class_docstr: Tacotron2 Encoder
  
  Args:
      in_out_channels (int): number of input and output channels.
  
  Shapes:
      - input: (B, C_in, T)
      - output: (B, C_in, T)
code: def inference(self, x):
      o = x
      for layer in self.convolutions:
          o = layer(o)
      o = o.transpose(1, 2)
      # self.lstm.flatten_parameters()
      o, _ = self.lstm(o)
      return o
  
imports: import torch
  from torch import nn
  from torch.nn import functional
  from .common_layers import Prenet, Linear
  from .attentions import init_attn
label_desc: Use image node_id 3 for calling the Encoder obj's underlying member method code with example usage: obj.inference(x) and returns: o