Open MeteoriteWeny opened 2 years ago
grimoire
commented
2 years ago The SABL model conversion succeeded on my device with master branch of mmdetection. And my environment is a little bit different from yours, with CUDA==11.3 and TensorRT ==8.2.3
MeteoriteWeny
commented
2 years ago The SABL model conversion succeeded on my device with master branch of mmdetection. And my environment is a little bit different from yours, with CUDA==11.3 and TensorRT ==8.2.3
Thanks for your reply. My another conversion for YOLOX seemed to succeeded, but the converted inference model seems not working. Do I need to downgrade the TensorRT 8.4 ea to an earlier version?
(tensorrt) root@P775TM1:/home/mmdetection-2.19.1# mmdet2trt --min-scale 1 3 640 640 --opt-scale 1 3 640 640 --max-scale 1 3 640 640 ../mmdetection-2.19.1/work_dirs/yolox_l_8x8_300e_coco_cloth.py ../mmdetection-2.19.1/work_dirs/yolox_l_8x8_300e_coco_cloth/best_bbox_mAP_epoch_300.pth ../mmdetection-2.19.1/work_dirs/yolox_l_8x8_300e_coco_cloth/yolox_l_8x8_300e_coco_cloth.trt
Use load_from_local loader
The model and loaded state dict do not match exactly
unexpected key in source state_dict: ema_backbone_stem_conv_conv_weight, ema_backbone_stem_conv_bn_weight, ema_backbone_stem_conv_bn_bias, ema_backbone_stem_conv_bn_running_mean, ema_backbone_stem_conv_bn_running_var, ema_backbone_stem_conv_bn_num_batches_tracked, ema_backbone_stage1_0_conv_weight, ema_backbone_stage1_0_bn_weight, ema_backbone_stage1_0_bn_bias, ema_backbone_stage1_0_bn_running_mean, ema_backbone_stage1_0_bn_running_var, ema_backbone_stage1_0_bn_num_batches_tracked, ema_backbone_stage1_1_main_conv_conv_weight, ema_backbone_stage1_1_main_conv_bn_weight, ema_backbone_stage1_1_main_conv_bn_bias, ema_backbone_stage1_1_main_conv_bn_running_mean, ema_backbone_stage1_1_main_conv_bn_running_var, ema_backbone_stage1_1_main_conv_bn_num_batches_tracked, ema_backbone_stage1_1_short_conv_conv_weight, ema_backbone_stage1_1_short_conv_bn_weight, ema_backbone_stage1_1_short_conv_bn_bias, ema_backbone_stage1_1_short_conv_bn_running_mean, ema_backbone_stage1_1_short_conv_bn_running_var, ema_backbone_stage1_1_short_conv_bn_num_batches_tracked, ema_backbone_stage1_1_final_conv_conv_weight, ema_backbone_stage1_1_final_conv_bn_weight, ema_backbone_stage1_1_final_conv_bn_bias, ema_backbone_stage1_1_final_conv_bn_running_mean, ema_backbone_stage1_1_final_conv_bn_running_var, ema_backbone_stage1_1_final_conv_bn_num_batches_tracked, ema_backbone_stage1_1_blocks_0_conv1_conv_weight, ema_backbone_stage1_1_blocks_0_conv1_bn_weight, ema_backbone_stage1_1_blocks_0_conv1_bn_bias, ema_backbone_stage1_1_blocks_0_conv1_bn_running_mean, ema_backbone_stage1_1_blocks_0_conv1_bn_running_var, ema_backbone_stage1_1_blocks_0_conv1_bn_num_batches_tracked, ema_backbone_stage1_1_blocks_0_conv2_conv_weight, ema_backbone_stage1_1_blocks_0_conv2_bn_weight, ema_backbone_stage1_1_blocks_0_conv2_bn_bias, ema_backbone_stage1_1_blocks_0_conv2_bn_running_mean, ema_backbone_stage1_1_blocks_0_conv2_bn_running_var, ema_backbone_stage1_1_blocks_0_conv2_bn_num_batches_tracked, ema_backbone_stage1_1_blocks_1_conv1_conv_weight, ema_backbone_stage1_1_blocks_1_conv1_bn_weight, ema_backbone_stage1_1_blocks_1_conv1_bn_bias, ema_backbone_stage1_1_blocks_1_conv1_bn_running_mean, ema_backbone_stage1_1_blocks_1_conv1_bn_running_var, ema_backbone_stage1_1_blocks_1_conv1_bn_num_batches_tracked, ema_backbone_stage1_1_blocks_1_conv2_conv_weight, ema_backbone_stage1_1_blocks_1_conv2_bn_weight, ema_backbone_stage1_1_blocks_1_conv2_bn_bias, ema_backbone_stage1_1_blocks_1_conv2_bn_running_mean, ema_backbone_stage1_1_blocks_1_conv2_bn_running_var, ema_backbone_stage1_1_blocks_1_conv2_bn_num_batches_tracked, ema_backbone_stage1_1_blocks_2_conv1_conv_weight, ema_backbone_stage1_1_blocks_2_conv1_bn_weight, ema_backbone_stage1_1_blocks_2_conv1_bn_bias, ema_backbone_stage1_1_blocks_2_conv1_bn_running_mean, ema_backbone_stage1_1_blocks_2_conv1_bn_running_var, ema_backbone_stage1_1_blocks_2_conv1_bn_num_batches_tracked, ema_backbone_stage1_1_blocks_2_conv2_conv_weight, ema_backbone_stage1_1_blocks_2_conv2_bn_weight, ema_backbone_stage1_1_blocks_2_conv2_bn_bias, ema_backbone_stage1_1_blocks_2_conv2_bn_running_mean, ema_backbone_stage1_1_blocks_2_conv2_bn_running_var, ema_backbone_stage1_1_blocks_2_conv2_bn_num_batches_tracked, ema_backbone_stage2_0_conv_weight, ema_backbone_stage2_0_bn_weight, ema_backbone_stage2_0_bn_bias, ema_backbone_stage2_0_bn_running_mean, ema_backbone_stage2_0_bn_running_var, ema_backbone_stage2_0_bn_num_batches_tracked, ema_backbone_stage2_1_main_conv_conv_weight, ema_backbone_stage2_1_main_conv_bn_weight, ema_backbone_stage2_1_main_conv_bn_bias, ema_backbone_stage2_1_main_conv_bn_running_mean, ema_backbone_stage2_1_main_conv_bn_running_var, ema_backbone_stage2_1_main_conv_bn_num_batches_tracked, ema_backbone_stage2_1_short_conv_conv_weight, ema_backbone_stage2_1_short_conv_bn_weight, ema_backbone_stage2_1_short_conv_bn_bias, ema_backbone_stage2_1_short_conv_bn_running_mean, ema_backbone_stage2_1_short_conv_bn_running_var, ema_backbone_stage2_1_short_conv_bn_num_batches_tracked, ema_backbone_stage2_1_final_conv_conv_weight, ema_backbone_stage2_1_final_conv_bn_weight, ema_backbone_stage2_1_final_conv_bn_bias, ema_backbone_stage2_1_final_conv_bn_running_mean, ema_backbone_stage2_1_final_conv_bn_running_var, ema_backbone_stage2_1_final_conv_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_0_conv1_conv_weight, ema_backbone_stage2_1_blocks_0_conv1_bn_weight, ema_backbone_stage2_1_blocks_0_conv1_bn_bias, ema_backbone_stage2_1_blocks_0_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_0_conv1_bn_running_var, ema_backbone_stage