ipu_commit_tests p7 (#38089)

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

+#  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.
+
+import unittest
+
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.compiler as compiler
+import paddle.optimizer
+import paddle.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import IPUOpTest
+
+paddle.enable_static()
+
+
+@unittest.skipIf(not paddle.is_compiled_with_ipu(),
+                 "core is not compiled with IPU")
+class TestBase(IPUOpTest):
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_feed()
+        self.set_attrs()
+
+    def set_feed(self):
+        self.feed_shape = []
+        self.feed_shape.append([1, 3, 10, 10])
+
+        self.feed = {}
+        self.feed["in_0"] = np.random.uniform(
+            size=self.feed_shape[0]).astype(np.float32)
+
+        self.feed_list = list(self.feed.keys())
+
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['axis'] = None
+        self.attrs['keepdim'] = False
+
+    def _test_base(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        SEED = self.SEED
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+
+        with fluid.scope_guard(scope):
+            with paddle.static.program_guard(main_prog, startup_prog):
+                x = paddle.static.data(
+                    name=self.feed_list[0],
+                    shape=self.feed_shape[0],
+                    dtype='float32')
+                out = paddle.mean(x, **self.attrs)
+
+                fetch_list = [out.name]
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = self.feed_list
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.is_training
+                program = compiler.IPUCompiledProgram(
+                    main_prog,
+                    ipu_strategy=ipu_strategy).compile(feed_list, fetch_list)
+            else:
+                program = main_prog
+
+            result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
+            return result[0]
+
+    def test_base(self):
+        res0 = self._test_base(True)
+        res1 = self._test_base(False)
+
+        self.assertTrue(
+            np.allclose(
+                res0.flatten(), res1.flatten(), atol=self.atol))
+
+
+class TestCase1(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['axis'] = 1
+        self.attrs['keepdim'] = False
+
+
+class TestCase2(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['axis'] = 2
+        self.attrs['keepdim'] = False
+
+
+class TestCase3(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['axis'] = 2
+        self.attrs['keepdim'] = True
+
+
+class TestCase4(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['axis'] = None
+        self.attrs['keepdim'] = True
+
+
+if __name__ == "__main__":
+    unittest.main()

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

+#  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.
+
+import unittest
+
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.compiler as compiler
+import paddle.optimizer
+import paddle.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import (IPUOpTest,
+                                                          np_dtype_to_fluid_str)
+
+paddle.enable_static()
+
+
+@unittest.skipIf(not paddle.is_compiled_with_ipu(),
+                 "core is not compiled with IPU")
+class TestBase(IPUOpTest):
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_feed()
+        self.set_feed_attr()
+        self.set_attrs()
+
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[2, 5]).astype('float32'),
+            "y": np.random.uniform(size=[5, 3]).astype('float32'),
+        }
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed.values()]
+        self.feed_list = list(self.feed.keys())
+        self.feed_dtype = [
+            np_dtype_to_fluid_str(x.dtype) for x in self.feed.values()
+        ]
+
+    def set_attrs(self):
+        self.attrs = {
+            "x_num_col_dims": 1,
+            "y_num_col_dims": 1,
+        }
+
+    def _test_base(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        SEED = self.SEED
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+
+        with fluid.scope_guard(scope):
+            with paddle.static.program_guard(main_prog, startup_prog):
+                x = paddle.static.data(
+                    name=self.feed_list[0],
+                    shape=self.feed_shape[0],
+                    dtype=self.feed_dtype[0])
+                y = paddle.static.data(
+                    name=self.feed_list[1],
+                    shape=self.feed_shape[1],
+                    dtype=self.feed_dtype[1])
+                out = paddle.fluid.layers.mul(x, y, **self.attrs)
+
+                fetch_list = [out.name]
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = self.feed_list
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.is_training
+                program = compiler.IPUCompiledProgram(
+                    main_prog,
+                    ipu_strategy=ipu_strategy).compile(feed_list, fetch_list)
+            else:
+                program = main_prog
+
+            result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
+            return result[0]
+
+    def test_base(self):
+        res0 = self._test_base(False)
+        res1 = self._test_base(True)
+
+        self.assertTrue(
+            np.allclose(
+                res0.flatten(), res1.flatten(), atol=self.atol))
+
+        self.assertTrue(res0.shape == res1.shape)
+
+
+class TestCase1(TestBase):
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[1, 2, 5]).astype('float32'),
+            "y": np.random.uniform(size=[5, 3]).astype('float32'),
+        }
+
+    def set_attrs(self):
+        self.attrs = {
+            "x_num_col_dims": 2,
+            "y_num_col_dims": 1,
+        }
+
+
+class TestCase2(TestBase):
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[3, 4, 2, 9]).astype('float32'),
+            "y": np.random.uniform(size=[3, 6, 1, 2, 3]).astype('float32'),
+        }
+
+    def set_attrs(self):
+        self.attrs = {
+            'x_num_col_dims': 2,
+            'y_num_col_dims': 2,
+        }
+
+
+if __name__ == "__main__":
+    unittest.main()

