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https://github.com/saymrwulf/pytorch.git
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8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
65 lines
2.8 KiB
Python
65 lines
2.8 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
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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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##############################################################################
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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from caffe2.python import core, workspace
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from caffe2.python.test_util import TestCase
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class TestAtomicOps(TestCase):
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def test_atomic_ops(self):
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"""
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Test that both countdown and checksum are update atomically by having
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cowntdown count from 20k to 0 from parallel the workers and updating
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the checksum to the value fetched. If operations are trully atomic,
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each value from 1 to 20k should be fetched exactly once from the
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countdown, and fed exactly once to the checksum, such that at the end
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checksum must contain the exact value of sum[i=0..20000](i).
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"""
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init_net = core.Net('init')
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mutex_countdown = init_net.CreateMutex([])
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mutex_checksum = init_net.CreateMutex([])
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countdown = init_net.ConstantFill([], shape=[], value=20000,
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dtype=core.DataType.INT32)
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checksum = init_net.ConstantFill(
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[], shape=[], value=0, dtype=core.DataType.INT32)
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minus_one = init_net.ConstantFill(
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[], shape=[], value=-1, dtype=core.DataType.INT32)
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steps = []
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for i in range(0, 100):
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net = core.Net('net:%d' % i)
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_, fetched_count = net.AtomicFetchAdd(
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[mutex_countdown, countdown, minus_one],
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[countdown, 'fetched_count:%d' % i])
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net.AtomicFetchAdd(
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[mutex_checksum, checksum, fetched_count],
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[checksum, 'not_used'])
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steps.append(
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core.execution_step('worker:%d' % i, net, num_iter=200))
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super_step = core.execution_step(
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'parent', steps, concurrent_substeps=True)
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plan = core.Plan('plan')
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plan.AddStep(core.execution_step('init', init_net))
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plan.AddStep(super_step)
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workspace.RunPlan(plan)
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# checksum = sum[i=1..20000](i) = 20000 * 20001 / 2 = 200010000
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self.assertEquals(workspace.FetchBlob(checksum), 200010000)
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if __name__ == "__main__":
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import unittest
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unittest.main()
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