code: def forward(self, x: Tensor) -> List[Tensor]:  # skipcq: PYL-W0221
      output_features = []
      for layer in self.encoder_layers:
          output = layer(x)
          output_features.append(output)
          x = output
      # Return only features that were requested
      return _take_tensors(output_features, self._layers)
  
imports: import math
  import warnings
  from typing import List, Union, Tuple, Iterable, Any
  import torch
  from torch import nn, Tensor
  from pytorch_toolbelt.utils.support import pytorch_toolbelt_deprecated
  from pytorch_toolbelt.modules.interfaces import HasOutputFeaturesSpecification, FeatureMapsSpecification, AbstractEncoder
label_desc: Use image node_id 2 for calling the EncoderModule obj's underlying member method code with example usage: obj.forward(x) and returns: _take_tensors