code: def test__process_tb_histogram_plugin_event_empty_no_values(self):
      # Given
      queue = Queue()
      tracker = TensorboardFolderTracker(
          tensorboard_event_folder="dummy", queue=queue
      )
      num_bins = 11
      histogram_counts_np = np.zeros(num_bins)
      left_edge_np = np.zeros(num_bins)
      right_edge_np = np.zeros(num_bins)
  
      # Create histogram summary in format of plugin
      plugin_data = SummaryMetadata.PluginData(plugin_name="histograms")
      smd = SummaryMetadata(plugin_data=plugin_data)
      tensor_content = np.hstack(
          [
              left_edge_np[:, None],
              right_edge_np[:, None],
              histogram_counts_np[:, None],
          ]
      )
      tensor = make_tensor_proto(
          tensor_content.astype(dtype=np.float64)
      )
      histogram_summary = Summary(
          value=[
              Summary.Value(
                  tag="test_histogram", metadata=smd, tensor=tensor
              )
          ]
      )
      event = Event(summary=histogram_summary)
  
      # When
      tracker._process_tb_event(event)
  
      # Then
      self.assertTrue(queue.empty())
  
imports: from queue import Queue
  import numpy
  from PIL import ImageChops
  import tensorflow
  from tensorboard.compat.proto.summary_pb2 import SummaryMetadata, Summary
  from tensorboard.compat.proto.tensor_pb2 import TensorProto
  from tensorboard.compat.proto.tensor_shape_pb2 import TensorShapeProto
  from tensorboard.compat.proto.event_pb2 import Event
  from tensorboard.util.tensor_util import make_tensor_proto
  from torch.utils.tensorboard.summary import image, scalar, histogram, histogram_raw
  from aim import Image, Distribution
  from aim.ext.tensorboard_tracker.tracker import TensorboardFolderTracker
  from tests.base import TestBase
label_desc: Use image node_id 9 for calling the TestTensorboardTracker obj's underlying member method code with example usage: obj.test__process_tb_histogram_plugin_event_empty_no_values() without return types