infer.py and infer_simple.py do not support RetinaNet (was: Can't load RetinaNet for inference)

Hi, first of all, thanks for releasing all of these wonderful models.

I succeeded in running inference code using Mask RCNN following the tutorial.

python2 tools/infer_simple.py \
    --cfg configs/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_2x.yaml \
    --output-dir /tmp/detectron-visualizations \
    --image-ext jpg \
    --wts https://s3-us-west-2.amazonaws.com/detectron/35861858/12_2017_baselines/e2e_mask_rcnn_R-101-FPN_2x.yaml.02_32_51.SgT4y1cO/output/train/coco_2014_train:coco_2014_valminusminival/generalized_rcnn/model_final.pkl \
    demo

But when I tried to run inference code using RetinaNet.

python2 tools/infer_simple.py \
  --cfg configs/12_2017_baselines/retinanet_R-50-FPN_1x.yaml \
  --output-dir /tmp/detectron-visualizations \
  --image-ext jpg \
  --wts https://s3-us-west-2.amazonaws.com/detectron/36768636/12_2017_baselines/retinanet_R-50-FPN_1x.yaml.08_29_48.t4zc9clc/output/train/coco_2014_train:coco_2014_valminusminival/retinanet/model_final.pkl \
  demo

I received the following error:

Traceback (most recent call last):
  File "tools/infer_simple.py", line 147, in <module>
    main(args)
  File "tools/infer_simple.py", line 99, in main
    model = infer_engine.initialize_model_from_cfg()
  File "/home/ecli/detectron/lib/core/test_engine.py", line 226, in initialize_model_from_cfg
    workspace.CreateNet(model.conv_body_net)
  File "/usr/local/caffe2/python/model_helper.py", line 468, in __getattr__
    ','.join(workspace.C.nearby_opnames(op_type)) + ']'
AttributeError: Method conv_body_net is not a registered operator. Did you mean: []

Any help would be greatly appreciated. Thanks a lot!

For your reference, I will attach the entire output on my terminal:

E0124 15:09:23.594583 23889 init_intrinsics_check.cc:54] 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.
E0124 15:09:23.594600 23889 init_intrinsics_check.cc:54] 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.
E0124 15:09:23.594604 23889 init_intrinsics_check.cc:54] 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.
WARNING cnn.py:  40: [====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:  54: Loading from: /tmp/detectron-download-cache/36768636/12_2017_baselines/retinanet_R-50-FPN_1x.yaml.08_29_48.t4zc9clc/output/train/coco_2014_train:coco_2014_valminusminival/retinanet/model_final.pkl
INFO net.py:  91: conv1_w loaded from weights file into gpu_0/conv1_w: (64, 3, 7, 7)
INFO net.py:  91: res_conv1_bn_s loaded from weights file into gpu_0/res_conv1_bn_s: (64,)
INFO net.py:  91: res_conv1_bn_b loaded from weights file into gpu_0/res_conv1_bn_b: (64,)
INFO net.py:  91: res2_0_branch2a_w loaded from weights file into gpu_0/res2_0_branch2a_w: (64, 64, 1, 1)
INFO net.py:  91: res2_0_branch2a_bn_s loaded from weights file into gpu_0/res2_0_branch2a_bn_s: (64,)
INFO net.py:  91: res2_0_branch2a_bn_b loaded from weights file into gpu_0/res2_0_branch2a_bn_b: (64,)
INFO net.py:  91: res2_0_branch2b_w loaded from weights file into gpu_0/res2_0_branch2b_w: (64, 64, 3, 3)
INFO net.py:  91: res2_0_branch2b_bn_s loaded from weights file into gpu_0/res2_0_branch2b_bn_s: (64,)
INFO net.py:  91: res2_0_branch2b_bn_b loaded from weights file into gpu_0/res2_0_branch2b_bn_b: (64,)
INFO net.py:  91: res2_0_branch2c_w loaded from weights file into gpu_0/res2_0_branch2c_w: (256, 64, 1, 1)
