code: def convert_slice(params, w_name, scope_name, inputs, layers, weights, names):
      
      print('Converting slice ...')
  
      if len(params['axes']) > 1:
          raise AssertionError('Cannot convert slice by multiple dimensions')
  
      if params['axes'][0] not in [0, 1, 2, 3]:
          raise AssertionError('Slice by dimension more than 3 or less than 0 is not supported')
  
      def target_layer(x, axis=int(params['axes'][0]), start=int(params['starts'][0]), end=int(params['ends'][0])):
          if axis == 0:
              return x[start:end]
          elif axis == 1:
              return x[:, start:end]
          elif axis == 2:
              return x[:, :, start:end]
          elif axis == 3:
              return x[:, :, :, start:end]
  
      lambda_layer = keras.layers.Lambda(target_layer)
      layers[scope_name] = lambda_layer(layers[inputs[0]])
docs: Convert slice operation.
  
      Args:
          params: dictionary with layer parameters
          w_name: name prefix in state_dict
          scope_name: pytorch scope name
          inputs: pytorch node inputs
          layers: dictionary with keras tensors
          weights: pytorch state_dict
          names: use short names for keras layers