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C++/CUDA library for SO(3) equivariant operations

License: Mozilla Public License 2.0

Makefile 3.23% C++ 64.44% Python 17.53% Cuda 12.43% Assembly 2.37%

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gelib's Issues

gelib_base star import overwrites python wrapper classes

Hello,

the from gelib_base import * import in the init.py is overwriting all Python wrapper classes. So for example when I use gelib.SO3vec it is from the shared lib gelib_base and not gelib

In [1]: import gelib
Initializing GElib without GPU support.

In [2]: gelib.SO3vec
Out[2]: gelib_base.SO3vec
In [3]: gelib.SO3vec.randn
---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[10], line 1
----> 1 gelib.SO3vec.randn

AttributeError: type object 'gelib_base.SO3vec' has no attribute 'randn'

I commented out the gelib_base import in this PR and it then it works

In [1]: import gelib
Initializing GElib without GPU support.

In [2]: gelib.SO3vec.randn
Out[2]: <bound method SO3vec.randn of <class 'gelib.SO3vec.SO3vec'>>

Cleanup, rename the python interface classes

Current python interface files are named by alphabet letters which are non-descriptive.

Change staticmethods to classmethods

Python alternate constructors currently use staticmethods, when they should use classmethods.

Benchmarks for CUDA version of the library ?

Hey I was curious to benchmark the CUDA kernels mentioned here if its possible in any way.

Failing tests in ci_tests/test_SO3vecArr.py and manual_tests/test_FFT_accuracies.py

In PR #5 I commented out these tests, because they are failing.

GElib/python/tests/ci_tests/test_SO3vecArr.py

Lines 102 to 106 in b2864c6

 # @pytest.mark.parametrize('b', [1, 2, 4])  

 # @pytest.mark.parametrize('a', [1, 2, 4])  

 # @pytest.mark.parametrize('maxl', range(7)) 

 # def test_Fproduct_backprop(self,b,a,maxl): 

 # return

GElib/python/tests/ci_tests/test_SO3vecArr.py

Lines 68 to 83 in b2864c6

 # @pytest.mark.parametrize('b', [1, 2, 4])  

 # @pytest.mark.parametrize('a', [1, 2, 4])  

 # @pytest.mark.parametrize('maxl', range(7)) 

 # def test_Fproduct(self,b,a,maxl): 

 # x=G.SO3vecArr.Frandn(b,[a],maxl) 

 # y=G.SO3vecArr.Frandn(b,[a],maxl) 

 # R = G.SO3element.uniform() 

 # xr=x.rotate(R) 

 # yr=y.rotate(R) 

 # 

 # z=G.Fproduct(x,y,maxl=maxl) 

 # zr=G.Fproduct(xr,yr,maxl=maxl) 

 # rz=z.rotate(R) 

 # 

 # for i in range(maxl+1 ): 

 # assert (torch.allclose(rz.parts[i] , zr.parts[i], rtol=1e-3, atol=1e-2))

GElib/python/tests/manual_tests/test_FFT_accuracies.py

Lines 11 to 63 in 6c394be

 ## TESTS FAILS, ERROR MESSAGE: 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/runner.py:341: in from_call 

 # result: Optional[TResult] = func() 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/runner.py:372: in <lambda> 

 # call = CallInfo.from_call(lambda: list(collector.collect()), "collect") 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:531: in collect 

 # self._inject_setup_module_fixture() 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:545: in _inject_setup_module_fixture 

 # self.obj, ("setUpModule", "setup_module") 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:310: in obj 

 # self._obj = obj = self._getobj() 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:528: in _getobj 

 # return self._importtestmodule() 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:617: in _importtestmodule 

 # mod = import_path(self.path, mode=importmode, root=self.config.rootpath) 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/pathlib.py:565: in import_path 

 # importlib.import_module(module_name) 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/importlib/__init__.py:126: in import_module 