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

+#  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.
+
+import unittest
+
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.compiler as compiler
+import paddle.optimizer
+import paddle.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import (IPUOpTest,
+                                                          np_dtype_to_fluid_str)
+
+paddle.enable_static()
+
+
+@unittest.skipIf(not paddle.is_compiled_with_ipu(),
+                 "core is not compiled with IPU")
+class TestBase(IPUOpTest):
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_feed()
+        self.set_feed_attr()
+        self.set_attrs()
+
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[1, 3, 10, 10]).astype('float32'),
+        }
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed.values()]
+        self.feed_list = list(self.feed.keys())
+        self.feed_dtype = [
+            np_dtype_to_fluid_str(x.dtype) for x in self.feed.values()
+        ]
+
+    def set_attrs(self):
+        self.attrs = {
+            "pool_size": 3,
+            "pool_type": 'avg',
+            "pool_stride": 1,
+            "pool_padding": 0,
+            "global_pooling": False,
+            "ceil_mode": False,
+            "exclusive": True,
+            "data_format": 'NCHW',
+        }
+
+    def _test_base(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        SEED = self.SEED
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+
+        with fluid.scope_guard(scope):
+            with paddle.static.program_guard(main_prog, startup_prog):
+                x = paddle.static.data(
+                    name=self.feed_list[0],
+                    shape=self.feed_shape[0],
+                    dtype=self.feed_dtype[0])
+                out = paddle.fluid.layers.pool2d(x, **self.attrs)
+
+                fetch_list = [out.name]
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = self.feed_list
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.is_training
+                program = compiler.IPUCompiledProgram(
+                    main_prog,
+                    ipu_strategy=ipu_strategy).compile(feed_list, fetch_list)
+            else:
+                program = main_prog
+
+            result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
+            return result[0]
+
+    def test_base(self):
+        res0 = self._test_base(False)
+        res1 = self._test_base(True)
+
+        self.assertTrue(
+            np.allclose(
+                res0.flatten(), res1.flatten(), atol=self.atol))
+
+        self.assertTrue(res0.shape == res1.shape)
+
+
+class TestCase1(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_size'] = 3
+
+
+class TestCase1_2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_size'] = [3, 1]
+
+
+class TestCase2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_stride'] = 2
+
+
+class TestCase2_2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_stride'] = [2, 1]
+
+
+class TestCase3(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_padding'] = [1, 1]
+
+
+class TestCase3_2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_padding'] = [1, 1, 2, 2]
+
+
+@unittest.skip('the results has a positional offset')
+class TestCase3_3(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_padding'] = [1, 2, 1, 1]
+
+
+@unittest.skip('paddle output has nan')
+class TestCase3_4(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_size'] = 1
+        self.attrs['pool_padding'] = 1
+
+
+class TestCase4(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['global_pooling'] = True
+
+
+class TestCase5(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['ceil_mode'] = True
+
+
+class TestCase6(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['exclusive'] = False
+
+
+if __name__ == "__main__":
+    unittest.main()

