code: def calculate_attribution(
      self,
      baselines: Optional[Sequence[Tuple[Tensor, ...]]],
      data: Tuple[Tensor, ...],
      additional_forward_args: Optional[Tuple[Tensor, ...]],
      label: Optional[Union[Tensor]],
      attribution_method_name: str,
      attribution_arguments: Dict,
      model: Module,
  ) -> Tuple[Tensor, ...]:
      attribution_cls = ATTRIBUTION_NAMES_TO_METHODS[
          attribution_method_name
      ]
      attribution_method = attribution_cls(model)
      if attribution_method_name in ATTRIBUTION_METHOD_CONFIG:
          param_config = ATTRIBUTION_METHOD_CONFIG[
              attribution_method_name
          ]
          if param_config.post_process:
              for k, v in attribution_arguments.items():
                  if k in param_config.post_process:
                      attribution_arguments[
                          k
                      ] = param_config.post_process[k](v)
  
      # TODO support multiple baselines
      baseline = (
          baselines[0] if baselines and len(baselines) > 0 else None
      )
      label = (
          None
          if not self.use_label_for_attr
          or label is None
          or label.nelement() == 0
          else label
      )
      if (
          "baselines"
          in inspect.signature(attribution_method.attribute).parameters
      ):
          attribution_arguments["baselines"] = baseline
      attr = attribution_method.attribute.__wrapped__(
          attribution_method,  # self
          data,
          additional_forward_args=additional_forward_args,
          target=label,
          **attribution_arguments,
      )
  
      return attr
  
file_path: captum/captum/insights/attr_vis/attribution_calculation.py
imports: import inspect
  from collections import namedtuple
  from typing import Callable, cast, Dict, Iterable, List, Optional, Sequence, Tuple, Union
  import torch
  from captum._utils.common import _run_forward, safe_div
  from captum.insights.attr_vis.config import ATTRIBUTION_METHOD_CONFIG, ATTRIBUTION_NAMES_TO_METHODS
  from captum.insights.attr_vis.features import BaseFeature
  from torch import Tensor
  from torch.nn import Module
label_desc: Use image node_id 3 for calling the AttributionCalculation obj's underlying member method code with example usage: obj.calculate_attribution(baselines, data, additional_forward_args, label, attribution_method_name, attribution_arguments, model) and returns: attr