code: def slicenet_params1():
      """Set of hyperparameters."""
      hparams = common_hparams.basic_params1()
      hparams.batch_size = 1024
      hparams.hidden_size = 768
      hparams.dropout = 0.5
      hparams.symbol_dropout = 0.2
      hparams.label_smoothing = 0.1
      hparams.clip_grad_norm = 2.0
      hparams.num_hidden_layers = 4
      hparams.kernel_height = 3
      hparams.kernel_width = 1
      hparams.norm_type = "layer"
      hparams.learning_rate_decay_scheme = "exp"
      hparams.learning_rate = 0.05
      hparams.learning_rate_warmup_steps = 3000
      hparams.initializer_gain = 1.0
      hparams.weight_decay = 3.0
      hparams.num_sampled_classes = 0
      hparams.sampling_method = "argmax"
      hparams.optimizer_adam_epsilon = 1e-6
      hparams.optimizer_adam_beta1 = 0.85
      hparams.optimizer_adam_beta2 = 0.997
      hparams.add_hparam(
          "large_kernel_size", 15
      )  # New ones are added like this.
      hparams.add_hparam("separability", -2)
      # A dilation scheme, one of _DILATION_SCHEMES.
      hparams.add_hparam("dilation_scheme", "1.1.1.1")
      # A kernel scheme, one of _KERNEL_SCHEMES; overrides large_kernel_size.
      hparams.add_hparam("kernel_scheme", "3.7.15.31")
      hparams.add_hparam("audio_compression", 8)
      # attention-related flags
      hparams.add_hparam("attention_type", "transformer")
      hparams.add_hparam("num_heads", 8)
      hparams.add_hparam("attention_key_channels", 0)
      hparams.add_hparam("attention_value_channels", 0)
      hparams.add_hparam(
          "sim_loss_mult", 0.0
      )  # Try 10.0 for experiments.
      hparams.add_hparam("attention_dropout", 0.2)
      hparams.shared_embedding_and_softmax_weights = True
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import range
  from six.moves import zip
  from tensor2tensor.layers import common_attention
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
label_desc: Use image node_id 9 for calling a global function with example usage: slicenet_params1() and returns: hparams