*     partitions
   * @throws IllegalArgumentException if {@code size} is nonpositive
   */
  public static <T extends @Nullable Object> UnmodifiableIterator<List<T>> partition(
      Iterator<T> iterator, int size) {
    return partitionImpl(iterator, size, false);
  }

  /**

// Create a variable handle with name `variable_name` on a device with name
// `device_name`.
TFE_TensorHandle* CreateVarHandle(TFE_Context* ctx,
                                  const tensorflow::string& device_name,
                                  const tensorflow::string& variable_name);

// Create a variable with value `value` and name `variable_name` on a device
// with name `device_name`.

			Typeflag: 0x53,
			Linkname: "",
			Uname:    "david",
			Gname:    "david",
			Devmajor: 0,
			Devminor: 0,
			Format:   FormatGNU,
		}, {
			Name:     "sparse-posix-0.0",
			Mode:     420,
			Uid:      1000,
			Gid:      1000,
			Size:     200,
			ModTime:  time.Unix(1392342187, 0),
			Typeflag: 0x30,
			Linkname: "",
			Uname:    "david",
			Gname:    "david",
			Devmajor: 0,
			Devminor: 0,

  // Returns the device which created the handle.
  virtual const char* DeviceName(absl::Status* status) const = 0;
  // Returns the device where the tensor was placed.
  virtual const char* BackingDeviceName(absl::Status* status) const = 0;
  // Returns the device type which created the handle.
  virtual const char* DeviceType(absl::Status* status) const = 0;
  // Returns the device ID which created the handle.

	if len(udids) == 0 {
		fail("no udid found; is a device connected?")
	}

	mps := detectMobileProvisionFiles(udids)
	if len(mps) == 0 {
		fail("did not find mobile provision matching device udids %q", udids)
	}

	fmt.Println("# Available provisioning profiles below.")
	fmt.Println("# NOTE: Any existing app on the device with the app id specified by GOIOS_APP_ID")

  }
  absl::Status s;
  const char* device_name = DeviceName(&s);
  if (!s.ok()) {
    device_name = "<error fetching device name>";
  }
  return absl::StrCat("TensorHandle(", value_string, ", shape=", shape_string,
                      ", dtype=", DataType_Name(DataType()), ", device=\"",
                      device_name, "\")");
}

absl::Status ImmediateExecutionTensorHandle::SummarizeValue(

      "      input: 'var'"
      "      device: '/job:localhost/replica:0/task:0/device:CPU:0'"
      "      attr {"
      "        key: 'dtype'"
      "        value {"
      "          type: DT_FLOAT"
      "        }"
      "      }"
      "    }"
      "    node_def {"
      "      name: 'read1'"
      "      op: 'ReadVariableOp'"
      "      input: 'var'"
      "      device: '/job:localhost/replica:0/task:1/device:CPU:0'"

Android Test
============

A gradle module for running Android instrumentation tests on a device or emulator.

1. Add an Emulator named `pixel5`, if you don't already have one

```
$ sdkmanager --install "system-images;android-29;google_apis;x86"
$ echo "no" | avdmanager --verbose create avd --force --name "pixel5" --device "pixel" --package "system-images;android-29;google_apis;x86" --tag "google_apis" --abi "x86"
```

Regression Test
===============

A gradle module for running Regression tests on a device, emulator or JVM.

1. Add an Emulator named `pixel5`, if you don't already have one

```
$ sdkmanager --install "system-images;android-29;google_apis;x86"
$ echo "no" | avdmanager --verbose create avd --force --name "pixel5" --device "pixel" --package "system-images;android-29;google_apis;x86" --tag "google_apis" --abi "x86"
```

                         first_underlying_devices, status.get());
  ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get());

  // Create a second parallel device with the first parallel device and one
  // additional CPU.
  const char* second_device_name =
      "/job:localhost/replica:0/task:0/device:CUSTOM:1";
  std::array<const char*, 2> second_underlying_devices{