class_docstr: The :class:`Input` class is the starting layer of a neural network.
  
  Parameters
  ----------
  shape : tuple (int)
      Including batch size.
  dtype: dtype
      The type of input values. By default, tf.float32.
  name : None or str
      A unique layer name.
class_docstr_tok: ["The",":","class",":","`","Input","`","class","is","the","starting","layer","of","a","neural","network",".","Parameters","--","--","--","--","--","shape",":","tuple","(","int",")","Including","batch","size",".","dtype",":","dtype","The","type","of","input","values",".","By","default",",","tf.float32",".","name",":","None","or","str","A","unique","layer","name","."]
code: def build(self, inputs_shape):
      pass
  
file_path: TensorLayer/tensorlayer/layers/inputs.py
imports: import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.layers.core import Layer, LayerNode
label_desc: Use image node_id 4 for calling the _InputLayer obj's underlying member method code with example usage: obj.build(inputs_shape) without return types