log warning for batch_size 1

[horheynm]

Show warning when overriding batch_size 0 to 1

https://app.asana.com/0/1201735099598270/1206262288703592

[dbarbuzzi]

Could this be made to be more in-line with the already existing validation check, or perhaps, just use that check instead? See https://github.com/neuralmagic/deepsparse/blob/main/src/deepsparse/engine.py#L108

Separately, while not a huge deal, I would be curious to know why the existing check catches, e.g. -3, but not 0, within the same sample code otherwise. The test that catches the missing warning when batch_size is 0 is simply:

Pipeline.create(task="text_classification", batch_size=batch_size)

In that test, the existing warning is thrown if batch_size is -3, but not if it’s 0, which seems odd, almost like 0 is being handled separately somewhere else before the check (perhaps due to a truthiness/falsiness check of batch_size since 0 would be falsey but -3 would be truthy).

[derekk-nm]

@dbarbuzzi , good catch. @horheynm, it may be good to understand why pipeline.py overrides batch_size when engine.py is already doing it differently? and if the statement on the old lines 195 and 209 is going to stay around, they should probably be refactored to be a single line in whatever is the appropriate place in the init function.

[horheynm]

Could this be made to be more in-line with the already existing validation check, or perhaps, just use that check instead? See https://github.com/neuralmagic/deepsparse/blob/main/src/deepsparse/engine.py#L108

Separately, while not a huge deal, I would be curious to know why the existing check catches, e.g. -3, but not 0, within the same sample code otherwise. The test that catches the missing warning when batch_size is 0 is simply:

Pipeline.create(task="text_classification", batch_size=batch_size)

In that test, the existing warning is thrown if batch_size is -3, but not if it’s 0, which seems odd, almost like 0 is being handled separately somewhere else before the check (perhaps due to a truthiness/falsiness check of batch_size since 0 would be falsey but -3 would be truthy).

Yeah I actually wanted the change there for overriding the values, but then i dont understand

1. why the current override happens in the location near where I change currently
2. because it is a common highway in the code base, changing it would cause issues in other pipelines.

I do prefer changing the values in the locs you sent bc I also do have to initialize a new logger.

If there are no conflicts changing the code snippet you mentioned, then ofc its better to make edits to that line.

@bfineran Any issues changing the snippet of code in engine.py? https://github.com/neuralmagic/deepsparse/blob/main/src/deepsparse/engine.py#L108

[mgoin]

@horheynm @dbarbuzzi @derekk-nm batch_size=0 was added as a special case to disable the engine from setting the batch size of the model. This is important because some models do not have a batch size at all! So we do need a way to express that case with the engine. Please see this PR for the original creation https://github.com/neuralmagic/deepsparse/pull/1169

[dbarbuzzi]

Thanks for that info @mgoin ! So it sounds like the changes we need are not to "fix" any logic, but just to ensure that this special case is properly displayed in a log message?

[dbogunowicz]

@dbarbuzzi @mgoin but it is, isn't it: https://github.com/neuralmagic/deepsparse/blob/main/src/deepsparse/engine.py#L110

[dbarbuzzi]

but it is, isn't it: https://github.com/neuralmagic/deepsparse/blob/main/src/deepsparse/engine.py#L110

Yes, I misunderstood that it is not exactly 0 that is a special case but anything under 1.

That brings us back to the original problem: when using 0 specifically, that log message is not being triggered/displayed like it is if you use -3. That inconsistency is what this PR is supposed to address.