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68 changes: 68 additions & 0 deletions
68
paddle/fluid/framework/ipu/popart_canonicalization/reduce_ops.cc
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| // 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. | ||
|
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| #include "paddle/fluid/framework/ipu/popart_canonicalization/canonicalization_utils.h" | ||
| #include "paddle/fluid/framework/ipu/popart_canonicalization/op_builder.h" | ||
| #include "paddle/fluid/platform/enforce.h" | ||
|
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| namespace paddle { | ||
| namespace framework { | ||
| namespace ipu { | ||
| namespace { | ||
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| Node *reduce_op_handler(Graph *graph, Node *node, const std::string &op_name) { | ||
| auto *op = node->Op(); | ||
| auto attrs = AttributeMap{}; | ||
| auto reduce_all = BOOST_GET_CONST(bool, op->GetAttr("reduce_all")); | ||
| if (!reduce_all) { | ||
| auto axes_ = BOOST_GET_CONST(std::vector<int>, op->GetAttr("dim")); | ||
| auto axes = std::vector<int64_t>{axes_.begin(), axes_.end()}; | ||
| attrs.emplace("axes", axes); | ||
| } | ||
| auto keepdims_ = BOOST_GET_CONST(bool, op->GetAttr("keep_dim")); | ||
| auto keepdims = int64_t{keepdims_}; | ||
| attrs.emplace("keepdims", keepdims); | ||
| return CreateBaseOp(graph, node, op_name, node->inputs, node->outputs, attrs); | ||
| } | ||
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| Node *reduce_mean_handler(Graph *graph, Node *node) { | ||
| return reduce_op_handler(graph, node, "popart_reducemean"); | ||
| } | ||
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| Node *reduce_min_handler(Graph *graph, Node *node) { | ||
| return reduce_op_handler(graph, node, "popart_reducemin"); | ||
| } | ||
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| Node *reduce_sum_handler(Graph *graph, Node *node) { | ||
| return reduce_op_handler(graph, node, "popart_reducesum"); | ||
| } | ||
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| Node *reduce_max_handler(Graph *graph, Node *node) { | ||
| return reduce_op_handler(graph, node, "popart_reducemax"); | ||
| } | ||
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| Node *reduce_prod_handler(Graph *graph, Node *node) { | ||
| return reduce_op_handler(graph, node, "popart_reduceprod"); | ||
| } | ||
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| REGISTER_HANDLER(reduce_mean, reduce_mean_handler); | ||
| REGISTER_HANDLER(reduce_min, reduce_min_handler); | ||
| REGISTER_HANDLER(reduce_sum, reduce_sum_handler); | ||
| REGISTER_HANDLER(reduce_max, reduce_max_handler); | ||
| REGISTER_HANDLER(reduce_prod, reduce_prod_handler); | ||
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| } // namespace | ||
| } // namespace ipu | ||
| } // namespace framework | ||
| } // namespace paddle |
180 changes: 180 additions & 0 deletions
180
python/paddle/fluid/tests/unittests/ipu/test_reduce_x_op_ipu.py
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| # 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. | ||
|
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| import unittest | ||
|
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| 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 | ||
|
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| paddle.enable_static() | ||
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| @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() | ||
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| def init_op(self): | ||
| self.op = paddle.fluid.layers.reduce_mean | ||
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| 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() | ||
| ] | ||
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| 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 | ||
|
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| 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) | ||
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| fetch_list = [out.name] | ||
|
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| if run_ipu: | ||
| place = paddle.IPUPlace() | ||
| else: | ||
| place = paddle.CPUPlace() | ||
| exe = paddle.static.Executor(place) | ||
| exe.run(startup_prog) | ||
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| if run_ipu: | ||
| feed_list = self.feed_list | ||
| ipu_strategy = compiler.get_ipu_strategy() | ||
| ipu_strategy.is_training = self.is_training | ||
| program = compiler.IpuCompiler( | ||
| main_prog, | ||
| ipu_strategy=ipu_strategy).compile(feed_list, fetch_list) | ||
| else: | ||
| program = main_prog | ||
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| result = exe.run(program, feed=self.feed, fetch_list=fetch_list) | ||
| return result[0] | ||
|
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| def run_test_base(self): | ||
| res0 = self._test_base(True) | ||
| res1 = self._test_base(False) | ||
|
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| self.assertTrue( | ||
| np.allclose( | ||
| res0.flatten(), res1.flatten(), atol=self.atol)) | ||
|
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| def set_feed0(self): | ||
| self.feed = {} | ||
| self.feed["in_0"] = np.random.uniform(size=[2, 4]).astype(np.float32) | ||
| self.set_feed_attr() | ||
|
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| def set_feed1(self): | ||
| self.feed = {} | ||
| self.feed["in_0"] = np.random.uniform(size=[2, 2, 2]).astype(np.float32) | ||
| self.set_feed_attr() | ||
|
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| def set_attr0(self): | ||
| self.attrs = {} | ||
| self.attrs['dim'] = None | ||
| self.attrs['keep_dim'] = False | ||
|
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| def test_case0(self): | ||
| self.set_feed0() | ||
| self.set_attr0() | ||
| self.run_test_base() | ||
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| def test_case1(self): | ||
| self.set_feed0() | ||
| self.set_attr0() | ||
| self.attrs['dim'] = 0 | ||
| self.run_test_base() | ||
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| def test_case2(self): | ||
| self.set_feed0() | ||
| self.set_attr0() | ||
| self.attrs['dim'] = -1 | ||
| self.run_test_base() | ||
|
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| def test_case3(self): | ||
| self.set_feed0() | ||
| self.set_attr0() | ||
| self.attrs['dim'] = 1 | ||
| self.run_test_base() | ||
|
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| def test_case4(self): | ||
| self.set_feed0() | ||
| self.attrs = {} | ||
| self.attrs['dim'] = 1 | ||
| self.attrs['keep_dim'] = True | ||
| self.run_test_base() | ||
|
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| def test_case5(self): | ||
| self.set_feed1() | ||
| self.attrs = {} | ||
| self.attrs['dim'] = [1, 2] | ||
| self.attrs['keep_dim'] = False | ||
| self.run_test_base() | ||
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| def test_case6(self): | ||
| self.set_feed1() | ||
| self.attrs = {} | ||
| self.attrs['dim'] = [0, 1] | ||
| self.attrs['keep_dim'] = False | ||
| self.run_test_base() | ||
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| def test_case7(self): | ||
| self.set_feed1() | ||
| self.attrs = {} | ||
| self.attrs['dim'] = [0, 1] | ||
| self.attrs['keep_dim'] = True | ||
| self.run_test_base() | ||
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| class TestMax(TestMean): | ||
| def init_op(self): | ||
| self.op = paddle.fluid.layers.reduce_max | ||
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| class TestMin(TestMean): | ||
| def init_op(self): | ||
| self.op = paddle.fluid.layers.reduce_min | ||
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| class TestProd(TestMean): | ||
| def init_op(self): | ||
| self.op = paddle.fluid.layers.reduce_prod | ||
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| class TestSum(TestMean): | ||
| def init_op(self): | ||
| self.op = paddle.fluid.layers.reduce_sum | ||
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| if __name__ == "__main__": | ||
| unittest.main() |