def start(num_encoder: int, num_decoder: int) -> nn.Module:
distill_config = make_config(num_encoder, num_decoder)
student_encoder_layer, student_decoder_layer = make_layer(num_encoder, num_decoder)
student = AsianBartForConditionalGeneration(distill_config)
model = make_student_model(student)
return model
def __init__(self, lang: str, device="cpu") -> None:
self.model = AsianBartForConditionalGeneration.from_pretrained(
"model_name").to(device)
self.tokenizer = AsianBartTokenizer.from_pretrained(
"hyunwoongko/asian-bart-ecjk")
if lang == "ko":
self.lang_code = "ko_KR"
elif lang == "en":
self.lang_code = "en_XX"
elif lang == "zh":
self.lang_code = "zh_XX"
else:
raise NotImplementedError(f"wrong language code : {lang}")
from itertools import combinations
from collections import OrderedDict
from typing import List
import torch.nn as nn
import json
"""
12_3
0,1,2,3,4,5,6,7,8,9,10,11 => 3, 7 ,12
To Leverage All Knowledge
"""
teacher_model = AsianBartForConditionalGeneration.from_pretrained(
"hyunwoongko/asian-bart-ecjk"
)
teacher_config = AsianBartConfig.from_pretrained(
"hyunwoongko/asian-bart-ecjk"
)
encoder_teacher_layers= [
i for i in range(teacher_config.encoder_layers)
]
decoder_teacher_layers= [
i for i in range(teacher_config.decoder_layers)
]