def __init__(self, methodName='runTest'):
super(TestCallbackList, self).__init__(methodName)
self.callback_1 = MagicMock(spec=torchbearer.callbacks.printer.Tqdm())
self.callback_2 = MagicMock(
spec=torchbearer.callbacks.tensor_board.TensorBoard())
callbacks = [self.callback_1, self.callback_2]
self.list = CallbackList(callbacks)
def test_iter_copy(self):
callback = 'test'
clist = CallbackList([callback])
cpy = clist.__copy__()
self.assertTrue(cpy.callback_list[0] == 'test')
self.assertTrue(cpy is not clist)
cpy = clist.copy()
self.assertTrue(cpy.callback_list[0] == 'test')
self.assertTrue(cpy is not clist)
for cback in clist:
self.assertTrue(cback == 'test')
class TestCallbackList(TestCase):
def __init__(self, methodName='runTest'):
super().__init__(methodName)
self.callback_1 = MagicMock(spec=torchbearer.callbacks.printer.Tqdm())
self.callback_2 = MagicMock(
spec=torchbearer.callbacks.tensor_board.TensorBoard())
callbacks = [self.callback_1, self.callback_2]
self.list = CallbackList(callbacks)
def test_state_dict(self):
self.callback_1.state_dict = Mock(return_value='test_1')
self.callback_2.state_dict = Mock(return_value='test_2')
state = self.list.state_dict()
self.assertEqual(self.callback_1.state_dict.call_count, 1)
self.assertEqual(self.callback_2.state_dict.call_count, 1)
self.assertEqual(state[CallbackList.CALLBACK_STATES][0], 'test_1')
self.assertEqual(state[CallbackList.CALLBACK_STATES][1], 'test_2')
self.assertEqual(state[CallbackList.CALLBACK_TYPES][0],
Tqdm().__class__)
self.assertEqual(state[CallbackList.CALLBACK_TYPES][1],
TensorBoard().__class__)
def test_load_state_dict(self):
self.callback_1.load_state_dict = Mock(return_value='test_1')
self.callback_2.load_state_dict = Mock(return_value='test_2')
self.callback_1.state_dict = Mock(return_value='test_1')
self.callback_2.state_dict = Mock(return_value='test_2')
state = self.list.state_dict()
self.list.load_state_dict(state)
self.callback_1.load_state_dict.assert_called_once_with('test_1')
self.callback_2.load_state_dict.assert_called_once_with('test_2')
state = self.list.state_dict()
state[CallbackList.CALLBACK_TYPES] = list(
reversed(state[CallbackList.CALLBACK_TYPES]))
with self.assertWarns(
UserWarning,
msg=
'Callback classes did not match, expected: {\'TensorBoard\', \'Tqdm\'}'
):
self.list.load_state_dict(state)
def test_for_list(self):
self.list.on_start({})
self.assertTrue(self.callback_1.method_calls[0][0] == 'on_start')
self.assertTrue(self.callback_2.method_calls[0][0] == 'on_start')
def test_list_in_list(self):
callback = 'test'
clist = CallbackList([callback])
clist2 = CallbackList([clist])
self.assertTrue(clist2.callback_list[0] == 'test')
def __init__(self, model, optimizer=None, criterion=None, metrics=[], callbacks=[], verbose=2):
if criterion is None:
def criterion(_, __):
return torch.zeros(1, device=self.state[torchbearer.DEVICE], dtype=self.state[torchbearer.DATA_TYPE], requires_grad=True)
self.verbose = verbose
self.closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE, torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
self.state = State()
self.state.update({
torchbearer.MODEL: model,
torchbearer.CRITERION: criterion,
torchbearer.OPTIMIZER: optimizer if optimizer is not None else MockOptimizer(),
torchbearer.METRIC_LIST: MetricList(metrics),
torchbearer.CALLBACK_LIST: CallbackList(callbacks),
torchbearer.DEVICE: 'cpu',
torchbearer.DATA_TYPE: torch.float32,
torchbearer.SELF: self,
torchbearer.HISTORY: [],