 # return _bootstrap._gcd_import(name[level:], package, level) 

 # <frozen importlib._bootstrap>:1050: in _gcd_import 

 # ??? 

 # <frozen importlib._bootstrap>:1027: in _find_and_load 

 # ??? 

 # <frozen importlib._bootstrap>:1006: in _find_and_load_unlocked 

 # ??? 

 # <frozen importlib._bootstrap>:688: in _load_unlocked 

 # ??? 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/assertion/rewrite.py:178: in exec_module 

 # exec(co, module.__dict__) 

 # python/tests/manual_tests/test_FFT_accuracies.py:12: in <module> 

 # inverse = gelib.SO3iFFT(signals, bandwidth) 

 # python/src/gelib/SO3vec.py:600: in SO3iFFT 

 # return v.iFFT(N) 

 # python/src/gelib/SO3vec.py:246: in iFFT 

 # return SO3vec_iFFTFn.apply(_N,*(self.parts)) 

 # /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/torch/autograd/function.py:506: in apply 

 # return super().apply(*args, **kwargs) # type: ignore[misc] 

 # python/src/gelib/SO3vec.py:467: in forward 

 # _r=ctensorb.view(r) 

 # E RuntimeError: expected scalar type ComplexFloat 

 #for bandwidth in range(1, 101): 

 # inverse = gelib.SO3iFFT(signals, bandwidth) 

 # signals_ = gelib.SO3FFT(inverse, maxl) 

 # sum_errors = 0 

 # total_elems = 0 

 # for l in range(len(signals.parts)): 

 # error = torch.sum(torch.abs(torch.tensor(signals.parts[l]) - torch.tensor(signals_.parts[l]))) 

 # print(torch.tensor(error)) 

 # total_elems += signals.parts[l].numel() 

 # average_error = sum_errors / total_elems 

 # print(bandwidth, sum_errors, average_error)

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	# @pytest.mark.parametrize('b', [1, 2, 4])
	# @pytest.mark.parametrize('a', [1, 2, 4])
	# @pytest.mark.parametrize('maxl', range(7))
	# def test_Fproduct_backprop(self,b,a,maxl):
	# return

	## TESTS FAILS, ERROR MESSAGE:
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/runner.py:341: in from_call
	# result: Optional[TResult] = func()
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/runner.py:372: in <lambda>
	# call = CallInfo.from_call(lambda: list(collector.collect()), "collect")
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:531: in collect
	# self._inject_setup_module_fixture()
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:545: in _inject_setup_module_fixture
	# self.obj, ("setUpModule", "setup_module")
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:310: in obj
	# self._obj = obj = self._getobj()
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:528: in _getobj
	# return self._importtestmodule()
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/python.py:617: in _importtestmodule
	# mod = import_path(self.path, mode=importmode, root=self.config.rootpath)
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/pathlib.py:565: in import_path
	# importlib.import_module(module_name)
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/importlib/__init__.py:126: in import_module
	# return _bootstrap._gcd_import(name[level:], package, level)
	# <frozen importlib._bootstrap>:1050: in _gcd_import
	# ???
	# <frozen importlib._bootstrap>:1027: in _find_and_load
	# ???
	# <frozen importlib._bootstrap>:1006: in _find_and_load_unlocked
	# ???
	# <frozen importlib._bootstrap>:688: in _load_unlocked
	# ???
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/_pytest/assertion/rewrite.py:178: in exec_module
	# exec(co, module.__dict__)
	# python/tests/manual_tests/test_FFT_accuracies.py:12: in <module>
	# inverse = gelib.SO3iFFT(signals, bandwidth)
	# python/src/gelib/SO3vec.py:600: in SO3iFFT
	# return v.iFFT(N)
	# python/src/gelib/SO3vec.py:246: in iFFT
	# return SO3vec_iFFTFn.apply(_N,*(self.parts))
	# /opt/anaconda3/envs/gelib-test-ci/lib/python3.10/site-packages/torch/autograd/function.py:506: in apply
	# return super().apply(args, *kwargs) # type: ignore[misc]
	# python/src/gelib/SO3vec.py:467: in forward
	# _r=ctensorb.view(r)
	# E RuntimeError: expected scalar type ComplexFloat


	#for bandwidth in range(1, 101):
	# inverse = gelib.SO3iFFT(signals, bandwidth)
	# signals_ = gelib.SO3FFT(inverse, maxl)
	# sum_errors = 0
	# total_elems = 0
	# for l in range(len(signals.parts)):
	# error = torch.sum(torch.abs(torch.tensor(signals.parts[l]) - torch.tensor(signals_.parts[l])))
	# print(torch.tensor(error))
	# total_elems += signals.parts[l].numel()
	# average_error = sum_errors / total_elems
	# print(bandwidth, sum_errors, average_error)