def test_begin(self, *args):
"""Test TrainLineage.begin method."""
args[1].return_value = None
args[2].return_value = Optimizer(Tensor(0.1))
args[3].return_value = None
args[5].serialize.return_value = {}
run_context = {'optimizer': Optimizer(Tensor(0.1)), 'epoch_num': 10}
train_lineage = self.my_train_module(
self.my_summary_record(self.summary_log_path))
train_lineage.begin(self.my_run_context(run_context))
args[4].assert_called()
def test_get_loss_fn_by_network(self, mock_vars):
"""Test get_loss_fn_by_network."""
mock_cell1 = {'_cells': {'key': SoftmaxCrossEntropyWithLogits(0.2)}}
mock_cell2 = {'_cells': {'opt': Optimizer(Tensor(0.1))}}
mock_cell3 = {'_cells': {'loss': SoftmaxCrossEntropyWithLogits(0.1)}}
mock_vars.side_effect = [mock_cell1, mock_cell2, mock_cell3]
res = AnalyzeObject.get_loss_fn_by_network(MagicMock())
self.assertEqual(res, mock_cell3['_cells']['loss'])
def test_get_optimizer_by_network(self, mock_vars):
"""Test get_optimizer_by_network."""
mock_optimizer = Optimizer(Tensor(0.1))
mock_cells = MagicMock()
mock_cells.items.return_value = [{'key': mock_optimizer}]
mock_vars.return_value = {'_cells': {'key': mock_optimizer}}
res = AnalyzeObject.get_optimizer_by_network(MagicMock())
self.assertEqual(res, mock_optimizer)
def test_begin_error(self, *args):
"""Test TrainLineage.begin method."""
args[1].return_value = None
args[2].return_value = Optimizer(Tensor(0.1))
args[3].return_value = None
args[4].side_effect = Exception
args[5].serialize.return_value = {}
run_context = {'optimizer': Optimizer(Tensor(0.1)), 'epoch_num': 10}
train_lineage = self.my_train_module(
self.my_summary_record(self.summary_log_path), True)
with self.assertRaisesRegex(LineageLogError,
'Dataset graph log error'):
train_lineage.begin(self.my_run_context(run_context))
train_lineage = self.my_train_module(
self.my_summary_record(self.summary_log_path))
train_lineage.begin(self.my_run_context(run_context))
args[4].assert_called()
def test_analyze_optimizer(self):
"""Test analyze_optimizer method."""
optimizer = Optimizer(Tensor(0.12))
res = self.analyzer.analyze_optimizer(optimizer)
assert res == 0.12