RuntimeError: [enforce fail at conv_op_cudnn.cc:554] filter.dim32(1) == C / group_. 8 vs 256

[varrella]

when I run : bash 4_inference.sh
The following problem arised, how to solve it ?
INFO: Running inference...
Found Detectron ops lib: /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/torch/lib/libcaffe2_detectron_ops_gpu.so
[E init_intrinsics_check.cc:43] CPU feature avx is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU.
[E init_intrinsics_check.cc:43] CPU feature avx2 is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU.
[E init_intrinsics_check.cc:43] CPU feature fma is present on your machine, but the Caffe2 binary is not compiled with it. It means you may not get the full speed of your CPU.
INFO coco.py: 49: loading COCO annotations into memory...
INFO coco.py: 55: Done (t=0.19s)
creating index...
index created!
INFO coco.py: 82: index created.
WARNING cnn.py: 25: [====DEPRECATE WARNING====]: you are creating an object from CNNModelHelper class which will be deprecated soon. Please use ModelHelper object with brew module. For more information, please refer to caffe2.ai and python/brew.py, python/brew_test.py for more information.
INFO net.py: 60: Loading weights from: /home/ZT/ZT_Project/RRPN-master/data/models/X_101_32x8d_FPN_1x_nucoco/train/nucoco_mini_train/generalized_rcnn/model_iter19999.pkl
INFO net.py: 96: conv1_w loaded from weights file into gpu_0/conv1_w: (64, 3, 7, 7)
INFO net.py: 96: res_conv1_bn_s loaded from weights file into gpu_0/res_conv1_bn_s: (64,)
INFO net.py: 96: res_conv1_bn_b loaded from weights file into gpu_0/res_conv1_bn_b: (64,)
INFO net.py: 96: res2_0_branch2a_w loaded from weights file into gpu_0/res2_0_branch2a_w: (256, 64, 1, 1)
INFO net.py: 96: res2_0_branch2a_bn_s loaded from weights file into gpu_0/res2_0_branch2a_bn_s: (256,)
INFO net.py: 96: res2_0_branch2a_bn_b loaded from weights file into gpu_0/res2_0_branch2a_bn_b: (256,)
INFO net.py: 96: res2_0_branch2b_w loaded from weights file into gpu_0/res2_0_branch2b_w: (256, 8, 3, 3)
INFO net.py: 96: res2_0_branch2b_bn_s loaded from weights file into gpu_0/res2_0_branch2b_bn_s: (256,)
INFO net.py: 96: res2_0_branch2b_bn_b loaded from weights file into gpu_0/res2_0_branch2b_bn_b: (256,)
INFO net.py: 96: res2_0_branch2c_w loaded from weights file into gpu_0/res2_0_branch2c_w: (256, 256, 1, 1)
INFO net.py: 96: res2_0_branch2c_bn_s loaded from weights file into gpu_0/res2_0_branch2c_bn_s: (256,)
INFO net.py: 96: res2_0_branch2c_bn_b loaded from weights file into gpu_0/res2_0_branch2c_bn_b: (256,)
INFO net.py: 96: res2_0_branch1_w loaded from weights file into gpu_0/res2_0_branch1_w: (256, 64, 1, 1)
INFO net.py: 96: res2_0_branch1_bn_s loaded from weights file into gpu_0/res2_0_branch1_bn_s: (256,)
INFO net.py: 96: res2_0_branch1_bn_b loaded from weights file into gpu_0/res2_0_branch1_bn_b: (256,)
INFO net.py: 96: res2_1_branch2a_w loaded from weights file into gpu_0/res2_1_branch2a_w: (256, 256, 1, 1)
INFO net.py: 96: res2_1_branch2a_bn_s loaded from weights file into gpu_0/res2_1_branch2a_bn_s: (256,)
INFO net.py: 96: res2_1_branch2a_bn_b loaded from weights file into gpu_0/res2_1_branch2a_bn_b: (256,)
INFO net.py: 96: res2_1_branch2b_w loaded from weights file into gpu_0/res2_1_branch2b_w: (256, 8, 3, 3)
INFO net.py: 96: res2_1_branch2b_bn_s loaded from weights file into gpu_0/res2_1_branch2b_bn_s: (256,)
INFO net.py: 96: res2_1_branch2b_bn_b loaded from weights file into gpu_0/res2_1_branch2b_bn_b: (256,)
INFO net.py: 96: res2_1_branch2c_w loaded from weights file into gpu_0/res2_1_branch2c_w: (256, 256, 1, 1)
INFO net.py: 96: res2_1_branch2c_bn_s loaded from weights file into gpu_0/res2_1_branch2c_bn_s: (256,)
INFO net.py: 96: res2_1_branch2c_bn_b loaded from weights file into gpu_0/res2_1_branch2c_bn_b: (256,)
INFO net.py: 96: res2_2_branch2a_w loaded from weights file into gpu_0/res2_2_branch2a_w: (256, 256, 1, 1)
INFO net.py: 96: res2_2_branch2a_bn_s loaded from weights file into gpu_0/res2_2_branch2a_bn_s: (256,)
INFO net.py: 96: res2_2_branch2a_bn_b loaded from weights file into gpu_0/res2_2_branch2a_bn_b: (256,)
INFO net.py: 96: res2_2_branch2b_w loaded from weights file into gpu_0/res2_2_branch2b_w: (256, 8, 3, 3)
INFO net.py: 96: res2_2_branch2b_bn_s loaded from weights file into gpu_0/res2_2_branch2b_bn_s: (256,)
INFO net.py: 96: res2_2_branch2b_bn_b loaded from weights file into gpu_0/res2_2_branch2b_bn_b: (256,)
INFO net.py: 96: res2_2_branch2c_w loaded from weights file into gpu_0/res2_2_branch2c_w: (256, 256, 1, 1)
