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_regression_2():
runner = tasks.RegressionRunner(
model, optimizer, nn.MSELoss(),
OfflineExperiment(offline_directory="./logs", display_summary_level=0))
runner.train_config(epochs=1)
try:
runner.run(verbose=False)
is_pass = True
except ValueError:
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_regression_3():
runner = tasks.RegressionRunner(
model, optimizer, nn.MSELoss(),
OfflineExperiment(offline_directory="./logs", display_summary_level=0))
try:
runner.fit(x.astype(np.float32),
y.astype(np.float32),
batch_size=32,
epochs=1,
verbose=False)
is_pass = True
except Exception:
is_pass = False
assert is_pass is True
def test_regression_1():
runner = tasks.RegressionRunner(
model, optimizer, nn.MSELoss(),
OfflineExperiment(offline_directory="./logs", display_summary_level=0))
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 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