Option:  settings["OPTION"],
					Fields: []IndexOption{{
						Field:      field,
						Expression: settings["EXPRESSION"],
						Sort:       settings["SORT"],
						Collate:    settings["COLLATE"],
						Length:     length,
						priority:   priority,
					}},
				})
			}
		}
	}

	err = nil
	return

  local gridWidth = 24,

  '#makeGrid':: d.func.new(
    |||
      `makeGrid` returns an array of `panels` organized in a grid with equal width
      and `panelHeight`. Row panels are used as "linebreaks", if a Row panel is collapsed,
      then all panels below it will be folded into the row.

      Optional `startY` can be provided to place generated grid above or below existing panels.
    |||,
    args=[
      d.arg('panels', d.T.array),

		"idx_user_indices_name3": {
			Name:  "idx_user_indices_name3",
			Type:  "btree",
			Where: "name3 != 'jinzhu'",
			Fields: []schema.IndexOption{{
				Field:   &schema.Field{Name: "Name3"},
				Sort:    "desc",
				Collate: "utf8",
				Length:  10,
			}},
		},
		"idx_user_indices_name4": {
			Name:   "idx_user_indices_name4",
			Class:  "UNIQUE",

                    first_child.read_source(config=config)
                    new_title = first_child.title or new_title
            # Creating a new section makes it render it collapsed by default
            # no idea why, so, let's just modify the existing one
            # new_section = Section(title=new_title, children=new_children)
            item.title = new_title

        "type": "dashboard"
      }
    ]
  },
  "editable": true,
  "fiscalYearStartMonth": 0,
  "graphTooltip": 0,
  "links": [],
  "liveNow": false,
  "panels": [
    {
      "collapsed": false,
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },
      "gridPos": {
        "h": 1,
        "w": 24,
        "x": 0,
        "y": 0
      },

		str := stmt.Quote(opt.DBName)
		if opt.Expression != "" {
			str = opt.Expression
		} else if opt.Length > 0 {
			str += fmt.Sprintf("(%d)", opt.Length)
		}

		if opt.Collate != "" {
			str += " COLLATE " + opt.Collate
		}

		if opt.Sort != "" {
			str += " " + opt.Sort
		}
		results = append(results, clause.Expr{SQL: str})
	}
	return
}

recommendation is not to serve models using Eager mode since it also has
performance limitations.

## Multi-Tenant environments

It is possible to run multiple TensorFlow models in parallel. For example,
`ModelServer` collates all computation graphs exposed to it (from multiple
`SavedModel`) and executes them in parallel on available executors. Running
TensorFlow in a multitenant design mixes the risks described above with the

    public static final String LOGIN_REQUIRED_PROPERTY = "login.required";

    public static final String RESULT_COLLAPSED_PROPERTY = "result.collapsed";

    public static final String LOGIN_LINK_ENALBED_PROPERTY = "login.link.enabled";

    public static final String THUMBNAIL_ENALBED_PROPERTY = "thumbnail.enabled";

        "type": "dashboard"
      }
    ]
  },
  "editable": true,
  "fiscalYearStartMonth": 0,
  "graphTooltip": 0,
  "links": [],
  "liveNow": false,
  "panels": [
    {
      "collapsed": false,
      "datasource": {
        "type": "prometheus",
        "uid": "${datasource}"
      },
      "gridPos": {
        "h": 1,
        "w": 24,
        "x": 0,
        "y": 0
      },

             key_name VARCHAR(3072) NOT NULL,
             key_hash CHAR(64) GENERATED ALWAYS AS (SHA2(key_name, 256)) STORED NOT NULL PRIMARY KEY,
             value JSON)
           CHARACTER SET = utf8mb4 COLLATE = utf8mb4_bin ROW_FORMAT = Dynamic;`
	mysqlCreateAccessTable = `CREATE TABLE %s (event_time DATETIME NOT NULL, event_data JSON)
                                    ROW_FORMAT = Dynamic;`