Skip to content

P
Paddle

Jahson / Paddle
与 Fork 源项目一致

Fork自 PaddlePaddle / Paddle

通知 1
Star 0
Fork 0
P
Paddle

前往新版Gitcode，体验更适合开发者的 AI 搜索 >>

未验证 提交 2a24a6bb 编写于 作者: H HongyuJia 提交者： GitHub
浏览文件
操作

[CustomOP Unittest] Polish unit test, unify check_output (#52737) 

* [CustomOP Unittest] Polish unit test, unify check_output

* fix test_static_save_and_run_inference_predictor
上级 8e9bfa7f
隐藏空白更改
内联 并排
Showing with 255 addition and 417 deletion
test/custom_op/test_custom_conj.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,7 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, extra_nvcc_args, paddle_includes
from utils import check_output, extra_cc_args, extra_nvcc_args, paddle_includes
import paddle
from paddle import static
......@@ -100,42 +100,27 @@ class TestCustomConjJit(unittest.TestCase):
self.dtypes = ['float32', 'float64']
self.shape = [2, 20, 2, 3]
def check_output(self, out, pd_out, name):
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def run_dynamic(self, dtype, np_input):
out, x_grad = conj_dynamic(custom_ops.custom_conj, dtype, np_input)
pd_out, pd_x_grad = conj_dynamic(paddle.conj, dtype, np_input)
self.check_output(out, pd_out, "out")
self.check_output(x_grad, pd_x_grad, "x's grad")
def run_static(self, dtype, np_input):
out, x_grad = conj_static(
custom_ops.custom_conj, self.shape, dtype, np_input
)
pd_out, pd_x_grad = conj_static(
paddle.conj, self.shape, dtype, np_input
)
self.check_output(out, pd_out, "out")
self.check_output(x_grad, pd_x_grad, "x's grad")
def test_dynamic(self):
for dtype in self.dtypes:
np_input = np.random.random(self.shape).astype(dtype)
self.run_dynamic(dtype, np_input)
out, x_grad = conj_dynamic(custom_ops.custom_conj, dtype, np_input)
pd_out, pd_x_grad = conj_dynamic(paddle.conj, dtype, np_input)
check_output(out, pd_out, "out")
check_output(x_grad, pd_x_grad, "x's grad")
def test_static(self):
for dtype in self.dtypes:
np_input = np.random.random(self.shape).astype(dtype)
self.run_static(dtype, np_input)
out, x_grad = conj_static(
custom_ops.custom_conj, self.shape, dtype, np_input
)
pd_out, pd_x_grad = conj_static(
paddle.conj, self.shape, dtype, np_input
)
check_output(out, pd_out, "out")
check_output(x_grad, pd_x_grad, "x's grad")
# complex only used in dynamic mode now
def test_complex_dynamic(self):
......@@ -143,7 +128,16 @@ class TestCustomConjJit(unittest.TestCase):
np_input = np.random.random(self.shape).astype(
dtype
) + 1j * np.random.random(self.shape).astype(dtype)
self.run_dynamic(to_complex(dtype), np_input)
out, x_grad = conj_dynamic(
custom_ops.custom_conj, to_complex(dtype), np_input
)
pd_out, pd_x_grad = conj_dynamic(
paddle.conj, to_complex(dtype), np_input
)
check_output(out, pd_out, "out")
check_output(x_grad, pd_x_grad, "x's grad")
if __name__ == "__main__":
......
