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[Hardware][Neuron] Refactor neuron support #3471
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@WoosukKwon This PR is ready for review! cc @liangfu please take a look as well! |
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Thanks @zhuohan123 for the proposed change. I like the idea of
- abstracting execution with
executor_class
- deduplicating llama and mixtral model support
My concern comes from missing input_metadata in the forward function call, where we might need an extra refactoring to support paged attention on neuron backend.
if parallel_config.worker_use_ray or engine_args.engine_use_ray: | ||
device_config = engine_configs[4] | ||
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if device_config.device_type == "neuron": |
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Instead of string comparison, set a property
in device_config?
FYI, we might consider some device-specific config with device="neuron config=(a=1, b=2, c=3)"
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device_type
is different from device
. I think we can safely assume device_type
can only be cuda
and neuron
for now? We can put the config string in other fields of device_config
.
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Sure, i think we are fine to move on with this.
Tested with tensor_parallel_size=2 for the branch:
|
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LGTM
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LGTM! Thanks for the great work! This is great refactoring. The code looks much cleaner now.
@@ -1,6 +1,6 @@ | |||
from vllm.model_executor.input_metadata import InputMetadata | |||
from vllm.model_executor.sampling_metadata import SamplingMetadata | |||
from vllm.model_executor.utils import set_random_seed, get_model |
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why remove this?
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there are two get_model
s, one for neuron and one for GPUs. Having get_model
here will be confusing.
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Also we removed the get_model
function from the utils. Previously this get_model
is a dispatcher for different devices. Now we no longer need the dispatcher.
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Then should we remove it from all as well?
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yeah it's already removed. See the latest commit
logger.warning(msg) | ||
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def is_pin_memory_available() -> bool: |
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QQ: Does it make sense to use cache for this function? Wondering if it helps performance.
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yes let me add that
Refactor the neuron support. After this refactoring, the neuron support is completely isolated from the GPU support. The development on the GPU side no longer needs to consider its effect on the neuron pass. Also, all the
is_neuron
flags in the code have been removed, except the one that tells us that we are usingneuron
device.Highlights of this change:
NeuronExecutor
,NeuronWorker
,NeuronModelRunner
, andget_neuron_model
function.Remaining issues for future PRs:
NeuronModelRunner
still has a complicatedprepare_inputs
function. This should be refactored together with the refactor ofprepare_inputs
in the future.PR Checklist (Click to expand. Please read before submitting.)
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