class_docstr: Speech-to-text alignment model (https://arxiv.org/pdf/2108.10447.pdf) that is used to learn alignments between mel spectrogram and text.
class_docstr_tok: ["Speech-to-text","alignment","model","(","https",":","\/\/arxiv.org\/pdf\/2108.10447.pdf",")","that","is","used","to","learn","alignments","between","mel","spectrogram","and","text","."]
code: def setup_validation_data(self, cfg):
      self._validation_dl = self._loader(cfg)
  
imports: from typing import List
  import numpy
  import omegaconf
  import torch
  from hydra.utils import instantiate
  from omegaconf import DictConfig
  from pytorch_lightning import Trainer
  from pytorch_lightning.loggers import WandbLogger
  from torch import nn
  from nemo.collections.tts.losses.aligner_loss import BinLoss, ForwardSumLoss
  from nemo.collections.tts.parts.utils.helpers import binarize_attention, g2p_backward_compatible_support, get_mask_from_lengths, plot_alignment_to_numpy
  from nemo.core.classes import ModelPT
  from nemo.core.classes.common import PretrainedModelInfo
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 11 for calling the AlignerModel obj's underlying member method code with example usage: obj.setup_validation_data(cfg) without return types