INFO net.py: 96: res2_2_branch2c_bn_s loaded from weights file into gpu_0/res2_2_branch2c_bn_s: (256,)
INFO net.py: 96: res2_2_branch2c_bn_b loaded from weights file into gpu_0/res2_2_branch2c_bn_b: (256,)
INFO net.py: 96: res3_0_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch2a_w: (512, 256, 1, 1)
INFO net.py: 96: res3_0_branch2a_bn_s loaded from weights file into gpu_0/res3_0_branch2a_bn_s: (512,)
INFO net.py: 96: res3_0_branch2a_bn_b loaded from weights file into gpu_0/res3_0_branch2a_bn_b: (512,)
INFO net.py: 96: res3_0_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch2b_w: (512, 16, 3, 3)
INFO net.py: 96: res3_0_branch2b_bn_s loaded from weights file into gpu_0/res3_0_branch2b_bn_s: (512,)
INFO net.py: 96: res3_0_branch2b_bn_b loaded from weights file into gpu_0/res3_0_branch2b_bn_b: (512,)
INFO net.py: 96: res3_0_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch2c_w: (512, 512, 1, 1)
INFO net.py: 96: res3_0_branch2c_bn_s loaded from weights file into gpu_0/res3_0_branch2c_bn_s: (512,)
INFO net.py: 96: res3_0_branch2c_bn_b loaded from weights file into gpu_0/res3_0_branch2c_bn_b: (512,)
INFO net.py: 96: res3_0_branch1_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch1_w: (512, 256, 1, 1)
INFO net.py: 96: res3_0_branch1_bn_s loaded from weights file into gpu_0/res3_0_branch1_bn_s: (512,)
INFO net.py: 96: res3_0_branch1_bn_b loaded from weights file into gpu_0/res3_0_branch1_bn_b: (512,)
INFO net.py: 96: res3_1_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_1_branch2a_w: (512, 512, 1, 1)
INFO net.py: 96: res3_1_branch2a_bn_s loaded from weights file into gpu_0/res3_1_branch2a_bn_s: (512,)
INFO net.py: 96: res3_1_branch2a_bn_b loaded from weights file into gpu_0/res3_1_branch2a_bn_b: (512,)
INFO net.py: 96: res3_1_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_1_branch2b_w: (512, 16, 3, 3)
INFO net.py: 96: res3_1_branch2b_bn_s loaded from weights file into gpu_0/res3_1_branch2b_bn_s: (512,)
INFO net.py: 96: res3_1_branch2b_bn_b loaded from weights file into gpu_0/res3_1_branch2b_bn_b: (512,)
INFO net.py: 96: res3_1_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_1_branch2c_w: (512, 512, 1, 1)
INFO net.py: 96: res3_1_branch2c_bn_s loaded from weights file into gpu_0/res3_1_branch2c_bn_s: (512,)
INFO net.py: 96: res3_1_branch2c_bn_b loaded from weights file into gpu_0/res3_1_branch2c_bn_b: (512,)
INFO net.py: 96: res3_2_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_2_branch2a_w: (512, 512, 1, 1)
INFO net.py: 96: res3_2_branch2a_bn_s loaded from weights file into gpu_0/res3_2_branch2a_bn_s: (512,)
INFO net.py: 96: res3_2_branch2a_bn_b loaded from weights file into gpu_0/res3_2_branch2a_bn_b: (512,)
INFO net.py: 96: res3_2_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_2_branch2b_w: (512, 16, 3, 3)
INFO net.py: 96: res3_2_branch2b_bn_s loaded from weights file into gpu_0/res3_2_branch2b_bn_s: (512,)
INFO net.py: 96: res3_2_branch2b_bn_b loaded from weights file into gpu_0/res3_2_branch2b_bn_b: (512,)
INFO net.py: 96: res3_2_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_2_branch2c_w: (512, 512, 1, 1)
INFO net.py: 96: res3_2_branch2c_bn_s loaded from weights file into gpu_0/res3_2_branch2c_bn_s: (512,)
INFO net.py: 96: res3_2_branch2c_bn_b loaded from weights file into gpu_0/res3_2_branch2c_bn_b: (512,)
INFO net.py: 96: res3_3_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_3_branch2a_w: (512, 512, 1, 1)
INFO net.py: 96: res3_3_branch2a_bn_s loaded from weights file into gpu_0/res3_3_branch2a_bn_s: (512,)
INFO net.py: 96: res3_3_branch2a_bn_b loaded from weights file into gpu_0/res3_3_branch2a_bn_b: (512,)
INFO net.py: 96: res3_3_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_3_branch2b_w: (512, 16, 3, 3)
INFO net.py: 96: res3_3_branch2b_bn_s loaded from weights file into gpu_0/res3_3_branch2b_bn_s: (512,)
INFO net.py: 96: res3_3_branch2b_bn_b loaded from weights file into gpu_0/res3_3_branch2b_bn_b: (512,)
INFO net.py: 96: res3_3_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_3_branch2c_w: (512, 512, 1, 1)
INFO net.py: 96: res3_3_branch2c_bn_s loaded from weights file into gpu_0/res3_3_branch2c_bn_s: (512,)
INFO net.py: 96: res3_3_branch2c_bn_b loaded from weights file into gpu_0/res3_3_branch2c_bn_b: (512,)
INFO net.py: 96: res4_0_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch2a_w: (1024, 512, 1, 1)