test/custom_op/test_custom_inplace.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,13 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, extra_nvcc_args, paddle_includes
from utils import (
check_output,
check_output_allclose,
extra_cc_args,
extra_nvcc_args,
paddle_includes,
)
import paddle
from paddle import static
......@@ -342,26 +348,6 @@ class TestCustomInplaceJit(unittest.TestCase):
np.random.random((3, 2)).astype("float32"),
]
def check_output(self, out, pd_out, name):
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def check_output_allclose(self, out, pd_out, name):
np.testing.assert_allclose(
out,
pd_out,
rtol=5e-5,
atol=1e-2,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def test_static_add(self):
for device in self.devices:
for dtype in self.dtypes:
......@@ -391,15 +377,15 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_x,
self.np_y,
)
self.check_output(custom_x, custom_out, "inplace_custom_x")
self.check_output(
check_output(custom_x, custom_out, "inplace_custom_x")
check_output(
custom_x_grad, custom_out_grad, "inplace_custom_x_grad"
)
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
self.check_output(custom_out_grad, pd_out_grad, "out_grad")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_out_grad, pd_out_grad, "out_grad")
def test_dynamic_add(self):
for device in self.devices:
......@@ -431,14 +417,14 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_y,
)
self.check_output(custom_x, custom_out, "inplace_custom_x")
self.check_output(pd_x, pd_out, "inplace_pd_x")
check_output(custom_x, custom_out, "inplace_custom_x")
check_output(pd_x, pd_out, "inplace_pd_x")
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_y, pd_y, "y")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_y, pd_y, "y")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
def test_static_add_vector(self):
for device in self.devices:
......@@ -468,10 +454,10 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_y,
)
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
self.check_output(custom_out_grad, pd_out_grad, "out_grad")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_out_grad, pd_out_grad, "out_grad")
def test_dynamic_add_vector(self):
for device in self.devices:
......@@ -503,14 +489,14 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_y,
)
self.check_output(custom_x, custom_out, "inplace_custom_x")
self.check_output(pd_x, pd_out, "inplace_pd_x")
check_output(custom_x, custom_out, "inplace_custom_x")
check_output(pd_x, pd_out, "inplace_pd_x")
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_y, pd_y, "y")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_y, pd_y, "y")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
def test_static_relu_net(self):
for device in self.devices:
......@@ -543,11 +529,11 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_y,
self.np_z,
)
self.check_output_allclose(custom_x, pd_x, "x")
self.check_output_allclose(custom_y, pd_y, "y")
self.check_output_allclose(custom_out, pd_out, "out")
self.check_output_allclose(custom_x_grad, pd_x_grad, "x_grad")
self.check_output_allclose(custom_y_grad, pd_y_grad, "y_grad")
check_output_allclose(custom_x, pd_x, "x")
check_output_allclose(custom_y, pd_y, "y")
check_output_allclose(custom_out, pd_out, "out")
check_output_allclose(custom_x_grad, pd_x_grad, "x_grad")
check_output_allclose(custom_y_grad, pd_y_grad, "y_grad")
def test_dynamic_relu_net(self):
for device in self.devices:
......@@ -581,11 +567,11 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_z,
)
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_y, pd_y, "y")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_y, pd_y, "y")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
def test_static_multi_inplace(self):
for device in self.devices:
......@@ -630,27 +616,23 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_a,
self.np_b,
)
self.check_output(custom_x, pd_out_xy, "inplace_custom_x")
self.check_output(
check_output(custom_x, pd_out_xy, "inplace_custom_x")
check_output(
custom_x_grad, custom_out_xy_grad, "inplace_custom_x_grad"
