Train error

[FirokOtaku]

Reproduce steps:

conda create -n deep-hawkeye python=3.6
conda activate deep-hawkeye
pip install opencv-python scipy

# pip install torch==1.8.0+cu111 torchvision==0.9.0+cu111 torchaudio==0.8.0 -f https://download.pytorch.org/whl/torch_stable.html
# command above is broken, used following instead ( provided by PyTorch website: https://pytorch.org/get-started/previous-versions/ )
conda install pytorch==1.8.0 torchvision==0.9.0 torchaudio==0.8.0 cudatoolkit=11.1 -c pytorch -c conda-forge

# conda install -c pytorch faiss-gpu cudatoolkit=10.2
# command above is broken too, used following instead ( provided by Anaconda package search results: https://anaconda.org/conda-forge/faiss-gpu )
conda install -c conda-forge faiss-gpu

# try to start training
python demo_train.py -d "./workdir/demo_data/grid/normal_data" -c "grid" --batch_size=64 --weight_path="./workdir/wide_r50_2.pth" --normal_feature_save_path="./workdir/export_pth" --model_device="cuda:0" --max_cluster_image_num=1000 --index_build_device=-1

Then comes a TypeError:

Traceback (most recent call last):
  File "demo_train.py", line 42, in <module>
    gen_lib(train_img_path, cls)
  File "demo_train.py", line 33, in __call__
    self.train_model.train()
  File "T:\Projects\DeepHawkeye\src\train.py", line 105, in train
    np.arange(0, seg_batch_size),
  File "C:\Users\firok\.conda\envs\deep-hawkeye\lib\site-packages\faiss\__init__.py", line 112, in replacement_add_with_ids
    self.add_with_ids_c(n, swig_ptr(x), swig_ptr(ids))
  File "C:\Users\firok\.conda\envs\deep-hawkeye\lib\site-packages\faiss\swigfaiss_avx2.py", line 3898, in add_with_ids
    return _swigfaiss_avx2.IndexIVFPQ_add_with_ids(self, n, x, xids)
TypeError: Wrong number or type of arguments for overloaded function 'IndexIVFPQ_add_with_ids'.
  Possible C/C++ prototypes are:
    faiss::IndexIVFPQ::add_with_ids(faiss::Index::idx_t,float const *,faiss::Index::idx_t const *)
    faiss::IndexIVFPQ::add_with_ids(faiss::Index::idx_t,float const *)

---

Environment:

Win x64 22H2

conda list -n deep-hawkeye

# Name                    Version                   Build  Channel
blas                      2.118                       mkl    conda-forge
blas-devel                3.9.0              18_win64_mkl    conda-forge
bzip2                     1.0.8                he774522_0
ca-certificates           2023.7.22            h56e8100_0    conda-forge
cudatoolkit               11.1.1              heb2d755_10    conda-forge
dataclasses               0.8                pyh787bdff_2    conda-forge
faiss                     1.7.0           py36cuda111hfcdb8f5_8_cuda    conda-forge
faiss-gpu                 1.7.0                h278398d_8    conda-forge
freetype                  2.7                      vc14_0    conda-forge
intel-openmp              2023.2.0         h57928b3_49502    conda-forge
jpeg                      9b                   hb83a4c4_2
libblas                   3.9.0              18_win64_mkl    conda-forge
libcblas                  3.9.0              18_win64_mkl    conda-forge
libfaiss                  1.7.0           cuda111hbde4fbc_8_cuda    conda-forge
libfaiss-avx2             1.7.0           cuda111h1234567_8_cuda    conda-forge
libffi                    3.4.4                hd77b12b_0
liblapack                 3.9.0              18_win64_mkl    conda-forge
liblapacke                3.9.0              18_win64_mkl    conda-forge
libpng                    1.6.37               h1d00b33_2    conda-forge
libtiff                   4.0.9                hf1753bf_1    conda-forge
libuv                     1.44.2               h8ffe710_0    conda-forge
m2w64-gcc-libgfortran     5.3.0                         6    conda-forge
m2w64-gcc-libs            5.3.0                         7    conda-forge
m2w64-gcc-libs-core       5.3.0                         7    conda-forge
m2w64-gmp                 6.1.0                         2    conda-forge
m2w64-libwinpthread-git   5.0.0.4634.697f757               2    conda-forge
mkl                       2022.1.0           h6a75c08_874    conda-forge
mkl-devel                 2022.1.0           h57928b3_875    conda-forge
mkl-include               2022.1.0           h6a75c08_874    conda-forge
msys2-conda-epoch         20160418                      1    conda-forge
ninja                     1.11.0               h2d74725_0    conda-forge
numpy                     1.26.0                   pypi_0    pypi
olefile                   0.46               pyh9f0ad1d_1    conda-forge
opencv-python             4.8.0.76                 pypi_0    pypi
openssl                   3.1.3                hcfcfb64_0    conda-forge
pillow                    4.2.1                    py36_0    conda-forge
pip                       21.3.1             pyhd8ed1ab_0    conda-forge
python                    3.6.15          h39d44d4_0_cpython    conda-forge
python_abi                3.6                     2_cp36m    conda-forge
pytorch                   1.8.0           py3.6_cuda11.1_cudnn8_0    pytorch
scipy                     1.11.2                   pypi_0    pypi
setuptools                58.0.4           py36ha15d459_2    conda-forge
sqlite                    3.41.2               h2bbff1b_0
tbb                       2021.5.0             h2d74725_1    conda-forge
tk                        8.6.12               h2bbff1b_0
torchaudio                0.8.0                      py36    pytorch
torchvision               0.9.0                py36_cu111    pytorch
typing_extensions         4.1.1              pyha770c72_0    conda-forge
tzdata                    2023c                h04d1e81_0
ucrt                      10.0.22621.0         h57928b3_0    conda-forge
vc                        14.2                 h21ff451_1
vc14_runtime              14.36.32532         hdcecf7f_17    conda-forge
vs2015_runtime            14.36.32532         h05e6639_17    conda-forge
wheel                     0.37.1             pyhd8ed1ab_0    conda-forge
xz                        5.4.2                h8cc25b3_0
zlib                      1.2.13               h8cc25b3_0

---

# BTW, parameter type conversion code missed several type declarations and would cause TypeError.
# Here is the fix
def get_train_args():
    parser = argparse.ArgumentParser()
    parser.add_argument('-d','--total_img_paths', type=str, default=None)
    parser.add_argument('-c','--category', type=str, default=None, help='category of sample')
    parser.add_argument('--batch_size', default=64, type=int)
    parser.add_argument('--embedding_layers', choices=['1_2', '2_3'], default='2_3')
    parser.add_argument('--input_size', default=(224, 224))
    parser.add_argument('--weight_path', default='./weights/wide_r50_2.pth')
    parser.add_argument('--normal_feature_save_path', default=f"./index_lib")
    parser.add_argument('--model_device', default="cuda:0")
    parser.add_argument('--max_cluster_image_num', default=1000, type=int, help='depend on CPU memory, more than total images number')
    parser.add_argument('--index_build_device', default=-1, type=int, help='CPU:-1 ,GPU number eg: 0, 1, 2 (only on Linux)')