INFO net.py:  91: res2_0_branch2c_bn_s loaded from weights file into gpu_0/res2_0_branch2c_bn_s: (256,)
INFO net.py:  91: res2_0_branch2c_bn_b loaded from weights file into gpu_0/res2_0_branch2c_bn_b: (256,)
INFO net.py:  91: res2_0_branch1_w loaded from weights file into gpu_0/res2_0_branch1_w: (256, 64, 1, 1)
INFO net.py:  91: res2_0_branch1_bn_s loaded from weights file into gpu_0/res2_0_branch1_bn_s: (256,)
INFO net.py:  91: res2_0_branch1_bn_b loaded from weights file into gpu_0/res2_0_branch1_bn_b: (256,)
INFO net.py:  91: res2_1_branch2a_w loaded from weights file into gpu_0/res2_1_branch2a_w: (64, 256, 1, 1)
INFO net.py:  91: res2_1_branch2a_bn_s loaded from weights file into gpu_0/res2_1_branch2a_bn_s: (64,)
INFO net.py:  91: res2_1_branch2a_bn_b loaded from weights file into gpu_0/res2_1_branch2a_bn_b: (64,)
INFO net.py:  91: res2_1_branch2b_w loaded from weights file into gpu_0/res2_1_branch2b_w: (64, 64, 3, 3)
INFO net.py:  91: res2_1_branch2b_bn_s loaded from weights file into gpu_0/res2_1_branch2b_bn_s: (64,)
INFO net.py:  91: res2_1_branch2b_bn_b loaded from weights file into gpu_0/res2_1_branch2b_bn_b: (64,)
INFO net.py:  91: res2_1_branch2c_w loaded from weights file into gpu_0/res2_1_branch2c_w: (256, 64, 1, 1)
INFO net.py:  91: res2_1_branch2c_bn_s loaded from weights file into gpu_0/res2_1_branch2c_bn_s: (256,)
INFO net.py:  91: res2_1_branch2c_bn_b loaded from weights file into gpu_0/res2_1_branch2c_bn_b: (256,)
INFO net.py:  91: res2_2_branch2a_w loaded from weights file into gpu_0/res2_2_branch2a_w: (64, 256, 1, 1)
INFO net.py:  91: res2_2_branch2a_bn_s loaded from weights file into gpu_0/res2_2_branch2a_bn_s: (64,)
INFO net.py:  91: res2_2_branch2a_bn_b loaded from weights file into gpu_0/res2_2_branch2a_bn_b: (64,)
INFO net.py:  91: res2_2_branch2b_w loaded from weights file into gpu_0/res2_2_branch2b_w: (64, 64, 3, 3)
INFO net.py:  91: res2_2_branch2b_bn_s loaded from weights file into gpu_0/res2_2_branch2b_bn_s: (64,)
INFO net.py:  91: res2_2_branch2b_bn_b loaded from weights file into gpu_0/res2_2_branch2b_bn_b: (64,)
INFO net.py:  91: res2_2_branch2c_w loaded from weights file into gpu_0/res2_2_branch2c_w: (256, 64, 1, 1)
INFO net.py:  91: res2_2_branch2c_bn_s loaded from weights file into gpu_0/res2_2_branch2c_bn_s: (256,)
INFO net.py:  91: res2_2_branch2c_bn_b loaded from weights file into gpu_0/res2_2_branch2c_bn_b: (256,)
INFO net.py:  91: res3_0_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch2a_w: (128, 256, 1, 1)
INFO net.py:  91: res3_0_branch2a_bn_s loaded from weights file into gpu_0/res3_0_branch2a_bn_s: (128,)
INFO net.py:  91: res3_0_branch2a_bn_b loaded from weights file into gpu_0/res3_0_branch2a_bn_b: (128,)
INFO net.py:  91: res3_0_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch2b_w: (128, 128, 3, 3)
INFO net.py:  91: res3_0_branch2b_bn_s loaded from weights file into gpu_0/res3_0_branch2b_bn_s: (128,)
INFO net.py:  91: res3_0_branch2b_bn_b loaded from weights file into gpu_0/res3_0_branch2b_bn_b: (128,)
INFO net.py:  91: res3_0_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch2c_w: (512, 128, 1, 1)
INFO net.py:  91: res3_0_branch2c_bn_s loaded from weights file into gpu_0/res3_0_branch2c_bn_s: (512,)
INFO net.py:  91: res3_0_branch2c_bn_b loaded from weights file into gpu_0/res3_0_branch2c_bn_b: (512,)
INFO net.py:  91: res3_0_branch1_w [+ momentum] loaded from weights file into gpu_0/res3_0_branch1_w: (512, 256, 1, 1)
INFO net.py:  91: res3_0_branch1_bn_s loaded from weights file into gpu_0/res3_0_branch1_bn_s: (512,)
