e489ad7a21
- **Add SPDX license headers to python source files**
- **Check for SPDX headers using pre-commit**
commit 9d7ef44c3cfb72ca4c32e1c677d99259d10d4745
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:18:24 2025 -0500
Add SPDX license headers to python source files
This commit adds SPDX license headers to python source files as
recommended to
the project by the Linux Foundation. These headers provide a concise way
that is
both human and machine readable for communicating license information
for each
source file. It helps avoid any ambiguity about the license of the code
and can
also be easily used by tools to help manage license compliance.
The Linux Foundation runs license scans against the codebase to help
ensure
we are in compliance with the licenses of the code we use, including
dependencies. Having these headers in place helps that tool do its job.
More information can be found on the SPDX site:
- https://spdx.dev/learn/handling-license-info/
Signed-off-by: Russell Bryant <rbryant@redhat.com>
commit 5a1cf1cb3b80759131c73f6a9dddebccac039dea
Author: Russell Bryant <rbryant@redhat.com>
Date: Fri Jan 31 14:36:32 2025 -0500
Check for SPDX headers using pre-commit
Signed-off-by: Russell Bryant <rbryant@redhat.com>
---------
Signed-off-by: Russell Bryant <rbryant@redhat.com>
87 lines
2.9 KiB
Python
87 lines
2.9 KiB
Python
# SPDX-License-Identifier: Apache-2.0
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import torch
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from vllm.engine.arg_utils import EngineArgs
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from vllm.sequence import ExecuteModelRequest
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from vllm.utils import get_distributed_init_method, get_ip, get_open_port
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from vllm.worker.worker import Worker
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def test_swap() -> None:
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# Configure the engine.
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engine_args = EngineArgs(model="facebook/opt-125m",
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dtype="half",
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load_format="dummy")
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engine_config = engine_args.create_engine_config()
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engine_config.cache_config.num_gpu_blocks = 1000
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engine_config.cache_config.num_cpu_blocks = 1000
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# Create the worker.
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distributed_init_method = get_distributed_init_method(
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get_ip(), get_open_port())
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worker = Worker(
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vllm_config=engine_config,
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local_rank=0,
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rank=0,
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distributed_init_method=distributed_init_method,
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is_driver_worker=True,
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)
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# Initialize the worker.
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worker.init_device()
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worker.load_model()
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worker.initialize_cache(
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num_gpu_blocks=engine_config.cache_config.num_gpu_blocks,
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num_cpu_blocks=engine_config.cache_config.num_cpu_blocks)
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# Randomly initialize the cache.
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gpu_cache = worker.cache_engine[0].gpu_cache
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cpu_cache = worker.cache_engine[0].cpu_cache
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num_layers = len(gpu_cache)
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for i in range(num_layers):
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gpu_key_cache, gpu_value_cache = gpu_cache[i]
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gpu_key_cache.random_()
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gpu_value_cache.random_()
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cpu_key_cache, cpu_value_cache = cpu_cache[i]
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cpu_key_cache.random_()
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cpu_value_cache.random_()
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allclose = lambda a, b: torch.allclose(
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a.cuda(), b.cuda(), rtol=0.0, atol=0.0)
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# Test swap out.
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blocks_to_swap_out = [(3, 72), (56, 35), (84, 34)]
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execute_model_req = ExecuteModelRequest(
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seq_group_metadata_list=[],
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blocks_to_swap_in=[],
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blocks_to_swap_out=blocks_to_swap_out,
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blocks_to_copy=[],
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)
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worker.execute_model(execute_model_req=execute_model_req)
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for i in range(num_layers):
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gpu_key_cache, gpu_value_cache = gpu_cache[i]
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cpu_key_cache, cpu_value_cache = cpu_cache[i]
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for src, dst in blocks_to_swap_out:
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assert allclose(gpu_key_cache[src], cpu_key_cache[dst])
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assert allclose(gpu_value_cache[src], cpu_value_cache[dst])
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# Test swap in.
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execute_model_req.blocks_to_swap_out = []
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execute_model_req.blocks_to_swap_in = [
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(19, 45),
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(67, 23),
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(12, 78),
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(40, 99),
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(1, 71),
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]
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worker.execute_model(execute_model_req=execute_model_req)
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for i in range(num_layers):
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gpu_key_cache, gpu_value_cache = gpu_cache[i]
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cpu_key_cache, cpu_value_cache = cpu_cache[i]
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for src, dst in execute_model_req.blocks_to_swap_in:
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assert allclose(gpu_key_cache[dst], cpu_key_cache[src])
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assert allclose(gpu_value_cache[dst], cpu_value_cache[src])
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