)
self.check_output(custom_a, pd_out_ab, "inplace_custom_a")
self.check_output(
check_output(custom_a, pd_out_ab, "inplace_custom_a")
check_output(
custom_a_grad, custom_out_ab_grad, "inplace_custom_a_grad"
)
self.check_output(custom_out_xy, pd_out_xy, "outxy")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
self.check_output(
custom_out_xy_grad, pd_out_xy_grad, "outxy_grad"
)
self.check_output(custom_out_ab, pd_out_ab, "outab")
self.check_output(custom_a_grad, pd_a_grad, "a_grad")
self.check_output(custom_b_grad, pd_b_grad, "b_grad")
self.check_output(
custom_out_ab_grad, pd_out_ab_grad, "outab_grad"
)
check_output(custom_out_xy, pd_out_xy, "outxy")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_out_xy_grad, pd_out_xy_grad, "outxy_grad")
check_output(custom_out_ab, pd_out_ab, "outab")
check_output(custom_a_grad, pd_a_grad, "a_grad")
check_output(custom_b_grad, pd_b_grad, "b_grad")
check_output(custom_out_ab_grad, pd_out_ab_grad, "outab_grad")
def test_dynamic_multi_inplace(self):
for device in self.devices:
......@@ -696,21 +678,21 @@ class TestCustomInplaceJit(unittest.TestCase):
self.np_b,
)
self.check_output(custom_x, custom_out_xy, "inplace_custom_x")
self.check_output(pd_x, pd_out_xy, "inplace_pd_x")
self.check_output(custom_a, custom_out_ab, "inplace_custom_a")
self.check_output(pd_a, pd_out_ab, "inplace_pd_a")
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_y, pd_y, "y")
self.check_output(custom_out_xy, pd_out_xy, "outxy")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
self.check_output(custom_a, pd_a, "a")
self.check_output(custom_b, pd_b, "b")
self.check_output(custom_out_ab, pd_out_ab, "outab")
self.check_output(custom_a_grad, pd_a_grad, "a_grad")
self.check_output(custom_b_grad, pd_b_grad, "b_grad")
check_output(custom_x, custom_out_xy, "inplace_custom_x")
check_output(pd_x, pd_out_xy, "inplace_pd_x")
check_output(custom_a, custom_out_ab, "inplace_custom_a")
check_output(pd_a, pd_out_ab, "inplace_pd_a")
check_output(custom_x, pd_x, "x")
check_output(custom_y, pd_y, "y")
check_output(custom_out_xy, pd_out_xy, "outxy")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_a, pd_a, "a")
check_output(custom_b, pd_b, "b")
check_output(custom_out_ab, pd_out_ab, "outab")
check_output(custom_a_grad, pd_a_grad, "a_grad")
check_output(custom_b_grad, pd_b_grad, "b_grad")
if __name__ == "__main__":
......
test/custom_op/test_custom_linear.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,7 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, extra_nvcc_args, paddle_includes
from utils import check_output, extra_cc_args, extra_nvcc_args, paddle_includes
import paddle
import paddle.nn.functional as F
......@@ -99,15 +99,6 @@ class TestCustomLinearJit(unittest.TestCase):
self.np_weight = np.full([2, 4], fill_value=0.5, dtype="float32")
self.np_bias = np.ones([4], dtype="float32")
def check_output(self, out, pd_out, name):
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def test_static(self):
for device in self.devices:
for dtype in self.dtypes:
......@@ -132,12 +123,10 @@ class TestCustomLinearJit(unittest.TestCase):
self.np_weight,
self.np_bias,
)
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(
custom_weight_grad, pd_weight_grad, "weight_grad"
)
self.check_output(custom_bias_grad, pd_bias_grad, "bias_grad")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_weight_grad, pd_weight_grad, "weight_grad")
check_output(custom_bias_grad, pd_bias_grad, "bias_grad")
def test_dynamic(self):
for device in self.devices:
......@@ -168,12 +157,10 @@ class TestCustomLinearJit(unittest.TestCase):
self.np_weight,
self.np_bias,
)
self.check_output(custom_out, pd_out, "custom_out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(
custom_weight_grad, pd_weight_grad, "weight_grad"
)
self.check_output(custom_bias_grad, pd_bias_grad, "bias_grad")
check_output(custom_out, pd_out, "custom_out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_weight_grad, pd_weight_grad, "weight_grad")
check_output(custom_bias_grad, pd_bias_grad, "bias_grad")
if __name__ == "__main__":
......