INFO net.py:  91: res3_0_branch1_bn_b loaded from weights file into gpu_0/res3_0_branch1_bn_b: (512,)
INFO net.py:  91: res3_1_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_1_branch2a_w: (128, 512, 1, 1)
INFO net.py:  91: res3_1_branch2a_bn_s loaded from weights file into gpu_0/res3_1_branch2a_bn_s: (128,)
INFO net.py:  91: res3_1_branch2a_bn_b loaded from weights file into gpu_0/res3_1_branch2a_bn_b: (128,)
INFO net.py:  91: res3_1_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_1_branch2b_w: (128, 128, 3, 3)
INFO net.py:  91: res3_1_branch2b_bn_s loaded from weights file into gpu_0/res3_1_branch2b_bn_s: (128,)
INFO net.py:  91: res3_1_branch2b_bn_b loaded from weights file into gpu_0/res3_1_branch2b_bn_b: (128,)
INFO net.py:  91: res3_1_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_1_branch2c_w: (512, 128, 1, 1)
INFO net.py:  91: res3_1_branch2c_bn_s loaded from weights file into gpu_0/res3_1_branch2c_bn_s: (512,)
INFO net.py:  91: res3_1_branch2c_bn_b loaded from weights file into gpu_0/res3_1_branch2c_bn_b: (512,)
INFO net.py:  91: res3_2_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_2_branch2a_w: (128, 512, 1, 1)
INFO net.py:  91: res3_2_branch2a_bn_s loaded from weights file into gpu_0/res3_2_branch2a_bn_s: (128,)
INFO net.py:  91: res3_2_branch2a_bn_b loaded from weights file into gpu_0/res3_2_branch2a_bn_b: (128,)
INFO net.py:  91: res3_2_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_2_branch2b_w: (128, 128, 3, 3)
INFO net.py:  91: res3_2_branch2b_bn_s loaded from weights file into gpu_0/res3_2_branch2b_bn_s: (128,)
INFO net.py:  91: res3_2_branch2b_bn_b loaded from weights file into gpu_0/res3_2_branch2b_bn_b: (128,)
INFO net.py:  91: res3_2_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_2_branch2c_w: (512, 128, 1, 1)
INFO net.py:  91: res3_2_branch2c_bn_s loaded from weights file into gpu_0/res3_2_branch2c_bn_s: (512,)
INFO net.py:  91: res3_2_branch2c_bn_b loaded from weights file into gpu_0/res3_2_branch2c_bn_b: (512,)
INFO net.py:  91: res3_3_branch2a_w [+ momentum] loaded from weights file into gpu_0/res3_3_branch2a_w: (128, 512, 1, 1)
INFO net.py:  91: res3_3_branch2a_bn_s loaded from weights file into gpu_0/res3_3_branch2a_bn_s: (128,)
INFO net.py:  91: res3_3_branch2a_bn_b loaded from weights file into gpu_0/res3_3_branch2a_bn_b: (128,)
INFO net.py:  91: res3_3_branch2b_w [+ momentum] loaded from weights file into gpu_0/res3_3_branch2b_w: (128, 128, 3, 3)
INFO net.py:  91: res3_3_branch2b_bn_s loaded from weights file into gpu_0/res3_3_branch2b_bn_s: (128,)
INFO net.py:  91: res3_3_branch2b_bn_b loaded from weights file into gpu_0/res3_3_branch2b_bn_b: (128,)
INFO net.py:  91: res3_3_branch2c_w [+ momentum] loaded from weights file into gpu_0/res3_3_branch2c_w: (512, 128, 1, 1)
INFO net.py:  91: res3_3_branch2c_bn_s loaded from weights file into gpu_0/res3_3_branch2c_bn_s: (512,)
INFO net.py:  91: res3_3_branch2c_bn_b loaded from weights file into gpu_0/res3_3_branch2c_bn_b: (512,)
INFO net.py:  91: res4_0_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch2a_w: (256, 512, 1, 1)
INFO net.py:  91: res4_0_branch2a_bn_s loaded from weights file into gpu_0/res4_0_branch2a_bn_s: (256,)
INFO net.py:  91: res4_0_branch2a_bn_b loaded from weights file into gpu_0/res4_0_branch2a_bn_b: (256,)
INFO net.py:  91: res4_0_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch2b_w: (256, 256, 3, 3)
