From 5fc8326732bcd5a40fd96190ba0fbc9a1fc135d1 Mon Sep 17 00:00:00 2001 From: fengjiayi Date: Mon, 16 Apr 2018 17:05:01 +0800 Subject: [PATCH] Add parallel accuracy test --- .../tests/unittests/test_parallel_executor.py | 24 +++++++++++++++++-- 1 file changed, 22 insertions(+), 2 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_parallel_executor.py b/python/paddle/fluid/tests/unittests/test_parallel_executor.py index 83d22fd799..fda8651032 100644 --- a/python/paddle/fluid/tests/unittests/test_parallel_executor.py +++ b/python/paddle/fluid/tests/unittests/test_parallel_executor.py @@ -203,10 +203,14 @@ class TestParallelExecutorBase(unittest.TestCase): iter=10, batch_size=None, allow_op_delay=False, - feed_dict={}): + feed_dict={}, + random_seed=None, + use_parallel_executor=True): main = fluid.Program() startup = fluid.Program() with fluid.program_guard(main, startup): + if seed is not None: + startup.random_seed(random_seed) loss = method(use_feed=len(feed_dict) > 0) adam = fluid.optimizer.Adam() adam.minimize(loss) @@ -217,7 +221,11 @@ class TestParallelExecutorBase(unittest.TestCase): startup_exe = fluid.Executor(place) startup_exe.run(startup) - exe = fluid.ParallelExecutor(True, loss_name=loss.name) + if use_parallel_executor: + exe = fluid.ParallelExecutor(True, loss_name=loss.name) + else: + exe = fluid.Executor(place=place) + if batch_size is not None: batch_size *= fluid.core.get_cuda_device_count() begin = time.time() @@ -238,6 +246,7 @@ class TestParallelExecutorBase(unittest.TestCase): print first_loss, last_loss # self.assertGreater(first_loss[0], last_loss[0]) + return first_loss, last_loss class TestMNIST(TestParallelExecutorBase): @@ -267,6 +276,17 @@ class TestMNIST(TestParallelExecutorBase): simple_fc_net, feed_dict={"image": img, "label": label}) + def test_simple_fc_parallel_accuracy(self): + single_first_loss, single_last_loss = self.check_network_convergence( + simple_fc_net, random_seed=0, use_parallel_executor=False) + parallel_first_loss, parallel_last_loss = self.check_network_convergence( + simple_fc_net, random_seed=0, use_parallel_executor=True) + print("FUCK") + print('single_first_loss=', single_first_loss) + print('single_last_loss=', single_last_loss) + print('parallel_first_loss=', parallel_first_loss) + print('parallel_last_loss=', parallel_last_loss) + def test_batchnorm_fc(self): self.check_network_convergence(fc_with_batchnorm) img = numpy.zeros(shape=[32, 784], dtype='float32') -- GitLab