test/custom_op/test_custom_optional.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,7 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, extra_nvcc_args, paddle_includes
from utils import check_output, extra_cc_args, extra_nvcc_args, paddle_includes
import paddle
from paddle import static
......@@ -465,44 +465,6 @@ class TestCustomOptionalJit(unittest.TestCase):
np.random.random((3, 2)).astype("float32"),
]
def check_output(self, out, pd_out, name):
if out is None and pd_out is None:
return
assert out is not None, "out value of " + name + " is None"
assert pd_out is not None, "pd_out value of " + name + " is None"
if isinstance(out, list) and isinstance(pd_out, list):
for idx in range(len(out)):
np.testing.assert_array_equal(
out[idx],
pd_out[idx],
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out[idx], name, pd_out[idx]
),
)
else:
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def check_output_allclose(self, out, pd_out, name):
if out is None and pd_out is None:
return
assert out is not None, "out value of " + name + " is None"
assert pd_out is not None, "pd_out value of " + name + " is None"
np.testing.assert_allclose(
out,
pd_out,
rtol=5e-5,
atol=1e-2,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def test_optional_static_add(self):
for device in self.devices:
for dtype in self.dtypes:
......@@ -526,9 +488,9 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
def test_optional_dynamic_add(self):
for device in self.devices:
......@@ -553,9 +515,9 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
def test_optional_inplace_static_add(self):
for device in self.devices:
......@@ -576,13 +538,11 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(custom_tuple[0], pd_tuple[0], "x")
self.check_output(custom_tuple[1], pd_tuple[1], "out")
self.check_output(custom_tuple[2], pd_tuple[2], "x_grad")
check_output(custom_tuple[0], pd_tuple[0], "x")
check_output(custom_tuple[1], pd_tuple[1], "out")
check_output(custom_tuple[2], pd_tuple[2], "x_grad")
if len(custom_tuple) > 3:
self.check_output(
custom_tuple[3], pd_tuple[3], "y_grad"
)
check_output(custom_tuple[3], pd_tuple[3], "y_grad")
def test_optional_inplace_dynamic_add(self):
for device in self.devices:
......@@ -619,16 +579,16 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(pd_y, pd_outy, "inplace_pd_y")
self.check_output(custom_y, custom_outy, "inplace_custom_y")
check_output(pd_y, pd_outy, "inplace_pd_y")
check_output(custom_y, custom_outy, "inplace_custom_y")
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_outx, pd_outx, "outx")
self.check_output(custom_y, pd_y, "y")
self.check_output(custom_outy, pd_outy, "outy")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_outx, pd_outx, "outx")
check_output(custom_y, pd_y, "y")
check_output(custom_outy, pd_outy, "outy")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
def test_optional_vector_static_add(self):
for device in self.devices:
......@@ -653,9 +613,9 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
def test_optional_vector_dynamic_add(self):
for device in self.devices:
......@@ -680,9 +640,9 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
def test_optional_inplace_vector_static_add(self):
for device in self.devices:
......@@ -703,16 +663,12 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(custom_tuple[0], pd_tuple[0], "x")
self.check_output(custom_tuple[1], pd_tuple[1], "out")
self.check_output(custom_tuple[2], pd_tuple[2], "x_grad")
check_output(custom_tuple[0], pd_tuple[0], "x")
check_output(custom_tuple[1], pd_tuple[1], "out")
check_output(custom_tuple[2], pd_tuple[2], "x_grad")
if len(custom_tuple) > 3:
self.check_output(
custom_tuple[3], pd_tuple[3], "y1_grad"
)
self.check_output(
custom_tuple[4], pd_tuple[4], "y2_grad"
)
check_output(custom_tuple[3], pd_tuple[3], "y1_grad")
check_output(custom_tuple[4], pd_tuple[4], "y2_grad")
def test_optional_inplace_vector_dynamic_add(self):
for device in self.devices:
......@@ -749,16 +705,16 @@ class TestCustomOptionalJit(unittest.TestCase):
np_y,
)
self.check_output(pd_y, pd_outy, "inplace_pd_y")
self.check_output(custom_y, custom_outy, "inplace_custom_y")
check_output(pd_y, pd_outy, "inplace_pd_y")
check_output(custom_y, custom_outy, "inplace_custom_y")
self.check_output(custom_x, pd_x, "x")
self.check_output(custom_outx, pd_outx, "outx")
self.check_output(custom_y, pd_y, "y")
self.check_output(custom_outy, pd_outy, "outy")
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_x_grad, pd_x_grad, "x_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_x, pd_x, "x")
check_output(custom_outx, pd_outx, "outx")
check_output(custom_y, pd_y, "y")
check_output(custom_outy, pd_outy, "outy")
check_output(custom_out, pd_out, "out")
check_output(custom_x_grad, pd_x_grad, "x_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
if __name__ == "__main__":
......
