Open suranap opened 3 months ago
Python : 3.10.14 | packaged by conda-forge | (main, Mar 20 2024, 12:45:18) [GCC 12.3.0] Platform : Linux-5.4.0-169-generic-x86_64-with-glibc2.31 Legion : legion-24.03.0 Legate : 24.01.00.dev+38.g90944d7.dirty Cunumeric : 24.01.00.dev+32.g364e95dc.dirty Numpy : 1.26.4 Scipy : 1.13.1 Numba : 0.59.1 CTK package : cuda-version-11.7-h67201e3_3 (conda-forge) GPU driver : 535.54.03 GPU devices : GPU 0: Tesla P100-SXM2-16GB GPU 1: Tesla P100-SXM2-16GB GPU 2: Tesla P100-SXM2-16GB GPU 3: Tesla P100-SXM2-16GB
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>>> import numpy as np >>> tmp = list(range(20)) >>> np.unique(np.array(tmp).reshape(10,2), axis=0) array([[ 0, 1], [ 2, 3], [ 4, 5], [ 6, 7], [ 8, 9], [10, 11], [12, 13], [14, 15], [16, 17], [18, 19]])
>>> import cunumeric as cnp >>> cnp.unique(np.array(tmp).reshape(10,2), axis=0) array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19])
Furthermore, I ran numpy's tests against cunumeric. PyTest reports the following errors for TestUnique:
FAILED test_arraysetops.py::TestUnique::test_unique_1d - NotImplementedError: cuNumeric does not support dtype=float128 FAILED test_arraysetops.py::TestUnique::test_unique_axis_errors - NotImplementedError: cuNumeric does not support dtype=object FAILED test_arraysetops.py::TestUnique::test_unique_axis_list - AssertionError: FAILED test_arraysetops.py::TestUnique::test_unique_axis - AssertionError: FAILED test_arraysetops.py::TestUnique::test_unique_axis_zeros - AssertionError: FAILED test_arraysetops.py::TestUnique::test_unique_masked - NotImplementedError: Keyword arguments for `unique` are not yet supported FAILED test_arraysetops.py::TestUnique::test_unique_sort_order_with_axis - AssertionError: FAILED test_arraysetops.py::TestUnique::test_unique_nanequals - TypeError: unique() got an unexpected keyword argument 'equal_nan'
In fact, you could port all the tests from numpy to check how you're doing on compatibility.
see above
Software versions
Python : 3.10.14 | packaged by conda-forge | (main, Mar 20 2024, 12:45:18) [GCC 12.3.0] Platform : Linux-5.4.0-169-generic-x86_64-with-glibc2.31 Legion : legion-24.03.0 Legate : 24.01.00.dev+38.g90944d7.dirty Cunumeric : 24.01.00.dev+32.g364e95dc.dirty Numpy : 1.26.4 Scipy : 1.13.1 Numba : 0.59.1 CTK package : cuda-version-11.7-h67201e3_3 (conda-forge) GPU driver : 535.54.03 GPU devices : GPU 0: Tesla P100-SXM2-16GB GPU 1: Tesla P100-SXM2-16GB GPU 2: Tesla P100-SXM2-16GB GPU 3: Tesla P100-SXM2-16GB
Jupyter notebook / Jupyter Lab version
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Expected behavior
Observed behavior
Furthermore, I ran numpy's tests against cunumeric. PyTest reports the following errors for TestUnique:
In fact, you could port all the tests from numpy to check how you're doing on compatibility.
Example code or instructions
Stack traceback or browser console output
No response