refactor tests

deep_river/anomaly/rolling_ae.py

@@ -11,9 +11,8 @@
 
 
 class _TestLSTMAutoencoder(nn.Module):
-    def __init__(
-        self, n_features, hidden_size=10, n_layers=1, batch_first=False
-    ):
+    def __init__(self, n_features, hidden_size=30, n_layers=1,
+                 batch_first=False):
         super().__init__()
         self.n_features = n_features
         self.hidden_size = hidden_size
@@ -39,9 +38,7 @@ def forward(self, x):
         x_flipped = torch.flip(x[1:], dims=[self.time_axis])
         input = torch.cat((h, x_flipped), dim=self.time_axis)
         x_hat, _ = self.decoder(input)
-        x_hat = torch.flip(x_hat, dims=[self.time_axis])
-
-        return x_hat
+        return torch.flip(x_hat, dims=[self.time_axis])
 
 
 class RollingAutoencoder(RollingDeepEstimator, anomaly.base.AnomalyDetector):