TGISStatLogger: fix stats usage #25
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cherry-pick from opendatahub-io/vllm@6100f4b
Signed-off-by: Travis Johnson <[email protected]>
njhill
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Thanks @dtrifiro @tjohnson31415!
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Jan 20, 2025
This PR implements support for `batch size > 1 `and tracks the progress of the warmup of multiple different `prompt-length/max-decode/batch-size` shapes. ### Contributions: - Introduce env var and interpret `BATCH_SIZE` as list of values (similar to `MIN_PAD_LENGTH` and `MAX_NEW_TOKENS`) - Adapt warmup loop over the zipped list containing **pad length**, **max new tokens** and **batch size** - Support batch dimension for input arguments (tokens, positions, masks) in warmup algorithm - Add batch dimension support in update function for the attention mask (`update_mask()` in sendnn.py) - Alter test scripts to work with `batch size > 1 ` #### The code has been tested in the following settings: - On **CPU**: `batch size = 4` and `batch size = 8` with `torch.compile(backend=inductor)` - On **AIU**: `batch size = 1` in both **offline** and **online** mode. ### Open questions (including unaddressed questions from [PR23](https://github.ibm.com/ai-foundation/vllm/pull/23)): - [x] verify code functionality for `batch size = 4` and `batch size = 8` on **AIU** - [ ] ideally, the `SENDNNWorker` checks how many compiled shapes fit in AIU memory before starting to warmup all of them. Unclear how to decide, implementation missing. - [ ] How to handle requests that are too long? Right now there are just cut to maximum padding length (we should probably fail the request and inform the client) - [ ] verify output of example prompts
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Cherry-pick of fix commit 6100f4b from ODH:
opendatahub-io/vllm#17