original_docstring: 
      3x3 version of the deconvolution block with batch normalization and activation.
  
      Parameters:
      ----------
      in_channels : int
          Number of input channels.
      out_channels : int
          Number of output channels.
      stride : int or tuple/list of 2 int
          Strides of the deconvolution.
      padding : int or tuple/list of 2 int, default 1
          Padding value for deconvolution layer.
      ext_padding : tuple/list of 4 int, default None
          Extra padding value for deconvolution layer.
      out_padding : int or tuple/list of 2 int, default 1
          Output padding value for deconvolution layer.
      dilation : int or tuple/list of 2 int, default 1
          Dilation value for deconvolution layer.
      groups : int, default 1
          Number of groups.
      bias : bool, default False
          Whether the layer uses a bias vector.
      use_bn : bool, default True
          Whether to use BatchNorm layer.
      bn_eps : float, default 1e-5
          Small float added to variance in Batch norm.
      activation : function or str or None, default nn.ReLU(inplace=True)
          Activation function or name of activation function.
      
docstring: 3x3 version of the deconvolution block with batch normalization and activation.
  Parameters.
  
  in_channels : int
  Number of input channels.
  out_channels : int
  Number of output channels.
  stride : int or tuple/list of 2 int
  Strides of the deconvolution.
  padding : int or tuple/list of 2 int, default 1
  Padding value for deconvolution layer.
  ext_padding : tuple/list of 4 int, default None
  Extra padding value for deconvolution layer.
  out_padding : int or tuple/list of 2 int, default 1
  Output padding value for deconvolution layer.
  dilation : int or tuple/list of 2 int, default 1
  Dilation value for deconvolution layer.
  groups : int, default 1
  Number of groups.
  bias : bool, default False
  Whether the layer uses a bias vector.
  use_bn : bool, default True
  Whether to use BatchNorm layer.
  bn_eps : float, default 1e-5
  Small float added to variance in Batch norm.
  activation : function or str or None, default nn.ReLU(inplace=True)
  Activation function or name of activation function.
docstring_tokens: 3x3 version of the deconvolution block with batch normalization and activation . Parameters . in_channels : int Number of input channels . out_channels : int Number of output channels . stride : int or tuple / list of 2 int Strides of the deconvolution . padding : int or tuple / list of 2 int default 1 Padding value for deconvolution layer . ext_padding : tuple / list of 4 int default None Extra padding value for deconvolution layer . out_padding : int or tuple / list of 2 int default 1 Output padding value for deconvolution layer . dilation : int or tuple / list of 2 int default 1 Dilation value for deconvolution layer . groups : int default 1 Number of groups . bias : bool default False Whether the layer uses a bias vector . use_bn : bool default True Whether to use BatchNorm layer . bn_eps : float default 1e - 5 Small float added to variance in Batch norm . activation : function or str or None default nn . ReLU ( inplace = True ) Activation function or name of activation function .
code: def deconv3x3_block(padding=1,
                      out_padding=1,
                      **kwargs):
      """
      3x3 version of the deconvolution block with batch normalization and activation.
  
      Parameters:
      ----------
      in_channels : int
          Number of input channels.
      out_channels : int
          Number of output channels.
      stride : int or tuple/list of 2 int
          Strides of the deconvolution.
      padding : int or tuple/list of 2 int, default 1
          Padding value for deconvolution layer.
      ext_padding : tuple/list of 4 int, default None
          Extra padding value for deconvolution layer.
      out_padding : int or tuple/list of 2 int, default 1
          Output padding value for deconvolution layer.
      dilation : int or tuple/list of 2 int, default 1
          Dilation value for deconvolution layer.
      groups : int, default 1
          Number of groups.
      bias : bool, default False
          Whether the layer uses a bias vector.
      use_bn : bool, default True
          Whether to use BatchNorm layer.
      bn_eps : float, default 1e-5
          Small float added to variance in Batch norm.
      activation : function or str or None, default nn.ReLU(inplace=True)
          Activation function or name of activation function.
      """
      return DeconvBlock(
          kernel_size=3,
          padding=padding,
          out_padding=out_padding,
          **kwargs)
code_tokens: def deconv3x3_block ( padding = 1 , out_padding = 1 , ** kwargs ) : return DeconvBlock ( kernel_size = 3 , padding = padding , out_padding = out_padding , ** kwargs )
short_docstring: 3x3 version of the deconvolution block with batch normalization and activation.
short_docstring_tokens: 3x3 version of the deconvolution block with batch normalization and activation .
comment: """
      3x3 version of the deconvolution block with batch normalization and activation.
  
      Parameters:
      ----------
      in_channels : int
          Number of input channels.
      out_channels : int
          Number of output channels.
      stride : int or tuple/list of 2 int
          Strides of the deconvolution.
      padding : int or tuple/list of 2 int, default 1
          Padding value for deconvolution layer.
      ext_padding : tuple/list of 4 int, default None
          Extra padding value for deconvolution layer.
      out_padding : int or tuple/list of 2 int, default 1
          Output padding value for deconvolution layer.
      dilation : int or tuple/list of 2 int, default 1
          Dilation value for deconvolution layer.
      groups : int, default 1
          Number of groups.
      bias : bool, default False
          Whether the layer uses a bias vector.
      use_bn : bool, default True
          Whether to use BatchNorm layer.
      bn_eps : float, default 1e-5
          Small float added to variance in Batch norm.
      activation : function or str or None, default nn.ReLU(inplace=True)
          Activation function or name of activation function.
      """