docstr: Build a new model instance.
docstr_tok: ["Build","a","new","model","instance","."]
code: def build_model(cls, args, task):
      """Build a new model instance."""
      base_architecture_enconly(args)
      encoder = VGGTransformerEncoderOnly(
          vocab_size=len(task.target_dictionary),
          input_feat_per_channel=args.input_feat_per_channel,
          vggblock_config=eval(args.vggblock_enc_config),
          transformer_config=eval(args.transformer_enc_config),
          encoder_output_dim=args.enc_output_dim,
          in_channels=args.in_channels,
          transformer_context=eval(args.transformer_context),
          transformer_sampling=eval(args.transformer_sampling),
      )
      return cls(encoder)
  
imports: import argparse
  import math
  from collections.abc import Iterable
  import torch
  import torch.nn
  from examples.speech_recognition.data.data_utils import lengths_to_encoder_padding_mask
  from fairseq import utils
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqEncoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.modules import LinearizedConvolution, TransformerDecoderLayer, TransformerEncoderLayer, VGGBlock
label_desc: Use image node_id 3 for calling the VGGTransformerEncoderModel obj's underlying member method code with example usage: obj.build_model(cls, args, task) and returns: cls