class_docstr: Feed Forward Transformer for TTS a.k.a. FastSpeech.
  
  This is a module of FastSpeech,
  feed-forward Transformer with duration predictor described in
  `FastSpeech: Fast, Robust and Controllable Text to Speech`_,
  which does not require any auto-regressive
  processing during inference,
  resulting in fast decoding compared with auto-regressive Transformer.
  
  .. _`FastSpeech: Fast, Robust and Controllable Text to Speech`:
      https://arxiv.org/pdf/1905.09263.pdf
class_docstr_tok: ["Feed","Forward","Transformer","for","TTS","a.k.a",".","FastSpeech",".","This","is","a","module","of","FastSpeech",",","feed-forward","Transformer","with","duration","predictor","described","in","`","FastSpeech",":","Fast",",","Robust","and","Controllable","Text","to","Speech","`","_",",","which","does","not","require","any","auto-regressive","processing","during","inference",",","resulting","in","fast","decoding","compared","with","auto-regressive","Transformer",".","..","_","`","FastSpeech",":","Fast",",","Robust","and","Controllable","Text","to","Speech","`",":","https",":","\/\/arxiv.org\/pdf\/1905.09263.pdf"]
code: def _load_teacher_model(self, model_path):
      # get teacher model config
      idim, odim, args = get_model_conf(model_path)
  
      # assert dimension is the same between teacher and studnet
      assert idim == self.idim
      assert odim == self.odim
      assert args.reduction_factor == self.reduction_factor
  
      # load teacher model
      from espnet.utils.dynamic_import import dynamic_import
  
      model_class = dynamic_import(args.model_module)
      model = model_class(idim, odim, args)
      torch_load(model_path, model)
  
      # freeze teacher model parameters
      for p in model.parameters():
          p.requires_grad = False
  
      return model
  
imports: import logging
  import torch
  import torch.nn.functional
  from espnet.asr.asr_utils import get_model_conf, torch_load
  from espnet.nets.pytorch_backend.fastspeech.duration_calculator import DurationCalculator
  from espnet.nets.pytorch_backend.fastspeech.duration_predictor import DurationPredictor, DurationPredictorLoss
  from espnet.nets.pytorch_backend.fastspeech.length_regulator import LengthRegulator
  from espnet.nets.pytorch_backend.nets_utils import make_non_pad_mask, make_pad_mask
  from espnet.nets.pytorch_backend.tacotron2.decoder import Postnet
  from espnet.nets.pytorch_backend.transformer.attention import MultiHeadedAttention
  from espnet.nets.pytorch_backend.transformer.embedding import PositionalEncoding, ScaledPositionalEncoding
  from espnet.nets.pytorch_backend.transformer.encoder import Encoder
  from espnet.nets.pytorch_backend.transformer.initializer import initialize
  from espnet.nets.tts_interface import TTSInterface
  from espnet.utils.cli_utils import strtobool
  from espnet.utils.fill_missing_args import fill_missing_args
label_desc: Use image node_id 9 for calling the FeedForwardTransformer obj's underlying member method code with example usage: obj._load_teacher_model(model_path) and returns: model