fix minor import errors and missing package imports
@@ -92,10 +92,8 @@ Each of these `streams` are _iterable_, _indexable_ and _sliceable_ objects that
_Avalanche_ maintains a set of commonly used benchmarks built on top of one or multiple datasets.
```python
-from avalanche.benchmarks.classic import CORe50, SplitTinyImageNet,
-
-SplitCIFAR10, SplitCIFAR100, SplitCIFAR110, SplitMNIST, RotatedMNIST, PermutedMNIST,
-SplitCUB200
+from avalanche.benchmarks.classic import CORe50, SplitTinyImageNet, SplitCIFAR10,\
+ SplitCIFAR100, SplitCIFAR110, SplitMNIST, RotatedMNIST, PermutedMNIST, SplitCUB200
# creating the benchmark (scenario object)
perm_mnist = PermutedMNIST(
@@ -344,14 +342,17 @@ Here we show how you can use all these modules together to **design your experim
```python
from avalanche.benchmarks.classic import SplitMNIST
-from avalanche.evaluation.metrics import ExperienceForgetting, accuracy_metrics,
-loss_metrics, timing_metrics, cpu_usage_metrics, StreamConfusionMatrix,
+from avalanche.evaluation.metrics import ExperienceForgetting, accuracy_metrics,\
+ loss_metrics, timing_metrics, cpu_usage_metrics, StreamConfusionMatrix,\
disk_usage_metrics, gpu_usage_metrics
from avalanche.models import SimpleMLP
from avalanche.logging import InteractiveLogger, TextLogger, TensorboardLogger
from avalanche.training.plugins import EvaluationPlugin
from avalanche.training.strategies import Naive
+from torch.optim import SGD
+from torch.nn import CrossEntropyLoss
+
scenario = SplitMNIST(n_experiences=5)
# MODEL CREATION
