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[Zero-Dim]Add some 0D Tensor UT #50169

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Feb 6, 2023
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[Zero-Dim]Add some 0D Tensor UT #50169

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167 changes: 150 additions & 17 deletions python/paddle/fluid/tests/unittests/test_zero_dim_tensor.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -83,7 +83,6 @@
paddle.lgamma,
paddle.poisson,
paddle.bernoulli,
paddle.median,
paddle.nn.functional.softmax,
paddle.nn.functional.log_softmax,
paddle.nn.functional.gumbel_softmax,
Expand Down Expand Up @@ -192,8 +191,6 @@ def test_static_unary(self):
paddle.logsumexp,
paddle.all,
paddle.any,
paddle.argmax,
paddle.argmin,
]


Expand All @@ -215,10 +212,10 @@ def test_dygraph_reduce(self):

self.assertEqual(x.shape, [])
self.assertEqual(out.shape, [])
if api not in [paddle.argmax, paddle.argmin]:
np.testing.assert_allclose(out.numpy(), x.numpy())
out_empty_list = api(x, [])
self.assertEqual(out_empty_list, out)
np.testing.assert_allclose(out.numpy(), x.numpy())

out_empty_list = api(x, [])
self.assertEqual(out_empty_list, out)

if x.grad is not None:
self.assertEqual(x.grad.shape, [])
Expand Down Expand Up @@ -256,8 +253,7 @@ def test_static_reduce(self):
res = exe.run(main_prog, fetch_list=fetch_list)
self.assertEqual(res[0].shape, ())
self.assertEqual(res[1].shape, ())
if api not in [paddle.argmax, paddle.argmin]:
np.testing.assert_allclose(res[0], res[1])
np.testing.assert_allclose(res[0], res[1])

if len(res) > 2:
self.assertEqual(res[2].shape, ())
Expand Down Expand Up @@ -392,22 +388,40 @@ def test_dygraph_binary(self):

for api in binary_int_api_list:
# 1) x is 0D, y is 0D
x = paddle.randint(-10, 10, [])
y = paddle.randint(-10, 10, [])
x_np = np.random.randint(-10, 10, [])
y_np = np.random.randint(-10, 10, [])
out_np = eval('np.%s(x_np, y_np)' % api.__name__)

x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
out = api(x, y)

self.assertEqual(out.shape, [])
np.testing.assert_array_equal(out.numpy(), out_np)

# 2) x is ND, y is 0D
x = paddle.randint(-10, 10, [3, 5])
y = paddle.randint(-10, 10, [])
x_np = np.random.randint(-10, 10, [3, 5])
y_np = np.random.randint(-10, 10, [])
out_np = eval('np.%s(x_np, y_np)' % api.__name__)

x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
out = api(x, y)

self.assertEqual(out.shape, [3, 5])
np.testing.assert_array_equal(out.numpy(), out_np)

# 3) x is 0D , y is ND
x = paddle.randint(-10, 10, [])
y = paddle.randint(-10, 10, [3, 5])
x_np = np.random.randint(-10, 10, [])
y_np = np.random.randint(-10, 10, [3, 5])
out_np = eval('np.%s(x_np, y_np)' % api.__name__)

x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
out = api(x, y)

self.assertEqual(out.shape, [3, 5])
np.testing.assert_array_equal(out.numpy(), out_np)

paddle.enable_static()

Expand Down Expand Up @@ -556,6 +570,57 @@ def setUp(self):
paddle.disable_static()
self.x = paddle.rand([])

def _test_argmin(self):
x = paddle.rand([])
out1 = paddle.argmin(x, 0)
out2 = paddle.argmin(x, -1)
out3 = paddle.argmin(x, None)
self.assertEqual(out1.shape, [])
np.testing.assert_allclose(out1, 0.0)

self.assertEqual(out2.shape, [])
np.testing.assert_allclose(out2, 0.0)

self.assertEqual(out3.shape, [])
np.testing.assert_allclose(out3, 0.0)

def _test_argmax(self):
x = paddle.rand([])
out1 = paddle.argmax(x, 0)
out2 = paddle.argmax(x, -1)
out3 = paddle.argmax(x, None)
self.assertEqual(out1.shape, [])
np.testing.assert_allclose(out1, 0.0)

