#!/usr/bin/env python
# -*- coding: utf-8 -*-

from transformers.configuration_utils import PretrainedConfig


class TAASConfig(PretrainedConfig):
    model_type = "TAAS"

    def __init__(
        self,
        hidd_dropout=0.1,
        intermediate_size=3072,
        initialize_range=0.02,
        max_pos_embeddings=2048,
        hidd_act="gelu",
        attention_dropout=0.1,
        using_task_id=True,
        vocabulary_size=40000,
        hidd_size=768,
        num_hidd_layers=12,
        layer_norm_rate=1e-05,
        num_atten_heads=12,
        pad_token_id=0,
        task_vocab_size=3,
        classifier_drop=None,
        pos_embedding="absolute",
        use_cache=True,
        vocab_size=4,
        **kwargs
    ):
        super().__init__(pad_token_id=pad_token_id, **kwargs)

        self.vocab_size = vocabulary_size
        self.max_position_embeddings = max_pos_embeddings
        self.type_vocab_size = vocab_size
        self.use_task_id = using_task_id
        self.layer_norm_eps = layer_norm_rate
        self.position_embedding_type = pos_embedding
        self.num_attention_heads = num_atten_heads
        self.hidden_size = hidd_size
        self.attention_probs_dropout_prob = attention_dropout
        self.initializer_range = initialize_range
        self.hidden_act = hidd_act
        self.intermediate_size = intermediate_size
        self.hidden_dropout_prob = hidd_dropout
        self.use_cache = use_cache
        self.classifier_dropout = classifier_drop
        self.num_hidden_layers = num_hidd_layers
        self.task_type_vocab_size = task_vocab_size