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