ipu_commit_tests p4 (#38092)

python/paddle/fluid/tests/unittests/ipu/test_cross_entropy2_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=[3, 7]).astype('float32'),
+            "label": np.arange(3).reshape([3]).astype(np.int64),
+        }
+
+    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 = {'soft_label': 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=self.feed_dtype[0])
+
+                # [warning] Copying (host) tensor input/1 from INT64 to INT32.
+                #  Will only warn once
+                if run_ipu:
+                    label = paddle.static.data(
+                        name=self.feed_list[1],
+                        shape=self.feed_shape[1],
+                        dtype='int32')
+                else:
+                    label = paddle.static.data(
+                        name=self.feed_list[1],
+                        shape=self.feed_shape[1],
+                        dtype='int64')
+
+                out = fluid.layers.cross_entropy(
+                    input=x, label=label, **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 = {
+            'soft_label': False,
+            'ignore_index': 1,
+        }
+
+
+@unittest.skip("soft_label=True id not supported")
+class TestCase2(TestBase):
+    def set_attrs(self):
+        self.attrs = {'soft_label': True, }
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_dropout_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 = {
+            "dropout_prob": 0.5,
+            "is_test": True,
+            "dropout_implementation": "downgrade_in_infer"
+        }
+
+    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])
+                dropout = paddle.fluid.layers.dropout(x, **self.attrs)
+                out = paddle.fluid.layers.elementwise_add(dropout, dropout)
+
+                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 = {
+            "dropout_prob": 0.5,
+            "is_test": True,
+            "dropout_implementation": "upscale_in_train"
+        }
+
+
+class TestCase2(TestBase):
+    def set_attrs(self):
+        self.attrs = {
+            "dropout_prob": 0.0,
+            "is_test": False,
+            "dropout_implementation": "upscale_in_train"
+        }
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_elemetwise_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 TestMul(IPUOpTest):
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.init_op()
+
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_mul
+
+    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=self.feed_dtype[0])
+                y = paddle.static.data(
+                    name=self.feed_list[1],
+                    shape=self.feed_shape[1],
+                    dtype=self.feed_dtype[1])
+                out = self.op(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 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))
+
+        self.assertTrue(res0.shape == res1.shape)
+
+    def test_case0(self):
+        self.feed = {
+            "x": np.random.uniform(size=(2, 3, 4, 5)).astype('float32'),
+            "y": np.random.uniform(size=(2, 3, 4, 5)).astype('float32'),
+        }
+        self.attrs = {}
+        self.set_feed_attr()
+        self.run_test_base()
+
+    def test_case1(self):
+        self.feed = {
+            "x": np.random.uniform(size=(2, 3, 4, 5)).astype('float32'),
+            "y": np.random.uniform(size=(3, 4)).astype('float32'),
+        }
+        self.set_feed_attr()
+        self.attrs = {"axis": 1}
+        self.run_test_base()
+
+    def test_case2(self):
+        self.feed = {
+            "x": np.random.uniform(size=(2, 3, 4, 5)).astype('float32'),
+            "y": np.random.uniform(size=(5)).astype('float32'),
+        }
+        self.set_feed_attr()
+        self.attrs = {"axis": -1}
+        self.run_test_base()
+
+    def test_case3(self):
+        self.feed = {
+            "x": np.random.uniform(size=(2, 3, 4, 5)).astype('float32'),
+            "y": np.random.uniform(size=(2)).astype('float32'),
+        }
+        self.set_feed_attr()
+        self.attrs = {"axis": 0}
+        self.run_test_base()
+
+
+class TestAdd(TestMul):
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_add
+
+
+class TestSub(TestMul):
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_sub
+
+
+class TestDiv(TestMul):
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_div
+
+
+class TestMin(TestMul):
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_min
+
+
+class TestMax(TestMul):
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_max
+
+
+class TestPow(TestMul):
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_pow
+
+
+class TestMod(TestMul):
+    def init_op(self):
+        self.op = paddle.fluid.layers.elementwise_mod
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_equal_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.ones([1, 10]).astype('float32'),
+            "y": np.zeros([1, 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 = {}
+
+    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):
+                # XX
+                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.equal(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(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_feed(self):
+        self.feed = {
+            "x": np.ones([1, 10]).astype('float32'),
+            "y": np.ones([1, 10]).astype('float32'),
+        }
+
+
+class TestCase2(TestBase):
+    def set_feed(self):
+        self.feed = {
+            "x": np.ones([1, 10]).astype('float32'),
+            "y": np.arange(0, 10).reshape([1, 10]).astype('float32'),
+        }
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_expand_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, 3, 1]).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 = {"expand_times": [1, 2, 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])
+                out = paddle.fluid.layers.expand(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=[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 = {}
+
+    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])
+                expand_times = fluid.layers.fill_constant(
+                    shape=[len(self.feed_shape[0])], dtype="int32", value=2)
+                out = paddle.fluid.layers.expand(
+                    x, expand_times=expand_times, **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_fill_constant_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 = {}
+
+    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 = {
+            'name': 'x',
+            'shape': [1, 3, 3, 3],
+            'dtype': 'float32',
+            'value': 0.3,
+        }
+
+    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.fluid.layers.fill_constant(**self.attrs)
+                out = paddle.fluid.layers.elementwise_add(x, x)
+
+                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 = {
+            'name': 'x',
+            'shape': [1, 3, 3, 3],
+            'dtype': 'int32',
+            'value': 3.0,
+        }
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/fluid/tests/unittests/ipu/test_gather_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=[10, 20]).astype('float32'),
+            "y": np.array([1, 3, 5]).astype('int32'),
+        }
+
+    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 = {}
+
+    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.gather(x, index=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=[100]).astype('float32'),
+            "y": np.array([1, 3, 5]).astype('int32'),
+        }
+
+
+if __name__ == "__main__":
+    unittest.main()