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test_bases.py
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test_bases.py
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import unittest
from mock import Mock, MagicMock, create_autospec, patch
import torch
import torchbearer
from torchbearer.bases import Metric, Callback, base_closure
from torchbearer.metrics.primitives import CategoricalAccuracy
class TestMetric(unittest.TestCase):
def setUp(self):
self._state = {
torchbearer.Y_TRUE: torch.LongTensor([0, 1, 2, 2, 1]),
torchbearer.Y_PRED: torch.FloatTensor([
[0.9, 0.1, 0.1], # Correct
[0.1, 0.9, 0.1], # Correct
[0.1, 0.1, 0.9], # Correct
[0.9, 0.1, 0.1], # Incorrect
[0.9, 0.1, 0.1], # Incorrect
])
}
self._state[torchbearer.Y_PRED].requires_grad = True
self._targets = [1, 1, 1, 0, 0]
self._metric = CategoricalAccuracy().root
def test_requires_grad(self):
result = self._metric.process(self._state)
self.assertTrue(self._state[torchbearer.Y_PRED].requires_grad is True)
self.assertTrue(result.requires_grad is False)
def test_empty_methods(self):
metric = Metric(name='test')
self.assertTrue(metric.process() is None)
self.assertTrue(metric.process_final() is None)
class TestCallback(unittest.TestCase):
def test_state_dict(self):
callback = Callback()
self.assertEqual(callback.state_dict(), {})
self.assertEqual(callback.load_state_dict({}), callback)
def test_str(self):
callback = Callback()
self.assertEqual(str(callback).strip(), "torchbearer.bases.Callback")
def test_empty_methods(self):
callback = Callback()
self.assertIsNone(callback.on_init({}))
self.assertIsNone(callback.on_start({}))
self.assertIsNone(callback.on_start_epoch({}))
self.assertIsNone(callback.on_start_training({}))
self.assertIsNone(callback.on_sample({}))
self.assertIsNone(callback.on_forward({}))
self.assertIsNone(callback.on_criterion({}))
self.assertIsNone(callback.on_backward({}))
self.assertIsNone(callback.on_step_training({}))
self.assertIsNone(callback.on_end_training({}))
self.assertIsNone(callback.on_end_epoch({}))
self.assertIsNone(callback.on_checkpoint({}))
self.assertIsNone(callback.on_end({}))
self.assertIsNone(callback.on_start_validation({}))
self.assertIsNone(callback.on_sample_validation({}))
self.assertIsNone(callback.on_forward_validation({}))
self.assertIsNone(callback.on_end_validation({}))
self.assertIsNone(callback.on_step_validation({}))
self.assertIsNone(callback.on_criterion_validation({}))
class TestBaseCrit(unittest.TestCase):
def state_model_with_e(self, e):
def model(x, state):
raise e
return x
return model
def stateless_model_with_e(self, e):
def model(x):
raise e
return x
return model
def optional_model_with_e(self, e):
def model(x, state=None):
raise e
return x
return model
def test_opt(self):
opt = Mock()
opt.zero_grad = Mock()
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: None, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(opt.zero_grad.call_count == 1)
def test_forward_x(self):
opt = Mock()
def model_forward(x):
return None
model = create_autospec(model_forward)
x = 'test'
state = {torchbearer.X: x, torchbearer.MODEL: model, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(model.call_args[0][0] == x)
def test_forward_multiple_x(self):
opt = Mock()
def model_forward(x1, x2):
return None
model = create_autospec(model_forward)
x1 = 'test1'
x2 = 'test2'
state = {torchbearer.X: [x1, x2], torchbearer.MODEL: model, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(model.call_args[0][0] == x1)
self.assertTrue(model.call_args[0][1] == x2)
def test_forward_state(self):
opt = Mock()
def model_forward(x, state):
return None
model = create_autospec(model_forward)
x = 'test'
state = {torchbearer.X: x, torchbearer.MODEL: model, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(model.call_args[0][0] == x)
self.assertDictEqual(model.call_args[1]['state'], state)
def test_forward_multiple_x_and_state(self):
opt = Mock()
def model_forward(x1, x2, state):
return None
model = create_autospec(model_forward)
x1 = 'test1'
x2 = 'test2'
state = {torchbearer.X: [x1, x2], torchbearer.MODEL: model, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(model.call_args[0][0] == x1)
self.assertTrue(model.call_args[0][1] == x2)
self.assertDictEqual(model.call_args[1]['state'], state)
def test_loss_no_state(self):
opt = Mock()
y_pred = 'yp'
y_true = 'yt'
def loss_sig(y_pred, y_true):
return None
crit = create_autospec(loss_sig)
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: y_pred, torchbearer.Y_TRUE: y_true,
torchbearer.CRITERION: crit, torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(crit.call_args[0] == (y_pred, y_true))
def test_loss_multiple_output_no_state(self):
opt = Mock()
y_pred1 = 'yp1'
y_pred2 = 'yp2'
y_true1 = 'yt1'
y_true2 = 'yt2'
def loss_sig(y_pred1, y_pred2, y_true1, y_true2):
return None
crit = create_autospec(loss_sig)
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: (y_pred1, y_pred2), torchbearer.Y_TRUE: (y_true1, y_true2),
torchbearer.CRITERION: crit, torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(crit.call_args[0] == (y_pred1, y_pred2, y_true1, y_true2))
def test_loss_state(self):
opt = Mock()
y_pred = 'yp'
y_true = 'yt'
def loss_sig(state):
return None
crit = create_autospec(loss_sig)
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: y_pred, torchbearer.Y_TRUE: y_true,
torchbearer.CRITERION: crit, torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertDictEqual(crit.call_args[0][0], state)
def test_backward(self):
opt = Mock()
loss = Mock()
loss.backward = Mock()
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: None, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda state: loss, torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(loss.backward.call_count == 1)
def test_callback_list(self):
opt = Mock()
callback_list = Mock()
callback_list.on_forward = Mock()
callback_list.on_criterion = Mock()
callback_list.on_backward = Mock()
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: None, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda state: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: callback_list, torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
