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[CI/Build] Update Ruff version (vllm-project#8469)
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Signed-off-by: Aaron Pham <contact@aarnphm.xyz>
Co-authored-by: Cyrus Leung <cyrus.tl.leung@gmail.com>
Signed-off-by: Sumit Dubey <sumit.dubey2@ibm.com>
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2 people authored and sumitd2 committed Nov 14, 2024
1 parent 6dbabf3 commit ada24a9
Showing 27 changed files with 50 additions and 77 deletions.
4 changes: 2 additions & 2 deletions .github/workflows/ruff.yml
Original file line number Diff line number Diff line change
@@ -25,10 +25,10 @@ jobs:
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install ruff==0.1.5 codespell==2.3.0 tomli==2.0.1 isort==5.13.2
pip install -r requirements-lint.txt
- name: Analysing the code with ruff
run: |
ruff .
ruff check .
- name: Spelling check with codespell
run: |
codespell --toml pyproject.toml
4 changes: 1 addition & 3 deletions benchmarks/kernels/graph_machete_bench.py
Original file line number Diff line number Diff line change
@@ -45,8 +45,7 @@
rows = int(math.ceil(len(results) / 2))
fig, axs = plt.subplots(rows, 2, figsize=(12, 5 * rows))
axs = axs.flatten()
axs_idx = 0
for shape, data in results.items():
for axs_idx, (shape, data) in enumerate(results.items()):
plt.sca(axs[axs_idx])
df = pd.DataFrame(data)
sns.lineplot(data=df,
@@ -59,6 +58,5 @@
palette="Dark2")
plt.title(f"Shape: {shape}")
plt.ylabel("time (median, s)")
axs_idx += 1
plt.tight_layout()
plt.savefig("graph_machete_bench.pdf")
4 changes: 2 additions & 2 deletions format.sh
Original file line number Diff line number Diff line change
@@ -159,7 +159,7 @@ echo 'vLLM codespell: Done'

# Lint specified files
lint() {
ruff "$@"
ruff check "$@"
}

# Lint files that differ from main branch. Ignores dirs that are not slated
@@ -175,7 +175,7 @@ lint_changed() {

if ! git diff --diff-filter=ACM --quiet --exit-code "$MERGEBASE" -- '*.py' '*.pyi' &>/dev/null; then
git diff --name-only --diff-filter=ACM "$MERGEBASE" -- '*.py' '*.pyi' | xargs \
ruff
ruff check
fi

}
2 changes: 2 additions & 0 deletions pyproject.toml
Original file line number Diff line number Diff line change
@@ -42,6 +42,8 @@ ignore = [
"E731",
# Loop control variable not used within loop body
"B007",
# f-string format
"UP032",
]

[tool.mypy]
2 changes: 1 addition & 1 deletion requirements-lint.txt
Original file line number Diff line number Diff line change
@@ -2,7 +2,7 @@
yapf==0.32.0
toml==0.10.2
tomli==2.0.1
ruff==0.1.5
ruff==0.6.5
codespell==2.3.0
isort==5.13.2
clang-format==18.1.5
5 changes: 1 addition & 4 deletions tests/conftest.py
Original file line number Diff line number Diff line change
@@ -158,10 +158,7 @@ def should_do_global_cleanup_after_test(request) -> bool:
to initialize torch.
"""

if request.node.get_closest_marker("skip_global_cleanup"):
return False

return True
return not request.node.get_closest_marker("skip_global_cleanup")


@pytest.fixture(autouse=True)
5 changes: 1 addition & 4 deletions tests/lora/conftest.py
Original file line number Diff line number Diff line change
@@ -65,10 +65,7 @@ def should_do_global_cleanup_after_test(request) -> bool:
to initialize torch.
"""

if request.node.get_closest_marker("skip_global_cleanup"):
return False

return True
return not request.node.get_closest_marker("skip_global_cleanup")


@pytest.fixture(autouse=True)
2 changes: 1 addition & 1 deletion tests/multimodal/test_base.py
Original file line number Diff line number Diff line change
@@ -5,7 +5,7 @@

def assert_nested_tensors_equal(expected: NestedTensors,
actual: NestedTensors):
assert type(expected) == type(actual)
assert type(expected) == type(actual) # noqa: E721
if isinstance(expected, torch.Tensor):
assert torch.equal(expected, actual)
else:
5 changes: 1 addition & 4 deletions tests/test_cache_block_hashing.py
Original file line number Diff line number Diff line change
@@ -66,8 +66,7 @@ def test_auto_prefix_caching(model: str, block_size: int, max_num_seqs: int,

hashes.append([])
prompts = [prefix + prompt for prompt in sample_prompts]
seq_id = 0
for prompt in prompts:
for seq_id, prompt in enumerate(prompts):
hashes[-1].append([])
prompt_token_ids = tokenizer.encode(prompt)
seq = Sequence(seq_id,
@@ -83,8 +82,6 @@ def test_auto_prefix_caching(model: str, block_size: int, max_num_seqs: int,
for idx in range(num_blocks):
hashes[-1][-1].append(seq.hash_of_block(idx))

seq_id += 1

# Check that hashes made with two prefixes with different first blocks are
# different everywhere.
for hash0, hash1 in zip(flatten_2d(hashes[0]), flatten_2d(hashes[1])):
4 changes: 2 additions & 2 deletions tests/test_logger.py
Original file line number Diff line number Diff line change
@@ -111,7 +111,7 @@ def test_an_error_is_raised_when_custom_logging_config_file_does_not_exist():
configuration occurs."""
with pytest.raises(RuntimeError) as ex_info:
_configure_vllm_root_logger()
assert ex_info.type == RuntimeError
assert ex_info.type == RuntimeError # noqa: E721
assert "File does not exist" in str(ex_info)


