	var devices []string
	io := handler.getIo
	// Split path /dev/dm-1 into "", "dev", "dm-1"
	parts := strings.Split(dm, "/")
	if len(parts) != 3 || !strings.HasPrefix(parts[1], "dev") {
		return devices
	}
	disk := parts[2]

    return signalPassFailure();
  }

  // Get the number of devices per host.
  int device_num = 0;
  mlir::TF::RuntimeDevices devices;
  if (failed(tensorflow::GetDevicesFromOp(
          getOperation()->getParentOfType<ModuleOp>(), &devices)))
    return signalPassFailure();
  for (const auto& device_name : devices.device_names()) {
    if (device_name.has_type && device_name.type == "TPU") ++device_num;
  }

	}

	// Error test
	args = &Args{7, 0}
	reply = new(Reply)
	err = client.Call("Arith.Div", args, reply)
	// expect an error: zero divide
	if err == nil {
		t.Error("Div: expected error")
	} else if err.Error() != "divide by zero" {
		t.Error("Div: expected divide by zero error; got", err)
	}
}

func TestBuiltinTypes(t *testing.T) {
	cli, srv := net.Pipe()
	go ServeConn(srv)

                            if (this.text === level) {
                                this.click();
                            }
                        });

                        var divider = \$("<hr>");
                        divider.css({ margin: "5px" });
                        var tip = \$("<small>").text("Use the 'bin.cmp.report.severity.filter' property to set the default severity filter");

// CHECK-SAME: tfrt_ifrt_serving.program_id = [[PROGRAM_ID]] : i64
// CHECK:      return

// RUN: tf-opt %s -split-input-file -tf-xla-rewrite | FileCheck %s


module attributes {tf.devices = ["/job:worker/replica:0/task:0/device:CPU:0", "/job:worker/replica:0/task:0/device:GPU:0"]} {
  // CHECK-LABEL: func.func @convert_cluster_func
  func.func @convert_cluster_func(%arg0: tensor<i32>) -> tensor<i32> {
    // CHECK: "tf.XlaLaunch"(%arg0) <{function = @func, operandSegmentSizes = array<i32: 0, 1, 0>}> : (tensor<i32>) -> tensor<i32>

	}

	return annotationPrefix + name, nil
}

// annotationValue returns an annotation value for the given devices.
func annotationValue(devices []string) (string, error) {
	value, sep := "", ""
	for _, d := range devices {
		if _, _, _, err := parseQualifiedName(d); err != nil {
			return "", err
		}
		value += sep + d
		sep = ","
	}

	return value, nil
}

### This jcifs or jcifs-ng

jcifs-ng will be a proper choice for many users. 
There are a lot of SMB devices in the world.
Some of them only work with the old jcifs library.
If you want to support many SMB devices, CodeLibs jcifs library will be helpful.
For example, since [Fess](https://github.com/codelibs/fess) needs to support many SMB devices, it uses this library.

		if len(entries) == 3 && entries[1] == "devices" {
			return strings.TrimSpace(entries[2]), nil
		}
	}
	return "", fmt.Errorf("could not find devices cgroup location")
}

// GetFullContainerName gets the container name given the root process id of the container.
// E.g. if the devices cgroup for the container is stored in /sys/fs/cgroup/devices/docker/nginx,