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| author | Raghuveer Devulapalli <raghuveer.devulapalli@intel.com> | 2019-05-20 10:13:08 -0700 |
|---|---|---|
| committer | Raghuveer Devulapalli <raghuveer.devulapalli@intel.com> | 2019-08-03 10:50:04 -0700 |
| commit | bca96282530fc15dc86c78b640a7b87581885513 (patch) | |
| tree | eb9c88f12d5b111815d659d77ab40a01ab92df42 /numpy | |
| parent | d56fbfda94a689e855ce8679c5828f7a729d777a (diff) | |
| download | numpy-bca96282530fc15dc86c78b640a7b87581885513.tar.gz | |
TEST: adding tests to validate AVX sin/cos implementation
Diffstat (limited to 'numpy')
| -rw-r--r-- | numpy/core/src/umath/simd.inc.src | 2 | ||||
| -rw-r--r-- | numpy/core/tests/test_umath.py | 15 |
2 files changed, 14 insertions, 3 deletions
diff --git a/numpy/core/src/umath/simd.inc.src b/numpy/core/src/umath/simd.inc.src index 7bd5aa2b5..07a3c19a4 100644 --- a/numpy/core/src/umath/simd.inc.src +++ b/numpy/core/src/umath/simd.inc.src @@ -164,7 +164,7 @@ run_unary_@isa@_@func@_FLOAT(char **args, npy_intp *dimensions, npy_intp *steps) #if defined HAVE_ATTRIBUTE_TARGET_@ISA@_WITH_INTRINSICS && defined NPY_HAVE_SSE2_INTRINSICS static NPY_INLINE void -@ISA@_sincos_FLOAT(npy_float *, npy_float *, const npy_int n, char*); +@ISA@_sincos_FLOAT(npy_float *, npy_float *, const npy_intp n, char*); #endif /**end repeat**/ diff --git a/numpy/core/tests/test_umath.py b/numpy/core/tests/test_umath.py index 0948cbfe6..747d893c2 100644 --- a/numpy/core/tests/test_umath.py +++ b/numpy/core/tests/test_umath.py @@ -695,7 +695,7 @@ class TestSpecialFloats(object): assert_raises(FloatingPointError, np.cos, np.float32(np.inf)) -class TestExpLogFloat32(object): +class TestSIMDFloat32(object): def test_exp_float32(self): np.random.seed(42) x_f32 = np.float32(np.random.uniform(low=0.0,high=88.1,size=1000000)) @@ -708,7 +708,14 @@ class TestExpLogFloat32(object): x_f64 = np.float64(x_f32) assert_array_max_ulp(np.log(x_f32), np.float32(np.log(x_f64)), maxulp=3.9) - def test_strided_exp_log_float32(self): + def test_sincos_float32(self): + np.random.seed(42) + x_f32 = np.float32(np.random.uniform(low=-100.,high=100.,size=1000000)) + x_f64 = np.float64(x_f32) + assert_array_max_ulp(np.sin(x_f32), np.float32(np.sin(x_f64)), maxulp=1.5) + assert_array_max_ulp(np.cos(x_f32), np.float32(np.cos(x_f64)), maxulp=1.5) + + def test_strided_float32(self): np.random.seed(42) strides = np.random.randint(low=-100, high=100, size=100) sizes = np.random.randint(low=1, high=2000, size=100) @@ -716,9 +723,13 @@ class TestExpLogFloat32(object): x_f32 = np.float32(np.random.uniform(low=0.01,high=88.1,size=ii)) exp_true = np.exp(x_f32) log_true = np.log(x_f32) + sin_true = np.sin(x_f32) + cos_true = np.cos(x_f32) for jj in strides: assert_array_almost_equal_nulp(np.exp(x_f32[::jj]), exp_true[::jj], nulp=2) assert_array_almost_equal_nulp(np.log(x_f32[::jj]), log_true[::jj], nulp=2) + assert_array_almost_equal_nulp(np.sin(x_f32[::jj]), sin_true[::jj], nulp=2) + assert_array_almost_equal_nulp(np.cos(x_f32[::jj]), cos_true[::jj], nulp=2) class TestLogAddExp(_FilterInvalids): def test_logaddexp_values(self): |