[Cpp Extension] Add unittest, mixed calling of op and extension (#50678)

* testcase init commit

* skip sign conflict

* fix year

python/paddle/fluid/tests/cpp_extension/mix_relu_and_extension.cc

+// Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include <iostream>
+#include <vector>
+
+#include "custom_power.h"  // NOLINT
+#include "paddle/extension.h"
+
+#define CHECK_CPU_INPUT(x) PD_CHECK(x.is_cpu(), #x " must be a CPU Tensor.")
+
+template <typename data_t>
+void relu_cpu_forward_kernel(const data_t* x_data,
+                             data_t* out_data,
+                             int64_t x_numel) {
+  PD_CHECK(x_data != nullptr, "x_data is nullptr.");
+  PD_CHECK(out_data != nullptr, "out_data is nullptr.");
+  for (int64_t i = 0; i < x_numel; ++i) {
+    out_data[i] = std::max(static_cast<data_t>(0.), x_data[i]);
+  }
+}
+
+template <typename data_t>
+void relu_cpu_backward_kernel(const data_t* grad_out_data,
+                              const data_t* out_data,
+                              data_t* grad_x_data,
+                              int64_t out_numel) {
+  for (int64_t i = 0; i < out_numel; ++i) {
+    grad_x_data[i] =
+        grad_out_data[i] * (out_data[i] > static_cast<data_t>(0) ? 1. : 0.);
+  }
+}
+
+template <typename data_t>
+void relu_cpu_double_backward_kernel(const data_t* out_data,
+                                     const data_t* ddx_data,
+                                     data_t* ddout_data,
+                                     int64_t ddout_numel) {
+  for (int64_t i = 0; i < ddout_numel; ++i) {
+    ddout_data[i] =
+        ddx_data[i] * (out_data[i] > static_cast<data_t>(0) ? 1. : 0.);
+  }
+}
+
+std::vector<paddle::Tensor> relu_cpu_forward(const paddle::Tensor& x) {
+  CHECK_CPU_INPUT(x);
+  auto out = paddle::empty_like(x);
+
+  PD_DISPATCH_FLOATING_TYPES(
+      x.type(), "relu_cpu_forward", ([&] {
+        relu_cpu_forward_kernel<data_t>(
+            x.data<data_t>(), out.data<data_t>(), x.numel());
+      }));
+
+  return {out};
+}
+
+std::vector<paddle::Tensor> relu_cpu_backward(const paddle::Tensor& x,
+                                              const paddle::Tensor& out,
+                                              const paddle::Tensor& grad_out) {
+  auto grad_x = paddle::empty_like(x);
+
+  PD_DISPATCH_FLOATING_TYPES(out.type(), "relu_cpu_backward", ([&] {
+                               relu_cpu_backward_kernel<data_t>(
+                                   grad_out.data<data_t>(),
+                                   out.data<data_t>(),
+                                   grad_x.data<data_t>(),
+                                   out.size());
+                             }));
+
+  return {grad_x};
+}
+
+std::vector<paddle::Tensor> relu_cpu_double_backward(
+    const paddle::Tensor& out, const paddle::Tensor& ddx) {
+  CHECK_CPU_INPUT(out);
+  CHECK_CPU_INPUT(ddx);
+  auto ddout = paddle::empty(out.shape(), out.dtype(), out.place());
+
+  PD_DISPATCH_FLOATING_TYPES(out.type(), "relu_cpu_double_backward", ([&] {
+                               relu_cpu_double_backward_kernel<data_t>(
+                                   out.data<data_t>(),
+                                   ddx.data<data_t>(),
+                                   ddout.mutable_data<data_t>(out.place()),
+                                   ddout.size());
+                             }));
+  return {ddout};
+}
+
+std::vector<paddle::Tensor> ReluForward(const paddle::Tensor& x) {
+  if (x.is_cpu()) {
+    return relu_cpu_forward(x);
+  } else {
+    PD_THROW("Not implemented.");
+  }
+}
+
+std::vector<paddle::Tensor> ReluBackward(const paddle::Tensor& x,
+                                         const paddle::Tensor& out,
+                                         const paddle::Tensor& grad_out) {
+  if (x.is_cpu()) {
+    return relu_cpu_backward(x, out, grad_out);
+  } else {
+    PD_THROW("Not implemented.");
+  }
+}
+
+std::vector<paddle::Tensor> ReluDoubleBackward(const paddle::Tensor& out,
+                                               const paddle::Tensor& ddx) {
+  if (out.place() == paddle::PlaceType::kCPU) {
+    return relu_cpu_double_backward(out, ddx);
+  } else {
+    PD_THROW("Not implemented.");
+  }
+}
+
+std::vector<std::vector<int64_t>> ReluDoubleBackwardInferShape(
+    const std::vector<int64_t>& out_shape,
+    const std::vector<int64_t>& ddx_shape) {
+  return {out_shape};
+}
+
+PD_BUILD_OP(custom_relu)
+    .Inputs({"X"})
+    .Outputs({"Out"})
+    .SetKernelFn(PD_KERNEL(ReluForward));
+
+PD_BUILD_GRAD_OP(custom_relu)
+    .Inputs({"X", "Out", paddle::Grad("Out")})
+    .Outputs({paddle::Grad("X")})
+    .SetKernelFn(PD_KERNEL(ReluBackward));
+
+PD_BUILD_DOUBLE_GRAD_OP(custom_relu)
+    .Inputs({"Out", paddle::Grad(paddle::Grad("X"))})
+    .Outputs({paddle::Grad(paddle::Grad("Out"))})
+    .SetKernelFn(PD_KERNEL(ReluDoubleBackward))
+    .SetInferShapeFn(PD_INFER_SHAPE(ReluDoubleBackwardInferShape));
+
+// Extension with tensor operator overloading
+paddle::Tensor custom_sub2(paddle::Tensor x, paddle::Tensor y) {
+  return paddle::exp(x) - paddle::exp(y);
+}
+
+// Extension with tensor operator overloading
+paddle::Tensor custom_add2(const paddle::Tensor& x, const paddle::Tensor& y) {
+  return paddle::exp(x) + paddle::exp(y);
+}
+
+PYBIND11_MODULE(mix_relu_extension, m) {
+  m.def("custom_add2", &custom_add2, "exp(x) + exp(y)");
+  m.def("custom_sub2", &custom_sub2, "exp(x) - exp(y)");
+}