test/custom_op/test_custom_relu_op_setup.py
浏览文件 @ 2a24a6bb
......@@ -18,6 +18,7 @@ import sys
import unittest
import numpy as np
from utils import check_output, check_output_allclose
import paddle
from paddle import static
......@@ -205,13 +206,7 @@ class TestNewCustomOpSetUpInstall(unittest.TestCase):
pd_out = custom_relu_static(
custom_op, device, dtype, x, False
)
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
check_output(out, pd_out, "out")
def test_dynamic(self):
for device in self.devices:
......@@ -226,20 +221,8 @@ class TestNewCustomOpSetUpInstall(unittest.TestCase):
pd_out, pd_x_grad = custom_relu_dynamic(
custom_op, device, dtype, x, False
)
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
np.testing.assert_array_equal(
x_grad,
pd_x_grad,
err_msg='custom op x grad: {},\n paddle api x grad: {}'.format(
x_grad, pd_x_grad
),
)
check_output(out, pd_out, "out")
check_output(x_grad, pd_x_grad, "x_grad")
def test_static_save_and_load_inference_model(self):
paddle.enable_static()
......@@ -263,13 +246,7 @@ class TestNewCustomOpSetUpInstall(unittest.TestCase):
feed={feed_target_names[0]: np_data},
fetch_list=fetch_targets,
)
np.testing.assert_array_equal(
predict,
predict_infer,
err_msg='custom op predict: {},\n custom op infer predict: {}'.format(
predict, predict_infer
),
)
check_output(predict, predict_infer, "predict")
paddle.disable_static()
def test_static_save_and_run_inference_predictor(self):
......@@ -298,12 +275,9 @@ class TestNewCustomOpSetUpInstall(unittest.TestCase):
predictor.get_output_names()[0]
)
predict_infer = output_tensor.copy_to_cpu()
self.assertTrue(
np.isclose(predict, predict_infer, rtol=5e-5).any(),
"custom op predict: {},\n custom op infer predict: {}".format(
predict, predict_infer
),
)
predict = np.array(predict).flatten()
predict_infer = np.array(predict_infer).flatten()
check_output_allclose(predict, predict_infer, "predict")
paddle.disable_static()
def test_double_grad_dynamic(self):
......@@ -318,20 +292,8 @@ class TestNewCustomOpSetUpInstall(unittest.TestCase):
pd_out, pd_dx_grad = custom_relu_double_grad_dynamic(
self.custom_ops[0], device, dtype, x, False
)
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
np.testing.assert_array_equal(
dx_grad,
pd_dx_grad,
err_msg='custom op dx grad: {},\n paddle api dx grad: {}'.format(
dx_grad, pd_dx_grad
),
)
check_output(out, pd_out, "out")
check_output(dx_grad, pd_dx_grad, "dx_grad")
def test_with_dataloader(self):
for device in self.devices:
......@@ -355,13 +317,7 @@ class TestNewCustomOpSetUpInstall(unittest.TestCase):
image = paddle.to_tensor(image)
out = self.custom_ops[0](image)
pd_out = paddle.nn.functional.relu(image)
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
check_output(out, pd_out, "out")
if batch_id == 5:
break
......
test/custom_op/test_custom_relu_op_xpu_setup.py
浏览文件 @ 2a24a6bb
......@@ -18,6 +18,7 @@ import sys
import unittest
import numpy as np
from utils import check_output, check_output_allclose
import paddle
from paddle import static
......@@ -183,13 +184,7 @@ class TestNewCustomOpXpuSetUpInstall(unittest.TestCase):
pd_out = custom_relu_static(
self.custom_op, self.device, dtype, x, False
)
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
check_output(out, pd_out, "out")
def test_dynamic(self):
for dtype in self.dtypes:
......@@ -200,20 +195,8 @@ class TestNewCustomOpXpuSetUpInstall(unittest.TestCase):
pd_out, pd_x_grad = custom_relu_dynamic(
self.custom_op, self.device, dtype, x, False
)
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
np.testing.assert_array_equal(
x_grad,
pd_x_grad,
err_msg='custom op x grad: {},\n paddle api x grad: {}'.format(
x_grad, pd_x_grad
),
)
check_output(out, pd_out, "out")
check_output(x_grad, pd_x_grad, "x_grad")
def test_static_save_and_load_inference_model(self):
