code: def model(name):
      return registry.model(name)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import six
  from tensor2tensor.layers import modalities
  from tensor2tensor.models import basic
  from tensor2tensor.models import bytenet
  from tensor2tensor.models import distillation
  from tensor2tensor.models import evolved_transformer
  from tensor2tensor.models import image_transformer
  from tensor2tensor.models import image_transformer_2d
  from tensor2tensor.models import lstm
  from tensor2tensor.models import neural_assistant
  from tensor2tensor.models import neural_gpu
  from tensor2tensor.models import resnet
  from tensor2tensor.models import revnet
  from tensor2tensor.models import shake_shake
  from tensor2tensor.models import slicenet
  from tensor2tensor.models import text_cnn
  from tensor2tensor.models import transformer
  from tensor2tensor.models import vanilla_gan
  from tensor2tensor.models import xception
  from tensor2tensor.models.neural_architecture_search import nas_model
  from tensor2tensor.models.research import adafactor_experiments
  from tensor2tensor.models.research import aligned
  from tensor2tensor.models.research import autoencoders
  from tensor2tensor.models.research import cycle_gan
  from tensor2tensor.models.research import gene_expression
  from tensor2tensor.models.research import neural_stack
  from tensor2tensor.models.research import residual_shuffle_exchange
  from tensor2tensor.models.research import rl
  from tensor2tensor.models.research import shuffle_network
  from tensor2tensor.models.research import similarity_transformer
  from tensor2tensor.models.research import super_lm
  from tensor2tensor.models.research import transformer_moe
  from tensor2tensor.models.research import transformer_nat
  from tensor2tensor.models.research import transformer_parallel
  from tensor2tensor.models.research import transformer_revnet
  from tensor2tensor.models.research import transformer_seq2edits
  from tensor2tensor.models.research import transformer_sketch
  from tensor2tensor.models.research import transformer_symshard
  from tensor2tensor.models.research import transformer_vae
  from tensor2tensor.models.research import universal_transformer
  from tensor2tensor.models.video import basic_deterministic
  from tensor2tensor.models.video import basic_recurrent
  from tensor2tensor.models.video import basic_stochastic
  from tensor2tensor.models.video import emily
  from tensor2tensor.models.video import savp
  from tensor2tensor.models.video import sv2p
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
label_desc: Use image node_id 1 for calling a global function with example usage: model(name) and returns: registry