class_docstr: The :class:`Conv3dLayer` class is a 3D CNN layer, see `tf.nn.conv3d <https://tensorflow.google.cn/versions/r2.0/api_docs/python/tf/nn/conv3d>`__.
  
  Parameters
  ----------
  act : activation function
      The activation function of this layer.
  shape : tuple of int
      Shape of the filters: (filter_depth, filter_height, filter_width, in_channels, out_channels).
  strides : tuple of int
      The sliding window strides for corresponding input dimensions.
      Must be in the same order as the shape dimension.
  padding : str
      The padding algorithm type: "SAME" or "VALID".
  data_format : str
      "NDHWC" or "NCDHW", default is "NDHWC".
  dilation_rate : tuple of int
      Filter up-sampling/input down-sampling rate.
  W_init : initializer
      The initializer for the weight matrix.
  b_init : initializer or None
      The initializer for the bias vector. If None, skip biases.
  name : None or str
      A unique layer name.
  
  Notes
  -----
  - shape = [d, h, w, the number of output channel of previous layer, the number of output channels]
  - the number of output channel of a layer is its last dimension.
  
  Examples
  --------
  With TensorLayer
  
  >>> net = tl.layers.Input([8, 100, 100, 100, 3], name='input')
  >>> conv3d = tl.layers.Conv3dLayer(shape=(2, 2, 2, 3, 32), strides=(1, 2, 2, 2, 1), b_init=None, name='conv3d_1')
  >>> print(conv3d)
  >>> tensor = tl.layers.Conv3dLayer(shape=(2, 2, 2, 3, 32), strides=(1, 2, 2, 2, 1), act=tf.nn.relu, name='conv3d_2')(net)
  >>> print(tensor)
code: def build(self, inputs):
      self.W = self._get_weights(
          "filters", shape=self.shape, init=self.W_init
      )
      if self.b_init:
          self.b = self._get_weights(
              "biases", shape=(self.n_filter), init=self.b_init
          )
  
imports: import tensorflow
  import tensorlayer
  from tensorlayer import logging
  from tensorlayer.decorators import deprecated_alias
  from tensorlayer.layers.core import Layer
label_desc: Use image node_id 3 for calling the Conv3dLayer obj's underlying member method code with example usage: obj.build(inputs) without return types