class_docstr: Flatten module attached in the model. It basically flattens the input tensor.
class_docstr_tok: ["Flatten","module","attached","in","the","model",".","It","basically","flattens","the","input","tensor","."]
docstr: flatten the input feat
code: def forward(self, feat):
      """
      flatten the input feat
      """
      return torch.flatten(feat, start_dim=self.dim)
  
imports: import logging
  import math
  import warnings
  from enum import Enum
  from typing import Dict, List, Tuple
  import torch
  import torch.distributed
  import torch.nn
  import torch.nn.functional
  from torch.nn.modules.utils import _ntuple
  from torch.utils.checkpoint import checkpoint
  from vissl.data.collators.collator_helper import MultiDimensionalTensor
  from vissl.utils.activation_checkpointing import checkpoint_trunk
  from vissl.utils.env import get_machine_local_and_dist_rank
  from vissl.utils.misc import is_apex_available
label_desc: Use image node_id 2 for calling the Flatten obj's underlying member method code with example usage: obj.forward(feat) and returns: torch