INFO net.py:  91: res4_0_branch2b_bn_s loaded from weights file into gpu_0/res4_0_branch2b_bn_s: (256,)
INFO net.py:  91: res4_0_branch2b_bn_b loaded from weights file into gpu_0/res4_0_branch2b_bn_b: (256,)
INFO net.py:  91: res4_0_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch2c_w: (1024, 256, 1, 1)
INFO net.py:  91: res4_0_branch2c_bn_s loaded from weights file into gpu_0/res4_0_branch2c_bn_s: (1024,)
INFO net.py:  91: res4_0_branch2c_bn_b loaded from weights file into gpu_0/res4_0_branch2c_bn_b: (1024,)
INFO net.py:  91: res4_0_branch1_w [+ momentum] loaded from weights file into gpu_0/res4_0_branch1_w: (1024, 512, 1, 1)
INFO net.py:  91: res4_0_branch1_bn_s loaded from weights file into gpu_0/res4_0_branch1_bn_s: (1024,)
INFO net.py:  91: res4_0_branch1_bn_b loaded from weights file into gpu_0/res4_0_branch1_bn_b: (1024,)
INFO net.py:  91: res4_1_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_1_branch2a_w: (256, 1024, 1, 1)
INFO net.py:  91: res4_1_branch2a_bn_s loaded from weights file into gpu_0/res4_1_branch2a_bn_s: (256,)
INFO net.py:  91: res4_1_branch2a_bn_b loaded from weights file into gpu_0/res4_1_branch2a_bn_b: (256,)
INFO net.py:  91: res4_1_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_1_branch2b_w: (256, 256, 3, 3)
INFO net.py:  91: res4_1_branch2b_bn_s loaded from weights file into gpu_0/res4_1_branch2b_bn_s: (256,)
INFO net.py:  91: res4_1_branch2b_bn_b loaded from weights file into gpu_0/res4_1_branch2b_bn_b: (256,)
INFO net.py:  91: res4_1_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_1_branch2c_w: (1024, 256, 1, 1)
INFO net.py:  91: res4_1_branch2c_bn_s loaded from weights file into gpu_0/res4_1_branch2c_bn_s: (1024,)
INFO net.py:  91: res4_1_branch2c_bn_b loaded from weights file into gpu_0/res4_1_branch2c_bn_b: (1024,)
INFO net.py:  91: res4_2_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_2_branch2a_w: (256, 1024, 1, 1)
INFO net.py:  91: res4_2_branch2a_bn_s loaded from weights file into gpu_0/res4_2_branch2a_bn_s: (256,)
INFO net.py:  91: res4_2_branch2a_bn_b loaded from weights file into gpu_0/res4_2_branch2a_bn_b: (256,)
INFO net.py:  91: res4_2_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_2_branch2b_w: (256, 256, 3, 3)
INFO net.py:  91: res4_2_branch2b_bn_s loaded from weights file into gpu_0/res4_2_branch2b_bn_s: (256,)
INFO net.py:  91: res4_2_branch2b_bn_b loaded from weights file into gpu_0/res4_2_branch2b_bn_b: (256,)
INFO net.py:  91: res4_2_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_2_branch2c_w: (1024, 256, 1, 1)
INFO net.py:  91: res4_2_branch2c_bn_s loaded from weights file into gpu_0/res4_2_branch2c_bn_s: (1024,)
INFO net.py:  91: res4_2_branch2c_bn_b loaded from weights file into gpu_0/res4_2_branch2c_bn_b: (1024,)
INFO net.py:  91: res4_3_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_3_branch2a_w: (256, 1024, 1, 1)
INFO net.py:  91: res4_3_branch2a_bn_s loaded from weights file into gpu_0/res4_3_branch2a_bn_s: (256,)
INFO net.py:  91: res4_3_branch2a_bn_b loaded from weights file into gpu_0/res4_3_branch2a_bn_b: (256,)
INFO net.py:  91: res4_3_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_3_branch2b_w: (256, 256, 3, 3)
INFO net.py:  91: res4_3_branch2b_bn_s loaded from weights file into gpu_0/res4_3_branch2b_bn_s: (256,)
INFO net.py:  91: res4_3_branch2b_bn_b loaded from weights file into gpu_0/res4_3_branch2b_bn_b: (256,)
INFO net.py:  91: res4_3_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_3_branch2c_w: (1024, 256, 1, 1)
