class_docstr: Provider of a collection of data loaders for a given collection of datasets.
class_docstr_tok: ["Provider","of","a","collection","of","data","loaders","for","a","given","collection","of","datasets","."]
docstr: Returns a collection of data loaders for a given collection of datasets.
docstr_tok: ["Returns","a","collection","of","data","loaders","for","a","given","collection","of","datasets","."]
code: def get_data_loader_map(self, datasets: DatasetMap) -> DataLoaderMap:
      """
      Returns a collection of data loaders for a given collection of datasets.
      """
      raise NotImplementedError()
  
imports: from dataclasses import dataclass
  from enum import Enum
  from typing import Iterator, List, Optional, Tuple
  import torch
  from pytorch3d.implicitron.tools.config import registry, ReplaceableBase
  from torch.utils.data import BatchSampler, ConcatDataset, DataLoader, RandomSampler, Sampler
  from .dataset_base import DatasetBase
  from .dataset_map_provider import DatasetMap
  from .frame_data import FrameData
  from .scene_batch_sampler import SceneBatchSampler
  from .utils import is_known_frame_scalar
label_desc: Use image node_id 1 for calling the DataLoaderMapProviderBase obj's underlying member method code with example usage: obj.get_data_loader_map(datasets) without return types