docstr: Remove a transform if within list_transform_class
  
  Arguments:
      transform_in {[type]} -- [Compose | List of transform]
      list_transform_class {[type]} -- [List of transform class to be removed]
  
  Returns:
      [type] -- [description]
docstr_tok: ["Remove","a","transform","if","within","list_transform_class","Arguments",":","transform_in","{","[","type","]","}","--","[","Compose","|","List","of","transform","]","list_transform_class","{","[","type","]","}","--","[","List","of","transform","class","to","be","removed","]","Returns",":","[","type","]","--","[","description","]"]
code: def remove_transform(transform_in, list_transform_class):
      """Remove a transform if within list_transform_class
  
      Arguments:
          transform_in {[type]} -- [Compose | List of transform]
          list_transform_class {[type]} -- [List of transform class to be removed]
  
      Returns:
          [type] -- [description]
      """
      if isinstance(transform_in, Compose) or isinstance(
          transform_in, list
      ):
          if len(list_transform_class) > 0:
              transform_out = []
              transforms = (
                  transform_in.transforms
                  if isinstance(transform_in, Compose)
                  else transform_in
              )
              for t in transforms:
                  if not isinstance(t, tuple(list_transform_class)):
                      transform_out.append(t)
              transform_out = Compose(transform_out)
      else:
          transform_out = transform_in
      return transform_out
  
imports: import os
  from abc import ABC, abstractmethod
  import logging
  import functools
  from functools import partial
  import numpy
  import torch
  import torch_geometric
  from torch_geometric.transforms import Compose, FixedPoints
  import copy
  from torch_points3d.models import model_interface
  from torch_points3d.core.data_transform import instantiate_transforms, MultiScaleTransform
  from torch_points3d.core.data_transform import instantiate_filters
  from torch_points3d.datasets.batch import SimpleBatch
  from torch_points3d.datasets.multiscale_data import MultiScaleBatch
  from torch_points3d.utils.enums import ConvolutionFormat
  from torch_points3d.utils.config import ConvolutionFormatFactory
  from torch_points3d.utils.colors import COLORS, colored_print
label_desc: Use image node_id 2 for calling the BaseDataset obj's underlying member method code with example usage: obj.remove_transform(transform_in, list_transform_class) and returns: transform_out