class_docstr: Pointwise multiplies by sigmoid(S) with a learnable vector S.
class_docstr_tok: ["Pointwise","multiplies","by","sigmoid","(","S",")","with","a","learnable","vector","S","."]
code: def init_weights_and_state(self, input_signature):
      self.weights = _inverse_sigmoid(self._residual_weight) * np.ones(
          (input_signature.shape[-1])
      ).astype("float32")
  
imports: import numpy
  from trax import fastmath
  from trax import layers
  from trax.fastmath import numpy
  from trax.layers.assert_shape import assert_shape
label_desc: Use image node_id 3 for calling the _ClippedScaling obj's underlying member method code with example usage: obj.init_weights_and_state(input_signature) without return types