class_docstr: Keras layer (specification key: `keras`).
  
  Args:
      layer (string): Keras layer class name, see
          `TensorFlow docs <https://www.tensorflow.org/api_docs/python/tf/keras/layers>`__
          (<span style="color:#C00000"><b>required</b></span>).
      l2_regularization (float >= 0.0): Scalar controlling L2 regularization
          (<span style="color:#00C000"><b>default</b></span>: inherit value of parent module).
      name (string): Layer name
          (<span style="color:#00C000"><b>default</b></span>: internally chosen).
      input_spec (specification): <span style="color:#00C000"><b>internal use</b></span>.
      kwargs: Arguments for the Keras layer, see
          `TensorFlow docs <https://www.tensorflow.org/api_docs/python/tf/keras/layers>`__.
code: def __init__(
      self,
      *,
      layer,
      l2_regularization=None,
      name=None,
      input_spec=None,
      **kwargs,
  ):
      super().__init__(
          l2_regularization=l2_regularization,
          name=name,
          input_spec=input_spec,
      )
  
      self.keras_layer = getattr(tf.keras.layers, layer)(
          name=name,
          dtype=tf_util.get_dtype(type="float"),
          input_shape=input_spec.shape,
          **kwargs,
      )
  
      self.architecture_kwargs["layer"] = str(layer)
      if l2_regularization is not None:
          self.architecture_kwargs["l2_regularization"] = str(
              l2_regularization
          )
  
file_path: tensorforce/tensorforce/core/layers/keras.py
imports: import tensorflow
  from tensorforce.core import tf_function, tf_util
  from tensorforce.core.layers import Layer
label_desc: Use image node_id 1 to create a new KerasLayer object from inherited base classes: Layer with example: obj = KerasLayer()