code: def pixel_wise_softmax(x, name="pixel_wise_softmax"):
      """Return the softmax outputs of images, every pixels have multiple label, the sum of a pixel is 1.
  
      Usually be used for image segmentation.
  
      Parameters
      ----------
      x : Tensor
          input.
              - For 2d image, 4D tensor (batch_size, height, weight, channel), where channel >= 2.
              - For 3d image, 5D tensor (batch_size, depth, height, weight, channel), where channel >= 2.
      name : str
          function name (optional)
  
      Returns
      -------
      Tensor
          A ``Tensor`` in the same type as ``x``.
  
      Examples
      --------
      >>> outputs = pixel_wise_softmax(network.outputs)
      >>> dice_loss = 1 - dice_coe(outputs, y_, epsilon=1e-5)
  
      References
      ----------
      - `tf.reverse <https://www.tensorflow.org/versions/master/api_docs/python/array_ops.html#reverse>`__
  
      """
      with tf.name_scope(name):
          return tf.nn.softmax(x)
  
file_path: TensorLayer/tensorlayer/activation.py
imports: import tensorflow
  from tensorlayer.decorators import deprecated
label_desc: Use image node_id 8 for calling a global function with example usage: pixel_wise_softmax(x, name) and returns: tf