Are there any ways to filter out or ignore a batch in engine?

❓ Questions/Help/Support

I'm really new to the ML area and I'm trying to train a network with a dataset that when sampling batches, it can create batches with really large sizes (the sampling method is just torch's weightedSampling). Though the batch size is fixed the data size in the batch will be really large sometimes.
It seems pretty complicated to define a customized sampler, and the way I originally did was just ignore that batch when the data size in the batch is too large. Now, I'm trying to use ignite as the framework to train the network, I don't know how to do this.
I think it might relate to event_filter? But it seems to be triggered by event, so are there any ways to pass in a batch instead?

Thanks so much for your time!

The issue mentions Ignite's event_filter and the training engine's batch handling, but names no files or tests. Start by tracing how batches enter the engine and how event_filter is applied; determine whether skipping an oversized batch is supported without a custom sampler, and define the expected behavior.