[IPU] add Op uts (PaddlePaddle#44415)

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

@@ -17,7 +17,7 @@
 import numpy as np
 import paddle
 import paddle.static
-from op_test_ipu import IPUOpTest
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import IPUOpTest
 
 
 class TestBase(IPUOpTest):

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

@@ -0,0 +1,91 @@
+#  Copyright (c) 2022 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.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import IPUOpTest
+
+
+class TestBase(IPUOpTest):
+
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_data_feed()
+        self.set_feed_attr()
+
+    def set_data_feed(self):
+        data = np.random.uniform(size=[2, 3, 1])
+        self.feed_fp32 = {'in_0': data.astype(np.float32)}
+        self.feed_fp16 = {'in_0': data.astype(np.float16)}
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed_fp32.values()]
+        self.feed_list = list(self.feed_fp32.keys())
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        y = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        self.main_prog.global_block().append_op(type="share_data",
+                                                inputs={"X": x},
+                                                outputs={'Out': y})
+        out = paddle.fluid.layers.elementwise_add(y, y)
+        self.fetch_list = [out.name]
+
+    def run_model(self, exec_mode):
+        self.run_op_test(exec_mode)
+
+    def test(self):
+        for m in IPUOpTest.ExecutionMode:
+            if not self.skip_mode(m):
+                self.build_model()
+                self.run_model(m)
+        self.check()
+
+
+class TestCase1(TestBase):
+
+    def set_data_feed(self):
+        data = np.random.uniform(size=[2, 3, 1])
+        self.feed_fp32 = {'in_0': data.astype(np.float32)}
+        self.feed_fp16 = {'in_0': data.astype(np.float16)}
+
+        data = np.random.uniform(size=[2, 3, 1])
+        self.assign_fp32 = data.astype(np.float32)
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        y = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        self.main_prog.global_block().append_op(type="share_data",
+                                                inputs={"X": x},
+                                                outputs={'Out': y})
+        out = paddle.fluid.layers.elementwise_add(x, y)
+        self.fetch_list = [out.name]
+
+
+if __name__ == "__main__":
+    unittest.main()

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

@@ -0,0 +1,142 @@
+#  Copyright (c) 2022 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.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import IPUOpTest
+
+
+class TestBase(IPUOpTest):
+
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_data_feed()
+        self.set_feed_attr()
+        self.set_op_attrs()
+
+    def set_data_feed(self):
+        data = np.random.uniform(size=[3, 4, 5, 6])
+        self.feed_fp32 = {"in_0": data.astype(np.float32)}
+        self.feed_fp16 = {"in_0": data.astype(np.float16)}
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed_fp32.values()]
+        self.feed_list = list(self.feed_fp32.keys())
+        self.feed_dtype = [x.dtype for x in self.feed_fp32.values()]
+
+    def set_op_attrs(self):
+        self.attrs = {
+            "axes": [1, 2, 3],
+            "starts": [-3, 0, 2],
+            "ends": [3, 2, 4],
+            "strides": [1, 1, 1]
+        }
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        out = paddle.fluid.layers.strided_slice(x, **self.attrs)
+        self.fetch_list = [out.name]
+
+    def run_model(self, exec_mode):
+        self.run_op_test(exec_mode)
+
+    def test(self):
+        for m in IPUOpTest.ExecutionMode:
+            if not self.skip_mode(m):
+                self.build_model()
+                self.run_model(m)
+        self.check()
+
+
+class TestCase1(TestBase):
+
+    def set_data_feed(self):
+        data = np.random.uniform(size=[2, 4])
+        self.feed_fp32 = {"in_0": data.astype(np.float32)}
+        self.feed_fp16 = {"in_0": data.astype(np.float16)}
+
+    def set_op_attrs(self):
+        self.attrs = {
+            "axes": [0, 1],
+            "starts": [1, 3],
+            "ends": [2, 0],
+            "strides": [1, -1]
+        }
+
+
+@unittest.skip('Only strides of 1 or -1 are supported.')
+class TestCase2(TestBase):
+
+    def set_data_feed(self):
+        data = np.random.uniform(size=[2, 4])
+        self.feed_fp32 = {"in_0": data.astype(np.float32)}
+        self.feed_fp16 = {"in_0": data.astype(np.float16)}
+
+    def set_op_attrs(self):
+        self.attrs = {
+            "axes": [0, 1],
+            "starts": [1, 3],
+            "ends": [-1, 1000],
+            "strides": [1, 3]
+        }
+
+
+@unittest.skip('dynamic graph is not support on IPU')
+class TestCase3(TestBase):
+
+    def set_data_feed(self):
+        x = np.random.uniform(size=[4, 5, 6])
+        s = np.array([0, 0, 2])
+        e = np.array([3, 2, 4])
+        self.feed_fp32 = {
+            "x": x.astype(np.float32),
+            "starts": s.astype(np.int32),
+            "ends": e.astype(np.int32)
+        }
+        self.feed_fp16 = {
+            "x": x.astype(np.float16),
+            "starts": s.astype(np.int32),
+            "ends": e.astype(np.int32)
+        }
+
+    def set_op_attrs(self):
+        self.attrs = {"strides": [1, 1, 1], "axes": [0, 1, 2]}
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        starts = paddle.static.data(name=self.feed_list[1],
+                                    shape=self.feed_shape[1],
+                                    dtype='int32')
+        ends = paddle.static.data(name=self.feed_list[2],
+                                  shape=self.feed_shape[2],
+                                  dtype='int32')
+        out = paddle.fluid.layers.strided_slice(x,
+                                                starts=starts,
+                                                ends=ends,
+                                                **self.attrs)
+        self.fetch_list = [out.name]
+
+
+if __name__ == "__main__":
+    unittest.main()

