class_docstr: Args:
code: def forward_features(self, input_x, no_reshape=False):
      if not no_reshape:
          sample_len = (
              3 if self.modality == "RGB" else 2
          ) * self.new_length
  
          if self.modality == "RGBDiff":
              sample_len = 3 * self.new_length
              input_x = self._get_diff(input_x)
  
          base_out = self.base_model(
              input_x.view((-1, sample_len) + input_x.size()[-2:])
          )
      else:
          base_out = self.base_model(input_x)
      return base_out
  
imports: import torch
  from torch import nn
  from torch.nn.init import normal_, constant_
  import numpy
  import torchvision
  from towhee.models.utils.basic_ops import ConsensusModule
  from towhee.models.layers.non_local import make_non_local
  from towhee.models.tsm.mobilenet_v2 import mobilenet_v2, InvertedResidual
  from towhee.models.tsm.temporal_shift import TemporalShift, make_temporal_shift
  from towhee.models.tsm.config import _C
label_desc: Use image node_id 7 for calling the TSN obj's underlying member method code with example usage: obj.forward_features(input_x, no_reshape) and returns: base_out