torchbearer.BACKWARD_ARGS: {},
torchbearer.TRAIN_GENERATOR: None,
torchbearer.VALIDATION_GENERATOR: None,
torchbearer.TEST_GENERATOR: None,
torchbearer.TRAIN_STEPS: None,
torchbearer.VALIDATION_STEPS: None,
torchbearer.TEST_STEPS: None,
torchbearer.TRAIN_DATA: None,
torchbearer.VALIDATION_DATA: None,
torchbearer.TEST_DATA: None,
torchbearer.INF_TRAIN_LOADING: False,
torchbearer.LOADER: None
})
self.state[torchbearer.CALLBACK_LIST].on_init(self.state)
def __init__(self, model, optimizer=None, criterion=None, metrics=[], callbacks=[], pass_state=False):
if criterion is None:
def criterion(_, y_true):
return torch.zeros(1, device=y_true.device)
self.pass_state = pass_state
self.state = State()
self.state.update({
torchbearer.MODEL: model,
torchbearer.CRITERION: criterion,
torchbearer.OPTIMIZER: optimizer if optimizer is not None else MockOptimizer(),
torchbearer.METRIC_LIST: MetricList(metrics),
torchbearer.CALLBACK_LIST: CallbackList(callbacks),
torchbearer.DEVICE: 'cpu',
torchbearer.DATA_TYPE: torch.float32,
torchbearer.SELF: self,
torchbearer.HISTORY: [],
torchbearer.BACKWARD_ARGS: {},
torchbearer.TRAIN_GENERATOR: None,
torchbearer.VALIDATION_GENERATOR: None,
torchbearer.TEST_GENERATOR: None,
torchbearer.TRAIN_STEPS: None,
torchbearer.VALIDATION_STEPS: None,
torchbearer.TEST_STEPS: None
})
class TestCallbackList(TestCase):
def __init__(self, methodName='runTest'):
super().__init__(methodName)
self.callback_1 = MagicMock()
self.callback_2 = MagicMock()
callbacks = [self.callback_1, self.callback_2]
self.list = CallbackList(callbacks)
def test_for_list(self):
self.list.on_start({})
self.assertTrue(self.callback_1.method_calls[0][0] == 'on_start')
self.assertTrue(self.callback_2.method_calls[0][0] == 'on_start')
def test_list_in_list(self):
callback = 'test'
clist = CallbackList([callback])
clist2 = CallbackList([clist])
self.assertTrue(clist2.callback_list[0] == 'test')
def replay(self, callbacks=[], verbose=2, one_batch=False): # TODO: Should we track if testing passes have happened?
""" Replay the fit passes stored in history with given callbacks, useful when reloading a saved Trial. Note that only progress and metric information is populated in state during a replay.
Args:
callbacks (list): List of callbacks to be run during the replay
verbose (int): If 2: use tqdm on batch, If 1: use tqdm on epoch, If 0: display no training progress
one_batch (bool): If True, only one batch per epoch is replayed. If False, all batches are replayed
Returns:
Trial: self
"""
history = self.state[torchbearer.HISTORY]
callbacks.append(get_printer(verbose=verbose, validation_label_letter='v'))
callbacks = CallbackList(callbacks)
state = State()
state.update(self.state)
state[torchbearer.STOP_TRAINING] = False
state[torchbearer.MAX_EPOCHS] = len(history)
callbacks.on_start(state)
for i in range(len(history)):
state[torchbearer.EPOCH] = i
if not one_batch:
state[torchbearer.TRAIN_STEPS], state[torchbearer.VALIDATION_STEPS] = history[i][0]
else:
state[torchbearer.TRAIN_STEPS], state[torchbearer.VALIDATION_STEPS] = 1, 1
state[torchbearer.METRICS] = history[i][1]
self._replay_pass(state, callbacks)
callbacks.on_end(state)
return self
def replay(self,
callbacks=[],
verbose=2
): # TODO: Should we track if testing passes have happened?
""" Replay the fit passes stored in history with given callbacks, useful when reloading a saved Trial. Note that only progress and metric information is populated in state during a replay.
