parameters: (layer)
return_statement: return ell.neural.SoftmaxLayer(layerParameters)
docstring: Returns ELL softmax layer from Darknet softmax layer
docstring_summary: Returns ELL softmax layer from Darknet softmax layer
docstring_tokens: Returns ELL softmax layer from Darknet softmax layer
function: def get_softmax_layer(layer):
      """Returns ELL softmax layer from Darknet softmax layer"""
  
      # Create the ELL pooling layer
      layerParameters = create_layer_parameters(
          layer['inputShape'], layer['inputPadding'], layer['inputPaddingScheme'],
          layer['outputShape'], layer['outputPadding'], layer['outputPaddingScheme'])
  
      return ell.neural.SoftmaxLayer(layerParameters)
function_tokens: def get_softmax_layer ( layer ) : # Create the ELL pooling layer layerParameters = create_layer_parameters ( layer [ 'inputShape' ] , layer [ 'inputPadding' ] , layer [ 'inputPaddingScheme' ] , layer [ 'outputShape' ] , layer [ 'outputPadding' ] , layer [ 'outputPaddingScheme' ] ) return ell . neural . SoftmaxLayer ( layerParameters )