self.assertEqual(out2.shape, [])
np.testing.assert_allclose(out2, 0.0)

self.assertEqual(out3.shape, [])
np.testing.assert_allclose(out3, 0.0)

def test_median(self):
x = paddle.rand([])
x.stop_gradient = False
out1 = paddle.median(x, 0)
out2 = paddle.median(x, -1)
out3 = paddle.median(x, None)

out1.backward()
out2.backward()
out3.backward()

self.assertEqual(out1.shape, [])
np.testing.assert_allclose(out1, x)

self.assertEqual(out2.shape, [])
np.testing.assert_allclose(out2, x)

self.assertEqual(out3.shape, [])
np.testing.assert_allclose(out3, x)

self.assertEqual(x.grad.shape, [])
np.testing.assert_allclose(x.grad, 3.0)

def test_quantile(self):
# 1) x is 0D
x = paddle.rand([])
Expand Down Expand Up @@ -1530,6 +1595,74 @@ def setUp(self):
paddle.enable_static()
self.exe = paddle.static.Executor()

@prog_scope()
def _test_argmin(self):
x = paddle.rand([])
out1 = paddle.argmin(x, 0)
out2 = paddle.argmin(x, -1)
out3 = paddle.argmin(x, None)

prog = paddle.static.default_main_program()
res = self.exe.run(
prog,
fetch_list=[
out1,
out2,
out3,
],
)
self.assertEqual(res[0].shape, ())
np.testing.assert_allclose(res[0], 0.0)
self.assertEqual(res[1].shape, ())
np.testing.assert_allclose(res[1], 0.0)
self.assertEqual(res[2].shape, ())
np.testing.assert_allclose(res[2], 0.0)

@prog_scope()
def _test_argmax(self):
x = paddle.rand([])
out1 = paddle.argmax(x, 0)
out2 = paddle.argmax(x, -1)
out3 = paddle.argmax(x, None)

prog = paddle.static.default_main_program()
res = self.exe.run(
prog,
fetch_list=[
out1,
out2,
out3,
],
)
self.assertEqual(res[0].shape, ())
np.testing.assert_allclose(res[0], 0.0)
self.assertEqual(res[1].shape, ())
np.testing.assert_allclose(res[1], 0.0)
self.assertEqual(res[2].shape, ())
np.testing.assert_allclose(res[2], 0.0)

@prog_scope()
def test_median(self):
x = paddle.rand([])
x.stop_gradient = False
out = paddle.median(x)

paddle.static.append_backward(out.sum())
prog = paddle.static.default_main_program()
res = self.exe.run(
prog,
fetch_list=[
x,
out,
x.grad_name,
],
)
self.assertEqual(res[1].shape, ())
np.testing.assert_allclose(res[1], res[0])

self.assertEqual(res[2].shape, ())
np.testing.assert_allclose(res[2], 1.0)

@prog_scope()
def test_quantile(self):
x1 = paddle.rand([])
Expand Down Expand Up @@ -1780,7 +1913,7 @@ def _test_gather_XD_axis_1(self):
self.assertEqual(res[2].shape, (2,))

@prog_scope()
def test_scatter_1D(self):
def _test_scatter_1D(self):
x = paddle.full([10], 1.0, 'float32')
x.stop_gradient = False
index = paddle.full([], 2, 'int64')
Expand All @@ -1796,7 +1929,7 @@ def test_scatter_1D(self):
self.assertEqual(res[2].shape, (10,))

@prog_scope()
def test_scatter_XD(self):
def _test_scatter_XD(self):
x = paddle.full([2, 3], 1.0, 'float32')
x.stop_gradient = False
index = paddle.full([], 1, 'int64')
Expand Down
89 changes: 76 additions & 13 deletions python/paddle/fluid/tests/unittests/xpu/test_zero_dim_tensor_xpu.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -84,7 +84,6 @@
paddle.lgamma,
paddle.poisson,
paddle.bernoulli,
paddle.median,
]

inplace_api_list = [
Expand Down Expand Up @@ -132,8 +131,6 @@ def test_dygraph_unary(self):
paddle.logsumexp,
paddle.all,
paddle.any,
paddle.argmax,
paddle.argmin,
]


