parameters: (self)
return_statement: return ell.neural.PaddingParameters(paddingScheme, padding)
docstring: Returns the ell.neural.PaddingParameters for a layer's input.
docstring_summary: Returns the ell.neural.PaddingParameters for a layer's input.
docstring_tokens: Returns the ell . neural . PaddingParameters for a layer s input .
function: def get_input_padding_parameters(self):
          """Returns the ell.neural.PaddingParameters for a layer's input."""
  
          paddingScheme = ell.neural.PaddingScheme.zeros
          padding = 0
          receptiveField = self.weights_parameter.shape[2]
  
          if 'autoPadding' in self.attributes:
              if self.attributes['autoPadding'][1]:
                  padding = int((receptiveField - 1) / 2)
              else:
                  padding = self.attributes['upperPad'][0]
          else:
              padding = self.attributes['upperPad'][0]
  
          return ell.neural.PaddingParameters(paddingScheme, padding)
function_tokens: def get_input_padding_parameters ( self ) : paddingScheme = ell . neural . PaddingScheme . zeros padding = 0 receptiveField = self . weights_parameter . shape [ 2 ] if 'autoPadding' in self . attributes : if self . attributes [ 'autoPadding' ] [ 1 ] : padding = int ( ( receptiveField - 1 ) / 2 ) else : padding = self . attributes [ 'upperPad' ] [ 0 ] else : padding = self . attributes [ 'upperPad' ] [ 0 ] return ell . neural . PaddingParameters ( paddingScheme , padding )