paddle.enable_static()
......@@ -237,14 +220,7 @@ class TestNewCustomOpXpuSetUpInstall(unittest.TestCase):
feed={feed_target_names[0]: np_data},
fetch_list=fetch_targets,
)
np.testing.assert_allclose(
predict,
predict_infer,
atol=1e-2,
err_msg='custom op predict: {},\n custom op infer predict: {}'.format(
predict, predict_infer
),
)
check_output(predict, predict_infer, "predict")
paddle.disable_static()
def test_static_save_and_run_inference_predictor(self):
......@@ -272,15 +248,7 @@ class TestNewCustomOpXpuSetUpInstall(unittest.TestCase):
predict_infer = output_tensor.copy_to_cpu()
predict = np.array(predict).flatten()
predict_infer = np.array(predict_infer).flatten()
np.testing.assert_allclose(
predict,
predict_infer,
rtol=5e-5,
atol=1e-2,
err_msg="custom op predict: {},\n custom op infer predict: {}".format(
predict, predict_infer
),
)
check_output_allclose(predict, predict_infer, "predict")
paddle.disable_static()
def test_func_double_grad_dynamic(self):
......@@ -292,20 +260,8 @@ class TestNewCustomOpXpuSetUpInstall(unittest.TestCase):
pd_out, pd_dx_grad = custom_relu_double_grad_dynamic(
self.custom_op, self.device, dtype, x, False
)
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
np.testing.assert_array_equal(
dx_grad,
pd_dx_grad,
err_msg='custom op dx grad: {},\n paddle api dx grad: {}'.format(
dx_grad, pd_dx_grad
),
)
check_output(out, pd_out, "out")
check_output(dx_grad, pd_dx_grad, "dx_grad")
def test_with_dataloader(self):
paddle.disable_static()
......@@ -328,14 +284,7 @@ class TestNewCustomOpXpuSetUpInstall(unittest.TestCase):
for batch_id, (image, _) in enumerate(train_loader()):
out = self.custom_op(image)
pd_out = paddle.nn.functional.relu(image)
np.testing.assert_allclose(
out,
pd_out,
atol=1e-2,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
check_output_allclose(out, pd_out, "out", atol=1e-2)
if batch_id == 5:
break
......
test/custom_op/test_custom_simple_slice.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,7 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, extra_nvcc_args, paddle_includes
from utils import check_output, extra_cc_args, extra_nvcc_args, paddle_includes
import paddle
from paddle.utils.cpp_extension import get_build_directory, load
......@@ -47,13 +47,7 @@ class TestCustomSimpleSliceJit(unittest.TestCase):
x = paddle.to_tensor(np_x)
custom_op_out = custom_ops.custom_simple_slice(x, 2, 3)
np_out = np_x[2:3]
np.testing.assert_array_equal(
custom_op_out,
np_out,
err_msg='custom op: {},\n numpy: {}'.format(
np_out, custom_op_out.numpy()
),
)
check_output(custom_op_out, np_out, "out")
if __name__ == "__main__":
......
test/custom_op/test_custom_tanh_double_grad.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,12 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, extra_nvcc_args, paddle_includes
from utils import (
check_output_allclose,
extra_cc_args,
extra_nvcc_args,
paddle_includes,
)
import paddle
from paddle.utils.cpp_extension import get_build_directory, load
......@@ -77,30 +82,9 @@ class TestCustomTanhDoubleGradJit(unittest.TestCase):
pd_out, pd_dx_grad, pd_dout = custom_tanh_double_grad_dynamic(
paddle.tanh, device, dtype, x
)
np.testing.assert_allclose(
out,
pd_out,
rtol=1e-05,
err_msg='custom op out: {},\n paddle api out: {}'.format(
out, pd_out
),
)
np.testing.assert_allclose(
dx_grad,
pd_dx_grad,
rtol=1e-05,
err_msg='custom op dx grad: {},\n paddle api dx grad: {}'.format(
dx_grad, pd_dx_grad
),
)
np.testing.assert_allclose(
dout,
pd_dout,
rtol=1e-05,
err_msg='custom op out grad: {},\n paddle api out grad: {}'.format(
dout, pd_dout
),
)
check_output_allclose(out, pd_out, "out", rtol=1e-05)
check_output_allclose(dx_grad, pd_dx_grad, "out", rtol=1e-05)
check_output_allclose(dout, pd_dout, "dout", rtol=1e-05)
if __name__ == "__main__":
......
