ai-content-maker/.venv/Lib/site-packages/numba/cuda/tests/cudapy/test_warning.py

140 lines
4.2 KiB
Python

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