Weight shape mismatch when running crop_align_vggface2_FFHQalign.py

[jhkonan]

After following the instructions to setup the environment, ./insightface_func/models, and ./experiments/pretrained_models...

Running the following command:

python scripts/crop_align_vggface2_FFHQalign.py --input_dir $DATAPATH$/VGGface2/train --output_dir_ffhqalign $ALIGN_OUTDIR$ --mode ffhq --crop_size 256

Results in the following output

input mean and std: 127.5 127.5
find model: ./insightface_func/models/antelope/glintr100.onnx recognition
find model: ./insightface_func/models/antelope/scrfd_10g_bnkps.onnx detection
set det-size: (320, 320)

  0%|                                                   | 0/500 [00:00<?, ?it/s]2021-12-20 16:21:17.029441668 [W:onnxruntime:, execution_frame.cc:811 VerifyOutputSizes] Expected shape from model of {800,10} does not match actual shape of {200,10} for output 500
2021-12-20 16:21:17.029507982 [W:onnxruntime:, execution_frame.cc:811 VerifyOutputSizes] Expected shape from model of {800,4} does not match actual shape of {200,4} for output 497
2021-12-20 16:21:17.029540840 [W:onnxruntime:, execution_frame.cc:811 VerifyOutputSizes] Expected shape from model of {800,1} does not match actual shape of {200,1} for output 494
2021-12-20 16:21:17.029912492 [W:onnxruntime:, execution_frame.cc:811 VerifyOutputSizes] Expected shape from model of {3200,10} does not match actual shape of {800,10} for output 477
2021-12-20 16:21:17.029973895 [W:onnxruntime:, execution_frame.cc:811 VerifyOutputSizes] Expected shape from model of {3200,4} does not match actual shape of {800,4} for output 474
2021-12-20 16:21:17.030020397 [W:onnxruntime:, execution_frame.cc:811 VerifyOutputSizes] Expected shape from model of {3200,1} does not match actual shape of {800,1} for output 471
...

It continues to throw warnings for hundreds of other weights, which I have not included here.

Is this expected behavior?

[NNNNAI]

This is a warning caused by onnxruntime, may be the version of onnxruntime did not match your computer. But it wont affect the effect of the final results.