def create_hparams()

in nmt/nmt.py [0:0]

• 69 lines of code
• 5 McCabe index (conditional complexity)

def create_hparams(flags):
  """Create training hparams."""
  return tf.contrib.training.HParams(
      # Data
      src=flags.src,
      tgt=flags.tgt,
      train_prefix=flags.train_prefix,
      dev_prefix=flags.dev_prefix,
      test_prefix=flags.test_prefix,
      vocab_prefix=flags.vocab_prefix,
      embed_prefix=flags.embed_prefix,
      out_dir=flags.out_dir,

      # Networks
      num_units=flags.num_units,
      num_encoder_layers=(flags.num_encoder_layers or flags.num_layers),
      num_decoder_layers=(flags.num_decoder_layers or flags.num_layers),
      dropout=flags.dropout,
      unit_type=flags.unit_type,
      encoder_type=flags.encoder_type,
      residual=flags.residual,
      time_major=flags.time_major,
      num_embeddings_partitions=flags.num_embeddings_partitions,

      # Attention mechanisms
      attention=flags.attention,
      attention_architecture=flags.attention_architecture,
      output_attention=flags.output_attention,
      pass_hidden_state=flags.pass_hidden_state,

      # Train
      optimizer=flags.optimizer,
      num_train_steps=flags.num_train_steps,
      batch_size=flags.batch_size,
      init_op=flags.init_op,
      init_weight=flags.init_weight,
      max_gradient_norm=flags.max_gradient_norm,
      learning_rate=flags.learning_rate,
      warmup_steps=flags.warmup_steps,
      warmup_scheme=flags.warmup_scheme,
      decay_scheme=flags.decay_scheme,
      colocate_gradients_with_ops=flags.colocate_gradients_with_ops,
      num_sampled_softmax=flags.num_sampled_softmax,

      # Data constraints
      num_buckets=flags.num_buckets,
      max_train=flags.max_train,
      src_max_len=flags.src_max_len,
      tgt_max_len=flags.tgt_max_len,

      # Inference
      src_max_len_infer=flags.src_max_len_infer,
      tgt_max_len_infer=flags.tgt_max_len_infer,
      infer_batch_size=flags.infer_batch_size,

      # Advanced inference arguments
      infer_mode=flags.infer_mode,
      beam_width=flags.beam_width,
      length_penalty_weight=flags.length_penalty_weight,
      coverage_penalty_weight=flags.coverage_penalty_weight,
      sampling_temperature=flags.sampling_temperature,
      num_translations_per_input=flags.num_translations_per_input,

      # Vocab
      sos=flags.sos if flags.sos else vocab_utils.SOS,
      eos=flags.eos if flags.eos else vocab_utils.EOS,
      subword_option=flags.subword_option,
      check_special_token=flags.check_special_token,
      use_char_encode=flags.use_char_encode,

      # Misc
      forget_bias=flags.forget_bias,
      num_gpus=flags.num_gpus,
      epoch_step=0,  # record where we were within an epoch.
      steps_per_stats=flags.steps_per_stats,
      steps_per_external_eval=flags.steps_per_external_eval,
      share_vocab=flags.share_vocab,
      metrics=flags.metrics.split(","),
      log_device_placement=flags.log_device_placement,
      random_seed=flags.random_seed,
      override_loaded_hparams=flags.override_loaded_hparams,
      num_keep_ckpts=flags.num_keep_ckpts,
      avg_ckpts=flags.avg_ckpts,
      language_model=flags.language_model,
      num_intra_threads=flags.num_intra_threads,
      num_inter_threads=flags.num_inter_threads,
  )