INFO net.py:  91: res4_3_branch2c_bn_s loaded from weights file into gpu_0/res4_3_branch2c_bn_s: (1024,)
INFO net.py:  91: res4_3_branch2c_bn_b loaded from weights file into gpu_0/res4_3_branch2c_bn_b: (1024,)
INFO net.py:  91: res4_4_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_4_branch2a_w: (256, 1024, 1, 1)
INFO net.py:  91: res4_4_branch2a_bn_s loaded from weights file into gpu_0/res4_4_branch2a_bn_s: (256,)
INFO net.py:  91: res4_4_branch2a_bn_b loaded from weights file into gpu_0/res4_4_branch2a_bn_b: (256,)
INFO net.py:  91: res4_4_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_4_branch2b_w: (256, 256, 3, 3)
INFO net.py:  91: res4_4_branch2b_bn_s loaded from weights file into gpu_0/res4_4_branch2b_bn_s: (256,)
INFO net.py:  91: res4_4_branch2b_bn_b loaded from weights file into gpu_0/res4_4_branch2b_bn_b: (256,)
INFO net.py:  91: res4_4_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_4_branch2c_w: (1024, 256, 1, 1)
INFO net.py:  91: res4_4_branch2c_bn_s loaded from weights file into gpu_0/res4_4_branch2c_bn_s: (1024,)
INFO net.py:  91: res4_4_branch2c_bn_b loaded from weights file into gpu_0/res4_4_branch2c_bn_b: (1024,)
INFO net.py:  91: res4_5_branch2a_w [+ momentum] loaded from weights file into gpu_0/res4_5_branch2a_w: (256, 1024, 1, 1)
INFO net.py:  91: res4_5_branch2a_bn_s loaded from weights file into gpu_0/res4_5_branch2a_bn_s: (256,)
INFO net.py:  91: res4_5_branch2a_bn_b loaded from weights file into gpu_0/res4_5_branch2a_bn_b: (256,)
INFO net.py:  91: res4_5_branch2b_w [+ momentum] loaded from weights file into gpu_0/res4_5_branch2b_w: (256, 256, 3, 3)
INFO net.py:  91: res4_5_branch2b_bn_s loaded from weights file into gpu_0/res4_5_branch2b_bn_s: (256,)
INFO net.py:  91: res4_5_branch2b_bn_b loaded from weights file into gpu_0/res4_5_branch2b_bn_b: (256,)
INFO net.py:  91: res4_5_branch2c_w [+ momentum] loaded from weights file into gpu_0/res4_5_branch2c_w: (1024, 256, 1, 1)
INFO net.py:  91: res4_5_branch2c_bn_s loaded from weights file into gpu_0/res4_5_branch2c_bn_s: (1024,)
INFO net.py:  91: res4_5_branch2c_bn_b loaded from weights file into gpu_0/res4_5_branch2c_bn_b: (1024,)
INFO net.py:  91: res5_0_branch2a_w [+ momentum] loaded from weights file into gpu_0/res5_0_branch2a_w: (512, 1024, 1, 1)
INFO net.py:  91: res5_0_branch2a_bn_s loaded from weights file into gpu_0/res5_0_branch2a_bn_s: (512,)
INFO net.py:  91: res5_0_branch2a_bn_b loaded from weights file into gpu_0/res5_0_branch2a_bn_b: (512,)
INFO net.py:  91: res5_0_branch2b_w [+ momentum] loaded from weights file into gpu_0/res5_0_branch2b_w: (512, 512, 3, 3)
INFO net.py:  91: res5_0_branch2b_bn_s loaded from weights file into gpu_0/res5_0_branch2b_bn_s: (512,)
INFO net.py:  91: res5_0_branch2b_bn_b loaded from weights file into gpu_0/res5_0_branch2b_bn_b: (512,)
INFO net.py:  91: res5_0_branch2c_w [+ momentum] loaded from weights file into gpu_0/res5_0_branch2c_w: (2048, 512, 1, 1)
INFO net.py:  91: res5_0_branch2c_bn_s loaded from weights file into gpu_0/res5_0_branch2c_bn_s: (2048,)
INFO net.py:  91: res5_0_branch2c_bn_b loaded from weights file into gpu_0/res5_0_branch2c_bn_b: (2048,)
INFO net.py:  91: res5_0_branch1_w [+ momentum] loaded from weights file into gpu_0/res5_0_branch1_w: (2048, 1024, 1, 1)
INFO net.py:  91: res5_0_branch1_bn_s loaded from weights file into gpu_0/res5_0_branch1_bn_s: (2048,)
INFO net.py:  91: res5_0_branch1_bn_b loaded from weights file into gpu_0/res5_0_branch1_bn_b: (2048,)
