Dear sir,
I tried to follow the instruction and I got the error message like below. The suggestions would be very appreciated.
deeplytough) sagemaker-user@default:~/DeeplyTough/deeplytough/misc$ python $DEEPLYTOUGH/deeplytough/scripts/custom_evaluation.py --dataset_subdir 'datasets/custom' --output_dir $DEEPLYTOUGH/results --device 'cpu' --nworkers 1 --net $DEEPLYTOUGH/networks/deeplytough_toughm1_test.pth.tar
HTMD: Logging setup failed
compute 0.pkl.gz... Traceback (most recent call last):
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 95, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 53, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 163, in init
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'cache/sh_cube/0.pkl.gz'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 69, in
main()
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 40, in main
matcher = DeeplyTough(args.net, device=args.device, batch_size=args.batch_size, nworkers=args.nworkers)
File "/home/sagemaker-user/DeeplyTough/deeplytough/matchers/deeply_tough.py", line 24, in init
self.model, self.args = load_model(model_dir, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/predictor.py", line 23, in load_model
model = create_model(checkpoint['args'], PointOfInterestVoxelizedDataset, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 103, in create_model
model = VoxelNetwork(args.model_config, dataset.num_channels)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 70, in init
activation=activation, normalization=normalization, smooth_stride=smooth)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/blocks/gated_block.py", line 80, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/batchnorm.py", line 151, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 239, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 89, in cube_basis_kernels
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 56, in _sample_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 100, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 37, in _sample_sh_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 120, in spherical_harmonics_xyz
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 88, in spherical_harmonics
ModuleNotFoundError: No module named 'lie_learn'
(deeplytough) sagemaker-user@default:~/DeeplyTough/deeplytough/misc$ pip install git+https://github.com/AMLab-Amsterdam/lie_learn
Collecting git+https://github.com/AMLab-Amsterdam/lie_learn
Cloning https://github.com/AMLab-Amsterdam/lie_learn to /tmp/pip-req-build-rwt8n9x_
Running command git clone --filter=blob:none -q https://github.com/AMLab-Amsterdam/lie_learn /tmp/pip-req-build-rwt8n9x_
Resolved https://github.com/AMLab-Amsterdam/lie_learn to commit edf012f5f60af320175d2e6269db78b984b5bfc3
Installing build dependencies ... done
Getting requirements to build wheel ... done
Installing backend dependencies ... done
Preparing metadata (pyproject.toml) ... done
Building wheels for collected packages: UNKNOWN
Building wheel for UNKNOWN (pyproject.toml) ... done
Created wheel for UNKNOWN: filename=UNKNOWN-0.0.0-cp36-cp36m-linux_x86_64.whl size=1343671 sha256=7ffe26379e00be93abd436aa1c794fe782af6b3be6c54195c13d2eda2b32e1e0
Stored in directory: /tmp/pip-ephem-wheel-cache-cbhfqsdr/wheels/91/f0/03/01513832c5bff128b0d43d11f6f66f21dd5037dfabc4d8b5fd
Successfully built UNKNOWN
Installing collected packages: UNKNOWN
Successfully installed UNKNOWN-0.0.0
(deeplytough) sagemaker-user@default:~/DeeplyTough/deeplytough/misc$ python $DEEPLYTOUGH/deeplytough/scripts/custom_evaluation.py --dataset_subdir 'datasets/custom' --output_dir $DEEPLYTOUGH/results --device 'cpu' --nworkers 1 --net $DEEPLYTOUGH/networks/deeplytough_toughm1_test.pth.tar
HTMD: Logging setup failed
compute 0.pkl.gz... Traceback (most recent call last):
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 95, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 53, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 163, in init
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'cache/sh_cube/0.pkl.gz'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 69, in
main()
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 40, in main
matcher = DeeplyTough(args.net, device=args.device, batch_size=args.batch_size, nworkers=args.nworkers)
File "/home/sagemaker-user/DeeplyTough/deeplytough/matchers/deeply_tough.py", line 24, in init
self.model, self.args = load_model(model_dir, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/predictor.py", line 23, in load_model
model = create_model(checkpoint['args'], PointOfInterestVoxelizedDataset, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 103, in create_model
model = VoxelNetwork(args.model_config, dataset.num_channels)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 70, in init
activation=activation, normalization=normalization, smooth_stride=smooth)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/blocks/gated_block.py", line 80, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/batchnorm.py", line 151, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 239, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 89, in cube_basis_kernels
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 56, in _sample_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 100, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 37, in _sample_sh_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 120, in spherical_harmonics_xyz
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 88, in spherical_harmonics
ModuleNotFoundError: No module named 'lie_learn.representations.SO3.spherical_harmonics'
(deeplytough) sagemaker-user@default:/DeeplyTough/deeplytough/misc$ git clone https://github.com/AMLab-Amsterdam/lie_learn && cd lie_learn && python setup.py install && cd .. && rm -rf lie_learn
Cloning into 'lie_learn'...
