docstr: Creates the data loaders. Must be called in order to complete the setup of the Dataset
          
docstr_tok: ["Creates","the","data","loaders",".","Must","be","called","in","order","to","complete","the","setup","of","the","Dataset"]
code: def create_dataloaders(
      self,
      model: model_interface.DatasetInterface,
      batch_size: int,
      shuffle: bool,
      num_workers: int,
      precompute_multi_scale: bool,
  ):
      """Creates the data loaders. Must be called in order to complete the setup of the Dataset"""
      conv_type = model.conv_type
      self._batch_size = batch_size
  
      if self.train_sampler:
          log.info(self.train_sampler)
  
      if self.train_dataset:
          self._train_loader = self._dataloader(
              self.train_dataset,
              self.train_pre_batch_collate_transform,
              conv_type,
              precompute_multi_scale,
              batch_size=batch_size,
              shuffle=shuffle and not self.train_sampler,
              num_workers=num_workers,
              sampler=self.train_sampler,
          )
  
      if self.test_dataset:
          self._test_loaders = [
              self._dataloader(
                  dataset,
                  self.test_pre_batch_collate_transform,
                  conv_type,
                  precompute_multi_scale,
                  batch_size=batch_size,
                  shuffle=False,
                  num_workers=num_workers,
                  sampler=self.test_sampler,
              )
              for dataset in self.test_dataset
          ]
  
      if self.val_dataset:
          self._val_loader = self._dataloader(
              self.val_dataset,
              self.val_pre_batch_collate_transform,
              conv_type,
              precompute_multi_scale,
              batch_size=batch_size,
              shuffle=False,
              num_workers=num_workers,
              sampler=self.val_sampler,
          )
  
      if precompute_multi_scale:
          self.set_strategies(model)
  
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 9 for calling the BaseDataset obj's underlying member method code with example usage: obj.create_dataloaders(model, batch_size, shuffle, num_workers, precompute_multi_scale) without return types