multigen
multigen copied to clipboard
haozheji
NotImplementedError
when i run inference code
python3 main.py \ --train_data_file ${ROOT_PATH}/data/${DATA_TYPE}/train \ --dev_data_file ${ROOT_PATH}/data/${DATA_TYPE}/dev \ --test_data_file ${ROOT_PATH}/data/${DATA_TYPE}/test \ --graph_path 2hops_100_directed_triple_filter.json \ --output_dir ${ROOT_PATH}/models/${DATA_TYPE}/grf-${DATA_TYPE} \ --source_length 32 \ --target_length 32 \ --model_type gpt2 \ --model_name_or_path ${ROOT_PATH}/models/gpt2-small \ --do_eval \ --per_gpu_train_batch_size 16 \ --per_gpu_eval_batch_size 16 \ --workers 7 \ --seed 42 \ --evaluate_metrics bleu \ --overwrite_output_dir \ --aggregate_method max \ --gamma 0.5 \
Error
[04/09/2022 21:49:57 - WARNING - root] Process rank: -1, device: cuda, n_gpu: 1, distributed training: False, 16-bits training: False
Setting 'max_len_single_sentence' is now deprecated. This value is automatically set up.
Setting 'max_len_sentences_pair' is now deprecated. This value is automatically set up.
source length: 32
[04/09/2022 21:49:58 - INFO - modeling_gpt2] Tie weights in head!!!!!
[04/09/2022 21:49:58 - INFO - modeling_gpt2] Tie weights in head!!!!!
Traceback (most recent call last):
File "main.py", line 620, in
Add these two functions to the GPT2Model class in modeling_gpt2.py:
def get_input_embeddings(self): return self.wte
def set_input_embeddings(self, new_embeddings): self.wte = new_embeddings
