code: def get_asymtric_padding(
      kernel_size, stride, dilation, future_context
  ):
      if stride > 1 and dilation > 1:
          raise ValueError(
              "Only stride OR dilation may be greater than 1"
          )
  
      left_context = kernel_size - 1 - future_context
      right_context = future_context
  
      symmetric_padding = get_same_padding(
          kernel_size, stride, dilation
      )
  
      if kernel_size <= future_context:
          # kernel size is smaller than future context, equivalent to using entire context of kernel
          # simply return symmetric padding for this scenario
          logging.warning(
              f"Future context window is larger than the kernel size!\n"
              f"Left context = {left_context} | Right context = greater than {right_context} | "
              f"Kernel size = {kernel_size}\n"
              f"Switching to symmetric padding (left context = right context = {symmetric_padding})"
          )
          return symmetric_padding
  
      if left_context < symmetric_padding:
          logging.warning(
              f"Future context window is larger than half the kernel size!\n"
              f"Conv layer therefore uses more future information than past to compute its output!\n"
              f"Left context = {left_context} | Right context = {right_context} | "
              f"Kernel size = {kernel_size}"
          )
  
      if dilation > 1:
          left_context = (
              dilation * kernel_size - 1 - dilation * future_context
          )
          right_context = dilation * future_context
          return (left_context, right_context)
  
      return (left_context, right_context)
  
imports: import math
  from typing import Callable, Iterable, List, Optional, Tuple
  import torch
  import torch.nn
  import torch.nn.functional
  from torch import Tensor
  from torch.nn.init import _calculate_correct_fan
  from torch.nn.modules.utils import _single
  from nemo.collections.common.parts.utils import activation_registry
  from nemo.core.classes.mixins import AccessMixin
  from nemo.core.classes.mixins.adapter_mixins import AdapterModuleMixin
  from nemo.utils import logging
label_desc: Use image node_id 6 for calling a global function with example usage: get_asymtric_padding(kernel_size, stride, dilation, future_context) and returns: left_context,  right_context, symmetric_padding, left_context,  right_context