//  noutputs - number of elements in `outputs` array
//  outputs - array of TF_Outputs that specify the outputs of the function.
//            If `noutputs` is zero (the function returns no outputs), `outputs`
//            can be null. `outputs` can contain the same tensor more than once.
//  output_names - The names of the function's outputs. `output_names` array

	// Output: true
}

func ExampleFields() {
	fmt.Printf("Fields are: %q", bytes.Fields([]byte("  foo bar  baz   ")))
	// Output: Fields are: ["foo" "bar" "baz"]
}

func ExampleFieldsFunc() {
	f := func(c rune) bool {
		return !unicode.IsLetter(c) && !unicode.IsNumber(c)
	}
	fmt.Printf("Fields are: %q", bytes.FieldsFunc([]byte("  foo1;bar2,baz3..."), f))
	// Output: Fields are: ["foo1" "bar2" "baz3"]

        CharMappingItem item3 = new CharMappingItem(3L, inputs1, "output");

        // Two items with same inputs and null output should be equal
        assertTrue(item1.equals(item2));

        // Item with null output should not equal item with non-null output
        assertFalse(item3.equals(item1));
        assertFalse(item1.equals(item3));

        // Item with null output should not equal item with different inputs

		for len(output) > 0 && (output[0] < want || output[0] != want && len(output[0]) >= 5 && output[0][:5] == want[:5]) {
			if len(output[0]) >= 5 && output[0][:5] == want[:5] {
				t.Errorf("mismatched output:\nhave %s\nwant %s", output[0], want)
				output = output[1:]
				continue Diff
			}
			t.Errorf("unexpected output: %q", output[0])
			output = output[1:]
		}

     * Adds a name/value pair to the formatted output in {@code name=value} format.
     *
     * @since 18.0 (since 11.0 as {@code Objects.ToStringHelper.add}).
     */
    @CanIgnoreReturnValue
    public ToStringHelper add(String name, boolean value) {
      return addUnconditionalHolder(name, String.valueOf(value));
    }

    /**
     * Adds a name/value pair to the formatted output in {@code name=value} format.
     *

  int num_dims_out = TF_NumDims(model_out_tensor);
  TF_DeleteTensor(model_out_tensor);

  // If the output is a scalar, then return the scalar output
  if (num_dims_out == 0) {
    outputs[0] = model_out.release();
    return absl::OkStatus();
  }

  // Else, reduce sum the output to get a scalar

  // Will sum all dimensions, so get a Tensor containing [0,...,num_dims_out-1].
  AbstractTensorHandlePtr sum_dims;

    }

    private Process createMockProcess(String output) {
        return new MockProcess(output);
    }

    private static class MockProcess extends Process {
        private final InputStream inputStream;

        public MockProcess(String output) {
            this.inputStream = new ByteArrayInputStream(output.getBytes());
        }

        @Override

		case output == "" && testCase.dlURL != "" && testCase.older > 0:
			t.Errorf("Testcase %d: newer release is available but got empty update message!", i+1)
		case output == "" && (testCase.dlURL == "" || testCase.older <= 0):
			// Valid no update message case. No further
			// validation needed.
			continue
		case !strings.Contains(output, line1):

 */
@Deprecated(since = "4.0.0")
public interface ModelWriter {

    /**
     * Writes the supplied model to the specified file. Any non-existing parent directories of the output file will be
     * created automatically.
     *
     * @param output The file to serialize the model to, must not be {@code null}.
     * @param options The options to use for serialization, may be {@code null} to use the default values.

@GwtIncompatible
@J2ktIncompatible
final class Serialization {
  private Serialization() {}

  /**
   * Stores the contents of a map in an output stream, as part of serialization. It does not support
   * concurrent maps whose content may change while the method is running.
   *
   * <p>The serialized output consists of the number of entries, first key, first value, second key,
   * second value, and so on.
   */