wehub-resource-sync
100 lines
3.1 KiB
Python
100 lines
3.1 KiB
Python
# Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test_ipu import IPUOpTest
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import paddle
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import paddle.static
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def set_serialize_factor(serialize_factor):
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main_prog = paddle.static.default_main_program()
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op = main_prog.current_block().ops[-1]
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op._set_attr('serialize_factor', serialize_factor)
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class TestBase(IPUOpTest):
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def setUp(self):
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self.set_atol()
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self.set_training()
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self.set_data_feed()
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self.set_feed_attr()
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self.set_op_attrs()
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def set_data_feed(self):
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self.feed = {
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"x": np.random.uniform(size=[16, 32]).astype('float32'),
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"y": np.random.uniform(size=[32, 16]).astype('float32'),
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}
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def set_feed_attr(self):
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self.feed_shape = [x.shape for x in self.feed.values()]
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self.feed_list = list(self.feed.keys())
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self.feed_dtype = [x.dtype for x in self.feed.values()]
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def set_op_attrs(self):
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self.attrs = {"transpose_x": False, "transpose_y": False}
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@IPUOpTest.static_graph
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def build_model(self):
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x = paddle.static.data(
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name=self.feed_list[0],
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shape=self.feed_shape[0],
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dtype=self.feed_dtype[0],
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)
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y = paddle.static.data(
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name=self.feed_list[1],
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shape=self.feed_shape[1],
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dtype=self.feed_dtype[1],
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)
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# decorator maybe the best choice, but need to modify api
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out = paddle.matmul(x, y, **self.attrs)
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set_serialize_factor(4)
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self.fetch_list = [out.name]
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def run_model(self, run_ipu):
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self.build_model()
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if run_ipu:
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place = paddle.IPUPlace()
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else:
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place = paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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exe.run(self.startup_prog)
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if run_ipu:
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feed_list = self.feed_list
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ipu_strategy = paddle.static.IpuStrategy()
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ipu_strategy.set_graph_config(is_training=self.is_training)
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program = paddle.static.IpuCompiledProgram(
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self.main_prog, ipu_strategy=ipu_strategy
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).compile(feed_list, self.fetch_list)
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else:
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program = self.main_prog
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result = exe.run(program, feed=self.feed, fetch_list=self.fetch_list)
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return result[0]
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def test_base(self):
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res0 = self.run_model(False)
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res1 = self.run_model(True)
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np.testing.assert_allclose(
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res0.flatten(), res1.flatten(), rtol=1e-05, atol=self.atol
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)
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self.assertTrue(res0.shape == res1.shape)
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if __name__ == "__main__":
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unittest.main()
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