2_1_blocks_0_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_0_conv2_conv_weight, ema_backbone_stage2_1_blocks_0_conv2_bn_weight, ema_backbone_stage2_1_blocks_0_conv2_bn_bias, ema_backbone_stage2_1_blocks_0_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_0_conv2_bn_running_var, ema_backbone_stage2_1_blocks_0_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_1_conv1_conv_weight, ema_backbone_stage2_1_blocks_1_conv1_bn_weight, ema_backbone_stage2_1_blocks_1_conv1_bn_bias, ema_backbone_stage2_1_blocks_1_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_1_conv1_bn_running_var, ema_backbone_stage2_1_blocks_1_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_1_conv2_conv_weight, ema_backbone_stage2_1_blocks_1_conv2_bn_weight, ema_backbone_stage2_1_blocks_1_conv2_bn_bias, ema_backbone_stage2_1_blocks_1_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_1_conv2_bn_running_var, ema_backbone_stage2_1_blocks_1_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_2_conv1_conv_weight, ema_backbone_stage2_1_blocks_2_conv1_bn_weight, ema_backbone_stage2_1_blocks_2_conv1_bn_bias, ema_backbone_stage2_1_blocks_2_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_2_conv1_bn_running_var, ema_backbone_stage2_1_blocks_2_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_2_conv2_conv_weight, ema_backbone_stage2_1_blocks_2_conv2_bn_weight, ema_backbone_stage2_1_blocks_2_conv2_bn_bias, ema_backbone_stage2_1_blocks_2_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_2_conv2_bn_running_var, ema_backbone_stage2_1_blocks_2_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_3_conv1_conv_weight, ema_backbone_stage2_1_blocks_3_conv1_bn_weight, ema_backbone_stage2_1_blocks_3_conv1_bn_bias, ema_backbone_stage2_1_blocks_3_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_3_conv1_bn_running_var, ema_backbone_stage2_1_blocks_3_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_3_conv2_conv_weight, ema_backbone_stage2_1_blocks_3_conv2_bn_weight, ema_backbone_stage2_1_blocks_3_conv2_bn_bias, ema_backbone_stage2_1_blocks_3_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_3_conv2_bn_running_var, ema_backbone_stage2_1_blocks_3_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_4_conv1_conv_weight, ema_backbone_stage2_1_blocks_4_conv1_bn_weight, ema_backbone_stage2_1_blocks_4_conv1_bn_bias, ema_backbone_stage2_1_blocks_4_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_4_conv1_bn_running_var, ema_backbone_stage2_1_blocks_4_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_4_conv2_conv_weight, ema_backbone_stage2_1_blocks_4_conv2_bn_weight, ema_backbone_stage2_1_blocks_4_conv2_bn_bias, ema_backbone_stage2_1_blocks_4_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_4_conv2_bn_running_var, ema_backbone_stage2_1_blocks_4_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_5_conv1_conv_weight, ema_backbone_stage2_1_blocks_5_conv1_bn_weight, ema_backbone_stage2_1_blocks_5_conv1_bn_bias, ema_backbone_stage2_1_blocks_5_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_5_conv1_bn_running_var, ema_backbone_stage2_1_blocks_5_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_5_conv2_conv_weight, ema_backbone_stage2_1_blocks_5_conv2_bn_weight, ema_backbone_stage2_1_blocks_5_conv2_bn_bias, ema_backbone_stage2_1_blocks_5_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_5_conv2_bn_running_var, ema_backbone_stage2_1_blocks_5_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_6_conv1_conv_weight, ema_backbone_stage2_1_blocks_6_conv1_bn_weight, ema_backbone_stage2_1_blocks_6_conv1_bn_bias, ema_backbone_stage2_1_blocks_6_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_6_conv1_bn_running_var, ema_backbone_stage2_1_blocks_6_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_6_conv2_conv_weight, ema_backbone_stage2_1_blocks_6_conv2_bn_weight, ema_backbone_stage2_1_blocks_6_conv2_bn_bias, ema_backbone_stage2_1_blocks_6_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_6_conv2_bn_running_var, ema_backbone_stage2_1_blocks_6_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_7_conv1_conv_weight, ema_backbone_stage2_1_blocks_7_conv1_bn_weight, ema_backbone_stage2_1_blocks_7_conv1_bn_bias, ema_backbone_stage2_1_blocks_7_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_7_conv1_bn_running_var, ema_backbone_stage2_1_blocks_7_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_7_conv2_conv_weight, ema_backbone_stage2_1_blocks_7_conv2_bn_weight, ema_backbone_stage2_1_blocks_7_conv2_bn_bias, ema_backbone_stage2_1_blocks_7_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_7_conv2_bn_running_var, ema_backbone_stage2_1_blocks_7_conv2_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_8_conv1_conv_weight, ema_backbone_stage2_1_blocks_8_conv1_bn_weight, ema_backbone_stage2_1_blocks_8_conv1_bn_bias, ema_backbone_stage2_1_blocks_8_conv1_bn_running_mean, ema_backbone_stage2_1_blocks_8_conv1_bn_running_var, ema_backbone_stage2_1_blocks_8_conv1_bn_num_batches_tracked, ema_backbone_stage2_1_blocks_8_conv2_conv_weight, ema_backbone_stage2_1_blocks_8_conv2_bn_weight, ema_backbone_stage2_1_blocks_8_conv2_bn_bias, ema_backbone_stage2_1_blocks_8_conv2_bn_running_mean, ema_backbone_stage2_1_blocks_8_conv2_bn_running_var, ema_backbone_stage2_1_blocks_8_conv2_bn_num_batches_tracked, ema_backbone_stage3_0_conv_weight, ema_backbone_stage3_0_bn_weight, ema_backbone_stage3_0_bn_bias, ema_backbone_stage3_0_bn_running_mean, ema_backbone_stage3_0_bn_running_var, ema_backbone_stage3_0_bn_num_batches_tracked, ema_backbone_stage3_1_main_conv_conv_weight, ema_backbone_stage3_1_main_conv_bn_weight, ema_backbone_stage3_1_main_conv_bn_bias, ema_backbone_stage3_1_main