def test_classification_3():
runner = tasks.ClassificationRunner(model, optimizer,
nn.CrossEntropyLoss(),
TensorBoardLogger())
try:
runner.fit(x.astype(np.float32), y.astype(np.int64))
is_pass = True
except Exception:
is_pass = False
assert is_pass is True
def test_regression_2():
runner = tasks.RegressionRunner(model, optimizer, nn.MSELoss(),
TensorBoardLogger("./logs"))
runner.train_config(epochs=1)
try:
runner.run(verbose=False)
is_pass = True
except Exception:
is_pass = False
assert is_pass is False
def test_classification_2():
runner = tasks.ClassificationRunner(model, optimizer,
nn.CrossEntropyLoss(),
TensorBoardLogger())
runner.train_config(epochs=1)
try:
runner.run(verbose=False)
is_pass = True
except Exception:
is_pass = False
assert is_pass is False
def test_regression_3():
runner = tasks.RegressionRunner(model, optimizer, nn.MSELoss(),
TensorBoardLogger("./logs"))
try:
runner.fit(x.astype(np.float32),
y.astype(np.float32),
batch_size=32,
epochs=1)
is_pass = True
except Exception:
is_pass = False
assert is_pass is True
def test_classification_1():
runner = tasks.ClassificationRunner(model, optimizer,
nn.CrossEntropyLoss(),
TensorBoardLogger("./logs"))
runner.add_loader("train",
train_loader).add_loader("val", val_loader).add_loader(
"test", test_loader)
runner.train_config(epochs=1)
try:
runner.run(verbose=True)
is_pass = True
except Exception:
is_pass = False
assert is_pass is True
def test_classification_1():
runner = tasks.ClassificationRunner(
model,
optimizer,
nn.CrossEntropyLoss(),
TensorBoardLogger(),
scheduler=[optim.lr_scheduler.ExponentialLR(optimizer, gamma=0.9)])
runner.add_loader("train",
train_loader).add_loader("val", val_loader).add_loader(
"test", test_loader)
runner.train_config(epochs=1)
try:
runner.run(verbose=True)
is_pass = True
except Exception as e:
is_pass = False
print(e)
assert is_pass is True
def test_regression_1():
runner = tasks.RegressionRunner(
model,
optimizer,
nn.MSELoss(),
TensorBoardLogger("./logs"),
)
runner.add_loader("train",
train_loader).add_loader("val", val_loader).add_loader(
"test", test_loader)
runner.train_config(epochs=1)
try:
runner.run(verbose=True)
is_pass = True
except Exception as e:
print(e)
is_pass = False
assert is_pass is True
def __init__(self):
super(Runner2, self).__init__()
self.model = nn.Linear(10, 10)
self.optimizer = optim.Adam(self.model.parameters())
self.experiment = TensorBoardLogger("../tmp")
self.criterion = nn.CrossEntropyLoss()