Training Tests: Specify -save.
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@ -56,6 +56,7 @@ def test_dnn_training():
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assert p.returncode == 0
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netWorkDir = tempfile.mkdtemp(prefix='OpenFaceTrainingTest-Net-')
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saveDir = os.path.join(netWorkDir, '1')
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cmd = ['th', './main.lua',
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'-data', os.path.join(imgWorkDir, 'aligned'),
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'-modelDef', '../models/openface/nn4.def.lua',
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@ -64,6 +65,7 @@ def test_dnn_training():
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'-nEpochs', '10',
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'-epochSize', '1',
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'-cache', netWorkDir,
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'-save', saveDir,
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'-cuda', '-cudnn', '-testing',
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'-nDonkeys', '-1']
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p = Popen(cmd, stdout=PIPE, stderr=PIPE,
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@ -74,9 +76,8 @@ def test_dnn_training():
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assert p.returncode == 0
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# Training won't make much progress on lfw-subset, but as a sanity check,
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# make sure the training code runs and doesn't get worse than the initialize
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# loss value of 0.2.
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trainLoss = pd.read_csv(os.path.join(netWorkDir, '001', 'train.log'),
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# make sure the training code runs and doesn't get worse than 0.2.
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trainLoss = pd.read_csv(os.path.join(saveDir, 'train.log'),
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sep='\t').as_matrix()[:, 0]
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assert np.mean(trainLoss) < 0.3
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