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[PIR] D-7、D-10 Adapt test_errors #61963

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Merged
0x45f merged 3 commits into from
Feb 27, 2024
Merged

[PIR] D-7、D-10 Adapt test_errors #61963

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zrr1999 Feb 22, 2024
49e797f
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zrr1999 Feb 27, 2024
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zrr1999 Feb 27, 2024
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5 changes: 4 additions & 1 deletion test/legacy_test/test_cumsum_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -496,9 +496,12 @@ def test_check_grad(self):


class BadInputTest(unittest.TestCase):
@test_with_pir_api
def test_error(self):
paddle.enable_static()
with base.program_guard(base.Program()):
with paddle.static.program_guard(
paddle.static.Program(), paddle.static.Program()
):

def test_bad_x():
data = [1, 2, 4]
Expand Down
65 changes: 33 additions & 32 deletions test/legacy_test/test_pad_op.py
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Original file line number Diff line number Diff line change
Expand Up @@ -27,7 +27,7 @@

def pad_wrapper(x, paddings, pad_value):
return paddle.nn.functional.pad(
x, pad=list(paddings), mode='constant', value=pad_value
x, pad=list(paddings), mode="constant", value=pad_value
)


Expand All @@ -38,16 +38,16 @@ def setUp(self):
self.op_type = "pad"
self.python_api = pad_wrapper
self.inputs = {
'X': np.random.random(self.shape).astype(self.dtype),
"X": np.random.random(self.shape).astype(self.dtype),
}
self.attrs = {}
self.attrs['paddings'] = list(np.array(self.paddings).flatten())
self.attrs['pad_value'] = self.pad_value
self.attrs["paddings"] = list(np.array(self.paddings).flatten())
self.attrs["pad_value"] = self.pad_value
self.outputs = {
'Out': np.pad(
self.inputs['X'],
"Out": np.pad(
self.inputs["X"],
self.paddings,
mode='constant',
mode="constant",
constant_values=self.pad_value,
)
}
Expand All @@ -62,8 +62,8 @@ def test_check_output(self):

def test_check_grad_normal(self):
self.check_grad(
['X'],
'Out',
["X"],
"Out",
check_prim=True,
check_pir=True,
check_prim_pir=True,
Expand Down Expand Up @@ -109,8 +109,8 @@ def get_dtype(self):

def test_check_grad_normal(self):
self.check_grad(
['X'],
'Out',
["X"],
"Out",
check_prim=True,
check_pir=True,
check_prim_pir=True,
Expand All @@ -128,6 +128,7 @@ def test_check_grad_normal(self):


class TestPadOpError(unittest.TestCase):
@test_with_pir_api
def test_errors(self):
with static_guard():
with paddle.static.program_guard(
Expand All @@ -139,11 +140,11 @@ def test_Variable():
paddle.nn.functional.pad(x=input_data, pad=[1, 1, 1, 1])

self.assertRaises(TypeError, test_Variable)

data = paddle.static.data(
name='data', shape=[4], dtype='float16'
)
paddle.nn.functional.pad(x=data, pad=[0, 1])
if core.is_compiled_with_cuda():
data = paddle.static.data(
name="data", shape=[4], dtype="float16"
)
paddle.nn.functional.pad(x=data, pad=[0, 1])


class TestPaddingValueTensor(UnittestBase):
Expand Down Expand Up @@ -171,7 +172,7 @@ def test_static(self):
exe.run(startup_prog)
res = exe.run(fetch_list=[feat, out])
gt = np.pad(
res[0], [1, 1], 'constant', constant_values=[1.0, 1.0]
res[0], [1, 1], "constant", constant_values=[1.0, 1.0]
)
np.testing.assert_allclose(res[1], gt)

Expand All @@ -183,7 +184,7 @@ def test_static(self):
gt = np.pad(
infer_outs[0],
[1, 1],
'constant',
"constant",
constant_values=[1.0, 1.0],
)
np.testing.assert_allclose(infer_outs[1], gt)
Expand All @@ -207,20 +208,20 @@ def test_pir_static(self):
exe.run(startup_prog)
res = exe.run(fetch_list=[feat, out])
gt = np.pad(
res[0], [1, 1], 'constant', constant_values=[1.0, 1.0]
res[0], [1, 1], "constant", constant_values=[1.0, 1.0]
)
np.testing.assert_allclose(res[1], gt)

def path_prefix(self):
return 'padding_value'
return "padding_value"

def var_prefix(self):
return "Var["

def call_func(self, x):
padding_value = paddle.assign([1.0])
out = paddle.nn.functional.pad(
x, pad=[1, 1, 1, 1], value=padding_value, mode='constant'
x, pad=[1, 1, 1, 1], value=padding_value, mode="constant"
)
return out

Expand All @@ -238,12 +239,12 @@ class TestPaddingValueTensor3(unittest.TestCase):
@test_with_pir_api
def test_static(self):
with static_guard():
np_x = np.random.random((16, 16)).astype('float32')
np_x = np.random.random((16, 16)).astype("float32")
main_prog = paddle.static.Program()
startup_prog = paddle.static.Program()
with paddle.static.program_guard(main_prog, startup_prog):
x = paddle.assign(np_x).astype('float32')
pad_value = paddle.assign([0.0]).astype('float64')
x = paddle.assign(np_x).astype("float32")
pad_value = paddle.assign([0.0]).astype("float64")
y = paddle.nn.functional.pad(x, [0, 1, 2, 3], value=pad_value)
loss = y.sum()
optimize_ops, params_grads = paddle.optimizer.SGD(
Expand Down Expand Up @@ -273,13 +274,13 @@ def setUp(self):
self.python_api = pad_wrapper
x = np.random.random(self.shape).astype(np.float32)
self.attrs = {}
self.attrs['paddings'] = list(np.array(self.paddings).flatten())
self.attrs['pad_value'] = self.pad_value
self.attrs["paddings"] = list(np.array(self.paddings).flatten())
self.attrs["pad_value"] = self.pad_value
out = np.pad(
x, self.paddings, mode='constant', constant_values=self.pad_value
x, self.paddings, mode="constant", constant_values=self.pad_value
)
self.inputs = {'X': convert_float_to_uint16(x)}
self.outputs = {'Out': convert_float_to_uint16(out)}
self.inputs = {"X": convert_float_to_uint16(x)}
self.outputs = {"Out": convert_float_to_uint16(out)}
self.prim_op_type = "prim"
self.public_python_api = pad_wrapper
self.if_enable_cinn()
Expand All @@ -300,14 +301,14 @@ def test_check_grad(self):
place = core.CUDAPlace(0)
self.check_grad_with_place(
place,
['X'],
'Out',
["X"],
"Out",
check_prim=True,
check_pir=True,
check_prim_pir=True,
)


if __name__ == '__main__':
if __name__ == "__main__":
# paddle.enable_static()
unittest.main()