query.facet.fields.size=100
query.facet.fields.min_doc_count=1
query.facet.fields.sort=count.desc
query.facet.fields.missing=
query.facet.queries=\
labels.facet_timestamp_title:\
labels.facet_timestamp_1day=timestamp:[now/d-1d TO *]\t\
labels.facet_timestamp_1week=timestamp:[now/d-7d TO *]\t\
labels.facet_timestamp_1month=timestamp:[now/d-1M TO *]\t\
labels.facet_timestamp_1year=timestamp:[now/d-1y TO *]\n\
labels.facet_contentLength_title:\

    "to": "now"
  },
  "timepicker": {
    "refresh_intervals": [
      "10s",
      "30s",
      "1m",
      "5m",
      "15m",
      "30m",
      "1h",
      "2h",
      "1d"
    ],
    "time_options": [
      "5m",
      "15m",
      "1h",
      "6h",
      "12h",
      "24h",
      "2d",
      "7d",
      "30d"
    ]
  },

    "to": "now"
  },
  "timepicker": {
    "refresh_intervals": [
      "10s",
      "30s",
      "1m",
      "5m",
      "15m",
      "30m",
      "1h",
      "2h",
      "1d"
    ],
    "time_options": [
      "5m",
      "15m",
      "1h",
      "6h",
      "12h",
      "24h",
      "2d",
      "7d",
      "30d"
    ]
  },

    String QUERY_FACET_FIELDS_MISSING = "query.facet.fields.missing";

    /** The key of the configuration. e.g. labels.facet_timestamp_title:labels.facet_timestamp_1day=timestamp:[now/d-1d TO *]	labels.facet_timestamp_1week=timestamp:[now/d-7d TO *]	labels.facet_timestamp_1month=timestamp:[now/d-1M TO *]	labels.facet_timestamp_1year=timestamp:[now/d-1y TO *]<br>

    of other integer types) in `tf.constant`.
*   Make the `gain` argument of convolutional orthogonal initializers
    (`convolutional_delta_orthogonal`, `convolutional_orthogonal_1D`,
    `convolutional_orthogonal_2D`, `convolutional_orthogonal_3D`) have
    consistent behavior with the `tf.initializers.orthogonal` initializer, i.e.