class_docstr: Base class for preprocessing layers which require to be reset.
  
  Args:
      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>.
class_docstr_tok: ["Base","class","for","preprocessing","layers","which","require","to","be","reset",".","Args",":","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",">","."]
code: def __init__(self, *, name=None, input_spec=None):
      super().__init__(name=name, input_spec=input_spec)
  
imports: import tensorflow
  from tensorforce.core import parameter_modules, SignatureDict, TensorSpec, tf_function, tf_util
  from tensorforce.core.layers import Layer
label_desc: Use image node_id 1 to create a new PreprocessingLayer object from inherited base classes: Layer with example: obj = PreprocessingLayer()