code: def create_simclr_resnet_50(
      # Backbone
      backbone_creator: Callable = create_resnet,  # pyre-ignore[24]
      backbone_embed_dim: int = 128,
      dim_in: int = 2048,
      # Projector
      # TODO: Standardize projector conf across all SSL tasks
      mlp_activation: Callable = nn.ReLU,  # pyre-ignore[24]
      mlp_inner_dim: int = 2048,
      mlp_depth: int = 1,
      mlp_norm: Optional[Callable] = None,  # pyre-ignore[24]
  ) -> SimCLR:
      """
      Builds a Resnet video model with a projector for SimCLR
      SSL traning task.
      """
      backbone = backbone_creator(
          model_num_class=backbone_embed_dim,
          dropout_rate=0.0,
      )
      backbone.blocks[-1].proj = None
      projector = create_mlp_util(
          dim_in,
          backbone_embed_dim,
          mlp_inner_dim,
          mlp_depth,
          norm=mlp_norm,  # pyre-ignore[6]
      )
      simclr = SimCLR(
          backbone=backbone,
          projector=projector,
      )
      return simclr
  
imports: from dataclasses import dataclass
  from typing import Any, Callable, List, Optional, Union
  import torch
  import torch.nn
  import torch.nn.functional
  from hydra.core.config_store import ConfigStore
  from omegaconf import MISSING
  from pytorchvideo.models.resnet import create_resnet
  from pytorchvideo.models.weight_init import init_net_weights
  from pytorchvideo_trainer.module.byol import create_mlp_util
  from pytorchvideo_trainer.module.ssl_helper import SSLBaseModule
  from pytorchvideo_trainer.module.video_classification import Batch, BatchKey, EnsembleMethod
  from torchrecipes.core.conf import ModuleConf
  from torchrecipes.utils.config_utils import get_class_name_str
label_desc: Use image node_id 1 for calling a global function with example usage: create_simclr_resnet_50(backbone_creator, backbone_embed_dim, dim_in, mlp_activation, mlp_inner_dim, mlp_depth, mlp_norm) and returns: simclr