def METHOD_NAME(
    name,
    vertices,
    faces=None,
    colors=None,
    config_dict=None,
    step=None,
    description=None,
):
    """Writes a TensorFlow mesh summary.
    Args:
      name: A name for this summary. The summary tag used for TensorBoard will
        be this name prefixed by any active name scopes.
      vertices: Tensor of shape `[dim_1, ..., dim_n, 3]` representing the 3D
        coordinates of vertices.
      faces: Tensor of shape `[dim_1, ..., dim_n, 3]` containing indices of
        vertices within each triangle.
      colors: Tensor of shape `[dim_1, ..., dim_n, 3]` containing colors for each
        vertex.
      config_dict: Dictionary with ThreeJS classes names and configuration.
      step: Explicit `int64`-castable monotonic step value for this summary. If
        omitted, this defaults to `tf.summary.experimental.get_step()`, which must
        not be None.
      description: Optional long-form description for this summary, as a
        constant `str`. Markdown is supported. Defaults to empty.
    Returns:
      True if all components of the mesh were saved successfully and False
        otherwise.
    """
    json_config = _get_json_config(config_dict)
    # All tensors representing a single mesh will be represented as separate
    # summaries internally. Those summaries will be regrouped on the client before
    # rendering.
    tensors = [
        metadata.MeshTensor(
            vertices, plugin_data_pb2.MeshPluginData.VERTEX, tf.float32
        ),
        metadata.MeshTensor(
            faces, plugin_data_pb2.MeshPluginData.FACE, tf.int32
        ),
        metadata.MeshTensor(
            colors, plugin_data_pb2.MeshPluginData.COLOR, tf.uint8
        ),
    ]
    tensors = [tensor for tensor in tensors if tensor.data is not None]
    components = metadata.get_components_bitmask(
        [tensor.content_type for tensor in tensors]
    )
    summary_scope = (
        getattr(tf.summary.experimental, "summary_scope", None)
        or tf.summary.summary_scope
    )
    all_success = True
    with summary_scope(name, "mesh_summary", values=tensors):
        for tensor in tensors:
            all_success = all_success and _write_summary(
                name,
                description,
                tensor.data,
                tensor.content_type,
                components,
                json_config,
                step,
            )
    return all_success