code: def maxpool1d(
      module: Module,
      inputs: Tensor,
      outputs: Tensor,
      grad_input: Tensor,
      grad_output: Tensor,
      eps: float = 1e-10,
  ):
      return maxpool(
          module,
          F.max_pool1d,
          F.max_unpool1d,
          inputs,
          outputs,
          grad_input,
          grad_output,
          eps=eps,
      )
  
imports: import typing
  import warnings
  from typing import Any, Callable, List, Tuple, Union, cast
  import numpy
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from torch.nn import Module
  from torch.utils.hooks import RemovableHandle
  from captum.attr._utils.attribution import GradientAttribution
  from captum.attr._utils.common import ExpansionTypes, _call_custom_attribution_func, _compute_conv_delta_and_format_attrs, _expand_additional_forward_args, _expand_target, _format_additional_forward_args, _format_attributions, _format_baseline, _format_callable_baseline, _format_input, _format_tensor_into_tuples, _is_tuple, _run_forward, _tensorize_baseline, _validate_input
  from captum.attr._utils.gradient import apply_gradient_requirements, undo_gradient_requirements
  from captum.attr._utils.typing import BaselineType, Literal, TargetType, TensorOrTupleOfTensorsGeneric
label_desc: Use image node_id 4 for calling a global function with example usage: maxpool1d(module, inputs, outputs, grad_input, grad_output, eps) and returns: maxpool