_conv_bn_running_mean, ema_backbone_stage3_1_main_conv_bn_running_var, ema_backbone_stage3_1_main_conv_bn_num_batches_tracked, ema_backbone_stage3_1_short_conv_conv_weight, ema_backbone_stage3_1_short_conv_bn_weight, ema_backbone_stage3_1_short_conv_bn_bias, ema_backbone_stage3_1_short_conv_bn_running_mean, ema_backbone_stage3_1_short_conv_bn_running_var, ema_backbone_stage3_1_short_conv_bn_num_batches_tracked, ema_backbone_stage3_1_final_conv_conv_weight, ema_backbone_stage3_1_final_conv_bn_weight, ema_backbone_stage3_1_final_conv_bn_bias, ema_backbone_stage3_1_final_conv_bn_running_mean, ema_backbone_stage3_1_final_conv_bn_running_var, ema_backbone_stage3_1_final_conv_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_0_conv1_conv_weight, ema_backbone_stage3_1_blocks_0_conv1_bn_weight, ema_backbone_stage3_1_blocks_0_conv1_bn_bias, ema_backbone_stage3_1_blocks_0_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_0_conv1_bn_running_var, ema_backbone_stage3_1_blocks_0_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_0_conv2_conv_weight, ema_backbone_stage3_1_blocks_0_conv2_bn_weight, ema_backbone_stage3_1_blocks_0_conv2_bn_bias, ema_backbone_stage3_1_blocks_0_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_0_conv2_bn_running_var, ema_backbone_stage3_1_blocks_0_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_1_conv1_conv_weight, ema_backbone_stage3_1_blocks_1_conv1_bn_weight, ema_backbone_stage3_1_blocks_1_conv1_bn_bias, ema_backbone_stage3_1_blocks_1_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_1_conv1_bn_running_var, ema_backbone_stage3_1_blocks_1_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_1_conv2_conv_weight, ema_backbone_stage3_1_blocks_1_conv2_bn_weight, ema_backbone_stage3_1_blocks_1_conv2_bn_bias, ema_backbone_stage3_1_blocks_1_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_1_conv2_bn_running_var, ema_backbone_stage3_1_blocks_1_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_2_conv1_conv_weight, ema_backbone_stage3_1_blocks_2_conv1_bn_weight, ema_backbone_stage3_1_blocks_2_conv1_bn_bias, ema_backbone_stage3_1_blocks_2_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_2_conv1_bn_running_var, ema_backbone_stage3_1_blocks_2_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_2_conv2_conv_weight, ema_backbone_stage3_1_blocks_2_conv2_bn_weight, ema_backbone_stage3_1_blocks_2_conv2_bn_bias, ema_backbone_stage3_1_blocks_2_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_2_conv2_bn_running_var, ema_backbone_stage3_1_blocks_2_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_3_conv1_conv_weight, ema_backbone_stage3_1_blocks_3_conv1_bn_weight, ema_backbone_stage3_1_blocks_3_conv1_bn_bias, ema_backbone_stage3_1_blocks_3_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_3_conv1_bn_running_var, ema_backbone_stage3_1_blocks_3_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_3_conv2_conv_weight, ema_backbone_stage3_1_blocks_3_conv2_bn_weight, ema_backbone_stage3_1_blocks_3_conv2_bn_bias, ema_backbone_stage3_1_blocks_3_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_3_conv2_bn_running_var, ema_backbone_stage3_1_blocks_3_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_4_conv1_conv_weight, ema_backbone_stage3_1_blocks_4_conv1_bn_weight, ema_backbone_stage3_1_blocks_4_conv1_bn_bias, ema_backbone_stage3_1_blocks_4_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_4_conv1_bn_running_var, ema_backbone_stage3_1_blocks_4_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_4_conv2_conv_weight, ema_backbone_stage3_1_blocks_4_conv2_bn_weight, ema_backbone_stage3_1_blocks_4_conv2_bn_bias, ema_backbone_stage3_1_blocks_4_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_4_conv2_bn_running_var, ema_backbone_stage3_1_blocks_4_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_5_conv1_conv_weight, ema_backbone_stage3_1_blocks_5_conv1_bn_weight, ema_backbone_stage3_1_blocks_5_conv1_bn_bias, ema_backbone_stage3_1_blocks_5_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_5_conv1_bn_running_var, ema_backbone_stage3_1_blocks_5_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_5_conv2_conv_weight, ema_backbone_stage3_1_blocks_5_conv2_bn_weight, ema_backbone_stage3_1_blocks_5_conv2_bn_bias, ema_backbone_stage3_1_blocks_5_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_5_conv2_bn_running_var, ema_backbone_stage3_1_blocks_5_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_6_conv1_conv_weight, ema_backbone_stage3_1_blocks_6_conv1_bn_weight, ema_backbone_stage3_1_blocks_6_conv1_bn_bias, ema_backbone_stage3_1_blocks_6_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_6_conv1_bn_running_var, ema_backbone_stage3_1_blocks_6_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_6_conv2_conv_weight, ema_backbone_stage3_1_blocks_6_conv2_bn_weight, ema_backbone_stage3_1_blocks_6_conv2_bn_bias, ema_backbone_stage3_1_blocks_6_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_6_conv2_bn_running_var, ema_backbone_stage3_1_blocks_6_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_7_conv1_conv_weight, ema_backbone_stage3_1_blocks_7_conv1_bn_weight, ema_backbone_stage3_1_blocks_7_conv1_bn_bias, ema_backbone_stage3_1_blocks_7_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_7_conv1_bn_running_var, ema_backbone_stage3_1_blocks_7_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_7_conv2_conv_weight, ema_backbone_stage3_1_blocks_7_conv2_bn_weight, ema_backbone_stage3_1_blocks_7_conv2_bn_bias, ema_backbone_stage3_1_blocks_7_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_7_conv2_bn_running_var, ema_backbone_stage3_1_blocks_7_conv2_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