code: def forward(self, x, lens):
      if self.reduction_factor > 1:
          # borisf: here, float() instead of to(x.dtype) to work arounf ONNX exporter bug
          mask = get_mask_from_lengths(lens, x).unsqueeze(1).float()
          x = self.projection_fn(x, mask)
          if self.non_linearity == "relu":
              x = F.relu(x)
          elif self.non_linearity == "leakyrelu":
              x = F.leaky_relu(x)
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from nemo.collections.tts.modules.common import ConvLSTMLinear
  from nemo.collections.tts.modules.submodules import ConvNorm, MaskedInstanceNorm1d
  from nemo.collections.tts.modules.transformer import FFTransformer
  from nemo.collections.tts.parts.utils.helpers import get_mask_from_lengths
label_desc: Use image node_id 2 for calling the BottleneckLayerLayer obj's underlying member method code with example usage: obj.forward(x, lens) and returns: x