class_docstr: A layer which multiplies its input by a scalar variable.
class_docstr_tok: ["A","layer","which","multiplies","its","input","by","a","scalar","variable","."]
docstr: Initializes the MultiplyLayer.
  
  Args:
    regularizer: The weight regularizer on the scalar variable.
    activity_regularizer: The activity regularizer.
    use_operator: If True, add using the * operator. If False, add using
      tf.multiply.
    var_name: The name of the variable. It can be useful to pass a name other
      than 'v', to test having the attribute name (self.v) being different
      from the variable name.
    **kwargs: Passed to AssertTypeLayer constructor.
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code: def __init__(
      self,
      regularizer=None,
      activity_regularizer=None,
      use_operator=False,
      var_name="v",
      **kwargs,
  ):
      """Initializes the MultiplyLayer.
  
      Args:
        regularizer: The weight regularizer on the scalar variable.
        activity_regularizer: The activity regularizer.
        use_operator: If True, add using the * operator. If False, add using
          tf.multiply.
        var_name: The name of the variable. It can be useful to pass a name other
          than 'v', to test having the attribute name (self.v) being different
          from the variable name.
        **kwargs: Passed to AssertTypeLayer constructor.
      """
      self._regularizer = regularizer
      if isinstance(regularizer, dict):
          self._regularizer = regularizers.deserialize(
              regularizer, custom_objects=globals()
          )
      self._activity_regularizer = activity_regularizer
      if isinstance(activity_regularizer, dict):
          self._activity_regularizer = regularizers.deserialize(
              activity_regularizer, custom_objects=globals()
          )
  
      self._use_operator = use_operator
      self._var_name = var_name
      super(MultiplyLayer, self).__init__(
          activity_regularizer=self._activity_regularizer, **kwargs
      )
  
imports: from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import tensor_conversion
  from tensorflow.python.keras import regularizers
  from tensorflow.python.keras.engine import base_layer
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import check_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import custom_gradient
  from tensorflow.python.ops import math_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 1 to create a new MultiplyLayer object from inherited base classes: AssertTypeLayer with example: obj = MultiplyLayer(regularizer, activity_regularizer, use_operator, var_name)