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

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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
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76
tests/tpu/lora/test_lora.py
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@@ -29,17 +29,20 @@ def use_v1_only(monkeypatch: pytest.MonkeyPatch):
def setup_vllm(num_loras: int, tp: int) -> vllm.LLM:
return vllm.LLM(model="Qwen/Qwen2.5-3B-Instruct",
max_model_len=256,
max_num_seqs=8,
tensor_parallel_size=tp,
enable_lora=True,
max_loras=num_loras,
max_lora_rank=8)
return vllm.LLM(
model="Qwen/Qwen2.5-3B-Instruct",
max_model_len=256,
max_num_seqs=8,
tensor_parallel_size=tp,
enable_lora=True,
max_loras=num_loras,
max_lora_rank=8,
)
TPU_TENSOR_PARALLEL_SIZES = [1, tpu.num_available_chips()
] if tpu.num_available_chips() > 1 else [1]
TPU_TENSOR_PARALLEL_SIZES = (
[1, tpu.num_available_chips()] if tpu.num_available_chips() > 1 else [1]
)
@pytest.mark.parametrize("tp", TPU_TENSOR_PARALLEL_SIZES)
@@ -55,12 +58,19 @@ def test_single_lora(tp: int):
prompt = "What is 1+1? \n"
lora_request = LoRARequest(
"lora_adapter_1", 1,
"Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_1_adapter")
output = llm.generate(prompt,
sampling_params=vllm.SamplingParams(max_tokens=256,
temperature=0),
lora_request=lora_request)[0].outputs[0].text
"lora_adapter_1",
1,
"Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_1_adapter",
)
output = (
llm.generate(
prompt,
sampling_params=vllm.SamplingParams(max_tokens=256, temperature=0),
lora_request=lora_request,
)[0]
.outputs[0]
.text
)
answer = output.strip()[0]
@@ -73,13 +83,12 @@ def test_lora_hotswapping(tp: int):
"""
This test ensures we can run multiple LoRA adapters on the TPU backend, even
if we only have space to store 1.
We run "Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_x_adapter" which
will force Qwen2.5-3B-Instruct to claim 1+1=x, for a range of x.
"""
lora_name_template = \
"Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_{}_adapter"
lora_name_template = "Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_{}_adapter"
lora_requests = [
LoRARequest(f"lora_adapter_{i}", i, lora_name_template.format(i))
for i in range(1, 5)
@@ -90,10 +99,15 @@ def test_lora_hotswapping(tp: int):
prompt = "What is 1+1? \n"
for i, req in enumerate(lora_requests):
output = llm.generate(prompt,
sampling_params=vllm.SamplingParams(
max_tokens=256, temperature=0),
lora_request=req)[0].outputs[0].text
output = (
llm.generate(
prompt,
sampling_params=vllm.SamplingParams(max_tokens=256, temperature=0),
lora_request=req,
)[0]
.outputs[0]
.text
)
answer = output.strip()[0]
assert answer.isdigit()
@@ -105,12 +119,11 @@ def test_multi_lora(tp: int):
"""
This test ensures we can run multiple LoRA adapters on the TPU backend, when
we have enough space to store all of them.
We run "Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_x_adapter" which
will force Qwen2.5-3B-Instruct to claim 1+1=x, for a range of x.
"""
lora_name_template = \
"Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_{}_adapter"
lora_name_template = "Username6568/Qwen2.5-3B-Instruct-1_plus_1_equals_{}_adapter"
lora_requests = [
LoRARequest(f"lora_adapter_{i}", i, lora_name_template.format(i))
for i in range(1, 5)
@@ -121,10 +134,15 @@ def test_multi_lora(tp: int):
prompt = "What is 1+1? \n"
for i, req in enumerate(lora_requests):
output = llm.generate(prompt,
sampling_params=vllm.SamplingParams(
max_tokens=256, temperature=0),
lora_request=req)[0].outputs[0].text
output = (
llm.generate(
prompt,
sampling_params=vllm.SamplingParams(max_tokens=256, temperature=0),
lora_request=req,
)[0]
.outputs[0]
.text
)
answer = output.strip()[0]