closure(state)
self.assertTrue(callback_list.on_forward.call_count == 1)
self.assertTrue(callback_list.on_criterion.call_count == 1)
self.assertTrue(callback_list.on_backward.call_count == 1)
def test_stateless_type_error(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.stateless_model_with_e(TypeError('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 2)
def test_stateless_exception(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.stateless_model_with_e(Exception('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 1)
self.assertTrue('test' in context.exception.args[0][0].args)
def test_exception_exception(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.optional_model_with_e(Exception('test')),
torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 2)
self.assertTrue('test' in context.exception.args[0][0].args)
self.assertTrue('test' in context.exception.args[0][1].args)
def test_state_exception(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.state_model_with_e(Exception('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 1)
self.assertTrue('test' in context.exception.args[0][0].args)
def test_state_type_error(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.state_model_with_e(TypeError('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = base_closure(torchbearer.X, torchbearer.MODEL, torchbearer.Y_PRED, torchbearer.Y_TRUE,
torchbearer.CRITERION, torchbearer.LOSS, torchbearer.OPTIMIZER)
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 2)
class TestApexCrit(unittest.TestCase):
def setUp(self):
super(TestApexCrit, self).setUp()
import types
import sys
module_name = 'apex'
bogus_module = types.ModuleType(module_name)
self.old_module = sys.modules[module_name] if module_name in sys.modules else None
sys.modules[module_name] = bogus_module
self.mock_amp = MagicMock(name=module_name + '.amp')
bogus_module.amp = self.mock_amp
from torchbearer.bases import apex_closure
self.closure = apex_closure()
def tearDown(self):
super(TestApexCrit, self).tearDown()
if self.old_module is not None:
import sys
sys.modules['apex'] = self.old_module
def state_model_with_e(self, e):
def model(x, state):
raise e
return x
return model
def stateless_model_with_e(self, e):
def model(x):
raise e
return x
return model
def test_opt(self):
opt = Mock()
opt.zero_grad = Mock()
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: None, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
closure(state)
self.assertTrue(opt.zero_grad.call_count == 1)
def test_forward_x(self):
opt = Mock()
def model_forward(x):
return None
model = create_autospec(model_forward)
x = 'test'
state = {torchbearer.X: x, torchbearer.MODEL: model, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
closure(state)
self.assertTrue(model.call_args[0][0] == x)
def test_forward_state(self):
opt = Mock()
def model_forward(x, state):
return None
model = create_autospec(model_forward)
x = 'test'
state = {torchbearer.X: x, torchbearer.MODEL: model, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda x,y: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
closure(state)
self.assertTrue(model.call_args[0][0] == x)
self.assertDictEqual(model.call_args[1]['state'], state)
def test_loss_no_state(self):
opt = Mock()
y_pred = 'yp'
y_true = 'yt'
def loss_sig(y_pred, y_true):
return None
crit = create_autospec(loss_sig)
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: y_pred, torchbearer.Y_TRUE: y_true,
torchbearer.CRITERION: crit, torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
closure(state)
self.assertTrue(crit.call_args[0] == (y_pred, y_true))
def test_loss_state(self):
opt = Mock()
y_pred = 'yp'
y_true = 'yt'
def loss_sig(state):
return None
crit = create_autospec(loss_sig)
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: y_pred, torchbearer.Y_TRUE: y_true,
torchbearer.CRITERION: crit, torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
closure(state)
self.assertDictEqual(crit.call_args[0][0], state)
def test_backward(self):
opt = Mock()
loss = Mock()
loss.backward = Mock()
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: None, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda state: loss, torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: MagicMock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
closure(state)
self.assertTrue('backward' in self.mock_amp.scale_loss.mock_calls[2][0])
def test_callback_list(self):
opt = Mock()
callback_list = Mock()
callback_list.on_forward = Mock()
callback_list.on_criterion = Mock()
callback_list.on_backward = Mock()
state = {torchbearer.X: None, torchbearer.MODEL: lambda x: None, torchbearer.Y_TRUE: None,
torchbearer.CRITERION: lambda state: MagicMock(), torchbearer.LOSS: None, torchbearer.OPTIMIZER: opt,
torchbearer.CALLBACK_LIST: callback_list, torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
closure(state)
self.assertTrue(callback_list.on_forward.call_count == 1)
self.assertTrue(callback_list.on_criterion.call_count == 1)
self.assertTrue(callback_list.on_backward.call_count == 1)
def test_stateless_type_error(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.stateless_model_with_e(TypeError('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 2)
def test_stateless_exception(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.stateless_model_with_e(Exception('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 1)
self.assertTrue('test' in context.exception.args[0][0].args)
def test_state_exception(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.state_model_with_e(Exception('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 1)
self.assertTrue('test' in context.exception.args[0][0].args)
def test_state_type_error(self):
state = {torchbearer.X: None, torchbearer.MODEL: self.state_model_with_e(TypeError('test')), torchbearer.CRITERION: lambda state: MagicMock(),
torchbearer.OPTIMIZER: Mock(), torchbearer.CALLBACK_LIST: Mock(), torchbearer.BACKWARD_ARGS: {}}
closure = self.closure
with self.assertRaises(Exception) as context:
closure(state)
self.assertTrue(len(context.exception.args[0]) == 2)