#!/usr/bin/env python
# coding=utf-8
# Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.

from transformers.configuration_utils import PretrainedConfig

CODESAGE_PRETRAINED_CONFIG_ARCHIVE_MAP = {
    "SageLite/SageLite-s": "https://huggingface.co/SageLite/SageLite-s/resolve/main/config.json",
    "SageLite/SageLite-l": "https://huggingface.co/SageLite/SageLite-l/resolve/main/config.json",
}


class SageLiteConfig(PretrainedConfig):
    model_type = "SageLite"

    def __init__(
            self,
            vocab_size=100318,
            max_position_embeddings=2048,
            hidden_size=1536,
            num_hidden_layers=24,
            num_attention_heads=12,
            intermediate_size=6144,
            activation_function="gelu_new",
            residual_dropout_prob=0.1,
            embedding_dropout_prob=0.1,
            attention_dropout_prob=0.1,
            layer_norm_epsilon=1e-5,
            initializer_range=0.02,
            position_embedding_type='absolute',
            bos_token_id=100257,
            eos_token_id=100257,
            pad_token_id=100317,
            **kwargs
    ):
        self.vocab_size = vocab_size
        self.max_position_embeddings = max_position_embeddings
        self.hidden_size = hidden_size
        self.num_hidden_layers = num_hidden_layers
        self.num_attention_heads = num_attention_heads
        self.intermediate_size = intermediate_size
        assert 'gelu' in activation_function
        self.activation_function = activation_function
        self.residual_dropout_prob = residual_dropout_prob
        self.embedding_dropout_prob = embedding_dropout_prob
        self.attention_dropout_prob = attention_dropout_prob
        self.layer_norm_epsilon = layer_norm_epsilon
        self.initializer_range = initializer_range
        self.position_embedding_type = position_embedding_type

        super().__init__(pad_token_id=pad_token_id, bos_token_id=bos_token_id, eos_token_id=eos_token_id, **kwargs)