remote: Enumerating objects: 464, done.
remote: Counting objects: 100% (53/53), done.
remote: Compressing objects: 100% (25/25), done.
remote: Total 464 (delta 38), reused 28 (delta 28), pack-reused 411 (from 2)
Receiving objects: 100% (464/464), 14.57 MiB | 13.56 MiB/s, done.
Resolving deltas: 100% (261/261), done.
Compiling lie_learn/groups/SO3.pyx because it changed.
Compiling lie_learn/representations/SO3/irrep_bases.pyx because it changed.
Compiling lie_learn/representations/SO3/pinchon_hoggan/pinchon_hoggan.pyx because it changed.
Compiling lie_learn/spaces/spherical_quadrature.pyx because it changed.
[1/4] Cythonizing lie_learn/groups/SO3.pyx
warning: lie_learn/groups/SO3.pyx:100:8: Unreachable code
[2/4] Cythonizing lie_learn/representations/SO3/irrep_bases.pyx
[3/4] Cythonizing lie_learn/representations/SO3/pinchon_hoggan/pinchon_hoggan.pyx
[4/4] Cythonizing lie_learn/spaces/spherical_quadrature.pyx
running install
running bdist_egg
running egg_info
creating UNKNOWN.egg-info
writing UNKNOWN.egg-info/PKG-INFO
writing dependency_links to UNKNOWN.egg-info/dependency_links.txt
writing top-level names to UNKNOWN.egg-info/top_level.txt
writing manifest file 'UNKNOWN.egg-info/SOURCES.txt'
error: each element of 'ext_modules' option must be an Extension instance or 2-tuple
(deeplytough) sagemaker-user@default:/DeeplyTough/deeplytough/misc/lie_learn$ python $DEEPLYTOUGH/deeplytough/scripts/custom_evaluation.py --dataset_subdir 'datasets/custom' --output_dir $DEEPLYTOUGH/results --device 'cpu' --nworkers 1 --net $DEEPLYTOUGH/networks/deeplytough_toughm1_test.pth.tar
HTMD: Logging setup failed
compute 0.pkl.gz... save 0.pkl.gz... done
compute 0.pkl.gz... Traceback (most recent call last):
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 95, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 53, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 163, in init
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'cache/trans_Q/0.pkl.gz'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 69, in
main()
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 40, in main
matcher = DeeplyTough(args.net, device=args.device, batch_size=args.batch_size, nworkers=args.nworkers)
File "/home/sagemaker-user/DeeplyTough/deeplytough/matchers/deeply_tough.py", line 24, in init
self.model, self.args = load_model(model_dir, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/predictor.py", line 23, in load_model
model = create_model(checkpoint['args'], PointOfInterestVoxelizedDataset, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 103, in create_model
model = VoxelNetwork(args.model_config, dataset.num_channels)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 70, in init
activation=activation, normalization=normalization, smooth_stride=smooth)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/blocks/gated_block.py", line 80, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/batchnorm.py", line 151, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 239, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 89, in cube_basis_kernels
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 59, in _sample_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 100, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 262, in basis_transformation_Q_J
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 262, in
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 250, in _sylvester_submatrix
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 246, in _R_tensor
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 69, in irr_repr
File "/home/sagemaker-user/DeeplyTough/deeplytough/misc/lie_learn/lie_learn/representations/SO3/wigner_d.py", line 5, in
from lie_learn.representations.SO3.irrep_bases import change_of_basis_matrix
ModuleNotFoundError: No module named 'lie_learn.representations.SO3.irrep_bases'
Dear sir,
I tried to follow the instruction and I got the error message like below. The suggestions would be very appreciated.