test/custom_op/test_custom_tensor_operator.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,12 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, paddle_includes
from utils import (
check_output,
check_output_allclose,
extra_cc_args,
paddle_includes,
)
import paddle
from paddle import static
......@@ -260,7 +265,7 @@ class TestJITLoad(unittest.TestCase):
pd_out = test_custom_add_static(
self.add, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
out = test_custom_subtract_static(
self.subtract, device, dtype, x
......@@ -268,7 +273,7 @@ class TestJITLoad(unittest.TestCase):
pd_out = test_custom_subtract_static(
self.subtract, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
out = test_custom_multiply_static(
self.multiply, device, dtype, x
......@@ -276,13 +281,13 @@ class TestJITLoad(unittest.TestCase):
pd_out = test_custom_multiply_static(
self.multiply, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
out = test_custom_divide_static(self.divide, device, dtype, x)
pd_out = test_custom_divide_static(
self.divide, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
def _test_dynamic(self):
for device in self.devices:
......@@ -297,9 +302,9 @@ class TestJITLoad(unittest.TestCase):
pd_out, pd_x_grad = test_custom_add_dynamic(
self.add, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
np.testing.assert_allclose(
x_grad, pd_x_grad, rtol=1e-5, atol=1e-8
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
check_output_allclose(
x_grad, pd_x_grad, "x_grad", rtol=1e-5, atol=1e-8
)
out, x_grad = test_custom_subtract_dynamic(
......@@ -308,9 +313,9 @@ class TestJITLoad(unittest.TestCase):
pd_out, pd_x_grad = test_custom_subtract_dynamic(
self.subtract, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
np.testing.assert_allclose(
x_grad, pd_x_grad, rtol=1e-5, atol=1e-8
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
check_output_allclose(
x_grad, pd_x_grad, "x_grad", rtol=1e-5, atol=1e-8
)
out, x_grad = test_custom_multiply_dynamic(
......@@ -319,9 +324,9 @@ class TestJITLoad(unittest.TestCase):
pd_out, pd_x_grad = test_custom_multiply_dynamic(
self.multiply, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
np.testing.assert_allclose(
x_grad, pd_x_grad, rtol=1e-5, atol=1e-8
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
check_output_allclose(
x_grad, pd_x_grad, "x_grad", rtol=1e-5, atol=1e-8
)
out, x_grad = test_custom_divide_dynamic(
......@@ -330,7 +335,7 @@ class TestJITLoad(unittest.TestCase):
pd_out, pd_x_grad = test_custom_divide_dynamic(
self.divide, device, dtype, x, False
)
np.testing.assert_allclose(out, pd_out, rtol=1e-5, atol=1e-8)
check_output_allclose(out, pd_out, "out", rtol=1e-5, atol=1e-8)
def _test_logical_operants(self):
for device in self.devices:
......@@ -342,19 +347,19 @@ class TestJITLoad(unittest.TestCase):
out = self.custom_module.custom_logical_and(x, y)
pd_out = paddle.bitwise_and(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_logical_or(x, y)
pd_out = paddle.bitwise_or(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_logical_xor(x, y)
pd_out = paddle.bitwise_xor(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_logical_not(x)
pd_out = paddle.bitwise_not(x)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
def _test_compare_operants(self):
for device in self.devices:
......@@ -366,27 +371,27 @@ class TestJITLoad(unittest.TestCase):
out = self.custom_module.custom_less_than(x, y)
pd_out = paddle.less_than(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_less_equal(x, y)
pd_out = paddle.less_equal(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_equal(x, y)
pd_out = paddle.equal(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_not_equal(x, y)
pd_out = paddle.not_equal(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_greater_than(x, y)
pd_out = paddle.greater_than(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
out = self.custom_module.custom_greater_equal(x, y)
pd_out = paddle.greater_equal(x, y)
np.testing.assert_equal(out.numpy(), pd_out.numpy())
check_output(out.numpy(), pd_out.numpy(), "out")
if __name__ == '__main__':
......