python/paddle/fluid/tests/cpp_extension/mix_relu_and_extension_setup.py

+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+
+from utils import paddle_includes
+
+from paddle.utils.cpp_extension import CppExtension, setup
+
+setup(
+    name='mix_relu_extension',
+    ext_modules=CppExtension(
+        sources=["mix_relu_and_extension.cc", "custom_sub.cc"],
+        include_dirs=paddle_includes
+        + [os.path.dirname(os.path.abspath(__file__))],
+        extra_compile_args={'cc': ['-w', '-g']},
+        verbose=True,
+    ),
+)

python/paddle/fluid/tests/cpp_extension/test_cpp_extension_setup.py

@@ -20,9 +20,80 @@ import unittest
 import numpy as np
 
 import paddle
+import paddle.static as static
 from paddle.utils.cpp_extension.extension_utils import run_cmd
 
 
+def custom_relu_static(
+    func, device, dtype, np_x, use_func=True, test_infer=False
+):
+    paddle.enable_static()
+    paddle.set_device(device)
+
+    with static.scope_guard(static.Scope()):
+        with static.program_guard(static.Program()):
+            x = static.data(name='X', shape=[None, 8], dtype=dtype)
+            x.stop_gradient = False
+            out = func(x) if use_func else paddle.nn.functional.relu(x)
+            static.append_backward(out)
+
+            exe = static.Executor()
+            exe.run(static.default_startup_program())
+            # in static graph mode, x data has been covered by out
+            out_v = exe.run(
+                static.default_main_program(),
+                feed={'X': np_x},
+                fetch_list=[out.name],
+            )
+
+    paddle.disable_static()
+    return out_v
+
+
+def custom_relu_dynamic(func, device, dtype, np_x, use_func=True):
+    paddle.set_device(device)
+
+    t = paddle.to_tensor(np_x, dtype=dtype)
+    t.stop_gradient = False
+
+    out = func(t) if use_func else paddle.nn.functional.relu(t)
+    out.stop_gradient = False
+
+    out.backward()
+
+    if t.grad is None:
+        return out.numpy(), t.grad
+    else:
+        return out.numpy(), t.grad.numpy()
+
+
+def custom_relu_double_grad_dynamic(func, device, dtype, np_x, use_func=True):
+    paddle.set_device(device)
+
+    t = paddle.to_tensor(np_x, dtype=dtype, stop_gradient=False)
+    t.retain_grads()
+
+    out = func(t) if use_func else paddle.nn.functional.relu(t)
+    out.retain_grads()
+    dx = paddle.grad(
+        outputs=out,
+        inputs=t,
+        grad_outputs=paddle.ones_like(t),
+        create_graph=True,
+        retain_graph=True,
+    )
+
+    ddout = paddle.grad(
+        outputs=dx[0],
+        inputs=out.grad,
+        grad_outputs=paddle.ones_like(t),
+        create_graph=False,
+    )
+
+    assert ddout[0].numpy() is not None
+    return dx[0].numpy(), ddout[0].numpy()
+
+
 class TestCppExtensionSetupInstall(unittest.TestCase):
     """
     Tests setup install cpp extensions.
@@ -30,23 +101,14 @@ class TestCppExtensionSetupInstall(unittest.TestCase):
 