deeplytough) sagemaker-user@default:~/DeeplyTough/deeplytough/misc$ python $DEEPLYTOUGH/deeplytough/scripts/custom_evaluation.py --dataset_subdir 'datasets/custom' --output_dir $DEEPLYTOUGH/results --device 'cpu' --nworkers 1 --net $DEEPLYTOUGH/networks/deeplytough_toughm1_test.pth.tar
HTMD: Logging setup failed
compute 0.pkl.gz... Traceback (most recent call last):
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 95, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 53, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 163, in init
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'cache/sh_cube/0.pkl.gz'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 69, in
main()
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 40, in main
matcher = DeeplyTough(args.net, device=args.device, batch_size=args.batch_size, nworkers=args.nworkers)
File "/home/sagemaker-user/DeeplyTough/deeplytough/matchers/deeply_tough.py", line 24, in init
self.model, self.args = load_model(model_dir, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/predictor.py", line 23, in load_model
model = create_model(checkpoint['args'], PointOfInterestVoxelizedDataset, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 103, in create_model
model = VoxelNetwork(args.model_config, dataset.num_channels)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 70, in init
activation=activation, normalization=normalization, smooth_stride=smooth)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/blocks/gated_block.py", line 80, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/batchnorm.py", line 151, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 239, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 89, in cube_basis_kernels
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 56, in _sample_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 100, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 37, in _sample_sh_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 120, in spherical_harmonics_xyz
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 88, in spherical_harmonics
ModuleNotFoundError: No module named 'lie_learn'
(deeplytough) sagemaker-user@default:~/DeeplyTough/deeplytough/misc$ pip install git+https://github.com/AMLab-Amsterdam/lie_learn
Collecting git+https://github.com/AMLab-Amsterdam/lie_learn
Cloning https://github.com/AMLab-Amsterdam/lie_learn to /tmp/pip-req-build-rwt8n9x_
Running command git clone --filter=blob:none -q https://github.com/AMLab-Amsterdam/lie_learn /tmp/pip-req-build-rwt8n9x_
Resolved https://github.com/AMLab-Amsterdam/lie_learn to commit edf012f5f60af320175d2e6269db78b984b5bfc3
Installing build dependencies ... done
Getting requirements to build wheel ... done
Installing backend dependencies ... done
Preparing metadata (pyproject.toml) ... done
Building wheels for collected packages: UNKNOWN
Building wheel for UNKNOWN (pyproject.toml) ... done
Created wheel for UNKNOWN: filename=UNKNOWN-0.0.0-cp36-cp36m-linux_x86_64.whl size=1343671 sha256=7ffe26379e00be93abd436aa1c794fe782af6b3be6c54195c13d2eda2b32e1e0
Stored in directory: /tmp/pip-ephem-wheel-cache-cbhfqsdr/wheels/91/f0/03/01513832c5bff128b0d43d11f6f66f21dd5037dfabc4d8b5fd
Successfully built UNKNOWN
Installing collected packages: UNKNOWN
Successfully installed UNKNOWN-0.0.0
(deeplytough) sagemaker-user@default:~/DeeplyTough/deeplytough/misc$ python $DEEPLYTOUGH/deeplytough/scripts/custom_evaluation.py --dataset_subdir 'datasets/custom' --output_dir $DEEPLYTOUGH/results --device 'cpu' --nworkers 1 --net $DEEPLYTOUGH/networks/deeplytough_toughm1_test.pth.tar
HTMD: Logging setup failed
compute 0.pkl.gz... Traceback (most recent call last):
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 95, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 53, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 163, in init
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'cache/sh_cube/0.pkl.gz'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 69, in
main()
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 40, in main
matcher = DeeplyTough(args.net, device=args.device, batch_size=args.batch_size, nworkers=args.nworkers)
File "/home/sagemaker-user/DeeplyTough/deeplytough/matchers/deeply_tough.py", line 24, in init
self.model, self.args = load_model(model_dir, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/predictor.py", line 23, in load_model
model = create_model(checkpoint['args'], PointOfInterestVoxelizedDataset, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 103, in create_model
model = VoxelNetwork(args.model_config, dataset.num_channels)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 70, in init
activation=activation, normalization=normalization, smooth_stride=smooth)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/blocks/gated_block.py", line 80, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/batchnorm.py", line 151, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 239, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 89, in cube_basis_kernels
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 56, in _sample_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 100, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 37, in _sample_sh_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 120, in spherical_harmonics_xyz
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 88, in spherical_harmonics
ModuleNotFoundError: No module named 'lie_learn.representations.SO3.spherical_harmonics'
(deeplytough) sagemaker-user@default:
/DeeplyTough/deeplytough/misc$ git clone https://github.com/AMLab-Amsterdam/lie_learn && cd lie_learn && python setup.py install && cd .. && rm -rf lie_learn/DeeplyTough/deeplytough/misc/lie_learn$ python $DEEPLYTOUGH/deeplytough/scripts/custom_evaluation.py --dataset_subdir 'datasets/custom' --output_dir $DEEPLYTOUGH/results --device 'cpu' --nworkers 1 --net $DEEPLYTOUGH/networks/deeplytough_toughm1_test.pth.tarCloning into 'lie_learn'...
