class_docstr: Audio Plugin for TensorBoard.
class_docstr_tok: ["Audio","Plugin","for","TensorBoard","."]
docstr: Return information about the tags in each run.
  
  Result is a dictionary of the form
  
      {
        "runName1": {
          "tagName1": {
            "displayName": "The first tag",
            "description": "<p>Long ago there was just one tag...</p>",
            "samples": 3
          },
          "tagName2": ...,
          ...
        },
        "runName2": ...,
        ...
      }
  
  For each tag, `samples` is the greatest number of audio clips that
  appear at any particular step. (It's not related to "samples of a
  waveform.") For example, if for tag `minibatch_input` there are
  five audio clips at step 0 and ten audio clips at step 1, then the
  dictionary for `"minibatch_input"` will contain `"samples": 10`.
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code: def _index_impl(self, ctx, experiment):
      """Return information about the tags in each run.
  
      Result is a dictionary of the form
  
          {
            "runName1": {
              "tagName1": {
                "displayName": "The first tag",
                "description": "<p>Long ago there was just one tag...</p>",
                "samples": 3
              },
              "tagName2": ...,
              ...
            },
            "runName2": ...,
            ...
          }
  
      For each tag, `samples` is the greatest number of audio clips that
      appear at any particular step. (It's not related to "samples of a
      waveform.") For example, if for tag `minibatch_input` there are
      five audio clips at step 0 and ten audio clips at step 1, then the
      dictionary for `"minibatch_input"` will contain `"samples": 10`.
      """
      mapping = self._data_provider.list_blob_sequences(
          ctx,
          experiment_id=experiment,
          plugin_name=metadata.PLUGIN_NAME,
      )
      result = {run: {} for run in mapping}
      for run, tag_to_time_series in mapping.items():
          for tag, time_series in tag_to_time_series.items():
              md = metadata.parse_plugin_metadata(
                  time_series.plugin_content
              )
              if not self._version_checker.ok(md.version, run, tag):
                  continue
              description = plugin_util.markdown_to_safe_html(
                  time_series.description
              )
              result[run][tag] = {
                  "displayName": time_series.display_name,
                  "description": description,
                  "samples": time_series.max_length,
              }
      return result
  
file_path: tensorboard/tensorboard/plugins/audio/audio_plugin.py
imports: import urllib.parse
  from werkzeug import wrappers
  from tensorboard import errors
  from tensorboard import plugin_util
  from tensorboard.backend import http_util
  from tensorboard.data import provider
  from tensorboard.plugins import base_plugin
  from tensorboard.plugins.audio import metadata
label_desc: Use image node_id 5 for calling the AudioPlugin obj's underlying member method code with example usage: obj._index_impl(ctx, experiment) and returns: result