INFO net.py:  91: res5_1_branch2a_w [+ momentum] loaded from weights file into gpu_0/res5_1_branch2a_w: (512, 2048, 1, 1)
INFO net.py:  91: res5_1_branch2a_bn_s loaded from weights file into gpu_0/res5_1_branch2a_bn_s: (512,)
INFO net.py:  91: res5_1_branch2a_bn_b loaded from weights file into gpu_0/res5_1_branch2a_bn_b: (512,)
INFO net.py:  91: res5_1_branch2b_w [+ momentum] loaded from weights file into gpu_0/res5_1_branch2b_w: (512, 512, 3, 3)
INFO net.py:  91: res5_1_branch2b_bn_s loaded from weights file into gpu_0/res5_1_branch2b_bn_s: (512,)
INFO net.py:  91: res5_1_branch2b_bn_b loaded from weights file into gpu_0/res5_1_branch2b_bn_b: (512,)
INFO net.py:  91: res5_1_branch2c_w [+ momentum] loaded from weights file into gpu_0/res5_1_branch2c_w: (2048, 512, 1, 1)
INFO net.py:  91: res5_1_branch2c_bn_s loaded from weights file into gpu_0/res5_1_branch2c_bn_s: (2048,)
INFO net.py:  91: res5_1_branch2c_bn_b loaded from weights file into gpu_0/res5_1_branch2c_bn_b: (2048,)
INFO net.py:  91: res5_2_branch2a_w [+ momentum] loaded from weights file into gpu_0/res5_2_branch2a_w: (512, 2048, 1, 1)
INFO net.py:  91: res5_2_branch2a_bn_s loaded from weights file into gpu_0/res5_2_branch2a_bn_s: (512,)
INFO net.py:  91: res5_2_branch2a_bn_b loaded from weights file into gpu_0/res5_2_branch2a_bn_b: (512,)
INFO net.py:  91: res5_2_branch2b_w [+ momentum] loaded from weights file into gpu_0/res5_2_branch2b_w: (512, 512, 3, 3)
INFO net.py:  91: res5_2_branch2b_bn_s loaded from weights file into gpu_0/res5_2_branch2b_bn_s: (512,)
INFO net.py:  91: res5_2_branch2b_bn_b loaded from weights file into gpu_0/res5_2_branch2b_bn_b: (512,)
INFO net.py:  91: res5_2_branch2c_w [+ momentum] loaded from weights file into gpu_0/res5_2_branch2c_w: (2048, 512, 1, 1)
INFO net.py:  91: res5_2_branch2c_bn_s loaded from weights file into gpu_0/res5_2_branch2c_bn_s: (2048,)
INFO net.py:  91: res5_2_branch2c_bn_b loaded from weights file into gpu_0/res5_2_branch2c_bn_b: (2048,)
INFO net.py:  91: fpn_inner_res5_2_sum_w [+ momentum] loaded from weights file into gpu_0/fpn_inner_res5_2_sum_w: (256, 2048, 1, 1)
INFO net.py:  91: fpn_inner_res5_2_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_inner_res5_2_sum_b: (256,)
INFO net.py:  91: fpn_inner_res4_5_sum_lateral_w [+ momentum] loaded from weights file into gpu_0/fpn_inner_res4_5_sum_lateral_w: (256, 1024, 1, 1)
INFO net.py:  91: fpn_inner_res4_5_sum_lateral_b [+ momentum] loaded from weights file into gpu_0/fpn_inner_res4_5_sum_lateral_b: (256,)
INFO net.py:  91: fpn_inner_res3_3_sum_lateral_w [+ momentum] loaded from weights file into gpu_0/fpn_inner_res3_3_sum_lateral_w: (256, 512, 1, 1)
INFO net.py:  91: fpn_inner_res3_3_sum_lateral_b [+ momentum] loaded from weights file into gpu_0/fpn_inner_res3_3_sum_lateral_b: (256,)
INFO net.py:  91: 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:  91: fpn_res5_2_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_res5_2_sum_b: (256,)
INFO net.py:  91: fpn_res4_5_sum_w [+ momentum] loaded from weights file into gpu_0/fpn_res4_5_sum_w: (256, 256, 3, 3)
INFO net.py:  91: fpn_res4_5_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_res4_5_sum_b: (256,)
INFO net.py:  91: 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:  91: fpn_res3_3_sum_b [+ momentum] loaded from weights file into gpu_0/fpn_res3_3_sum_b: (256,)
INFO net.py:  91: fpn_6_w [+ momentum] loaded from weights file into gpu_0/fpn_6_w: (256, 2048, 3, 3)