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

@@ -0,0 +1,105 @@
+#  Copyright (c) 2022 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.static
+from paddle.fluid.tests.unittests.ipu.op_test_ipu import IPUOpTest
+
+
+class TestBase(IPUOpTest):
+
+    def setUp(self):
+        self.set_atol()
+        self.set_training()
+        self.set_data_feed()
+        self.set_feed_attr()
+        self.set_op_attrs()
+
+    def set_data_feed(self):
+        data = np.random.uniform(size=[4, 5, 6])
+        self.feed_fp32 = {"in_0": data.astype(np.float32)}
+        self.feed_fp16 = {"in_0": data.astype(np.float16)}
+
+    def set_feed_attr(self):
+        self.feed_shape = [x.shape for x in self.feed_fp32.values()]
+        self.feed_list = list(self.feed_fp32.keys())
+        self.feed_dtype = [x.dtype for x in self.feed_fp32.values()]
+
+    def set_op_attrs(self):
+        self.attrs = {
+            "repeat_times": [1, 2],
+        }
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        out = paddle.tile(x, **self.attrs)
+        self.fetch_list = [out.name]
+
+    def run_model(self, exec_mode):
+        self.run_op_test(exec_mode)
+
+    def test(self):
+        for m in IPUOpTest.ExecutionMode:
+            if not self.skip_mode(m):
+                self.build_model()
+                self.run_model(m)
+        self.check()
+
+
+class TestCase1(TestBase):
+
+    def set_op_attrs(self):
+        self.attrs = {
+            "repeat_times": [2, 3, 2],
+        }
+
+
+@unittest.skip('dynamic graph is not support on IPU')
+class TestCase3(TestBase):
+
+    def set_data_feed(self):
+        x = np.random.uniform(size=[4, 5, 6])
+        r = np.array([3, 2, 4])
+        self.feed_fp32 = {
+            "x": x.astype(np.float32),
+            "repeat_times": r.astype(np.int32),
+        }
+        self.feed_fp16 = {
+            "x": x.astype(np.float16),
+            "repeat_times": r.astype(np.int32),
+        }
+
+    def set_op_attrs(self):
+        self.attrs = {}
+
+    @IPUOpTest.static_graph
+    def build_model(self):
+        x = paddle.static.data(name=self.feed_list[0],
+                               shape=self.feed_shape[0],
+                               dtype='float32')
+        r = paddle.static.data(name=self.feed_list[1],
+                               shape=self.feed_shape[1],
+                               dtype='int32')
+        out = paddle.tile(x, repeat_times=r, **self.attrs)
+        self.fetch_list = [out.name]
+
+
+if __name__ == "__main__":
+    unittest.main()