| import os |
| from pprint import pprint |
|
|
| import torch |
|
|
| os.environ['CUDA_VISIBLE_DEVICES'] = '1' |
| kwargs = { |
| 'per_device_train_batch_size': 4, |
| 'per_device_eval_batch_size': 4, |
| 'gradient_accumulation_steps': 4, |
| 'num_train_epochs': 1, |
| 'save_steps': 100, |
| 'max_length': 8192, |
| } |
|
|
|
|
| def calc_acc(infer_result): |
| n_correct = 0 |
| for res in infer_result: |
| if res['response'] == res['labels']: |
| n_correct += 1 |
| return f'acc: {n_correct/len(infer_result)}, n_correct: {n_correct}, len(res): {len(infer_result)}' |
|
|
|
|
| def calc_diff(infer_result, infer_result2): |
| n_correct = 0 |
| for x1, x2 in zip(infer_result, infer_result2): |
| if x1['response'] == x2['response']: |
| n_correct += 1 |
| return f'acc: {n_correct/len(infer_result)}, n_correct: {n_correct}, len(res): {len(infer_result)}' |
|
|
|
|
| def test_llm(): |
| from swift.llm import sft_main, TrainArguments, infer_main, InferArguments, Template |
| res = [] |
| for padding_side in ['left', 'right']: |
| model = 'Qwen/Qwen2.5-0.5B-Instruct' |
| dataset = ['damo/zh_cls_fudan-news#2000'] |
| result = sft_main( |
| TrainArguments(model=model, dataset=dataset, split_dataset_ratio=0.1, padding_side=padding_side, **kwargs)) |
| last_model_checkpoint = result['last_model_checkpoint'] |
| infer_result = infer_main(InferArguments(ckpt_dir=last_model_checkpoint, load_data_args=True)) |
| res.append(calc_acc(infer_result)) |
| infer_result2 = infer_main( |
| InferArguments(ckpt_dir=last_model_checkpoint, load_data_args=True, max_batch_size=16)) |
| res.append(calc_acc(infer_result2)) |
| pprint(res) |
|
|
|
|
| def test_mllm(): |
| from swift.llm import sft_main, TrainArguments, infer_main, InferArguments, Template |
| res = [] |
| for padding_side in ['left', 'right']: |
| model = 'Qwen/Qwen2-VL-2B-Instruct' |
| dataset = ['AI-ModelScope/LaTeX_OCR#2000'] |
| result = sft_main(TrainArguments(model=model, dataset=dataset, padding_side=padding_side, **kwargs)) |
| last_model_checkpoint = result['last_model_checkpoint'] |
| infer_result = infer_main(InferArguments(ckpt_dir=last_model_checkpoint, load_data_args=True)) |
| res.append(infer_result) |
| infer_result2 = infer_main( |
| InferArguments(ckpt_dir=last_model_checkpoint, load_data_args=True, max_batch_size=16)) |
| res.append(infer_result2) |
| print(calc_diff(res[0], res[1])) |
| print(calc_diff(res[2], res[3])) |
| print(calc_diff(res[0], res[2])) |
| print(calc_diff(res[0], res[3])) |
| print(calc_diff(res[2], res[1])) |
|
|
|
|
| if __name__ == '__main__': |
| test_llm() |
| test_mllm() |
|
|
