class_docstr: A layer receiving a tensor, and adding it to TensorBoard as an image.
  
  It takes an input and returns it unchanged. It stores this input as a state to
  be used as a metric in TensorBoard.
  It converts a tensor to a scalar by running a given aggregation function (mean
  by default). On TensorBoard, results for each device will be reported
  separately.
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docstr: Returns newly initialized weights for this layer.
  
  Weights is a single  `w` tensor with previously specified shape.
  
  Args:
    input_signature: `ShapeDtype` instance characterizing the input this layer
        should compute on. Unused.
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code: def init_weights_and_state(self, input_signature):
      """Returns newly initialized weights for this layer.
  
      Weights is a single  `w` tensor with previously specified shape.
  
      Args:
        input_signature: `ShapeDtype` instance characterizing the input this layer
            should compute on. Unused.
      """
      del input_signature  # Unused.
      self.weights = ()
      self.state = {self._name: jnp.array(0.0)}
  
imports: from absl import logging
  import numpy
  import tensorflow
  from trax import fastmath
  from trax.fastmath import numpy
  from trax.layers import base
  from trax.layers import initializers
  from trax.layers.assert_shape import assert_shape
  from trax.layers.base import Fn
label_desc: Use image node_id 3 for calling the SummaryImage obj's underlying member method code with example usage: obj.init_weights_and_state(input_signature) without return types