set `use_gpu=True` but the debugging log shows `use_gpu=False`

annahung31 commented 7 months ago

Hi I set use_gpu=True but the debugging log shows use_gpu=False.... What should I do?

The following is my env setting:

paddlepaddle-gpu 2.5.0
paddlepaddle 2.6.1
paddleocr 2.7.2
cuda version  10.8

my code:

    ocr = PaddleOCR(use_angle_cls=True, 
                    use_gpu=True,
                    lang="ch")

debugging message:

[2024/04/12 03:27:49] ppocr DEBUG: Namespace(alpha=1.0, alphacolor=(255, 255, 255), benchmark=False, beta=1.0, binarize=False, cls_batch_num=6, cls_image_shape='3, 48, 192', cls_model_dir='/root/.paddleocr/whl/cls/ch/ch_ppocr_mobile_v2.0_cls_infer', cls_thresh=0.9, cpu_threads=10, crop_res_save_dir='./output', det=True, det_algorithm='DB', det_box_type='quad', det_db_box_thresh=0.6, det_db_score_mode='fast', det_db_thresh=0.3, det_db_unclip_ratio=1.5, det_east_cover_thresh=0.1, det_east_nms_thresh=0.2, det_east_score_thresh=0.8, det_limit_side_len=960, det_limit_type='max', det_model_dir='/root/.paddleocr/whl/det/en/ch_PP-OCRv4_det_server_infer', det_pse_box_thresh=0.85, det_pse_min_area=16, det_pse_scale=1, det_pse_thresh=0, det_sast_nms_thresh=0.2, det_sast_score_thresh=0.5, draw_img_save_dir='./inference_results', drop_score=0.5, e2e_algorithm='PGNet', e2e_char_dict_path='./ppocr/utils/ic15_dict.txt', e2e_limit_side_len=768, e2e_limit_type='max', e2e_model_dir=None, e2e_pgnet_mode='fast', e2e_pgnet_score_thresh=0.5, e2e_pgnet_valid_set='totaltext', enable_mkldnn=False, fourier_degree=5, gpu_id=0, gpu_mem=500, help='==SUPPRESS==', image_dir=None, image_orientation=False, invert=False, ir_optim=True, kie_algorithm='LayoutXLM', label_list=['0', '180'], lang='ch', layout=True, layout_dict_path=None, layout_model_dir=None, layout_nms_threshold=0.5, layout_score_threshold=0.5, max_batch_size=10, max_text_length=25, merge_no_span_structure=True, min_subgraph_size=15, mode='structure', ocr=True, ocr_order_method=None, ocr_version='PP-OCRv4', output='./output', page_num=0, precision='fp32', process_id=0, re_model_dir=None, rec=True, rec_algorithm='SVTR_LCNet', rec_batch_num=6, rec_char_dict_path='/usr/local/lib/python3.8/dist-packages/paddleocr/ppocr/utils/ppocr_keys_v1.txt', rec_image_inverse=True, rec_image_shape='3, 48, 320', rec_model_dir='/root/.paddleocr/whl/rec/en/ch_PP-OCRv4_rec_server_infer', recovery=False, save_crop_res=False, save_log_path='./log_output/', scales=[8, 16, 32], ser_dict_path='../train_data/XFUND/class_list_xfun.txt', ser_model_dir=None, show_log=True, sr_batch_num=1, sr_image_shape='3, 32, 128', sr_model_dir=None, structure_version='PP-StructureV2', table=True, table_algorithm='TableAttn', table_char_dict_path=None, table_max_len=488, table_model_dir=None, total_process_num=1, type='ocr', use_angle_cls=True, use_dilation=False, use_gpu=False, use_mp=False, use_npu=False, use_onnx=False, use_pdf2docx_api=False, use_pdserving=False, use_space_char=True, use_tensorrt=False, use_visual_backbone=True, use_xpu=False, vis_font_path='./doc/fonts/simfang.ttf', warmup=False) [2024/04/12 03:27:54] ppocr DEBUG: dt_boxes num : 49, elapsed : 3.9109363555908203 [2024/04/12 03:27:55] ppocr DEBUG: cls num : 49, elapsed : 0.08451628684997559 [2024/04/12 03:28:05] ppocr DEBUG: rec_res num : 49, elapsed : 10.290374040603638

inference time: 15.56s

UserWangZz commented 7 months ago

Check if the log output is before updating useugpu=true. During the training process, it is possible to check if the GPU memory has changed to determine whether the GPU has been used.

annahung31 commented 7 months ago

Thanks for replying. I use the check_gpu function to test directly and still found the result is False. It turns out that I didn't set up the paddlepaddle-gpu correctly so it cannot access to my GPU.

The reason is that the Cuda version is not aligned with my environment.

So instead of installing paddlepaddle-gpu via pip, I turned to use the docker image with the correct cuda version, and then it worked.