class_docstr: Simplified version of :class:`DeConv2dLayer`, see `tf.nn.conv3d_transpose <https://tensorflow.google.cn/versions/r2.0/api_docs/python/tf/nn/conv2d_transpose>`__.
  
  Parameters
  ----------
  n_filter : int
      The number of filters.
  filter_size : tuple of int
      The filter size (height, width).
  strides : tuple of int
      The stride step (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" (NHWC, default) or "channels_first" (NCHW).
  dilation_rate : int of tuple of int
      The dilation rate to use for dilated convolution
  W_init : initializer
      The initializer for the weight matrix.
  b_init : initializer or None
      The initializer for the bias vector. If None, skip biases.
  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, 32], name='input')
  >>> deconv2d = tl.layers.DeConv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), in_channels=32, name='DeConv2d_1')
  >>> print(deconv2d)
  >>> tensor = tl.layers.DeConv2d(n_filter=32, filter_size=(3, 3), strides=(2, 2), name='DeConv2d_2')(net)
  >>> print(tensor)
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code: def __repr__(self):
      actstr = (
          self.act.__name__ if self.act is not None else "No Activation"
      )
      s = (
          "{classname}(in_channels={in_channels}, out_channels={n_filter}, kernel_size={filter_size}"
          ", strides={strides}, padding={padding}"
      )
      if self.dilation_rate != (1,) * len(self.dilation_rate):
          s += ", dilation={dilation_rate}"
      if self.b_init is None:
          s += ", bias=False"
      s += ", " + actstr
      if self.name is not None:
          s += ", name='{name}'"
      s += ")"
      return s.format(
          classname=self.__class__.__name__, **self.__dict__
      )
  
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 2 for calling the DeConv2d obj's underlying member method code with example usage: obj.__repr__() and returns: s