remote: Enumerating objects: 464, done.
remote: Counting objects: 100% (53/53), done.
remote: Compressing objects: 100% (25/25), done.
remote: Total 464 (delta 38), reused 28 (delta 28), pack-reused 411 (from 2)
Receiving objects: 100% (464/464), 14.57 MiB | 13.56 MiB/s, done.
Resolving deltas: 100% (261/261), done.
Compiling lie_learn/groups/SO3.pyx because it changed.
Compiling lie_learn/representations/SO3/irrep_bases.pyx because it changed.
Compiling lie_learn/representations/SO3/pinchon_hoggan/pinchon_hoggan.pyx because it changed.
Compiling lie_learn/spaces/spherical_quadrature.pyx because it changed.
[1/4] Cythonizing lie_learn/groups/SO3.pyx
warning: lie_learn/groups/SO3.pyx:100:8: Unreachable code
[2/4] Cythonizing lie_learn/representations/SO3/irrep_bases.pyx
[3/4] Cythonizing lie_learn/representations/SO3/pinchon_hoggan/pinchon_hoggan.pyx
[4/4] Cythonizing lie_learn/spaces/spherical_quadrature.pyx
running install
running bdist_egg
running egg_info
creating UNKNOWN.egg-info
writing UNKNOWN.egg-info/PKG-INFO
writing dependency_links to UNKNOWN.egg-info/dependency_links.txt
writing top-level names to UNKNOWN.egg-info/top_level.txt
writing manifest file 'UNKNOWN.egg-info/SOURCES.txt'
error: each element of 'ext_modules' option must be an Extension instance or 2-tuple
(deeplytough) sagemaker-user@default:
HTMD: Logging setup failed
compute 0.pkl.gz... save 0.pkl.gz... done
compute 0.pkl.gz... Traceback (most recent call last):
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 95, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 53, in open
binary_file = GzipFile(filename, gz_mode, compresslevel)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/gzip.py", line 163, in init
fileobj = self.myfileobj = builtins.open(filename, mode or 'rb')
FileNotFoundError: [Errno 2] No such file or directory: 'cache/trans_Q/0.pkl.gz'
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 69, in
main()
File "/home/sagemaker-user/DeeplyTough/deeplytough/scripts/custom_evaluation.py", line 40, in main
matcher = DeeplyTough(args.net, device=args.device, batch_size=args.batch_size, nworkers=args.nworkers)
File "/home/sagemaker-user/DeeplyTough/deeplytough/matchers/deeply_tough.py", line 24, in init
self.model, self.args = load_model(model_dir, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/predictor.py", line 23, in load_model
model = create_model(checkpoint['args'], PointOfInterestVoxelizedDataset, device)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 103, in create_model
model = VoxelNetwork(args.model_config, dataset.num_channels)
File "/home/sagemaker-user/DeeplyTough/deeplytough/engine/models.py", line 70, in init
activation=activation, normalization=normalization, smooth_stride=smooth)
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/blocks/gated_block.py", line 80, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/batchnorm.py", line 151, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 239, in init
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 89, in cube_basis_kernels
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/kernel.py", line 59, in _sample_cube
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/util/cache_file.py", line 100, in wrapper
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 262, in basis_transformation_Q_J
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 262, in
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 250, in _sylvester_submatrix
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 246, in _R_tensor
File "/home/sagemaker-user/.conda/envs/deeplytough/lib/python3.6/site-packages/se3cnn-0.0.0-py3.6.egg/se3cnn/SO3.py", line 69, in irr_repr
File "/home/sagemaker-user/DeeplyTough/deeplytough/misc/lie_learn/lie_learn/representations/SO3/wigner_d.py", line 5, in
from lie_learn.representations.SO3.irrep_bases import change_of_basis_matrix
ModuleNotFoundError: No module named 'lie_learn.representations.SO3.irrep_bases'