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

+#  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.
+
+import unittest
+
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.compiler as compiler
+import paddle.optimizer
+import paddle.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import (IPUOpTest,
+                                                          np_dtype_to_fluid_str)
+
+paddle.enable_static()
+
+
+@unittest.skipIf(not paddle.is_compiled_with_ipu(),
+                 "core is not compiled with IPU")
+class TestBase(IPUOpTest):
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_feed()
+        self.set_feed_attr()
+        self.set_attrs()
+
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[1, 3, 10, 10]).astype('float32'),
+        }
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed.values()]
+        self.feed_list = list(self.feed.keys())
+        self.feed_dtype = [
+            np_dtype_to_fluid_str(x.dtype) for x in self.feed.values()
+        ]
+
+    def set_attrs(self):
+        self.attrs = {
+            "pool_size": 3,
+            "pool_type": 'max',
+            "pool_stride": 1,
+            "pool_padding": 0,
+            "global_pooling": False,
+            "ceil_mode": False,
+            "exclusive": True,
+            "data_format": 'NCHW',
+        }
+
+    def _test_base(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        SEED = self.SEED
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+
+        with fluid.scope_guard(scope):
+            with paddle.static.program_guard(main_prog, startup_prog):
+                x = paddle.static.data(
+                    name=self.feed_list[0],
+                    shape=self.feed_shape[0],
+                    dtype=self.feed_dtype[0])
+                out = paddle.fluid.layers.pool2d(x, **self.attrs)
+
+                fetch_list = [out.name]
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = self.feed_list
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.is_training
+                program = compiler.IPUCompiledProgram(
+                    main_prog,
+                    ipu_strategy=ipu_strategy).compile(feed_list, fetch_list)
+            else:
+                program = main_prog
+
+            result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
+            return result[0]
+
+    def test_base(self):
+        res0 = self._test_base(False)
+        res1 = self._test_base(True)
+
+        self.assertTrue(
+            np.allclose(
+                res0.flatten(), res1.flatten(), atol=self.atol))
+
+        self.assertTrue(res0.shape == res1.shape)
+
+
+class TestCase1(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_size'] = 3
+
+
+class TestCase1_2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_size'] = [3, 1]
+
+
+class TestCase2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_stride'] = 2
+
+
+class TestCase2_2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_stride'] = [2, 1]
+
+
+class TestCase3(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_padding'] = [1, 1]
+
+
+class TestCase3_2(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_padding'] = [1, 1, 2, 2]
+
+
+@unittest.skip('auto_pad is not currently supported')
+class TestCase3_3(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_padding'] = 'VALID'
+
+
+@unittest.skip('auto_pad is not currently supported')
+class TestCase3_4(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['pool_padding'] = 'SAME'
+
+
+class TestCase4(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['global_pooling'] = True
+
+
+class TestCase5(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['ceil_mode'] = True
+
+
+class TestCase6(TestBase):
+    def set_attrs(self):
+        super().set_attrs()
+        self.attrs['exclusive'] = False
+
+
+if __name__ == "__main__":
+    unittest.main()

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

+#  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.
+
+import unittest
+
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.compiler as compiler
+import paddle.optimizer
+import paddle.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import (IPUOpTest,
+                                                          np_dtype_to_fluid_str)
+
+paddle.enable_static()
+
+
+@unittest.skipIf(not paddle.is_compiled_with_ipu(),
+                 "core is not compiled with IPU")
+class TestBase(IPUOpTest):
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_feed()
+        self.set_feed_attr()
+        self.set_attrs()
+
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[1, 3, 2, 2]).astype('float32'),
+        }
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed.values()]
+        self.feed_list = list(self.feed.keys())
+        self.feed_dtype = [
+            np_dtype_to_fluid_str(x.dtype) for x in self.feed.values()
+        ]
+
+    def set_attrs(self):
+        self.attrs = {"factor": 2.0}
+
+    def _test_base(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        SEED = self.SEED
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+
+        with fluid.scope_guard(scope):
+            with paddle.static.program_guard(main_prog, startup_prog):
+                x = paddle.static.data(
+                    name=self.feed_list[0],
+                    shape=self.feed_shape[0],
+                    dtype=self.feed_dtype[0])
+                out = paddle.fluid.layers.pow(x, **self.attrs)
+
+                fetch_list = [out.name]
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = self.feed_list
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.is_training
+                program = compiler.IPUCompiledProgram(
+                    main_prog,
+                    ipu_strategy=ipu_strategy).compile(feed_list, fetch_list)
+            else:
+                program = main_prog
+
+            result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
+            return result[0]
+
+    def test_base(self):
+        res0 = self._test_base(False)
+        res1 = self._test_base(True)
+
+        self.assertTrue(
+            np.allclose(
+                res0.flatten(), res1.flatten(), atol=self.atol))
+
+        self.assertTrue(res0.shape == res1.shape)
+
+
+class TestCase1(TestBase):
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[1, 3, 2, 2]).astype('float32'),
+            "y": np.array([2.0]).astype('float32'),
+        }
+
+    def set_attrs(self):
+        self.attrs = {}
+
+    def _test_base(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        SEED = self.SEED
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+
+        with fluid.scope_guard(scope):
+            with paddle.static.program_guard(main_prog, startup_prog):
+                x = paddle.static.data(
+                    name=self.feed_list[0],
+                    shape=self.feed_shape[0],
+                    dtype=self.feed_dtype[0])
+                factor = paddle.static.data(
+                    name=self.feed_list[1],
+                    shape=self.feed_shape[1],
+                    dtype=self.feed_dtype[1])
+                out = paddle.fluid.layers.pow(x, factor=factor, **self.attrs)
+
+                fetch_list = [out.name]
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = self.feed_list
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.is_training
+                program = compiler.IPUCompiledProgram(
+                    main_prog,
+                    ipu_strategy=ipu_strategy).compile(feed_list, fetch_list)
+            else:
+                program = main_prog
+
+            result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
+            return result[0]
+
+
+if __name__ == "__main__":
+    unittest.main()

