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| 1 | +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. |
| 2 | +# |
| 3 | +# Licensed under the Apache License, Version 2.0 (the "License"); |
| 4 | +# you may not use this file except in compliance with the License. |
| 5 | +# You may obtain a copy of the License at |
| 6 | +# |
| 7 | +# http://www.apache.org/licenses/LICENSE-2.0 |
| 8 | +# |
| 9 | +# Unless required by applicable law or agreed to in writing, software |
| 10 | +# distributed under the License is distributed on an "AS IS" BASIS, |
| 11 | +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| 12 | +# See the License for the specific language governing permissions and |
| 13 | +# limitations under the License. |
| 14 | + |
| 15 | +from __future__ import print_function |
| 16 | +import paddle |
| 17 | +import paddle.fluid as fluid |
| 18 | +import contextlib |
| 19 | +import unittest |
| 20 | + |
| 21 | + |
| 22 | +def train_simulator(use_cuda, test_batch_size=10): |
| 23 | + if test_batch_size <= 0: |
| 24 | + raise ValueError("batch_size should be a positive integeral value, " |
| 25 | + "but got batch_size={}".format(test_batch_size)) |
| 26 | + |
| 27 | + x = fluid.layers.data(name='x', shape=[13], dtype='float32') |
| 28 | + y_predict = fluid.layers.fc(input=x, size=1, act=None) |
| 29 | + y = fluid.layers.data(name='y', shape=[1], dtype='float32') |
| 30 | + |
| 31 | + cost = fluid.layers.square_error_cost(input=y_predict, label=y) |
| 32 | + avg_cost = fluid.layers.mean(cost) |
| 33 | + |
| 34 | + sgd_optimizer = fluid.optimizer.SGD(learning_rate=0.001) |
| 35 | + sgd_optimizer.minimize(avg_cost) |
| 36 | + |
| 37 | + train_reader = paddle.batch( |
| 38 | + paddle.reader.shuffle( |
| 39 | + paddle.dataset.uci_housing.train(), buf_size=500), |
| 40 | + batch_size=test_batch_size) |
| 41 | + |
| 42 | + place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() |
| 43 | + exe = fluid.Executor(place) |
| 44 | + |
| 45 | + lower_usage, upper_usage, unit = fluid.contrib.memory_usage( |
| 46 | + fluid.default_main_program(), batch_size=test_batch_size) |
| 47 | + |
| 48 | + print("memory usage is about %.3f - %.3f %s" % |
| 49 | + (lower_usage, upper_usage, unit)) |
| 50 | + |
| 51 | + |
| 52 | +class TestMemoryUsage(unittest.TestCase): |
| 53 | + def test_cpu(self): |
| 54 | + with self.program_scope_guard(): |
| 55 | + train_simulator(use_cuda=False) |
| 56 | + |
| 57 | + def test_cpu_with_unit_KB(self): |
| 58 | + with self.program_scope_guard(): |
| 59 | + train_simulator(use_cuda=False, test_batch_size=1000) |
| 60 | + |
| 61 | + def test_cpu_with_unit_MB(self): |
| 62 | + with self.program_scope_guard(): |
| 63 | + train_simulator(use_cuda=False, test_batch_size=100000) |
| 64 | + |
| 65 | + def test_cuda(self): |
| 66 | + with self.program_scope_guard(): |
| 67 | + train_simulator(use_cuda=True) |
| 68 | + |
| 69 | + @contextlib.contextmanager |
| 70 | + def program_scope_guard(self): |
| 71 | + prog = fluid.Program() |
| 72 | + startup_prog = fluid.Program() |
| 73 | + scope = fluid.core.Scope() |
| 74 | + with fluid.scope_guard(scope): |
| 75 | + with fluid.program_guard(prog, startup_prog): |
| 76 | + yield |
| 77 | + |
| 78 | + |
| 79 | +if __name__ == '__main__': |
| 80 | + unittest.main() |
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