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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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78
tests/models/language/generation/test_phimoe.py
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@@ -15,62 +15,56 @@ MODELS = [
def test_phimoe_routing_function():
from vllm.model_executor.models.phimoe import phimoe_routing_function
test_case = {
0: {
"hidden_states":
torch.tensor([1, 2, 3, 4, 5, 6, 7, 8],
dtype=torch.float32,
requires_grad=False).view(4, 2),
"gating_output":
torch.tensor([0.1, 0.2, 0.3, 0.4],
dtype=torch.float32,
requires_grad=False),
"topk":
2,
"renormalize":
False,
"hidden_states": torch.tensor(
[1, 2, 3, 4, 5, 6, 7, 8], dtype=torch.float32, requires_grad=False
).view(4, 2),
"gating_output": torch.tensor(
[0.1, 0.2, 0.3, 0.4], dtype=torch.float32, requires_grad=False
),
"topk": 2,
"renormalize": False,
},
1: {
"hidden_states":
torch.tensor([1, 2, 3, 4, 5, 6, 7, 8],
dtype=torch.float32,
requires_grad=False).view(4, 2),
"gating_output":
torch.tensor([0.4, 0.2, 0.3, 0.4],
dtype=torch.float32,
requires_grad=False),
"topk":
2,
"renormalize":
False,
}
"hidden_states": torch.tensor(
[1, 2, 3, 4, 5, 6, 7, 8], dtype=torch.float32, requires_grad=False
).view(4, 2),
"gating_output": torch.tensor(
[0.4, 0.2, 0.3, 0.4], dtype=torch.float32, requires_grad=False
),
"topk": 2,
"renormalize": False,
},
}
ground_truth = {
0: {
"topk_weights":
torch.tensor([1., 1.], dtype=torch.float32, requires_grad=False),
"topk_ids":
torch.tensor([3, 2], dtype=torch.long, requires_grad=False),
"topk_weights": torch.tensor(
[1.0, 1.0], dtype=torch.float32, requires_grad=False
),
"topk_ids": torch.tensor([3, 2], dtype=torch.long, requires_grad=False),
},
1: {
"topk_weights":
torch.tensor([0.5, 1.], dtype=torch.float32, requires_grad=False),
"topk_ids":
torch.tensor([0, 3], dtype=torch.long, requires_grad=False),
}
"topk_weights": torch.tensor(
[0.5, 1.0], dtype=torch.float32, requires_grad=False
),
"topk_ids": torch.tensor([0, 3], dtype=torch.long, requires_grad=False),
},
}
for test_id in test_case:
topk_weights, topk_ids = phimoe_routing_function(**test_case[test_id])
assert torch.allclose(topk_weights,
ground_truth[test_id]["topk_weights"])
assert torch.allclose(topk_weights, ground_truth[test_id]["topk_weights"])
assert torch.equal(topk_ids, ground_truth[test_id]["topk_ids"])
@pytest.mark.skipif(condition=current_platform.is_cpu(),
reason="This test takes a lot time to run on CPU, "
"and vllm CI's disk space is not enough for this model.")
@pytest.mark.skipif(
condition=current_platform.is_cpu(),
reason="This test takes a lot time to run on CPU, "
"and vllm CI's disk space is not enough for this model.",
)
@large_gpu_test(min_gb=80)
@pytest.mark.parametrize("model", MODELS)
@pytest.mark.parametrize("dtype", ["bfloat16"])
@@ -87,11 +81,13 @@ def test_models(
) -> None:
with hf_runner(model, dtype=dtype) as hf_model:
hf_outputs = hf_model.generate_greedy_logprobs_limit(
example_prompts, max_tokens, num_logprobs)
example_prompts, max_tokens, num_logprobs
)
with vllm_runner(model, dtype=dtype) as vllm_model:
vllm_outputs = vllm_model.generate_greedy_logprobs(
example_prompts, max_tokens, num_logprobs)
example_prompts, max_tokens, num_logprobs
)
check_logprobs_close(
outputs_0_lst=hf_outputs,
outputs_1_lst=vllm_outputs,