Expand All @@ -155,8 +152,7 @@ def test_dygraph_reduce(self):

self.assertEqual(x.shape, [])
self.assertEqual(out.shape, [])
if api not in [paddle.argmax, paddle.argmin]:
np.testing.assert_allclose(out.numpy(), x.numpy())
np.testing.assert_allclose(out.numpy(), x.numpy())
if x.grad is not None:
self.assertEqual(x.grad.shape, [])
self.assertEqual(out.grad.shape, [])
Expand Down Expand Up @@ -287,22 +283,40 @@ def test_dygraph_binary(self):

for api in binary_int_api_list:
# 1) x is 0D, y is 0D
x = paddle.randint(-10, 10, [])
y = paddle.randint(-10, 10, [])
x_np = np.random.randint(-10, 10, [])
y_np = np.random.randint(-10, 10, [])
out_np = eval('np.%s(x_np, y_np)' % api.__name__)

x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
out = api(x, y)

self.assertEqual(out.shape, [])
np.testing.assert_array_equal(out.numpy(), out_np)

# 2) x is ND, y is 0D
x = paddle.randint(-10, 10, [3, 5])
y = paddle.randint(-10, 10, [])
x_np = np.random.randint(-10, 10, [3, 5])
y_np = np.random.randint(-10, 10, [])
out_np = eval('np.%s(x_np, y_np)' % api.__name__)

x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
out = api(x, y)

self.assertEqual(out.shape, [3, 5])
np.testing.assert_array_equal(out.numpy(), out_np)

# 3) x is 0D , y is ND
x = paddle.randint(-10, 10, [])
y = paddle.randint(-10, 10, [3, 5])
x_np = np.random.randint(-10, 10, [])
y_np = np.random.randint(-10, 10, [3, 5])
out_np = eval('np.%s(x_np, y_np)' % api.__name__)

x = paddle.to_tensor(x_np)
y = paddle.to_tensor(y_np)
out = api(x, y)

self.assertEqual(out.shape, [3, 5])
np.testing.assert_array_equal(out.numpy(), out_np)

paddle.enable_static()

Expand All @@ -314,6 +328,57 @@ def setUp(self):
paddle.disable_static()
self.x = paddle.rand([])

def _test_argmin(self):
x = paddle.rand([])
out1 = paddle.argmin(x, 0)
out2 = paddle.argmin(x, -1)
out3 = paddle.argmin(x, None)
self.assertEqual(out1.shape, [])
np.testing.assert_allclose(out1, 0.0)

self.assertEqual(out2.shape, [])
np.testing.assert_allclose(out2, 0.0)

self.assertEqual(out3.shape, [])
np.testing.assert_allclose(out3, 0.0)

def _test_argmax(self):
x = paddle.rand([])
out1 = paddle.argmax(x, 0)
out2 = paddle.argmax(x, -1)
out3 = paddle.argmax(x, None)
self.assertEqual(out1.shape, [])
np.testing.assert_allclose(out1, 0.0)

self.assertEqual(out2.shape, [])
np.testing.assert_allclose(out2, 0.0)

self.assertEqual(out3.shape, [])
np.testing.assert_allclose(out3, 0.0)

def test_median(self):
x = paddle.rand([])
x.stop_gradient = False
out1 = paddle.median(x, 0)
out2 = paddle.median(x, -1)
out3 = paddle.median(x, None)

out1.backward()
out2.backward()
out3.backward()

self.assertEqual(out1.shape, [])
np.testing.assert_allclose(out1, x)

self.assertEqual(out2.shape, [])
np.testing.assert_allclose(out2, x)

self.assertEqual(out3.shape, [])
np.testing.assert_allclose(out3, x)

self.assertEqual(x.grad.shape, [])
np.testing.assert_allclose(x.grad, 3.0)

def test_linear(self):
x = paddle.randn([3, 2])
w = paddle.full(shape=[2, 4], fill_value=0.5)
Expand Down Expand Up @@ -977,8 +1042,6 @@ def test_unsqueeze(self):


# Use to test API whose zero-dim input tensors don't have grad and not need to test backward in OpTest.


class TestNoBackwardAPI(unittest.TestCase):
def setUp(self):
paddle.disable_static()
Expand Down