benchmark_with_validation stream removes attribute 'benchmark'

[ordass00]

🐛 Describe the bug
I am using benchmark_with_validation_stream to split my benchmark into a version where the train_stream is divided into train_stream and valid_stream. However, training fails as soon as I set eval_streams=[cl_val_stream] in my strategy.

Error: AttributeError: 'DatasetExperience' object has no attribute 'benchmark'

When inspecting the streams it seems like the train_steam, as well as the valid_stream, no longer have the benchmark attribute, whereas test_stream still has it.

I think the issue here is that the generated streams from benchmark_with_validation_stream, so the train_stream and valid_stream, belong to EagerCLStream while the test_stream still belongs to NCStream.
Also the train_stream and valid_stream lose the benchmark attribute after calling benchmark_with_validation_stream, while test_stream retains it.

🐜 To Reproduce

cl_mnist = SplitMNIST(
    n_experiences=5,
    return_task_id=False,
    seed=42,
    fixed_class_order=[0, 1, 2, 3, 4, 5, 6, 7, 8, 9]
)

cl_mnist_with_val = benchmark_with_validation_stream(
    cl_mnist,
    validation_size=0.1,
    shuffle=True,
    seed=42
)

cl_train_stream = cl_mnist_with_val.train_stream
cl_test_stream = cl_mnist_with_val.test_stream
cl_val_stream = cl_mnist_with_val.valid_stream

baseline_model = SimpleMLP(num_classes=10)

baseline_optimizer = SGD(baseline_model.parameters(), lr=0.001, momentum=0.9)
baseline_criterion = CrossEntropyLoss()

baseline_naive_strategy = Naive(
    model=baseline_model,
    optimizer=baseline_optimizer,
    criterion=baseline_criterion,
    train_mb_size=64,
    train_epochs=5,
    eval_mb_size=64,
    eval_every=0, 
    evaluator=baseline_eval_plugin
)

baseline_results = []
for exp in cl_train_stream:
    res = baseline_naive_strategy.train(exp, eval_streams=[cl_val_stream])           # <- Error is happening here
    baseline_results.append(res)

🐝 Expected behavior
I should be able to train the model on the train set, validate it during training on the validation set and do inference on the test set afterwards. However, since cl_val_stream laks the benchmark attribute, training fails when eval_streams=[cl_val_stream] is used.