_8_conv1_conv_weight, ema_backbone_stage3_1_blocks_8_conv1_bn_weight, ema_backbone_stage3_1_blocks_8_conv1_bn_bias, ema_backbone_stage3_1_blocks_8_conv1_bn_running_mean, ema_backbone_stage3_1_blocks_8_conv1_bn_running_var, ema_backbone_stage3_1_blocks_8_conv1_bn_num_batches_tracked, ema_backbone_stage3_1_blocks_8_conv2_conv_weight, ema_backbone_stage3_1_blocks_8_conv2_bn_weight, ema_backbone_stage3_1_blocks_8_conv2_bn_bias, ema_backbone_stage3_1_blocks_8_conv2_bn_running_mean, ema_backbone_stage3_1_blocks_8_conv2_bn_running_var, ema_backbone_stage3_1_blocks_8_conv2_bn_num_batches_tracked, ema_backbone_stage4_0_conv_weight, ema_backbone_stage4_0_bn_weight, ema_backbone_stage4_0_bn_bias, ema_backbone_stage4_0_bn_running_mean, ema_backbone_stage4_0_bn_running_var, ema_backbone_stage4_0_bn_num_batches_tracked, ema_backbone_stage4_1_conv1_conv_weight, ema_backbone_stage4_1_conv1_bn_weight, ema_backbone_stage4_1_conv1_bn_bias, ema_backbone_stage4_1_conv1_bn_running_mean, ema_backbone_stage4_1_conv1_bn_running_var, ema_backbone_stage4_1_conv1_bn_num_batches_tracked, ema_backbone_stage4_1_conv2_conv_weight, ema_backbone_stage4_1_conv2_bn_weight, ema_backbone_stage4_1_conv2_bn_bias, ema_backbone_stage4_1_conv2_bn_running_mean, ema_backbone_stage4_1_conv2_bn_running_var, ema_backbone_stage4_1_conv2_bn_num_batches_tracked, ema_backbone_stage4_2_main_conv_conv_weight, ema_backbone_stage4_2_main_conv_bn_weight, ema_backbone_stage4_2_main_conv_bn_bias, ema_backbone_stage4_2_main_conv_bn_running_mean, ema_backbone_stage4_2_main_conv_bn_running_var, ema_backbone_stage4_2_main_conv_bn_num_batches_tracked, ema_backbone_stage4_2_short_conv_conv_weight, ema_backbone_stage4_2_short_conv_bn_weight, ema_backbone_stage4_2_short_conv_bn_bias, ema_backbone_stage4_2_short_conv_bn_running_mean, ema_backbone_stage4_2_short_conv_bn_running_var, ema_backbone_stage4_2_short_conv_bn_num_batches_tracked, ema_backbone_stage4_2_final_conv_conv_weight, ema_backbone_stage4_2_final_conv_bn_weight, ema_backbone_stage4_2_final_conv_bn_bias, ema_backbone_stage4_2_final_conv_bn_running_mean, ema_backbone_stage4_2_final_conv_bn_running_var, ema_backbone_stage4_2_final_conv_bn_num_batches_tracked, ema_backbone_stage4_2_blocks_0_conv1_conv_weight, ema_backbone_stage4_2_blocks_0_conv1_bn_weight, ema_backbone_stage4_2_blocks_0_conv1_bn_bias, ema_backbone_stage4_2_blocks_0_conv1_bn_running_mean, ema_backbone_stage4_2_blocks_0_conv1_bn_running_var, ema_backbone_stage4_2_blocks_0_conv1_bn_num_batches_tracked, ema_backbone_stage4_2_blocks_0_conv2_conv_weight, ema_backbone_stage4_2_blocks_0_conv2_bn_weight, ema_backbone_stage4_2_blocks_0_conv2_bn_bias, ema_backbone_stage4_2_blocks_0_conv2_bn_running_mean, ema_backbone_stage4_2_blocks_0_conv2_bn_running_var, ema_backbone_stage4_2_blocks_0_conv2_bn_num_batches_tracked, ema_backbone_stage4_2_blocks_1_conv1_conv_weight, ema_backbone_stage4_2_blocks_1_conv1_bn_weight, ema_backbone_stage4_2_blocks_1_conv1_bn_bias, ema_backbone_stage4_2_blocks_1_conv1_bn_running_mean, ema_backbone_stage4_2_blocks_1_conv1_bn_running_var, ema_backbone_stage4_2_blocks_1_conv1_bn_num_batches_tracked, ema_backbone_stage4_2_blocks_1_conv2_conv_weight, ema_backbone_stage4_2_blocks_1_conv2_bn_weight, ema_backbone_stage4_2_blocks_1_conv2_bn_bias, ema_backbone_stage4_2_blocks_1_conv2_bn_running_mean, ema_backbone_stage4_2_blocks_1_conv2_bn_running_var, ema_backbone_stage4_2_blocks_1_conv2_bn_num_batches_tracked, ema_backbone_stage4_2_blocks_2_conv1_conv_weight, ema_backbone_stage4_2_blocks_2_conv1_bn_weight, ema_backbone_stage4_2_blocks_2_conv1_bn_bias, ema_backbone_stage4_2_blocks_2_conv1_bn_running_mean, ema_backbone_stage4_2_blocks_2_conv1_bn_running_var, ema_backbone_stage4_2_blocks_2_conv1_bn_num_batches_tracked, ema_backbone_stage4_2_blocks_2_conv2_conv_weight, ema_backbone_stage4_2_blocks_2_conv2_bn_weight, ema_backbone_stage4_2_blocks_2_conv2_bn_bias, ema_backbone_stage4_2_blocks_2_conv2_bn_running_mean, ema_backbone_stage4_2_blocks_2_conv2_bn_running_var, ema_backbone_stage4_2_blocks_2_conv2_bn_num_batches_tracked, ema_neck_reduce_layers_0_conv_weight, ema_neck_reduce_layers_0_bn_weight, ema_neck_reduce_layers_0_bn_bias, ema_neck_reduce_layers_0_bn_running_mean, ema_neck_reduce_layers_0_bn_running_var, ema_neck_reduce_layers_0_bn_num_batches_tracked, ema_neck_reduce_layers_1_conv_weight, ema_neck_reduce_layers_1_bn_weight, ema_neck_reduce_layers_1_bn_bias, ema_neck_reduce_layers_1_bn_running_mean, ema_neck_reduce_layers_1_bn_running_var, ema_neck_reduce_layers_1_bn_num_batches_tracked, ema_neck_top_down_blocks_0_main_conv_conv_weight, ema_neck_top_down_blocks_0_main_conv_bn_weight, ema_neck_top_down_blocks_0_main_conv_bn_bias, ema_neck_top_down_blocks_0_main_conv_bn_running_mean, ema_neck_top_down_blocks_0_main_conv_bn_running_var, ema_neck_top_down_blocks_0_main_conv_bn_num_batches_tracked, ema_neck_top_down_blocks_0_short_conv_conv_weight, ema_neck_top_down_blocks_0_short_conv_bn_weight, ema_neck_top_down_blocks_0_short_conv_bn_bias, ema_neck_top_down_blocks_0_short_conv_bn_running_mean, ema_neck_top_down_blocks_0_short_conv_bn_running_var, ema_neck_top_down_blocks_0_short_conv_bn_num_batches_tracked, ema_neck_top_down_blocks_0_final_conv_conv_weight, ema_neck_top_down_blocks_0_final_conv_bn_weight, ema_neck_top_down_blocks_0_final_conv_bn_bias, ema_neck_top_down_blocks_0_final_conv_bn_running_mean, ema_neck_top_down_blocks_0_final_conv_bn_running_var, ema_neck_top_down_blocks_0_final_conv_bn_num_batches_tracked, ema_neck_top_down_blocks_0_blocks_0_conv1_conv_weight, ema_neck_top_down_blocks_0_blocks_0_conv1_bn_weight, ema_neck_top_down_blocks_0_blocks_0_conv1_bn_bias, ema_neck_top_down_blocks_0_