def test_invalid_shape(self, shape):
dp_array1 = dpnp.arange(10, dtype=dpnp.float64)
dp_array2 = dpnp.arange(5, 15, dtype=dpnp.float64)
dp_out = dpnp.empty(shape, dtype=dpnp.float64)
with pytest.raises(ValueError):
dpnp.power(dp_array1, dp_array2, out=dp_out)
def test_power(array, val, data_type, val_type):
a = numpy.array(array, dtype=data_type)
ia = inp.array(a)
val_ = val_type(val)
result = inp.power(ia, val_)
expected = numpy.power(ia, val_)
numpy.testing.assert_array_equal(expected, result)
def test_power(array, val, data_type, val_type):
np_a = numpy.array(array, dtype=data_type)
dpnp_a = dpnp.array(array, dtype=data_type)
val_ = val_type(val)
result = dpnp.power(dpnp_a, val_)
expected = numpy.power(np_a, val_)
numpy.testing.assert_array_equal(expected, result)
def test_power(self):
array1_data = numpy.arange(10)
array2_data = numpy.arange(5, 15)
out = numpy.empty(10, dtype=numpy.float64)
# DPNP
dp_array1 = dpnp.array(array1_data, dtype=dpnp.float64)
dp_array2 = dpnp.array(array2_data, dtype=dpnp.float64)
dp_out = dpnp.array(out, dtype=dpnp.float64)
result = dpnp.power(dp_array1, dp_array2, out=dp_out)
# original
np_array1 = numpy.array(array1_data, dtype=numpy.float64)
np_array2 = numpy.array(array2_data, dtype=numpy.float64)
expected = numpy.power(np_array1, np_array2, out=out)
numpy.testing.assert_array_equal(expected, result)
def __pow__(self, other):
return dpnp.power(self, other)