add unit test for conv inference (PaddlePaddle#35)

python/paddle/fluid/tests/unittests/ipu/ipu_conv_test.py

@@ -0,0 +1,72 @@
+#  Copyright (c) 2021 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.
+
+from __future__ import print_function
+
+import numpy as np
+import unittest
+import sys
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.compiler as compiler
+
+paddle.enable_static()
+SEED = 2021
+
+
+@unittest.skipIf(not paddle.is_compiled_with_ipu(),
+                 "core is not compiled with IPU")
+class TestConvNet(unittest.TestCase):
+    def _test(self, run_ipu=True):
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+        np.random.seed(SEED)
+
+        np_image = np.random.rand(1, 3, 10, 10).astype(np.float32)
+
+        with paddle.static.program_guard(main_prog, startup_prog):
+            image = paddle.static.data(
+                name='image', shape=[1, 3, 10, 10], dtype='float32')
+            conv1 = paddle.static.nn.conv2d(
+                image, num_filters=3, filter_size=3, bias_attr=False)
+            conv2 = conv1 + conv1
+            loss = paddle.mean(conv2)
+
+        if run_ipu:
+            place = paddle.IPUPlace(0)
+        else:
+            place = paddle.CPUPlace()
+        exe = paddle.static.Executor(place)
+
+        exe.run(startup_prog)
+
+        print("Start run on {}".format(place))
+        for epoch in range(100):
+            loss_res = exe.run(main_prog,
+                               feed={"image": np_image},
+                               fetch_list=[loss])
+
+        return loss_res
+
+    def test_ipu(self):
+        cpu_loss = self._test(False)
+        ipu_loss = self._test(True)
+
+        self.assertTrue(np.allclose(ipu_loss, cpu_loss, atol=1e-3))
+
+
+if __name__ == "__main__":
+    unittest.main()