blocks_0_conv1_bn_running_mean, ema_neck_top_down_blocks_0_blocks_0_conv1_bn_running_var, ema_neck_top_down_blocks_0_blocks_0_conv1_bn_num_batches_tracked, ema_neck_top_down_blocks_0_blocks_0_conv2_conv_weight, ema_neck_top_down_blocks_0_blocks_0_conv2_bn_weight, ema_neck_top_down_blocks_0_blocks_0_conv2_bn_bias, ema_neck_top_down_blocks_0_blocks_0_conv2_bn_running_mean, ema_neck_top_down_blocks_0_blocks_0_conv2_bn_running_var, ema_neck_top_down_blocks_0_blocks_0_conv2_bn_num_batches_tracked, ema_neck_top_down_blocks_0_blocks_1_conv1_conv_weight, ema_neck_top_down_blocks_0_blocks_1_conv1_bn_weight, ema_neck_top_down_blocks_0_blocks_1_conv1_bn_bias, ema_neck_top_down_blocks_0_blocks_1_conv1_bn_running_mean, ema_neck_top_down_blocks_0_blocks_1_conv1_bn_running_var, ema_neck_top_down_blocks_0_blocks_1_conv1_bn_num_batches_tracked, ema_neck_top_down_blocks_0_blocks_1_conv2_conv_weight, ema_neck_top_down_blocks_0_blocks_1_conv2_bn_weight, ema_neck_top_down_blocks_0_blocks_1_conv2_bn_bias, ema_neck_top_down_blocks_0_blocks_1_conv2_bn_running_mean, ema_neck_top_down_blocks_0_blocks_1_conv2_bn_running_var, ema_neck_top_down_blocks_0_blocks_1_conv2_bn_num_batches_tracked, ema_neck_top_down_blocks_0_blocks_2_conv1_conv_weight, ema_neck_top_down_blocks_0_blocks_2_conv1_bn_weight, ema_neck_top_down_blocks_0_blocks_2_conv1_bn_bias, ema_neck_top_down_blocks_0_blocks_2_conv1_bn_running_mean, ema_neck_top_down_blocks_0_blocks_2_conv1_bn_running_var, ema_neck_top_down_blocks_0_blocks_2_conv1_bn_num_batches_tracked, ema_neck_top_down_blocks_0_blocks_2_conv2_conv_weight, ema_neck_top_down_blocks_0_blocks_2_conv2_bn_weight, ema_neck_top_down_blocks_0_blocks_2_conv2_bn_bias, ema_neck_top_down_blocks_0_blocks_2_conv2_bn_running_mean, ema_neck_top_down_blocks_0_blocks_2_conv2_bn_running_var, ema_neck_top_down_blocks_0_blocks_2_conv2_bn_num_batches_tracked, ema_neck_top_down_blocks_1_main_conv_conv_weight, ema_neck_top_down_blocks_1_main_conv_bn_weight, ema_neck_top_down_blocks_1_main_conv_bn_bias, ema_neck_top_down_blocks_1_main_conv_bn_running_mean, ema_neck_top_down_blocks_1_main_conv_bn_running_var, ema_neck_top_down_blocks_1_main_conv_bn_num_batches_tracked, ema_neck_top_down_blocks_1_short_conv_conv_weight, ema_neck_top_down_blocks_1_short_conv_bn_weight, ema_neck_top_down_blocks_1_short_conv_bn_bias, ema_neck_top_down_blocks_1_short_conv_bn_running_mean, ema_neck_top_down_blocks_1_short_conv_bn_running_var, ema_neck_top_down_blocks_1_short_conv_bn_num_batches_tracked, ema_neck_top_down_blocks_1_final_conv_conv_weight, ema_neck_top_down_blocks_1_final_conv_bn_weight, ema_neck_top_down_blocks_1_final_conv_bn_bias, ema_neck_top_down_blocks_1_final_conv_bn_running_mean, ema_neck_top_down_blocks_1_final_conv_bn_running_var, ema_neck_top_down_blocks_1_final_conv_bn_num_batches_tracked, ema_neck_top_down_blocks_1_blocks_0_conv1_conv_weight, ema_neck_top_down_blocks_1_blocks_0_conv1_bn_weight, ema_neck_top_down_blocks_1_blocks_0_conv1_bn_bias, ema_neck_top_down_blocks_1_blocks_0_conv1_bn_running_mean, ema_neck_top_down_blocks_1_blocks_0_conv1_bn_running_var, ema_neck_top_down_blocks_1_blocks_0_conv1_bn_num_batches_tracked, ema_neck_top_down_blocks_1_blocks_0_conv2_conv_weight, ema_neck_top_down_blocks_1_blocks_0_conv2_bn_weight, ema_neck_top_down_blocks_1_blocks_0_conv2_bn_bias, ema_neck_top_down_blocks_1_blocks_0_conv2_bn_running_mean, ema_neck_top_down_blocks_1_blocks_0_conv2_bn_running_var, ema_neck_top_down_blocks_1_blocks_0_conv2_bn_num_batches_tracked, ema_neck_top_down_blocks_1_blocks_1_conv1_conv_weight, ema_neck_top_down_blocks_1_blocks_1_conv1_bn_weight, ema_neck_top_down_blocks_1_blocks_1_conv1_bn_bias, ema_neck_top_down_blocks_1_blocks_1_conv1_bn_running_mean, ema_neck_top_down_blocks_1_blocks_1_conv1_bn_running_var, ema_neck_top_down_blocks_1_blocks_1_conv1_bn_num_batches_tracked, ema_neck_top_down_blocks_1_blocks_1_conv2_conv_weight, ema_neck_top_down_blocks_1_blocks_1_conv2_bn_weight, ema_neck_top_down_blocks_1_blocks_1_conv2_bn_bias, ema_neck_top_down_blocks_1_blocks_1_conv2_bn_running_mean, ema_neck_top_down_blocks_1_blocks_1_conv2_bn_running_var, ema_neck_top_down_blocks_1_blocks_1_conv2_bn_num_batches_tracked, ema_neck_top_down_blocks_1_blocks_2_conv1_conv_weight, ema_neck_top_down_blocks_1_blocks_2_conv1_bn_weight, ema_neck_top_down_blocks_1_blocks_2_conv1_bn_bias, ema_neck_top_down_blocks_1_blocks_2_conv1_bn_running_mean, ema_neck_top_down_blocks_1_blocks_2_conv1_bn_running_var, ema_neck_top_down_blocks_1_blocks_2_conv1_bn_num_batches_tracked, ema_neck_top_down_blocks_1_blocks_2_conv2_conv_weight, ema_neck_top_down_blocks_1_blocks_2_conv2_bn_weight, ema_neck_top_down_blocks_1_blocks_2_conv2_bn_bias, ema_neck_top_down_blocks_1_blocks_2_conv2_bn_running_mean, ema_neck_top_down_blocks_1_blocks_2_conv2_bn_running_var, ema_neck_top_down_blocks_1_blocks_2_conv2_bn_num_batches_tracked, ema_neck_downsamples_0_conv_weight, ema_neck_downsamples_0_bn_weight, ema_neck_downsamples_0_bn_bias, ema_neck_downsamples_0_bn_running_mean, ema_neck_downsamples_0_bn_running_var, ema_neck_downsamples_0_bn_num_batches_tracked, ema_neck_downsamples_1_conv_weight, ema_neck_downsamples_1_bn_weight, ema_neck_downsamples_1_bn_bias, ema_neck_downsamples_1_bn_running_mean, ema_neck_downsamples_1_bn_running_var, ema_neck_downsamples_1_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_main_conv_conv_weight, ema_neck_bottom_up_blocks_0_main_conv_bn_weight, ema_neck_bottom_up_blocks_0_main_conv_bn_bias, ema_neck_bottom_up_blocks_0_main_conv_bn_running_mean, ema_neck_bottom_up_blocks_0_main_conv_bn_running_var, ema_neck_bottom_up_blocks_0_main_conv_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_short_conv_conv_weight, ema_neck_bottom_up_blocks_0_short_conv_bn_weight, ema_neck_bottom_up_blocks_0_short_conv_bn_bias, ema_neck_bottom_up_blocks_0_short_conv_bn_running_mean, ema_neck_bottom_up_blocks_0_short_conv_bn_running_var, ema_neck_bottom_up_blocks_0_short_conv_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_final_conv_conv_weight, ema_neck_bottom_up_blocks_0_final_conv_bn_weight, ema_neck_bottom_up_blocks_0_final_conv_bn_bias, ema_neck_bottom_up_blocks_0_final_conv_bn_running_mean, ema_neck_bottom_up_blocks_0_final_conv_bn_running_var, ema_neck_bottom_up_blocks_0_final_conv_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_blocks_0_conv1_conv_weight, ema_neck_bottom_up_blocks_0_blocks_0_conv1_bn_weight, ema_neck_bottom_up_blocks_0_blocks_0_conv1_bn_bias, ema_neck_bottom_up_blocks_0_blocks_0_conv1_bn_running_mean, ema_neck_bottom_up_blocks_0_blocks_0_conv1_bn_running_var, ema_neck_bottom_up_blocks_0_blocks_0_conv1_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_blocks_0_conv2_conv_weight, ema_neck_bottom_up_blocks_0_blocks_0_conv2_bn_weight, ema_neck_bottom_up_blocks_0_blocks_0_conv2_bn_bias, ema_neck_bottom_up_blocks_0_blocks_0_conv2_bn_running_mean, ema_neck_bottom_up_blocks_0_blocks_0_conv2_bn_running_var, ema_neck_bottom_up_blocks_0_blocks_0_conv2_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_blocks_1_conv1_conv_weight, ema_neck_bottom_up_blocks_0_blocks_1_conv1_bn_weight, ema_neck_bottom_up_blocks_0_blocks_1_conv1_bn_bias, ema_neck_bottom_up_blocks_0_blocks_1_conv1_bn_running_mean, ema_neck_bottom_up_blocks_0_blocks_1_conv1_bn_running_var, ema_neck_bottom_up_blocks_0_blocks_1_conv1_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_blocks_1_conv2_conv_weight, ema_neck_bottom_up_blocks_0_blocks_1_conv2_bn_weight, ema_neck_bottom_up_blocks_0_blocks_1_conv2_bn_bias, ema_neck_bottom_up_blocks_0_blocks_1_conv2_bn_running_mean, ema_neck_bottom_up_blocks_0_blocks_1_conv2_bn_running_var, ema_neck_bottom_up_blocks_0_blocks_1_conv2_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_blocks_2_conv1_conv_weight, ema_neck_bottom_up_blocks_0_blocks_2_conv1_bn_weight, ema_neck_bottom_up_blocks_0_blocks_2_conv1_bn_bias, ema_neck_bottom_up_blocks_0_blocks_2_conv1_bn_running_mean, ema_neck_bottom_up_blocks_0_blocks_2_conv1_bn_running_var, ema_neck_bottom_up_blocks_0_blocks_2_conv1_bn_num_batches_tracked, ema_neck_bottom_up_blocks_0_blocks_2_conv2_conv_weight, ema_neck_bottom_up_blocks_0_blocks_2_conv2_bn_weight, ema_neck_bottom_up_blocks_0_blocks_2_conv2_bn_bias, ema_neck_bottom_up_blocks_0_blocks_2_conv2_bn_running_mean, ema_neck_bottom_up_blocks_0_blocks_2_conv2_bn_running_var, ema_neck_bottom_up_blocks_0_blocks_2_conv2_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_main_conv_conv_weight, ema_neck_bottom_up_blocks_1_main_conv_bn_weight, ema_neck_bottom_up_blocks_1_main_conv_bn_bias, ema_neck_bottom_up_blocks_1_main_conv_bn_running_mean, ema_neck_bottom_up_blocks_1_main_conv_bn_running_var, ema_neck_bottom_up_blocks_1_main_conv_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_short_conv_conv_weight, ema_neck_bottom_up_blocks_1_short_conv_bn_weight, ema_neck_bottom_up_blocks_1_short_conv_bn_bias, ema_neck_bottom_up_blocks_1_short_conv_bn_running_mean, ema_neck_bottom_up_blocks_1_short_conv_bn_running_var, ema_neck_bottom_up_blocks_1_short_conv_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_final_conv_conv_weight, ema_neck_bottom_up_blocks_1_final_conv_bn_weight, ema_neck_bottom_up_blocks_1_final_conv_bn_bias, ema_neck_bottom_up_blocks_1_final_conv_bn_running_mean, ema_neck_bottom_up_blocks_1_final_conv_bn_running_var, ema_neck_bottom_up_blocks_1_final_conv_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_blocks_0_conv1_conv_weight, ema_neck_bottom_up_blocks_1_blocks_0_conv1_bn_weight, ema_neck_bottom_up_blocks_1_blocks_0_conv1_bn_bias, ema_neck_bottom_up_blocks_1_blocks_0_conv1_bn_running_mean, ema_neck_bottom_up_blocks_1_blocks_0_conv1_bn_running_var, ema_neck_bottom_up_blocks_1_blocks_0_conv1_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_blocks_0_conv2_conv_weight, ema_neck_bottom_up_blocks_1_blocks_0_conv2_bn_weight, ema_neck_bottom_up_blocks_1_blocks_0_conv2_bn_bias, ema_neck_bottom_up_blocks_1_blocks_0_conv2_bn_running_mean, ema_neck_bottom_up_blocks_1_blocks_0_conv2_bn_running_var, ema_neck_bottom_up_blocks_1_blocks_0_conv2_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_blocks_1_conv1_conv_weight, ema_neck_bottom_up_blocks_1_blocks_1_conv1_bn_weight, ema_neck_bottom_up_blocks_1_blocks_1_conv1_bn_bias, ema_neck_bottom_up_blocks_1_blocks_1_conv1_bn_running_mean, ema_neck_bottom_up_blocks_1_blocks_1_conv1_bn_running_var, ema_neck_bottom_up_blocks_1_blocks_1_conv1_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_blocks_1_conv2_conv_weight, ema_neck_bottom_up_blocks_1_blocks_1_conv2_bn_weight, ema_neck_bottom_up_blocks_1_blocks_1_conv2_bn_bias, ema_neck_bottom_up_blocks_1_blocks_1_conv2_bn_running_mean, ema_neck_bottom_up_blocks_1_blocks_1_conv2_bn_running_var, ema_neck_bottom_up_blocks_1_blocks_1_conv2_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_blocks_2_conv1_conv_weight, ema_neck_bottom_up_blocks_1_blocks_2_conv1_bn_weight, ema_neck_bottom_up_blocks_1_blocks_2_conv1_bn_bias, ema_neck_bottom_up_blocks_1_blocks_2_conv1_bn_running_mean, ema_neck_bottom_up_blocks_1_blocks_2_conv1_bn_running_var, ema_neck_bottom_up_blocks_1_blocks_2_conv1_bn_num_batches_tracked, ema_neck_bottom_up_blocks_1_blocks_2_conv2_conv_weight, ema_neck_bottom_up_blocks_1_blocks_2_conv2_bn_weight, ema_neck_bottom_up_blocks_1_blocks_2_conv2_bn_bias, ema_neck_bottom_up_blocks_1_blocks_2_conv2_bn_running_mean, ema_neck_bottom_up_blocks