text: # coding=utf-8
  # Copyright 2022 The Google Research Authors.
  #
  # Licensed under the Apache License, Version 2.0 (the "License");
  # you may not use this file except in compliance with the License.
  # You may obtain a copy of the License at
  #
  #     http://www.apache.org/licenses/LICENSE-2.0
  #
  # Unless required by applicable law or agreed to in writing, software
  # distributed under the License is distributed on an "AS IS" BASIS,
  # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  # See the License for the specific language governing permissions and
  # limitations under the License.
  
  from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  
  import tensorflow.compat.v1 as tf
  
  
  def get_config():
    return tf.contrib.training.HParams(**{
        'total_bs': 64,
        'eval_total_bs': 16,
        'dataset_name': 'imagenet32',
        'dataset_config': tf.contrib.training.HParams(),
        'model_name': 'SlicedChannelModel',
        'model_config': tf.contrib.training.HParams(**{
            'optim': tf.contrib.training.HParams(**{
                'max_lr': 1e-4,
                'warmup': 5000,
                'grad_clip_norm': 1.0,
                'ema': 0.99995,
                'optimizer': 'adam',
                'adam_beta1': 0.9,
                'adam_beta2': 0.999,
            }),
            'dropout': 0.04,
            'img_size': 32,
            'ardec': tf.contrib.training.HParams(**{
                'emb_dim': 1536,
                'hdim_factor': 1,
                'emb_init_scale': 5.0,
                'num_heads': 16,
                'num_exterior_layers': 8,
                'num_outer_layers': 8,
                'num_inner_layers': 8,
                'res_init_scale': 1e-10,
            }),
        })
    })
  