     def setUp(self):
         cur_dir = os.path.dirname(os.path.abspath(__file__))
+        # install general extension
         # compile, install the custom op egg into site-packages under background
-        if os.name == 'nt':
-            cmd = 'cd /d {} && python cpp_extension_setup.py install'.format(
-                cur_dir
-            )
-        else:
-            cmd = 'cd {} && {} cpp_extension_setup.py install'.format(
-                cur_dir, sys.executable
-            )
+        cmd = 'cd {} && {} cpp_extension_setup.py install'.format(
+            cur_dir, sys.executable
+        )
         run_cmd(cmd)
-        # os.system(cmd)
 
-        # See: https://stackoverflow.com/questions/56974185/import-runtime-installed-module-using-pip-in-python-3
-        if os.name == 'nt':
-            site_dir = site.getsitepackages()[1]
-        else:
-            site_dir = site.getsitepackages()[0]
+        site_dir = site.getsitepackages()[0]
         custom_egg_path = [
             x for x in os.listdir(site_dir) if 'custom_cpp_extension' in x
         ]
@@ -55,6 +117,22 @@ class TestCppExtensionSetupInstall(unittest.TestCase):
         )
         sys.path.append(os.path.join(site_dir, custom_egg_path[0]))
 
+        # install mixed custom_op and extension
+        cmd = 'cd {} && {} mix_relu_and_extension_setup.py install'.format(
+            cur_dir, sys.executable
+        )
+        run_cmd(cmd)
+
+        site_dir = site.getsitepackages()[0]
+        custom_egg_path = [
+            x for x in os.listdir(site_dir) if 'mix_relu_extension' in x
+        ]
+        assert len(custom_egg_path) == 1, "Matched egg number is %d." % len(
+            custom_egg_path
+        )
+        sys.path.append(os.path.join(site_dir, custom_egg_path[0]))
+        #################################
+
         # config seed
         SEED = 2021
         paddle.seed(SEED)
@@ -66,10 +144,16 @@ class TestCppExtensionSetupInstall(unittest.TestCase):
         pass
 
     def test_cpp_extension(self):
-        self._test_extension_function()
+        # Extension
+        self._test_extension_function_plain()
+        self._test_extension_function_mixed()
         self._test_extension_class()
+        # Custom op
+        self._test_static()
+        self._test_dynamic()
+        self._test_double_grad_dynamic()
 
-    def _test_extension_function(self):
+    def _test_extension_function_plain(self):
         import custom_cpp_extension
 
         for dtype in self.dtypes:
@@ -77,7 +161,7 @@ class TestCppExtensionSetupInstall(unittest.TestCase):
             x = paddle.to_tensor(np_x, dtype=dtype)
             np_y = np.random.uniform(-1, 1, [4, 8]).astype(dtype)
             y = paddle.to_tensor(np_y, dtype=dtype)
-
+            # Test custom_cpp_extension
             out = custom_cpp_extension.custom_add(x, y)
             target_out = np.exp(np_x) + np.exp(np_y)
             np.testing.assert_allclose(out.numpy(), target_out, atol=1e-5)
@@ -87,10 +171,30 @@ class TestCppExtensionSetupInstall(unittest.TestCase):
             target_out = np.exp(np_x) - np.exp(np_y)
             np.testing.assert_allclose(out.numpy(), target_out, atol=1e-5)
 
