ipu_commit_tests p10 (#38095)

python/paddle/fluid/tests/unittests/ipu/test_reshape_inplace_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 = {
+            "shape": [30, 10],
+            "inplace": True,
+        }
+
+    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])
+                add = paddle.fluid.layers.elementwise_add(x, x)
+                out = paddle.fluid.layers.reshape(add, **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))
+
+        self.assertTrue(res0.shape == res1.shape)
+
+
+class TestCase1(TestBase):
+    def set_attrs(self):
+        self.attrs = {
+            "shape": [-1, 0, 10],
+            "inplace": True,
+        }
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_reshape_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([2, 4, 6])
+
+        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['shape'] = [6, 8]
+        self.attrs['inplace'] = 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.fluid.layers.reshape(x=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))
+
+        self.assertTrue(res0.shape == res1.shape)
+
+
+class TestCase1(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['shape'] = [2, 3, -1, 2]
+        self.attrs['inplace'] = False
+
+
+class TestCase2(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['shape'] = [-1, 0, 3, 2]
+        self.attrs['inplace'] = False
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_save_load.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 shutil
+
+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_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['steps'] = 100
+        self.attrs['save_at_step'] = 20
+        self.attrs['is_training'] = True
+        self.attrs['opt_type'] = 'sgd'
+
+    def _test_base(self, save_otherwise_load):
+        scope = fluid.core.Scope()
+        main_prog = paddle.static.Program()
+        startup_prog = paddle.static.Program()
+        main_prog.random_seed = self.SEED
+        startup_prog.random_seed = self.SEED
+        generator = fluid.unique_name.UniqueNameGenerator()
+
+        with fluid.unique_name.guard(generator):
+            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')
+                    conv1 = paddle.static.nn.conv2d(
+                        x,
+                        num_filters=3,
+                        filter_size=3,
+                        bias_attr=False,
+                        name='conv2d')
+                    loss = paddle.mean(conv1)
+
+                    if self.attrs['is_training']:
+                        if self.attrs['opt_type'] == 'sgd':
+                            sgd = paddle.optimizer.SGD(learning_rate=1e-2)
+                            sgd.minimize(loss)
+                        elif self.attrs['opt_type'] == 'adam':
+                            adam = paddle.optimizer.Adam(learning_rate=1e-2)
+                            adam.minimize(loss)
+                        elif self.attrs['opt_type'] == 'lamb':
+                            lamb = paddle.optimizer.Lamb(learning_rate=1e-2)
+                            lamb.minimize(loss)
+                    fetch_list = [loss.name]
+
+                place = paddle.IPUPlace()
+                exe = paddle.static.Executor(place)
+                exe.run(startup_prog)
+
+                if not save_otherwise_load:
+                    paddle.static.load(main_prog, "model/model")
+
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = self.attrs['is_training']
+                program = compiler.IPUCompiledProgram(
+                    main_prog, ipu_strategy=ipu_strategy).compile(
+                        self.feed_list, fetch_list)
+
+                result = []
+                run_steps = self.attrs['steps'] if save_otherwise_load \
+                    else self.attrs['steps'] - self.attrs['save_at_step']
+
+                for i in range(run_steps):
+                    tmp = exe.run(program,
+                                  feed=self.feed,
+                                  fetch_list=fetch_list)
+
+                    # currently, we update opt state every sess.run,
+                    # will optimize
+                    if save_otherwise_load and \
+                        i == self.attrs['save_at_step'] - 1:
+                        paddle.static.save(main_prog, "model/model")
+
+                    if save_otherwise_load and i >= self.attrs['save_at_step']:
+                        result.append(tmp)
+                    elif not save_otherwise_load:
+                        result.append(tmp)
+
+                return np.asarray(result).flatten()
+
+    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))
+        shutil.rmtree("model", True)
+
+
+class TestAdam(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['steps'] = 100
+        self.attrs['save_at_step'] = 20
+        self.attrs['is_training'] = True
+        self.attrs['opt_type'] = 'adam'
+
+
+class TestLamb(TestBase):
+    def set_attrs(self):
+        self.attrs = {}
+        self.attrs['steps'] = 100
+        self.attrs['save_at_step'] = 20
+        self.attrs['is_training'] = True
+        self.attrs['opt_type'] = 'lamb'
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_scale_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 = {
+            "scale": 1.0,
+            "bias": 0.0,
+            "bias_after_scale": True,
+        }
+
+    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.scale(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):