INFO net.py: 96: res4_0_branch2a_bn_s loaded from weights file into gpu_0/res4_0_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_0_branch2a_bn_b loaded from weights file into gpu_0/res4_0_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_0_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_0_branch2b_bn_s loaded from weights file into gpu_0/res4_0_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_0_branch2b_bn_b loaded from weights file into gpu_0/res4_0_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_0_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_0_branch2c_bn_s loaded from weights file into gpu_0/res4_0_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_0_branch2c_bn_b loaded from weights file into gpu_0/res4_0_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_0_branch1_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch1_w: (1024, 512, 1, 1)
INFO net.py: 96: res4_0_branch1_bn_s loaded from weights file into gpu_0/res4_0_branch1_bn_s: (1024,)
INFO net.py: 96: res4_0_branch1_bn_b loaded from weights file into gpu_0/res4_0_branch1_bn_b: (1024,)
INFO net.py: 96: res4_1_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_1_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_1_branch2a_bn_s loaded from weights file into gpu_0/res4_1_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_1_branch2a_bn_b loaded from weights file into gpu_0/res4_1_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_1_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_1_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_1_branch2b_bn_s loaded from weights file into gpu_0/res4_1_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_1_branch2b_bn_b loaded from weights file into gpu_0/res4_1_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_1_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_1_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_1_branch2c_bn_s loaded from weights file into gpu_0/res4_1_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_1_branch2c_bn_b loaded from weights file into gpu_0/res4_1_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_2_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_2_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_2_branch2a_bn_s loaded from weights file into gpu_0/res4_2_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_2_branch2a_bn_b loaded from weights file into gpu_0/res4_2_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_2_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_2_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_2_branch2b_bn_s loaded from weights file into gpu_0/res4_2_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_2_branch2b_bn_b loaded from weights file into gpu_0/res4_2_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_2_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_2_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_2_branch2c_bn_s loaded from weights file into gpu_0/res4_2_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_2_branch2c_bn_b loaded from weights file into gpu_0/res4_2_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_3_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_3_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_3_branch2a_bn_s loaded from weights file into gpu_0/res4_3_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_3_branch2a_bn_b loaded from weights file into gpu_0/res4_3_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_3_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_3_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_3_branch2b_bn_s loaded from weights file into gpu_0/res4_3_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_3_branch2b_bn_b loaded from weights file into gpu_0/res4_3_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_3_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_3_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_3_branch2c_bn_s loaded from weights file into gpu_0/res4_3_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_3_branch2c_bn_b loaded from weights file into gpu_0/res4_3_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_4_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_4_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_4_branch2a_bn_s loaded from weights file into gpu_0/res4_4_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_4_branch2a_bn_b loaded from weights file into