INFO net.py:  91: fpn_6_b [+ momentum] loaded from weights file into gpu_0/fpn_6_b: (256,)
INFO net.py:  91: fpn_7_w [+ momentum] loaded from weights file into gpu_0/fpn_7_w: (256, 256, 3, 3)
INFO net.py:  91: fpn_7_b [+ momentum] loaded from weights file into gpu_0/fpn_7_b: (256,)
INFO net.py:  91: retnet_cls_conv_n0_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n0_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_cls_conv_n0_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n0_fpn3_b: (256,)
INFO net.py:  91: retnet_cls_conv_n1_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n1_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_cls_conv_n1_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n1_fpn3_b: (256,)
INFO net.py:  91: retnet_cls_conv_n2_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n2_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_cls_conv_n2_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n2_fpn3_b: (256,)
INFO net.py:  91: retnet_cls_conv_n3_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n3_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_cls_conv_n3_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_cls_conv_n3_fpn3_b: (256,)
INFO net.py:  91: retnet_cls_pred_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_cls_pred_fpn3_w: (720, 256, 3, 3)
INFO net.py:  91: retnet_cls_pred_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_cls_pred_fpn3_b: (720,)
INFO net.py:  91: retnet_bbox_conv_n0_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n0_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_bbox_conv_n0_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n0_fpn3_b: (256,)
INFO net.py:  91: retnet_bbox_conv_n1_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n1_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_bbox_conv_n1_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n1_fpn3_b: (256,)
INFO net.py:  91: retnet_bbox_conv_n2_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n2_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_bbox_conv_n2_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n2_fpn3_b: (256,)
INFO net.py:  91: retnet_bbox_conv_n3_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n3_fpn3_w: (256, 256, 3, 3)
INFO net.py:  91: retnet_bbox_conv_n3_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_bbox_conv_n3_fpn3_b: (256,)
INFO net.py:  91: retnet_bbox_pred_fpn3_w [+ momentum] loaded from weights file into gpu_0/retnet_bbox_pred_fpn3_w: (36, 256, 3, 3)
INFO net.py:  91: retnet_bbox_pred_fpn3_b [+ momentum] loaded from weights file into gpu_0/retnet_bbox_pred_fpn3_b: (36,)
INFO net.py: 125: res3_1_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res2_2_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res3_3_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_4_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res4_5_branch2b_b preserved in workspace (unused)
INFO net.py: 125: conv1_b preserved in workspace (unused)
INFO net.py: 125: fc1000_b preserved in workspace (unused)
INFO net.py: 125: fc1000_w preserved in workspace (unused)
INFO net.py: 125: res4_0_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res4_1_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res5_0_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res4_5_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res3_2_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res4_3_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res2_0_branch1_b preserved in workspace (unused)
