class_docstr: The :class:`OneHot` class is the starting layer of a neural network, see ``tf.one_hot``.
  Useful link: `https://www.tensorflow.org/api_docs/python/tf/one_hot`.
  
  Parameters
  ----------
  depth : None or int
      If the input indices is rank N, the output will have rank N+1. The new axis is created at dimension `axis` (default: the new axis is appended at the end).
  on_value : None or number
      The value to represnt `ON`. If None, it will default to the value 1.
  off_value : None or number
      The value to represnt `OFF`. If None, it will default to the value 0.
  axis : None or int
      The axis.
  dtype : None or TensorFlow dtype
      The data type, None means tf.float32.
  name : str
      A unique layer name.
  
  Examples
  ---------
  >>> import tensorflow as tf
  >>> import tensorlayer as tl
  >>> net = tl.layers.Input([32], dtype=tf.int32)
  >>> onehot = tl.layers.OneHot(depth=8)
  >>> print(onehot)
  OneHot(depth=8, name='onehot')
  >>> tensor = tl.layers.OneHot(depth=8)(net)
  >>> print(tensor)
  tf.Tensor([...], shape=(32, 8), dtype=float32)
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code: def build(self, inputs_shape):
      pass
  
imports: import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.layers.core import Layer
label_desc: Use image node_id 3 for calling the OneHot obj's underlying member method code with example usage: obj.build(inputs_shape) without return types