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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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63
tests/models/language/generation_ppl_test/ppl_utils.py
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@@ -8,8 +8,7 @@ import torch
from datasets import load_dataset
import tests.ci_envs as ci_envs
from tests.models.utils import (GenerateModelInfo,
TokensTextLogprobsPromptLogprobs)
from tests.models.utils import GenerateModelInfo, TokensTextLogprobsPromptLogprobs
from vllm.logprobs import Logprob
# See #24485
@@ -18,13 +17,14 @@ MAX_LENGTH = 1024
@torch.inference_mode
def wikitext_ppl_test(hf_runner,
vllm_runner,
model_info: GenerateModelInfo,
max_length=MAX_LENGTH,
vllm_extra_kwargs=None,
atol=PPL_TOL):
def wikitext_ppl_test(
hf_runner,
vllm_runner,
model_info: GenerateModelInfo,
max_length=MAX_LENGTH,
vllm_extra_kwargs=None,
atol=PPL_TOL,
):
# A model family has many models with the same architecture,
# and we don't need to test each one.
if not ci_envs.VLLM_CI_NO_SKIP and not model_info.enable_test:
@@ -44,15 +44,16 @@ def wikitext_ppl_test(hf_runner,
if ci_envs.VLLM_CI_HEAD_DTYPE is not None:
if "hf_overrides" not in vllm_extra_kwargs:
vllm_extra_kwargs["hf_overrides"] = {}
vllm_extra_kwargs["hf_overrides"][
"head_dtype"] = ci_envs.VLLM_CI_HEAD_DTYPE
vllm_extra_kwargs["hf_overrides"]["head_dtype"] = ci_envs.VLLM_CI_HEAD_DTYPE
with vllm_runner(model_info.name,
gpu_memory_utilization=0.7,
max_model_len=max_length,
max_num_seqs=1,
enforce_eager=True,
**vllm_extra_kwargs) as vllm_model:
with vllm_runner(
model_info.name,
gpu_memory_utilization=0.7,
max_model_len=max_length,
max_num_seqs=1,
enforce_eager=True,
**vllm_extra_kwargs,
) as vllm_model:
# Use max_num_seqs=1 to avoid OOM,
# and avoid batch different requests together.
@@ -60,7 +61,7 @@ def wikitext_ppl_test(hf_runner,
# Confirm whether vllm is using the correct architecture
if model_info.architecture:
assert (model_info.architecture in model_config.architectures)
assert model_info.architecture in model_config.architectures
max_length = min(model_config.max_model_len - 1, max_length)
stride = max_length
@@ -74,12 +75,14 @@ def wikitext_ppl_test(hf_runner,
end_loc = min(begin_loc + max_length, n_tokens)
chunks.append(tokens[begin_loc:end_loc])
outputs = vllm_model.generate_greedy_logprobs(prompts=chunks,
max_tokens=1,
num_logprobs=None,
num_prompt_logprobs=0,
use_tqdm=False)
nll_sum = torch.tensor(0., dtype=torch.float32, device="cpu")
outputs = vllm_model.generate_greedy_logprobs(
prompts=chunks,
max_tokens=1,
num_logprobs=None,
num_prompt_logprobs=0,
use_tqdm=False,
)
nll_sum = torch.tensor(0.0, dtype=torch.float32, device="cpu")
n_tokens = 0
for output in outputs:
output = cast(TokensTextLogprobsPromptLogprobs, output)
@@ -94,7 +97,8 @@ def wikitext_ppl_test(hf_runner,
token_log_probs.append(token_log_prob)
neg_log_likelihood = -torch.tensor(
token_log_probs, dtype=torch.float32, device="cpu").sum()
token_log_probs, dtype=torch.float32, device="cpu"
).sum()
nll_sum += neg_log_likelihood
n_tokens += len(token_log_probs)
vllm_ppl = float(torch.exp(nll_sum / n_tokens))
@@ -104,14 +108,13 @@ def wikitext_ppl_test(hf_runner,
# Accelerate ppl test by setting Transformers ppl score to a constant
if model_info.hf_ppl is None:
with hf_runner(
model_info.name,
dtype=ci_envs.VLLM_CI_HF_DTYPE or model_info.hf_dtype,
model_info.name,
dtype=ci_envs.VLLM_CI_HF_DTYPE or model_info.hf_dtype,
) as hf_model:
nll_sum = torch.tensor(0., dtype=torch.float32, device="cpu")
nll_sum = torch.tensor(0.0, dtype=torch.float32, device="cpu")
n_tokens = 0
for chunk in chunks:
inputs = hf_model.wrap_device(
{"input_ids": torch.tensor([chunk])})
inputs = hf_model.wrap_device({"input_ids": torch.tensor([chunk])})
input_ids = inputs["input_ids"]
outputs = hf_model.model(input_ids, labels=input_ids)
neg_log_likelihood = outputs.loss