class_docstr: Keras layer that only adds a bias to the input.
  
  `BiasLayer` implements the operation:
  `output = input + bias`
  
  Args:
      bias_initializer: Initializer for the bias vector.
  
  Input shape:
      nD tensor with shape: `(batch_size, ..., input_dim)`. The most common
        situation would be a 2D input with shape `(batch_size, input_dim)`. Note
        a rank of at least 2 is required.
  Output shape:
      nD tensor with shape: `(batch_size, ..., input_dim)`. For instance, for a
        2D input with shape `(batch_size, input_dim)`, the output would have
        shape `(batch_size, input_dim)`.
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code: def get_config(self):
      config = {
          "bias_initializer": tf.keras.initializers.serialize(
              self.bias_initializer
          ),
      }
      base_config = super(BiasLayer, self).get_config()
      return dict(list(base_config.items()) + list(config.items()))
  
file_path: agents/tf_agents/keras_layers/bias_layer.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import tensorflow
label_desc: Use image node_id 5 for calling the BiasLayer obj's underlying member method code with example usage: obj.get_config() and returns: dict