140 lines
4.2 KiB
Python
140 lines
4.2 KiB
Python
import numpy as np
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from numba import cuda
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from numba.cuda.testing import unittest, CUDATestCase, skip_on_cudasim
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from numba.tests.support import linux_only, override_config
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from numba.core.errors import NumbaPerformanceWarning
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import warnings
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@skip_on_cudasim('cudasim does not raise performance warnings')
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class TestWarnings(CUDATestCase):
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def test_inefficient_launch_configuration(self):
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@cuda.jit
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def kernel():
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pass
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with override_config('CUDA_LOW_OCCUPANCY_WARNINGS', 1):
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with warnings.catch_warnings(record=True) as w:
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kernel[1, 1]()
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self.assertEqual(w[0].category, NumbaPerformanceWarning)
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self.assertIn('Grid size', str(w[0].message))
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self.assertIn('low occupancy', str(w[0].message))
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def test_efficient_launch_configuration(self):
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@cuda.jit
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def kernel():
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pass
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with override_config('CUDA_LOW_OCCUPANCY_WARNINGS', 1):
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with warnings.catch_warnings(record=True) as w:
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kernel[256, 256]()
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self.assertEqual(len(w), 0)
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def test_warn_on_host_array(self):
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@cuda.jit
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def foo(r, x):
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r[0] = x + 1
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N = 10
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arr_f32 = np.zeros(N, dtype=np.float32)
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with override_config('CUDA_WARN_ON_IMPLICIT_COPY', 1):
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with warnings.catch_warnings(record=True) as w:
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foo[1, N](arr_f32, N)
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self.assertEqual(w[0].category, NumbaPerformanceWarning)
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self.assertIn('Host array used in CUDA kernel will incur',
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str(w[0].message))
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self.assertIn('copy overhead', str(w[0].message))
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def test_pinned_warn_on_host_array(self):
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@cuda.jit
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def foo(r, x):
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r[0] = x + 1
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N = 10
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ary = cuda.pinned_array(N, dtype=np.float32)
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with override_config('CUDA_WARN_ON_IMPLICIT_COPY', 1):
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with warnings.catch_warnings(record=True) as w:
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foo[1, N](ary, N)
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self.assertEqual(w[0].category, NumbaPerformanceWarning)
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self.assertIn('Host array used in CUDA kernel will incur',
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str(w[0].message))
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self.assertIn('copy overhead', str(w[0].message))
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def test_nowarn_on_mapped_array(self):
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@cuda.jit
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def foo(r, x):
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r[0] = x + 1
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N = 10
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ary = cuda.mapped_array(N, dtype=np.float32)
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with override_config('CUDA_WARN_ON_IMPLICIT_COPY', 1):
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with warnings.catch_warnings(record=True) as w:
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foo[1, N](ary, N)
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self.assertEqual(len(w), 0)
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@linux_only
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def test_nowarn_on_managed_array(self):
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@cuda.jit
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def foo(r, x):
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r[0] = x + 1
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N = 10
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ary = cuda.managed_array(N, dtype=np.float32)
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with override_config('CUDA_WARN_ON_IMPLICIT_COPY', 1):
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with warnings.catch_warnings(record=True) as w:
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foo[1, N](ary, N)
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self.assertEqual(len(w), 0)
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def test_nowarn_on_device_array(self):
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@cuda.jit
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def foo(r, x):
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r[0] = x + 1
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N = 10
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ary = cuda.device_array(N, dtype=np.float32)
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with override_config('CUDA_WARN_ON_IMPLICIT_COPY', 1):
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with warnings.catch_warnings(record=True) as w:
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foo[1, N](ary, N)
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self.assertEqual(len(w), 0)
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def test_warn_on_debug_and_opt(self):
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with warnings.catch_warnings(record=True) as w:
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cuda.jit(debug=True, opt=True)
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self.assertEqual(len(w), 1)
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self.assertIn('not supported by CUDA', str(w[0].message))
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def test_warn_on_debug_and_opt_default(self):
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with warnings.catch_warnings(record=True) as w:
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cuda.jit(debug=True)
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self.assertEqual(len(w), 1)
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self.assertIn('not supported by CUDA', str(w[0].message))
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def test_no_warn_on_debug_and_no_opt(self):
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with warnings.catch_warnings(record=True) as w:
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cuda.jit(debug=True, opt=False)
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self.assertEqual(len(w), 0)
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def test_no_warn_with_no_debug_and_opt_kwargs(self):
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with warnings.catch_warnings(record=True) as w:
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cuda.jit()
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self.assertEqual(len(w), 0)
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if __name__ == '__main__':
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unittest.main()
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