+    def _test_extension_function_mixed(self):
+        import mix_relu_extension
+
+        for dtype in self.dtypes:
+            np_x = np.random.uniform(-1, 1, [4, 8]).astype(dtype)
+            x = paddle.to_tensor(np_x, dtype=dtype)
+            np_y = np.random.uniform(-1, 1, [4, 8]).astype(dtype)
+            y = paddle.to_tensor(np_y, dtype=dtype)
+
+            # Test mix_relu_extension
+            out = mix_relu_extension.custom_add2(x, y)
+            target_out = np.exp(np_x) + np.exp(np_y)
+            np.testing.assert_allclose(out.numpy(), target_out, atol=1e-5)
+
+            # Test we can call a method not defined in the main C++ file.
+            out = mix_relu_extension.custom_sub2(x, y)
+            target_out = np.exp(np_x) - np.exp(np_y)
+            np.testing.assert_allclose(out.numpy(), target_out, atol=1e-5)
+
     def _test_extension_class(self):
         import custom_cpp_extension
 
         for dtype in self.dtypes:
+            # Test custom_cpp_extension
             # Test we can use CppExtension class with C++ methods.
             power = custom_cpp_extension.Power(3, 3)
             self.assertEqual(power.get().sum(), 9)
@@ -109,6 +213,77 @@ class TestCppExtensionSetupInstall(unittest.TestCase):
                 atol=1e-5,
             )
 
+    def _test_static(self):
+        import mix_relu_extension
+
+        for dtype in self.dtypes:
+            x = np.random.uniform(-1, 1, [4, 8]).astype(dtype)
+            out = custom_relu_static(
+                mix_relu_extension.custom_relu, "CPU", dtype, x
+            )
+            pd_out = custom_relu_static(
+                mix_relu_extension.custom_relu, "CPU", dtype, x, False
+            )
+            np.testing.assert_array_equal(
+                out,
+                pd_out,
+                err_msg='custom op out: {},\n paddle api out: {}'.format(
+                    out, pd_out
+                ),
+            )
+
+    def _test_dynamic(self):
+        import mix_relu_extension
+
+        for dtype in self.dtypes:
+            x = np.random.uniform(-1, 1, [4, 8]).astype(dtype)
+            out, x_grad = custom_relu_dynamic(
+                mix_relu_extension.custom_relu, "CPU", dtype, x
+            )
+            pd_out, pd_x_grad = custom_relu_dynamic(
+                mix_relu_extension.custom_relu, "CPU", 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
+                ),
+            )
+
+    def _test_double_grad_dynamic(self):
+        import mix_relu_extension
+
+        for dtype in self.dtypes:
+            x = np.random.uniform(-1, 1, [4, 8]).astype(dtype)
+            out, dx_grad = custom_relu_double_grad_dynamic(
+                mix_relu_extension.custom_relu, "CPU", dtype, x
+            )
+            pd_out, pd_dx_grad = custom_relu_double_grad_dynamic(
+                mix_relu_extension.custom_relu, "CPU", 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
+                ),
+            )
+
 
 if __name__ == '__main__':
     if os.name == 'nt' or sys.platform.startswith('darwin'):

python/paddle/fluid/tests/cpp_extension/utils.py

+# Copyright (c) 2023 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import os
+import sys
+from site import getsitepackages
+
+from paddle.utils.cpp_extension.extension_utils import IS_WINDOWS
+
+IS_MAC = sys.platform.startswith('darwin')
+
+# Note(Aurelius84): We use `add_test` in Cmake to config how to run unittest in CI.
+# `PYTHONPATH` will be set as `build/python/paddle` that will make no way to find
+# paddle include directory. Because the following path is generated after installing
+# PaddlePaddle whl. So here we specific `include_dirs` to avoid errors in CI.
+paddle_includes = []
+for site_packages_path in getsitepackages():
+    paddle_includes.append(
+        os.path.join(site_packages_path, 'paddle', 'include')
+    )
+    paddle_includes.append(
+        os.path.join(site_packages_path, 'paddle', 'include', 'third_party')
+    )
+
+# Test for extra compile args
+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}