test/custom_op/test_multi_out_jit.py
浏览文件 @ 2a24a6bb
......@@ -16,7 +16,7 @@ import os
import unittest
import numpy as np
from utils import extra_cc_args, paddle_includes
from utils import check_output, extra_cc_args, paddle_includes
import paddle
from paddle import static
......@@ -105,15 +105,6 @@ class TestMultiOutputDtypes(unittest.TestCase):
self.np_y = np.random.uniform(-1, 1, [4, 8]).astype("float32")
self.np_z = np.random.uniform(-1, 1, [4, 8]).astype("float32")
def check_output(self, out, pd_out, name):
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def run_static(self, device, dtype):
paddle.set_device(device)
x_data = np.random.uniform(-1, 1, [4, 8]).astype(dtype)
......@@ -140,14 +131,12 @@ class TestMultiOutputDtypes(unittest.TestCase):
one_int32 = one_int32.numpy()
# Fake_float64
self.assertTrue('float64' in str(zero_float64.dtype))
np.testing.assert_array_equal(
zero_float64, np.zeros([4, 8]).astype('float64')
check_output(
zero_float64, np.zeros([4, 8]).astype('float64'), "zero_float64"
)
# ZFake_int32
self.assertTrue('int32' in str(one_int32.dtype))
np.testing.assert_array_equal(
one_int32, np.ones([4, 8]).astype('int32')
)
check_output(one_int32, np.ones([4, 8]).astype('int32'), "one_int32")
def test_multi_out_static(self):
paddle.enable_static()
......@@ -193,10 +182,10 @@ class TestMultiOutputDtypes(unittest.TestCase):
self.np_y,
self.np_z,
)
self.check_output(custom_out, pd_out, "out")
check_output(custom_out, pd_out, "out")
# NOTE: In static mode, the output gradient of custom operator has been optimized to shape=[1]. However, native paddle op's output shape = [4, 8], hence we need to fetch pd_w_grad[0][0] (By the way, something wrong with native paddle's gradient, the outputs with other indexes instead of pd_w_grad[0][0] is undefined in this unittest.)
self.check_output(custom_w_grad, pd_w_grad[0][0], "w_grad")
self.check_output(custom_y_grad, pd_y_grad[0][0], "y_grad")
check_output(custom_w_grad, pd_w_grad[0][0], "w_grad")
check_output(custom_y_grad, pd_y_grad[0][0], "y_grad")
def test_discrete_out_dynamic(self):
for device in self.devices:
......@@ -223,9 +212,9 @@ class TestMultiOutputDtypes(unittest.TestCase):
self.np_y,
self.np_z,
)
self.check_output(custom_out, pd_out, "out")
self.check_output(custom_w_grad, pd_w_grad, "w_grad")
self.check_output(custom_y_grad, pd_y_grad, "y_grad")
check_output(custom_out, pd_out, "out")
check_output(custom_w_grad, pd_w_grad, "w_grad")
check_output(custom_y_grad, pd_y_grad, "y_grad")
if __name__ == '__main__':
......
test/custom_op/utils.py
浏览文件 @ 2a24a6bb
......@@ -16,6 +16,8 @@ import os
import sys
from site import getsitepackages
import numpy as np
from paddle.utils.cpp_extension.extension_utils import IS_WINDOWS
IS_MAC = sys.platform.startswith('darwin')
......@@ -39,3 +41,43 @@ for site_packages_path in getsitepackages():
extra_cc_args = ['-w', '-g'] if not IS_WINDOWS else ['/w']
extra_nvcc_args = ['-O3']
extra_compile_args = {'cc': extra_cc_args, 'nvcc': extra_nvcc_args}
def check_output(out, pd_out, name):
if out is None and pd_out is None:
return
assert out is not None, "out value of " + name + " is None"
assert pd_out is not None, "pd_out value of " + name + " is None"
if isinstance(out, list) and isinstance(pd_out, list):
for idx in range(len(out)):
np.testing.assert_array_equal(
out[idx],
pd_out[idx],
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out[idx], name, pd_out[idx]
),
)
else:
np.testing.assert_array_equal(
out,
pd_out,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
def check_output_allclose(out, pd_out, name, rtol=5e-5, atol=1e-2):
if out is None and pd_out is None:
return
assert out is not None, "out value of " + name + " is None"
assert pd_out is not None, "pd_out value of " + name + " is None"
np.testing.assert_allclose(
out,
pd_out,
rtol,
atol,
err_msg='custom op {}: {},\n paddle api {}: {}'.format(
name, out, name, pd_out
),
)
Markdown is supported
0% 或 .
You are about to add 0 people to the discussion. Proceed with caution.
先完成此消息的编辑！
想要评论请 注册 或