gpu_0/res4_4_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_4_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_4_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_4_branch2b_bn_s loaded from weights file into gpu_0/res4_4_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_4_branch2b_bn_b loaded from weights file into gpu_0/res4_4_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_4_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_4_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_4_branch2c_bn_s loaded from weights file into gpu_0/res4_4_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_4_branch2c_bn_b loaded from weights file into gpu_0/res4_4_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_5_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_5_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_5_branch2a_bn_s loaded from weights file into gpu_0/res4_5_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_5_branch2a_bn_b loaded from weights file into gpu_0/res4_5_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_5_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_5_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_5_branch2b_bn_s loaded from weights file into gpu_0/res4_5_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_5_branch2b_bn_b loaded from weights file into gpu_0/res4_5_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_5_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_5_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_5_branch2c_bn_s loaded from weights file into gpu_0/res4_5_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_5_branch2c_bn_b loaded from weights file into gpu_0/res4_5_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_6_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_6_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_6_branch2a_bn_s loaded from weights file into gpu_0/res4_6_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_6_branch2a_bn_b loaded from weights file into gpu_0/res4_6_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_6_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_6_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_6_branch2b_bn_s loaded from weights file into gpu_0/res4_6_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_6_branch2b_bn_b loaded from weights file into gpu_0/res4_6_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_6_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_6_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_6_branch2c_bn_s loaded from weights file into gpu_0/res4_6_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_6_branch2c_bn_b loaded from weights file into gpu_0/res4_6_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_7_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_7_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_7_branch2a_bn_s loaded from weights file into gpu_0/res4_7_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_7_branch2a_bn_b loaded from weights file into gpu_0/res4_7_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_7_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_7_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_7_branch2b_bn_s loaded from weights file into gpu_0/res4_7_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_7_branch2b_bn_b loaded from weights file into gpu_0/res4_7_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_7_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_7_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_7_branch2c_bn_s loaded from weights file into gpu_0/res4_7_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_7_branch2c_bn_b loaded from weights file into gpu_0/res4_7_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_8_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_8_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_8_branch2a_bn_s loaded from weights file into gpu_0/res4_8_branch2a_bn_s: (1024,)
INFO net.py: 96: res4_8_branch2a_bn_b loaded from weights file into gpu_0/res4_8_branch2a_bn_b: (1024,)
INFO net.py: 96: res4_8_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_8_branch2b_w: (1024, 32, 3, 3)
INFO net.py: 96: res4_8_branch2b_bn_s loaded from weights file into gpu_0/res4_8_branch2b_bn_s: (1024,)
INFO net.py: 96: res4_8_branch2b_bn_b loaded from weights file into gpu_0/res4_8_branch2b_bn_b: (1024,)
INFO net.py: 96: res4_8_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_8_branch2c_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_8_branch2c_bn_s loaded from weights file into gpu_0/res4_8_branch2c_bn_s: (1024,)
