def test_init_random_scale_normal_distribution(self, scale):
arr = init_random(1000, 1000, scale, distr='normal')
resulting_scale = np.std(arr.get_value())
assert np.isclose(scale, resulting_scale, 0.01)
def test_init_random_scale(self, scale):
arr = init_random(1000, 1000, scale)
resulting_scale = np.std(arr.get_value())
assert np.isclose(scale, resulting_scale, 0.01)
def test_init_random_shape(self, shape):
arr = init_random(shape[0], shape[1])
resulting_shape = arr.get_value().shape
assert shape == resulting_shape
def test_init_random_scale_normal_distribution(self, scale):
arr = init_random(1000, 1000, scale, distr='normal')
resulting_scale = np.std(arr.get_value())
assert np.isclose(scale, resulting_scale, 0.01)
def test_init_random_scale(self, scale):
arr = init_random(1000, 1000, scale)
resulting_scale = np.std(arr.get_value())
assert np.isclose(scale, resulting_scale, 0.01)
def test_init_random_shape(self, shape):
arr = init_random(shape[0], shape[1])
resulting_shape = arr.get_value().shape
assert shape == resulting_shape