INFO net.py: 125: res2_1_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_0_branch1_b preserved in workspace (unused)
INFO net.py: 125: res2_2_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res5_1_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res2_1_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res3_2_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res3_0_branch1_b preserved in workspace (unused)
INFO net.py: 125: res4_2_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res2_0_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res5_2_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res4_1_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_0_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res4_0_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_5_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_2_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res2_1_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res3_1_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res3_0_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res2_2_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res3_1_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res5_1_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res5_1_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_4_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res5_2_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res3_3_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res3_2_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res3_3_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res4_1_branch2b_b preserved in workspace (unused)
INFO net.py: 125: res4_2_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res2_0_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_4_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res4_3_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res5_0_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res5_2_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res5_0_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res3_0_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res5_0_branch1_b preserved in workspace (unused)
INFO net.py: 125: res3_0_branch2c_b preserved in workspace (unused)
INFO net.py: 125: res2_0_branch2a_b preserved in workspace (unused)
INFO net.py: 125: res4_3_branch2c_b preserved in workspace (unused)
I0124 15:09:25.705162 23889 net_dag_utils.cc:118] Operator graph pruning prior to chain compute took: 7.5954e-05 secs
I0124 15:09:25.705276 23889 net_dag.cc:61] Number of parallel execution chains 41 Number of operators = 281
Traceback (most recent call last):
  File "tools/infer_simple.py", line 147, in <module>
    main(args)
  File "tools/infer_simple.py", line 99, in main
    model = infer_engine.initialize_model_from_cfg()
  File "/home/ecli/detectron/lib/core/test_engine.py", line 226, in initialize_model_from_cfg
    workspace.CreateNet(model.conv_body_net)
  File "/usr/local/caffe2/python/model_helper.py", line 468, in __getattr__
    ','.join(workspace.C.nearby_opnames(op_type)) + ']'
AttributeError: Method conv_body_net is not a registered operator. Did you mean: []

[learnbott]

EDIT: turns out I love Detectron so much I cloned it twice. Both infer.py and infer_simple.py work great for retinanet. Thank you so much for fixing this!

[ir413]

Hi @moyans, please make sure that you’ve pulled the latest master.