INFO net.py: 96: res4_8_branch2c_bn_b loaded from weights file into gpu_0/res4_8_branch2c_bn_b: (1024,)
INFO net.py: 96: res4_9_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_9_branch2a_w: (1024, 1024, 1, 1)
INFO net.py: 96: res4_9_branch2a_bn_s loaded from weights file into gpu_0/res4_9_branch2a_bn_s: (1024,)
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INFO net.py: 96: fpn_inner_res2_2_sum_lateral_w [+ momentum] loaded from weights file into gpu_0/fpn_inner_res2_2_sum_lateral_w: (256, 256, 1, 1)
INFO net.py: 96: fpn_inner_res2_2_sum_lateral_b [+ momentum] loaded from weights file into gpu_0/fpn_inner_res2_2_sum_lateral_b: (256,)
INFO net.py: 96: fpn_res5_2_sum_w [+ momentum] loaded from weights file into gpu_0/fpn_res5_2_sum_w: (256, 256, 3, 3)
INFO net.py: 96: fpn_res5_2_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_res5_2_sum_b: (256,)
INFO net.py: 96: fpn_res4_22_sum_w [+ momentum] loaded from weights file into gpu_0/fpn_res4_22_sum_w: (256, 256, 3, 3)
INFO net.py: 96: fpn_res4_22_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_res4_22_sum_b: (256,)
INFO net.py: 96: fpn_res3_3_sum_w [+ momentum] loaded from weights file into gpu_0/fpn_res3_3_sum_w: (256, 256, 3, 3)
INFO net.py: 96: fpn_res3_3_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_res3_3_sum_b: (256,)
INFO net.py: 96: fpn_res2_2_sum_w [+ momentum] loaded from weights file into gpu_0/fpn_res2_2_sum_w: (256, 256, 3, 3)
INFO net.py: 96: fpn_res2_2_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_res2_2_sum_b: (256,)
INFO net.py: 96: fc6_w [+ momentum] loaded from weights file into gpu_0/fc6_w: (1024, 12544)
INFO net.py: 96: fc6_b [+ momentum] loaded from weights file into gpu_0/fc6_b: (1024,)
INFO net.py: 96: fc7_w [+ momentum] loaded from weights file into gpu_0/fc7_w: (1024, 1024)
INFO net.py: 96: fc7_b [+ momentum] loaded from weights file into gpu_0/fc7_b: (1024,)
INFO net.py: 96: cls_score_w [+ momentum] loaded from weights file into gpu_0/cls_score_w: (7, 1024)
INFO net.py: 96: cls_score_b [+ momentum] loaded from weights file into gpu_0/cls_score_b: (7,)
INFO net.py: 96: bbox_pred_w [+ momentum] loaded from weights file into gpu_0/bbox_pred_w: (28, 1024)
INFO net.py: 96: bbox_pred_b [+ momentum] loaded from weights file into gpu_0/bbox_pred_b: (28,)
INFO net.py: 133: pred_b preserved in workspace (unused)
INFO net.py: 133: pred_w preserved in workspace (unused)
[I net_dag_utils.cc:102] Operator graph pruning prior to chain compute took: 0.00015352 secs
[I net_dag_utils.cc:102] Operator graph pruning prior to chain compute took: 0.000154624 secs
[I net_async_base.h:207] Using specified CPU pool size: 4; device id: -1
[I net_async_base.h:212] Created new CPU pool, size: 4; device id: -1
[E net_async_base.cc:382] [enforce fail at conv_op_cudnn.cc:554] filter.dim32(1) == C / group_. 8 vs 256
Error from operator:
input: "gpu_0/res2_0_branch2a" input: "gpu_0/res2_0_branch2b_w" output: "gpu_0/res2_0_branch2b" name: "" type: "Conv" arg { name: "kernel" i: 3 } arg { name: "order" s: "NCHW" } arg { name: "stride" i: 1 } arg { name: "pad" i: 1 } arg { name: "dilation" i: 1 } arg { name: "exhaustive_search" i: 0 } device_option { device_type: 1 device_id: 0 } engine: "CUDNN"frame #0: c10::ThrowEnforceNotMet(char const*, int, char const*, std::string const&, void const*) + 0x5b (0x7f52136813bb in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #1: + 0x44a5b4f (0x7f5217f78b4f in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #2: + 0x4491988 (0x7f5217f64988 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #3: + 0x4414805 (0x7f5217ee7805 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #4: caffe2::AsyncNetBase::run(int, int) + 0x10e (0x7f52163336de in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #5: + 0x28670e7 (0x7f521633a0e7 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #6: c10::ThreadPool::main_loop(unsigned long) + 0x293 (0x7f521367cc73 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #7: + 0x3989f (0x7f521368789f in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #8: + 0x76db (0x7f525cd986db in /lib/x86_64-linux-gnu/libpthread.so.0)
frame #9: clone + 0x3f (0x7f525cac171f in /lib/x86_64-linux-gnu/libc.so.6)
, op Conv
[E net_async_base.cc:134] Rethrowing exception from the run of 'generalized_rcnn'
WARNING workspace.py: 223: Original python traceback for operator 7 in network generalized_rcnn in exception above (most recent call last):