_1_blocks_2_conv2_bn_running_var, ema_neck_bottom_up_blocks_1_blocks_2_conv2_bn_num_batches_tracked, ema_neck_out_convs_0_conv_weight, ema_neck_out_convs_0_bn_weight, ema_neck_out_convs_0_bn_bias, ema_neck_out_convs_0_bn_running_mean, ema_neck_out_convs_0_bn_running_var, ema_neck_out_convs_0_bn_num_batches_tracked, ema_neck_out_convs_1_conv_weight, ema_neck_out_convs_1_bn_weight, ema_neck_out_convs_1_bn_bias, ema_neck_out_convs_1_bn_running_mean, ema_neck_out_convs_1_bn_running_var, ema_neck_out_convs_1_bn_num_batches_tracked, ema_neck_out_convs_2_conv_weight, ema_neck_out_convs_2_bn_weight, ema_neck_out_convs_2_bn_bias, ema_neck_out_convs_2_bn_running_mean, ema_neck_out_convs_2_bn_running_var, ema_neck_out_convs_2_bn_num_batches_tracked, ema_bbox_head_multi_level_cls_convs_0_0_conv_weight, ema_bbox_head_multi_level_cls_convs_0_0_bn_weight, ema_bbox_head_multi_level_cls_convs_0_0_bn_bias, ema_bbox_head_multi_level_cls_convs_0_0_bn_running_mean, ema_bbox_head_multi_level_cls_convs_0_0_bn_running_var, ema_bbox_head_multi_level_cls_convs_0_0_bn_num_batches_tracked, ema_bbox_head_multi_level_cls_convs_0_1_conv_weight, ema_bbox_head_multi_level_cls_convs_0_1_bn_weight, ema_bbox_head_multi_level_cls_convs_0_1_bn_bias, ema_bbox_head_multi_level_cls_convs_0_1_bn_running_mean, ema_bbox_head_multi_level_cls_convs_0_1_bn_running_var, ema_bbox_head_multi_level_cls_convs_0_1_bn_num_batches_tracked, ema_bbox_head_multi_level_cls_convs_1_0_conv_weight, ema_bbox_head_multi_level_cls_convs_1_0_bn_weight, ema_bbox_head_multi_level_cls_convs_1_0_bn_bias, ema_bbox_head_multi_level_cls_convs_1_0_bn_running_mean, ema_bbox_head_multi_level_cls_convs_1_0_bn_running_var, ema_bbox_head_multi_level_cls_convs_1_0_bn_num_batches_tracked, ema_bbox_head_multi_level_cls_convs_1_1_conv_weight, ema_bbox_head_multi_level_cls_convs_1_1_bn_weight, ema_bbox_head_multi_level_cls_convs_1_1_bn_bias, ema_bbox_head_multi_level_cls_convs_1_1_bn_running_mean, ema_bbox_head_multi_level_cls_convs_1_1_bn_running_var, ema_bbox_head_multi_level_cls_convs_1_1_bn_num_batches_tracked, ema_bbox_head_multi_level_cls_convs_2_0_conv_weight, ema_bbox_head_multi_level_cls_convs_2_0_bn_weight, ema_bbox_head_multi_level_cls_convs_2_0_bn_bias, ema_bbox_head_multi_level_cls_convs_2_0_bn_running_mean, ema_bbox_head_multi_level_cls_convs_2_0_bn_running_var, ema_bbox_head_multi_level_cls_convs_2_0_bn_num_batches_tracked, ema_bbox_head_multi_level_cls_convs_2_1_conv_weight, ema_bbox_head_multi_level_cls_convs_2_1_bn_weight, ema_bbox_head_multi_level_cls_convs_2_1_bn_bias, ema_bbox_head_multi_level_cls_convs_2_1_bn_running_mean, ema_bbox_head_multi_level_cls_convs_2_1_bn_running_var, ema_bbox_head_multi_level_cls_convs_2_1_bn_num_batches_tracked, ema_bbox_head_multi_level_reg_convs_0_0_conv_weight, ema_bbox_head_multi_level_reg_convs_0_0_bn_weight, ema_bbox_head_multi_level_reg_convs_0_0_bn_bias, ema_bbox_head_multi_level_reg_convs_0_0_bn_running_mean, ema_bbox_head_multi_level_reg_convs_0_0_bn_running_var, ema_bbox_head_multi_level_reg_convs_0_0_bn_num_batches_tracked, ema_bbox_head_multi_level_reg_convs_0_1_conv_weight, ema_bbox_head_multi_level_reg_convs_0_1_bn_weight, ema_bbox_head_multi_level_reg_convs_0_1_bn_bias, ema_bbox_head_multi_level_reg_convs_0_1_bn_running_mean, ema_bbox_head_multi_level_reg_convs_0_1_bn_running_var, ema_bbox_head_multi_level_reg_convs_0_1_bn_num_batches_tracked, ema_bbox_head_multi_level_reg_convs_1_0_conv_weight, ema_bbox_head_multi_level_reg_convs_1_0_bn_weight, ema_bbox_head_multi_level_reg_convs_1_0_bn_bias, ema_bbox_head_multi_level_reg_convs_1_0_bn_running_mean, ema_bbox_head_multi_level_reg_convs_1_0_bn_running_var, ema_bbox_head_multi_level_reg_convs_1_0_bn_num_batches_tracked, ema_bbox_head_multi_level_reg_convs_1_1_conv_weight, ema_bbox_head_multi_level_reg_convs_1_1_bn_weight, ema_bbox_head_multi_level_reg_convs_1_1_bn_bias, ema_bbox_head_multi_level_reg_convs_1_1_bn_running_mean, ema_bbox_head_multi_level_reg_convs_1_1_bn_running_var, ema_bbox_head_multi_level_reg_convs_1_1_bn_num_batches_tracked, ema_bbox_head_multi_level_reg_convs_2_0_conv_weight, ema_bbox_head_multi_level_reg_convs_2_0_bn_weight, ema_bbox_head_multi_level_reg_convs_2_0_bn_bias, ema_bbox_head_multi_level_reg_convs_2_0_bn_running_mean, ema_bbox_head_multi_level_reg_convs_2_0_bn_running_var, ema_bbox_head_multi_level_reg_convs_2_0_bn_num_batches_tracked, ema_bbox_head_multi_level_reg_convs_2_1_conv_weight, ema_bbox_head_multi_level_reg_convs_2_1_bn_weight, ema_bbox_head_multi_level_reg_convs_2_1_bn_bias, ema_bbox_head_multi_level_reg_convs_2_1_bn_running_mean, ema_bbox_head_multi_level_reg_convs_2_1_bn_running_var, ema_bbox_head_multi_level_reg_convs_2_1_bn_num_batches_tracked, ema_bbox_head_multi_level_conv_cls_0_weight, ema_bbox_head_multi_level_conv_cls_0_bias, ema_bbox_head_multi_level_conv_cls_1_weight, ema_bbox_head_multi_level_conv_cls_1_bias, ema_bbox_head_multi_level_conv_cls_2_weight, ema_bbox_head_multi_level_conv_cls_2_bias, ema_bbox_head_multi_level_conv_reg_0_weight, ema_bbox_head_multi_level_conv_reg_0_bias, ema_bbox_head_multi_level_conv_reg_1_weight, ema_bbox_head_multi_level_conv_reg_1_bias, ema_bbox_head_multi_level_conv_reg_2_weight, ema_bbox_head_multi_level_conv_reg_2_bias, ema_bbox_head_multi_level_conv_obj_0_weight, ema_bbox_head_multi_level_conv_obj_0_bias, ema_bbox_head_multi_level_conv_obj_1_weight, ema_bbox_head_multi_level_conv_obj_1_bias, ema_bbox_head_multi_level_conv_obj_2_weight, ema_bbox_head_multi_level_conv_obj_2_bias
/root/anaconda3/envs/tensorrt/lib/python3.7/site-packages/torch/nn/functional.py:718: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at /pytorch/c10/core/TensorImpl.h:1156.)
