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# Licensed under the Apache License, Version 2.0 (the "License");
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"""Roformer model configurations and instantiation methods."""
import tensorflow as tf

from official.modeling import tf_utils
from official.modeling.hyperparams import base_config
from official.nlp.configs import encoders
from official.projects.roformer import roformer_encoder


class RoformerEncoderConfig(encoders.BertEncoderConfig):
  pass


@base_config.bind(RoformerEncoderConfig)
def get_encoder(encoder_cfg: RoformerEncoderConfig):
  """Gets a 'RoformerEncoder' object.

  Args:
    encoder_cfg: A 'RoformerEncoderConfig'.

  Returns:
    A encoder object.
  """
  return roformer_encoder.RoformerEncoder(
      vocab_size=encoder_cfg.vocab_size,
      hidden_size=encoder_cfg.hidden_size,
      num_layers=encoder_cfg.num_layers,
      num_attention_heads=encoder_cfg.num_attention_heads,
      intermediate_size=encoder_cfg.intermediate_size,
      activation=tf_utils.get_activation(encoder_cfg.hidden_activation),
      dropout_rate=encoder_cfg.dropout_rate,
      attention_dropout_rate=encoder_cfg.attention_dropout_rate,
      max_sequence_length=encoder_cfg.max_position_embeddings,
      type_vocab_size=encoder_cfg.type_vocab_size,
      initializer=tf.keras.initializers.TruncatedNormal(
          stddev=encoder_cfg.initializer_range),
      output_range=encoder_cfg.output_range,
      embedding_width=encoder_cfg.embedding_size,
      norm_first=encoder_cfg.norm_first)