:param callbacks: List of callbacks to be run during the replay
:type callbacks: list
:param verbose: If 2: use tqdm on batch, If 1: use tqdm on epoch, Else: display no training progress
:type verbose: int
:return: self
:rtype: Trial
"""
history = self.state[torchbearer.HISTORY]
callbacks.append(
get_printer(verbose=verbose, validation_label_letter='v'))
callbacks = CallbackList(callbacks)
state = State()
state.update(self.state)
state[torchbearer.STOP_TRAINING] = False
state[torchbearer.MAX_EPOCHS] = len(history)
callbacks.on_start(state)
for i in range(len(history)):
state[torchbearer.EPOCH] = i
state[torchbearer.TRAIN_STEPS], state[
torchbearer.VALIDATION_STEPS] = history[i][0]
state[torchbearer.METRICS] = history[i][1]
self._replay_pass(state, callbacks)
callbacks.on_end(state)
class TestCallbackList(TestCase):
def __init__(self, methodName='runTest'):
super(TestCallbackList, self).__init__(methodName)
self.callback_1 = MagicMock(spec=torchbearer.callbacks.printer.Tqdm())
self.callback_2 = MagicMock(
spec=torchbearer.callbacks.tensor_board.TensorBoard())
callbacks = [self.callback_1, self.callback_2]
self.list = CallbackList(callbacks)
def test_state_dict(self):
self.callback_1.state_dict = Mock(return_value='test_1')
self.callback_2.state_dict = Mock(return_value='test_2')
state = self.list.state_dict()
self.assertEqual(self.callback_1.state_dict.call_count, 1)
self.assertEqual(self.callback_2.state_dict.call_count, 1)
self.assertEqual(state[CallbackList.CALLBACK_STATES][0], 'test_1')
self.assertEqual(state[CallbackList.CALLBACK_STATES][1], 'test_2')
self.assertEqual(state[CallbackList.CALLBACK_TYPES][0],
Tqdm().__class__)
self.assertEqual(state[CallbackList.CALLBACK_TYPES][1],
TensorBoard().__class__)
def test_load_state_dict(self):
self.callback_1.load_state_dict = Mock(return_value='test_1')
self.callback_2.load_state_dict = Mock(return_value='test_2')
self.callback_1.state_dict = Mock(return_value='test_1')
self.callback_2.state_dict = Mock(return_value='test_2')
state = self.list.state_dict()
self.list.load_state_dict(state)
self.callback_1.load_state_dict.assert_called_once_with('test_1')
self.callback_2.load_state_dict.assert_called_once_with('test_2')
state = self.list.state_dict()
state[CallbackList.CALLBACK_TYPES] = list(
reversed(state[CallbackList.CALLBACK_TYPES]))
with warnings.catch_warnings(record=True) as w:
self.list.load_state_dict(state)
self.assertTrue(len(w) == 1)
self.assertTrue(issubclass(w[-1].category, UserWarning))
self.assertTrue(
'Callback classes did not match, expected: [\'TensorBoard\', \'Tqdm\']'
in str(w[-1].message))
def test_for_list(self):
self.list.on_start({})
self.assertTrue(self.callback_1.method_calls[0][0] == 'on_start')
self.assertTrue(self.callback_2.method_calls[0][0] == 'on_start')
def test_list_in_list(self):
callback = 'test'
clist = CallbackList([callback])
clist2 = CallbackList([clist])
self.assertTrue(clist2.callback_list[0] == 'test')
def test_iter_copy(self):
callback = 'test'
clist = CallbackList([callback])
cpy = clist.__copy__()
self.assertTrue(cpy.callback_list[0] == 'test')
self.assertTrue(cpy is not clist)
cpy = clist.copy()
self.assertTrue(cpy.callback_list[0] == 'test')
self.assertTrue(cpy is not clist)
for cback in clist:
self.assertTrue(cback == 'test')
def test_list_in_list(self):
callback = 'test'
clist = CallbackList([callback])
clist2 = CallbackList([clist])
self.assertTrue(clist2.callback_list[0] == 'test')
def __init__(self, methodName='runTest'):
super().__init__(methodName)
self.callback_1 = MagicMock()
self.callback_2 = MagicMock()
callbacks = [self.callback_1, self.callback_2]
self.list = CallbackList(callbacks)