class_docstr: Simplified version of :class:`DeConv3dLayer`, see `tf.nn.conv3d_transpose <https://tensorflow.google.cn/versions/r2.0/api_docs/python/tf/nn/conv3d_transpose>`__.
  
  Parameters
  ----------
  n_filter : int
      The number of filters.
  filter_size : tuple of int
      The filter size (depth, height, width).
  strides : tuple of int
      The stride step (depth, height, width).
  padding : str
      The padding algorithm type: "SAME" or "VALID".
  act : activation function
      The activation function of this layer.
  data_format : str
      "channels_last" (NDHWC, default) or "channels_first" (NCDHW).
  W_init : initializer
      The initializer for the weight matrix.
  b_init : initializer or None
      The initializer for the bias vector. If None, skip bias.
  in_channels : int
      The number of in channels.
  name : None or str
      A unique layer name.
  
  Examples
  --------
  With TensorLayer
  
  >>> net = tl.layers.Input([5, 100, 100, 100, 32], name='input')
  >>> deconv3d = tl.layers.DeConv3d(n_filter=32, filter_size=(3, 3, 3), strides=(2, 2, 2), in_channels=32, name='DeConv3d_1')
  >>> print(deconv3d)
  >>> tensor = tl.layers.DeConv3d(n_filter=32, filter_size=(3, 3, 3), strides=(2, 2, 2), name='DeConv3d_2')(net)
  >>> print(tensor)
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code: def forward(self, inputs):
      outputs = self.layer(inputs)
      return outputs
  
file_path: TensorLayer/tensorlayer/layers/convolution/simplified_deconv.py
imports: import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.decorators import deprecated_alias
  from tensorlayer.layers.core import Layer
  from tensorlayer.layers.utils import get_collection_trainable
label_desc: Use image node_id 4 for calling the DeConv3d obj's underlying member method code with example usage: obj.forward(inputs) and returns: outputs