+        self.attrs = {
+            "scale": 5.0,
+            "bias": 0.0,
+            "bias_after_scale": True,
+        }
+
+
+class TestCase2(TestBase):
+    def set_attrs(self):
+        self.attrs = {
+            "scale": 1.0,
+            "bias": 0.5,
+            "bias_after_scale": True,
+        }
+
+
+class TestCase3(TestBase):
+    def set_attrs(self):
+        self.attrs = {
+            "scale": 1.0,
+            "bias": 0.0,
+            "bias_after_scale": False,
+        }
+
+
+class TestCase4(TestBase):
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[3, 3, 10, 10]).astype('float32'),
+            "y": np.array([3.0]).astype('float32'),
+        }
+
+    def set_attrs(self):
+        self.attrs = {
+            "bias": 0.0,
+            "bias_after_scale": True,
+        }
+
+    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.scale(x, scale=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]
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_set_batch_size_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, 128, 128])
+
+        self.feed = {}
+        self.feed["in_0"] = np.random.uniform(
+            size=[2, 3, 128, 128]).astype(np.float32)
+
+        self.feed_list = list(self.feed.keys())
+
+    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='float32')
+                conv1 = paddle.static.nn.conv2d(
+                    x, num_filters=3, filter_size=3, bias_attr=False)
+                conv2 = paddle.static.nn.conv2d(
+                    conv1, num_filters=3, filter_size=3, bias_attr=False)
+                conv3 = paddle.static.nn.conv2d(
+                    conv2, num_filters=3, filter_size=3, bias_attr=False)
+                conv4 = paddle.static.nn.conv2d(
+                    conv3, num_filters=3, filter_size=3, bias_attr=False)
+
+                fetch_list = [conv4.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
+                # set batch size
+                ipu_strategy.batch_size = 2
+                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))
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_sgd_optimizer.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.
+
+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 TestSGD(unittest.TestCase):
+    def _test_sgd(self, run_ipu=True):
+        scope = fluid.core.Scope()
+        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 fluid.scope_guard(scope):
+            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)
+                loss = paddle.mean(conv1)
+
+                sgd = paddle.optimizer.SGD(learning_rate=1e-1)
+                sgd.minimize(loss)
+
+            if run_ipu:
+                place = paddle.IPUPlace()
+            else:
+                place = paddle.CPUPlace()
+            exe = paddle.static.Executor(place)
+            exe.run(startup_prog)
+
+            if run_ipu:
+                feed_list = [image.name]
+                fetch_list = [loss.name]
+                ipu_strategy = compiler.get_ipu_strategy()
+                ipu_strategy.is_training = True
+                program = compiler.IPUCompiledProgram(
+                    main_prog, ipu_strategy=ipu_strategy).compile(feed_list,
+                                                                  fetch_list)
+            else:
+                program = main_prog
+
+            result = []
+            for epoch in range(100):
+                loss_res = exe.run(program,
+                                   feed={"image": np_image},
+                                   fetch_list=[loss])
+                result.append(loss_res)
+
+            return np.array(result)
+
+    def test_sgd(self):
+        # cpu and ipu dimenstion mismatch, cpu:(100, 1, 1), ipu:(100, 1)
+        ipu_loss = self._test_sgd(True).flatten()
+        cpu_loss = self._test_sgd(False).flatten()
+
+        self.assertTrue(np.allclose(ipu_loss, cpu_loss, atol=1e-4))
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_slice_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=[4, 5, 6]).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 = {
+            "axes": [0, 1, 2],
+            "starts": [-3, 0, 2],
+            "ends": [3, 2, 4],
+        }
+
+    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.slice(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):
+        self.attrs = {
+            "axes": [0, 1],
+            "starts": [0, 0],
+            "ends": [-1, 2],
+        }
+
+
+@unittest.skip('dynamic graph is not support on IPU')
+class TestCase2(TestBase):
+    def set_feed(self):
+        self.feed = {
+            "x": np.random.uniform(size=[4, 5, 6]).astype('float32'),
+            "starts": np.array([0, 0, 2]).astype('int32'),
+            "ends": np.array([3, 2, 4]).astype('int32'),
+        }
+
+    def set_attrs(self):
+        self.attrs = {"axes": [0, 1, 2]}
+
+    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])
+                starts = paddle.static.data(
+                    name=self.feed_list[1],
+                    shape=self.feed_shape[1],
+                    dtype=self.feed_dtype[1])
+                ends = paddle.static.data(
+                    name=self.feed_list[2],
+                    shape=self.feed_shape[2],
+                    dtype=self.feed_dtype[2])
+                out = paddle.fluid.layers.slice(
+                    x, starts=starts, ends=ends, **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()