WARNING workspace.py: 228: File "inference.py", line 197, in
WARNING workspace.py: 228: File "inference.py", line 143, in main
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/core/test_engine.py", line 327, in initialize_model_from_cfg
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/model_builder.py", line 124, in create
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/model_builder.py", line 89, in generalized_rcnn
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/model_builder.py", line 229, in build_generic_detection_model
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/optimizer.py", line 54, in build_data_parallel_model
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/model_builder.py", line 169, in _single_gpu_build_func
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/FPN.py", line 63, in add_fpn_ResNet101_conv5_body
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/FPN.py", line 104, in add_fpn_onto_conv_body
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/ResNet.py", line 48, in add_ResNet101_conv5_body
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/ResNet.py", line 103, in add_ResNet_convX_body
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/ResNet.py", line 85, in add_stage
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/ResNet.py", line 183, in add_residual_block
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/ResNet.py", line 316, in bottleneck_transformation
WARNING workspace.py: 228: File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/modeling/detector.py", line 407, in ConvAffine
WARNING workspace.py: 228: File "/home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/cnn.py", line 97, in Conv
WARNING workspace.py: 228: File "/home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/brew.py", line 108, in scope_wrapper
WARNING workspace.py: 228: File "/home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/helpers/conv.py", line 186, in conv
WARNING workspace.py: 228: File "/home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/helpers/conv.py", line 139, in ConvBase
Traceback (most recent call last):
File "inference.py", line 197, in
main(args)
File "inference.py", line 146, in main
model_engine.im_detect_all(model, im, proposal_boxes)
File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/core/test.py", line 66, in im_detect_all
model, im, cfg.TEST.SCALE, cfg.TEST.MAX_SIZE, boxes=box_proposals
File "/home/ZT/ZT_Project/RRPN-master/detectron/detectron/core/test.py", line 158, in im_detect_bbox
workspace.RunNet(model.net.Proto().name)
File "/home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/workspace.py", line 255, in RunNet
StringifyNetName(name), num_iter, allow_fail,
File "/home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/workspace.py", line 216, in CallWithExceptionIntercept
return func(*args, **kwargs)
RuntimeError: [enforce fail at conv_op_cudnn.cc:554] filter.dim32(1) == C / group. 8 vs 256
Error from operator:
input: "gpu_0/res2_0_branch2a" input: "gpu_0/res2_0_branch2b_w" output: "gpu_0/res2_0_branch2b" name: "" type: "Conv" arg { name: "kernel" i: 3 } arg { name: "order" s: "NCHW" } arg { name: "stride" i: 1 } arg { name: "pad" i: 1 } arg { name: "dilation" i: 1 } arg { name: "exhaustive_search" i: 0 } device_option { device_type: 1 device_id: 0 } engine: "CUDNN"frame #0: c10::ThrowEnforceNotMet(char const*, int, char const*, std::string const&, void const*) + 0x5b (0x7f52136813bb in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #1: + 0x44a5b4f (0x7f5217f78b4f in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #2: + 0x4491988 (0x7f5217f64988 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #3: + 0x4414805 (0x7f5217ee7805 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #4: caffe2::AsyncNetBase::run(int, int) + 0x10e (0x7f52163336de in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #5: + 0x28670e7 (0x7f521633a0e7 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libtorch.so)
frame #6: c10::ThreadPool::main_loop(unsigned long) + 0x293 (0x7f521367cc73 in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #7: + 0x3989f (0x7f521368789f in /home/ZT/anaconda3/envs/pytorch-1.4.0/lib/python3.7/site-packages/caffe2/python/../../torch/lib/libc10.so)
frame #8: + 0x76db (0x7f525cd986db in /lib/x86_64-linux-gnu/libpthread.so.0)
frame #9: clone + 0x3f (0x7f525cac171f in /lib/x86_64-linux-gnu/libc.so.6)