  Poetry generation is an interesting research topic in the field of text
generation. As one of the most valuable literary and cultural heritages of
China, Chinese classical poetry is very familiar and loved by Chinese people
from generation to generation. It has many particular characteristics in its
language structure, ranging from form, sound to meaning, thus is regarded as an
ideal testing task for text generation. In this paper, we propose a GPT-2 based
uniformed framework for generating major types of Chinese classical poems. We
define a unified format for formulating all types of training samples by
integrating detailed form information, then present a simple form-stressed
weighting method in GPT-2 to strengthen the control to the form of the
generated poems, with special emphasis on those forms with longer body length.
Preliminary experimental results show this enhanced model can generate Chinese
classical poems of major types with high quality in both form and content,
validating the effectiveness of the proposed strategy. The model has been
incorporated into Jiuge, the most influential Chinese classical poetry
generation system developed by Tsinghua University (Guo et al., 2019).
