class_docstr: WIT widget for Jupyter.
class_docstr_tok: ["WIT","widget","for","Jupyter","."]
docstr: Constructor for Jupyter notebook WitWidget.
  
  Args:
    config_builder: WitConfigBuilder object containing settings for WIT.
    height: Optional height in pixels for WIT to occupy. Defaults to 1000.
    delay_rendering. Optional. This argument is ignored in the Jupyter
    implementation but is included for API compatibility between Colab and
    Jupyter implementations. Rendering in Jupyter is always delayed until
    the render method is called or the WitWidget object is directly evaluated
    in a notebook cell.
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code: def __init__(
      self, config_builder, height=1000, delay_rendering=False
  ):
      """Constructor for Jupyter notebook WitWidget.
  
      Args:
        config_builder: WitConfigBuilder object containing settings for WIT.
        height: Optional height in pixels for WIT to occupy. Defaults to 1000.
        delay_rendering. Optional. This argument is ignored in the Jupyter
        implementation but is included for API compatibility between Colab and
        Jupyter implementations. Rendering in Jupyter is always delayed until
        the render method is called or the WitWidget object is directly evaluated
        in a notebook cell.
      """
      self.transfer_block = False
      self.examples_generator = None
      self.inferences_generator = None
      # TODO(wit-dev) This should depend on the example size targeting less than
      # 10MB per batch to avoid websocket issues.
      self.batch_size = 10000
  
      widgets.DOMWidget.__init__(
          self, layout=Layout(height="%ipx" % height)
      )
      base.WitWidgetBase.__init__(self, config_builder)
      self.error_counter = 0
  
      # Ensure the visualization takes all available width.
      display(
          HTML("<style>.container { width:100% !important; }</style>")
      )
  
imports: import math
  import ipywidgets
  import tensorflow
  from IPython.core.display import display, HTML
  from ipywidgets import Layout
  from traitlets import Dict
  from traitlets import Int
  from traitlets import List
  from traitlets import observe
  from traitlets import Unicode
  from traitlets import Set
  from witwidget.notebook import base
label_desc: Use image node_id 1 to create a new WitWidget object from inherited base classes: widgets, base with example: obj = WitWidget(config_builder, height, delay_rendering)