Convert formatting to use ruff instead of yapf + isort (#26247)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
This commit is contained in:
Harry Mellor
2025-10-05 15:06:22 +01:00
committed by GitHub
parent 17edd8a807
commit d6953beb91
1508 changed files with 115244 additions and 94146 deletions

View File

@@ -24,13 +24,15 @@ sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
# set different `gpu_memory_utilization` and `swap_space` for different ranks,
# to test if all ranks agree on the same kv cache configuration.
llm = LLM(model="facebook/opt-125m",
tensor_parallel_size=2,
pipeline_parallel_size=int(os.getenv("PP_SIZE", 1)),
distributed_executor_backend="external_launcher",
gpu_memory_utilization=random.uniform(0.7, 0.9),
swap_space=random.randint(1, 4),
seed=0)
llm = LLM(
model="facebook/opt-125m",
tensor_parallel_size=2,
pipeline_parallel_size=int(os.getenv("PP_SIZE", 1)),
distributed_executor_backend="external_launcher",
gpu_memory_utilization=random.uniform(0.7, 0.9),
swap_space=random.randint(1, 4),
seed=0,
)
outputs = llm.generate(prompts, sampling_params)
@@ -48,15 +50,14 @@ def test_consistent_across_ranks(obj):
assert container[0] == obj
test_consistent_across_ranks(
llm.llm_engine.vllm_config.cache_config.num_cpu_blocks)
test_consistent_across_ranks(
llm.llm_engine.vllm_config.cache_config.num_gpu_blocks)
test_consistent_across_ranks(llm.llm_engine.vllm_config.cache_config.num_cpu_blocks)
test_consistent_across_ranks(llm.llm_engine.vllm_config.cache_config.num_gpu_blocks)
# make sure we can access the model parameters from the calling process
# of the `LLM` instance.
params = list(llm.llm_engine.model_executor.driver_worker.worker.model_runner.
model.parameters())
params = list(
llm.llm_engine.model_executor.driver_worker.worker.model_runner.model.parameters()
)
test_consistent_across_ranks(len(params))
# all ranks should have the same outputs
@@ -65,5 +66,4 @@ for output in outputs:
generated_text = output.outputs[0].text
test_consistent_across_ranks(prompt)
test_consistent_across_ranks(generated_text)
print(f"Rank {torch_rank}, Prompt: {prompt!r}, "
f"Generated text: {generated_text!r}")
print(f"Rank {torch_rank}, Prompt: {prompt!r}, Generated text: {generated_text!r}")