def test_quantile_include_NaN(self):
input_data = np.random.randn(2, 3, 4)
input_data[0, 1, 1] = np.nan
x = paddle.to_tensor(input_data)
paddle_res = paddle.quantile(x, q=0.35, axis=0)
np_res = np.quantile(input_data, q=0.35, axis=0)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res,
equal_nan=True))
def test_quantile_with_keepdim_and_multiple_axis(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=0.1, axis=[1, 4], keepdim=True)
np_res = np.quantile(self.input_data,
q=0.1,
axis=[1, 4],
keepdims=True)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_quantile_multiple_axis_keepdim(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x,
q=[0.1, 0.2, 0.3],
axis=[1, 2],
keepdim=True)
np_res = np.quantile(self.input_data,
q=[0.1, 0.2, 0.3],
axis=[1, 2],
keepdims=True)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_axis_value_error_3():
paddle_res = paddle.quantile(self.x, q=0.4, axis=[])
def test_axis_type_error_2():
paddle_res = paddle.quantile(self.x, q=0.4, axis=[1, 0.4])
def test_x_type_error():
x = [1, 3, 4]
paddle_res = paddle.quantile(x, q=0.9)
def test_q_range_error_3():
paddle_res = paddle.quantile(self.x, q=[])
def test_q_range_error_2():
paddle_res = paddle.quantile(self.x, q=[0.2, -0.3])
def test_quantile_multiple_axis(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=[0.2, 0.67], axis=[1, -1])
np_res = np.quantile(self.input_data, q=[0.2, 0.67], axis=[1, -1])
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_quantile(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=[0.3, 0.44], axis=-2)
np_res = np.quantile(self.input_data, q=[0.3, 0.44], axis=-2)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_quantile_include_NaN(self):
input_data = np.random.randn(2, 3, 4)
input_data[0, 1, 1] = np.nan
x = paddle.to_tensor(input_data)
paddle_res = paddle.quantile(x, q=0.35, axis=0)
self.assertTrue(paddle.isnan(paddle_res[1, 1]))
def test_quantile_with_boundary_q(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=0, axis=3)
np_res = np.quantile(self.input_data, q=0, axis=3)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_quantile_with_keepdim(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=0.35, axis=4, keepdim=True)
np_res = np.quantile(self.input_data, q=0.35, axis=4, keepdims=True)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_quantile_with_multi_axis(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=0.75, axis=[0, 2, 3])
np_res = np.quantile(self.input_data, q=0.75, axis=[0, 2, 3])
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_quantile_with_no_axis(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=0.35)
np_res = np.quantile(self.input_data, q=0.35)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
def test_quantile_single_q(self):
x = paddle.to_tensor(self.input_data)
paddle_res = paddle.quantile(x, q=0.5, axis=2)
np_res = np.quantile(self.input_data, q=0.5, axis=2)
self.assertTrue(np.allclose(paddle_res.numpy(), np_res))
