# batch_size_per_card: 1024 batch_size_per_card: 256 drop_last: True num_workers: 4Eval: dataset: name: SimpleDataSet data_dir: /home/aistudio/data/data128403/TAL_OCR_ENG手写英文数据集/data_composition label_file_list: ["/home/aistudio/data/data128403/TAL_OCR_ENG手写英文数据集/test.tx...
即test_batch_size_per_card=1 A:测试的时候,对图像等比例缩放,最长边960,不同图像等比例缩放后长宽不一致,无法组成batch,所以设置为test_batch_size为1。 Q3.4.5:为什么使用c++ inference和python inference结果不一致? A:可能是导出的inference model版本与预测库版本需要保持一致,比如在Windows下,Paddle官网提供...
drop_last: False batch_size_per_card: 1 # must be 1 num_workers: 2 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32. 33. 34. 35. 36. 37. 38. 39. 40. 41. 42. 43. 44...
shuffle: true batch_size_per_card: 128 drop_last: true num_workers: 4 Eval: dataset: name: SimpleDataSet data_dir: /home/aistudio/data label_file_list: - /home/aistudio/data/dev.txt transforms: - DecodeImage: img_mode: BGR channel_first: false - MultiLabelEncode: - RecResizeImg: ima...
[2021/09/15 17:35:06] root INFO: batch_size_per_card : 16[2021/09/15 17:35:06] root INFO: drop_last : False[2021/09/15 17:35:06] root INFO: num_workers : 8[2021/09/15 17:35:06] root INFO: shuffle : True[2021/09/15 17:35:06] root INFO: use_shared_memory : False...
False - CTCLabelEncode: # Class handling label - RecResizeImg: image_shape: [3, 32, 100] - KeepKeys: keep_keys: ['image', 'label', 'length'] # dataloader will return list in this order loader: shuffle: False drop_last: False batch_size_per_card: 256 num_workers: 4 use_shared_...
mean: [0.485, 0.456, 0.406] std: [0.229, 0.224, 0.225] order: 'hwc' - PaddingTableImage: - ToCHWImage: - KeepKeys: keep_keys: ['image', 'structure', 'bbox_list', 'sp_tokens', 'bbox_list_mask'] loader: shuffle: False drop_last: False batch_size_per_card: 16 num_workers: ...
'eval_batch_step': 500, 'train_batch_size_per_card': 256, 'test_batch_size_per_card': 256, 'image_shape': [3, 32, 320], 'max_text_length': 8, 'character_type': 'ch', 'character_dict_path': '../word_dict.txt', 'loss_type': 'attention', 'tps': True, 'reader_yml':...
['image', 'label', 'length'] # dataloader will return list in this orderloader:shuffle: Truebatch_size_per_card: 256drop_last: Truenum_workers: 8use_shared_memory: FalseEval:dataset:name: SimpleDataSet# 评估数据根目录data_dir: ./train_data/ic15_data# 评估数据标签label_file_list: ["....
1、Windows上这边用paddlepaddle-gpu==2.2.2没问题,可以跑(上面已经说了) 2、ValueError: all input arrays must have the same shape 这个问题也解决了,Eval.loader.batch_size_per_card设置成1就行(上面也说过了) 3、Windows下显卡跑不满Train.loader.num_workers只能设置成0(不能使用子线程),速度会慢很多,...