return torch.max_pool2d(input, kernel_size, stride, padding, dilation, ceil_mode)
[03/21/2022-11:12:47] [TRT] [I] [MemUsageChange] Init CUDA: CPU +306, GPU +0, now: CPU 3100, GPU 2665 (MiB)
[03/21/2022-11:12:48] [TRT] [I] [MemUsageSnapshot] Begin constructing builder kernel library: CPU 3117 MiB, GPU 2665 MiB
[03/21/2022-11:12:53] [TRT] [I] [MemUsageSnapshot] End constructing builder kernel library: CPU 3182 MiB, GPU 2665 MiB
[03/21/2022-11:12:56] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +519, GPU +222, now: CPU 4123, GPU 2785 (MiB)
[03/21/2022-11:12:57] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +117, GPU +52, now: CPU 4240, GPU 2837 (MiB)
[03/21/2022-11:12:57] [TRT] [I] Local timing cache in use. Profiling results in this builder pass will not be stored.
[03/21/2022-11:13:17] [TRT] [I] Some tactics do not have sufficient workspace memory to run. Increasing workspace size will enable more tactics, please check verbose output for requested sizes.
[03/21/2022-11:14:25] [TRT] [I] Detected 1 inputs and 4 output network tensors.
[03/21/2022-11:14:26] [TRT] [I] Total Host Persistent Memory: 351888
[03/21/2022-11:14:26] [TRT] [I] Total Device Persistent Memory: 18877440
[03/21/2022-11:14:26] [TRT] [I] Total Scratch Memory: 2402816
[03/21/2022-11:14:26] [TRT] [I] [MemUsageStats] Peak memory usage of TRT CPU/GPU memory allocators: CPU 232 MiB, GPU 471 MiB
[03/21/2022-11:14:27] [TRT] [I] [BlockAssignment] Algorithm ShiftNTopDown took 187.157ms to assign 13 blocks to 329 nodes requiring 70236160 bytes.
[03/21/2022-11:14:27] [TRT] [I] Total Activation Memory: 70236160
[03/21/2022-11:14:27] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 4775, GPU 3273 (MiB)
[03/21/2022-11:14:27] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +1, GPU +10, now: CPU 4776, GPU 3283 (MiB)
[03/21/2022-11:14:27] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in building engine: CPU +206, GPU +207, now: CPU 206, GPU 207 (MiB)
[03/21/2022-11:14:27] [TRT] [I] [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +0, GPU +8, now: CPU 4774, GPU 3259 (MiB)
[03/21/2022-11:14:27] [TRT] [I] [MemUsageChange] Init cuDNN: CPU +1, GPU +8, now: CPU 4775, GPU 3267 (MiB)
[03/21/2022-11:14:27] [TRT] [I] [MemUsageChange] TensorRT-managed allocation in IExecutionContext creation: CPU +1, GPU +84, now: CPU 207, GPU 291 (MiB) (tensorrt) root@P775TM1:/home/mmdetection-2.19.1# python
Python 3.7.11 (default, Jul 27 2021, 14:32:16)
[GCC 7.5.0] :: Anaconda, Inc. on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> from mmdet.apis.inference import init_detector, inference_detector
>>> from mmdet2trt.apis import create_wrap_detector
>>> trt_detector = create_wrap_detector('work_dirs/yolox_l_8x8_300e_coco_cloth/yolox_l_8x8_300e_coco_cloth.trt', 'work_dirs/yolox_l_8x8_300e_coco_cloth.py', 'cuda:0')
Can not load dataset from config. Use default CLASSES instead.
>>> trt_detector
TRTDetector(
(model): TRTModule()
)
>>> result = inference_detector(trt_detector, 'demo/cloth_flaw.jpg')
#assertion/home/amirstan_plugin/src/plugin/batchedNMSPlugin/batchedNMSPlugin.cpp,127
Abortedtry add
cudaDeviceSynchronize(); // synchronize the device so we can read the log
printf("cuda error log: %s\n", cudaGetErrorString(cudaGetLastError())); // print the logbefore the assert, rebuild the plugin and see if there are any error log.
MeteoriteWeny
commented
2 years ago cuda error log: the provided PTX was compiled with an unsupported toolchain.
grimoire
commented
2 years ago OK, have you update your cuda or tensorrt? rebuild the plugin library might fix this.
MeteoriteWeny
commented
2 years ago I have update the cuda development environment to 11.6, and tensorrt is 8.4.0. The plugin is also rebuilt, but the same cuda error still exists.
(tensorrt) root@P775TM1:/home/mmdetection-2.19.1# dpkg -l | grep TensorRT
ii libnvinfer-bin 8.4.0-1+cuda11.6 amd64 TensorRT binaries
ii libnvinfer-dev 8.4.0-1+cuda11.6 amd64 TensorRT development libraries and headers
ii libnvinfer-doc 8.4.0-1+cuda11.6 all TensorRT documentation
ii libnvinfer-plugin-dev 8.4.0-1+cuda11.6 amd64 TensorRT plugin libraries
ii libnvinfer-plugin8 8.4.0-1+cuda11.6 amd64 TensorRT plugin libraries
ii libnvinfer-samples 8.4.0-1+cuda11.6 all TensorRT samples
ii libnvinfer8 8.4.0-1+cuda11.6 amd64 TensorRT runtime libraries
ii libnvonnxparsers-dev 8.4.0-1+cuda11.6 amd64 TensorRT ONNX libraries
ii libnvonnxparsers8 8.4.0-1+cuda11.6 amd64 TensorRT ONNX libraries
ii libnvparsers-dev 8.4.0-1+cuda11.6 amd64 TensorRT parsers libraries
ii libnvparsers8 8.4.0-1+cuda11.6 amd64 TensorRT parsers libraries
ii onnx-graphsurgeon 8.4.0-1+cuda11.6 amd64 ONNX GraphSurgeon for TensorRT package
ii python3-libnvinfer 8.4.0-1+cuda11.6 amd64 Python 3 bindings for TensorRT
ii python3-libnvinfer-dev 8.4.0-1+cuda11.6 amd64 Python 3 development package for TensorRT
ii tensorrt 8.4.0.6-1+cuda11.6 amd64 Meta package of TensorRT
Describe the bug First, thank you very much for your contribution. When I tried to convert the custom Side-Aware Boundary Localization model, I encountered [checkSanity.cpp::checkSanity::106] Error Code 2: Internal Error. By the way, the custom model works fine when directly use init_detector, inference_detector of mmdet.api.inference. I also found that the implement of SABL in mmdetection 2.12.0 has change a lot compared to 2.19.1. Is the newer version SABL no longer supported? I am beginner of tensorrt and confused with the TRT Error. Could you tell me where the problem exists? Thank you!
Error Output
environment: