class_docstr: Deconvolution layer.
  
  Args:
      inp (~nnabla.Variable): N-D array.
      outmaps (int): Number of deconvolution kernels (which is equal to the number of output channels). For example, to apply deconvolution on an input with 16 types of filters, specify 16.
      kernel (:obj:`tuple` of :obj:`int`): Convolution kernel size. For example, to apply deconvolution on an image with a 3 (height) by 5 (width) two-dimensional kernel, specify (3,5).
      pad (:obj:`tuple` of :obj:`int`): Padding sizes for dimensions.
      stride (:obj:`tuple` of :obj:`int`): Stride sizes for dimensions.
      dilation (:obj:`tuple` of :obj:`int`): Dilation sizes for dimensions.
      group (int): Number of groups of channels. This makes connections across channels sparser by grouping connections along map direction.
      w_init (:obj:`nnabla.initializer.BaseInitializer` or :obj:`numpy.ndarray`): Initializer for weight. By default, it is initialized with :obj:`nnabla.initializer.UniformInitializer` within the range determined by :obj:`nnabla.initializer.calc_uniform_lim_glorot`.  
      b_init (:obj:`nnabla.initializer.BaseInitializer` or :obj:`numpy.ndarray`): Initializer for bias. By default, it is initialized with zeros if `with_bias` is `True`.
      base_axis (int): Dimensions up to `base_axis` are treated as the sample dimensions.
      fix_parameters (bool): When set to `True`, the weights and biases will not be updated.
      rng (numpy.random.RandomState): Random generator for Initializer.
      with_bias (bool): Specify whether to include the bias term.
  
  Returns:
      :class:`~nnabla.Variable`: N-D array. See :obj:`~nnabla.functions.deconvolution` for the output shape.
code: def __call__(self, inp):
      return F.deconvolution(
          inp,
          self.W,
          self.b,
          self.base_axis,
          self.pad,
          self.stride,
          self.dilation,
          self.group,
      )
  
file_path: nnabla/python/src/nnabla/experimental/parametric_function_class/deconvolution.py
imports: import nnabla
  import nnabla.functions
  from nnabla.initializer import calc_uniform_lim_glorot, ConstantInitializer, UniformInitializer
  from .module import Module
label_desc: Use image node_id 2 for calling the Deconvolution obj's underlying member method code with example usage: obj.__call__(inp) and returns: F