Is your feature request related to a problem? Please describe.
This is a feature request for adding extra engine events within the click simulation loops during the deepgrow model training:
|
for j in range(self.max_interactions): |
|
inputs, _ = engine.prepare_batch(batchdata) |
|
inputs = inputs.to(engine.state.device) |
|
|
|
engine.network.eval() |
|
with torch.no_grad(): |
|
if engine.amp: |
|
with torch.cuda.amp.autocast(): |
|
predictions = engine.inferer(inputs, engine.network) |
|
else: |
|
predictions = engine.inferer(inputs, engine.network) |
|
|
|
batchdata.update({CommonKeys.PRED: predictions}) |
|
batchdata[self.key_probability] = torch.as_tensor( |
|
([1.0 - ((1.0 / self.max_interactions) * j)] if self.train else [1.0]) * len(inputs) |
|
) |
|
batchdata = self.transforms(batchdata) |
the main benefit is to have flexible simulation handlers attached to the inner loops
cc @danieltudosiu @diazandr3s @SachidanandAlle