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

+#  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.
+
+import unittest
+
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.compiler as compiler
+import paddle.optimizer
+import paddle.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import (IPUOpTest,
+                                                          np_dtype_to_fluid_str)
+
+paddle.enable_static()
+
+
+@unittest.skipIf(not paddle.is_compiled_with_ipu(),
+                 "core is not compiled with IPU")
+class TestMean(IPUOpTest):
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.init_op()
+
+    def init_op(self):
+        self.op = paddle.fluid.layers.reduce_mean
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed.values()]
+        self.feed_list = list(self.feed.keys())
+        self.feed_dtype = [
+            np_dtype_to_fluid_str(x.dtype) for x in self.feed.values()
+        ]
+
+    def _test_base(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        SEED = self.SEED
+        main_prog.random_seed = SEED
+        startup_prog.random_seed = SEED
+
+        with fluid.scope_guard(scope):
+            with paddle.static.program_guard(main_prog, startup_prog):
+                x = paddle.static.data(
+                    name=self.feed_list[0],
+                    shape=self.feed_shape[0],
+                    dtype='float32')
+                out = self.op(x, **self.attrs)
+
+                fetch_list = [out.name]
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = self.feed_list
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.is_training
+                program = compiler.IPUCompiledProgram(
+                    main_prog,
+                    ipu_strategy=ipu_strategy).compile(feed_list, fetch_list)
+            else:
+                program = main_prog
+
+            result = exe.run(program, feed=self.feed, fetch_list=fetch_list)
+            return result[0]
+
+    def run_test_base(self):
+        res0 = self._test_base(True)
+        res1 = self._test_base(False)
+
+        self.assertTrue(
+            np.allclose(
+                res0.flatten(), res1.flatten(), atol=self.atol))
+
+    def set_feed0(self):
+        self.feed = {}
+        self.feed["in_0"] = np.random.uniform(size=[2, 4]).astype(np.float32)
+        self.set_feed_attr()
+
+    def set_feed1(self):
+        self.feed = {}
+        self.feed["in_0"] = np.random.uniform(size=[2, 2, 2]).astype(np.float32)
+        self.set_feed_attr()
+
+    def set_attr0(self):
+        self.attrs = {}
+        self.attrs['dim'] = None
+        self.attrs['keep_dim'] = False
+
+    def test_case0(self):
+        self.set_feed0()
+        self.set_attr0()
+        self.run_test_base()
+
+    def test_case1(self):
+        self.set_feed0()
+        self.set_attr0()
+        self.attrs['dim'] = 0
+        self.run_test_base()
+
+    def test_case2(self):
+        self.set_feed0()
+        self.set_attr0()
+        self.attrs['dim'] = -1
+        self.run_test_base()
+
+    def test_case3(self):
+        self.set_feed0()
+        self.set_attr0()
+        self.attrs['dim'] = 1
+        self.run_test_base()
+
+    def test_case4(self):
+        self.set_feed0()
+        self.attrs = {}
+        self.attrs['dim'] = 1
+        self.attrs['keep_dim'] = True
+        self.run_test_base()
+
+    def test_case5(self):
+        self.set_feed1()
+        self.attrs = {}
+        self.attrs['dim'] = [1, 2]
+        self.attrs['keep_dim'] = False
+        self.run_test_base()
+
+    def test_case6(self):
+        self.set_feed1()
+        self.attrs = {}
+        self.attrs['dim'] = [0, 1]
+        self.attrs['keep_dim'] = False
+        self.run_test_base()
+
+    def test_case7(self):
+        self.set_feed1()
+        self.attrs = {}
+        self.attrs['dim'] = [0, 1]
+        self.attrs['keep_dim'] = True
+        self.run_test_base()
+
+
+class TestMax(TestMean):
+    def init_op(self):
+        self.op = paddle.fluid.layers.reduce_max
+
+
+class TestMin(TestMean):
+    def init_op(self):
+        self.op = paddle.fluid.layers.reduce_min
+
+
+class TestProd(TestMean):
+    def init_op(self):
+        self.op = paddle.fluid.layers.reduce_prod
+
+
+class TestSum(TestMean):
+    def init_op(self):
+        self.op = paddle.fluid.layers.reduce_sum
+
+
+if __name__ == "__main__":
+    unittest.main()