@@ -152,7 +152,7 @@ def test_an_error_is_raised_when_custom_logging_config_is_unexpected_json(
logging_config_file.name):
with pytest.raises(ValueError) as ex_info:
_configure_vllm_root_logger()
assert ex_info.type == ValueError
assert ex_info.type == ValueError # noqa: E721
assert "Invalid logging config. Expected Dict, got" in str(ex_info)


4 changes: 1 addition & 3 deletions tests/worker/test_encoder_decoder_model_runner.py
Original file line number Diff line number Diff line change
@@ -453,8 +453,7 @@ def test_prepare_decode(batch_size):
# each sequence) in the decode phase

expected_selected_token_indices = []
selected_token_start_idx = 0
for seq_len in seq_lens:
for selected_token_start_idx, seq_len in enumerate(seq_lens):
# Compute the index offset of the final token in each
# sequence's decoded outputs; since a single token is
# decoded per iteration per sequence, then the length
@@ -463,7 +462,6 @@ def test_prepare_decode(batch_size):
# generated tokens is 0 (i.e. the expected sampling index
# for a given sequence is just `selected_token_start_idx`)
expected_selected_token_indices.append(selected_token_start_idx)
selected_token_start_idx += 1

sampling_metadata = model_input.sampling_metadata
actual = sampling_metadata.selected_token_indices
4 changes: 1 addition & 3 deletions tests/worker/test_model_runner.py
Original file line number Diff line number Diff line change
@@ -241,10 +241,8 @@ def test_prepare_decode_cuda_graph(batch_size):

# Verify Sampling
expected_selected_token_indices = []
selected_token_start_idx = 0
for _ in context_lens:
for selected_token_start_idx, _ in enumerate(context_lens):
expected_selected_token_indices.append(selected_token_start_idx)
selected_token_start_idx += 1
sampling_metadata = SamplingMetadata.prepare(
seq_group_metadata_list,
seq_lens,
2 changes: 1 addition & 1 deletion vllm/adapter_commons/utils.py
Original file line number Diff line number Diff line change
@@ -42,7 +42,7 @@ def list_adapters(registered_adapters: Dict[int, Any]) -> Dict[int, Any]:

def get_adapter(adapter_id: int,
registered_adapters: Dict[int, Any]) -> Optional[Any]:
return registered_adapters.get(adapter_id, None)
return registered_adapters.get(adapter_id)


## worker functions
6 changes: 2 additions & 4 deletions vllm/attention/backends/utils.py
Original file line number Diff line number Diff line change
@@ -33,10 +33,8 @@ def is_block_tables_empty(block_tables: Union[None, Dict]):
"""
if block_tables is None:
return True
if isinstance(block_tables, dict) and all(
value is None for value in block_tables.values()):
return True
return False
return (isinstance(block_tables, dict)
and all(value is None for value in block_tables.values()))


def compute_slot_mapping_start_idx(is_prompt: bool, query_len: int,
4 changes: 1 addition & 3 deletions vllm/core/block/prefix_caching_block.py
Original file line number Diff line number Diff line change
@@ -417,9 +417,7 @@ def get_prefix_cache_hit_rate(self) -> float:

def is_block_cached(self, block: Block) -> bool:
assert block.content_hash is not None
if block.content_hash in self._cached_blocks:
return True
return False
return block.content_hash in self._cached_blocks

def promote_to_immutable_block(self, block: Block) -> BlockId:
"""Once a mutable block is full, it can be promoted to an immutable
4 changes: 1 addition & 3 deletions vllm/core/block_manager_v2.py
Original file line number Diff line number Diff line change
@@ -399,9 +399,7 @@ def can_swap_out(self, seq_group: SequenceGroup) -> bool:
"""
alloc_status = self._can_swap(seq_group, Device.CPU,
SequenceStatus.RUNNING)
if alloc_status == AllocStatus.OK:
return True
return False
return alloc_status == AllocStatus.OK

def swap_out(self, seq_group: SequenceGroup) -> List[Tuple[int, int]]:
"""Returns the block id mapping (from GPU to CPU) generated by
6 changes: 3 additions & 3 deletions vllm/engine/async_llm_engine.py
Original file line number Diff line number Diff line change
@@ -826,7 +826,7 @@ async def generate(
request_id: The unique id of the request.
lora_request: LoRA request to use for generation, if any.
trace_headers: OpenTelemetry trace headers.
prompt_adapter_request: Prompt Adapter request to use
prompt_adapter_request: Prompt Adapter request to use
for generation, if any.
Yields:
@@ -1042,15 +1042,15 @@ def remove_logger(self, logger_name: str) -> None:
async def start_profile(self) -> None:
# using type instead of isinstance to check to avoid capturing
# inherited classes
if type(self.engine.model_executor) == GPUExecutorAsync:
if type(self.engine.model_executor) == GPUExecutorAsync: # noqa: E721
self.engine.model_executor.start_profile()
else:
self.engine.model_executor._run_workers("start_profile")

async def stop_profile(self) -> None:
# using type instead of isinstance to check to avoid capturing
# inherited classes
if type(self.engine.model_executor) == GPUExecutorAsync:
if type(self.engine.model_executor) == GPUExecutorAsync: # noqa: E721
self.engine.model_executor.stop_profile()
else:
self.engine.model_executor._run_workers("stop_profile")
6 changes: 3 additions & 3 deletions vllm/engine/llm_engine.py
Original file line number Diff line number Diff line change
@@ -144,7 +144,7 @@ class LLMEngine:
decoding.
executor_class: The model executor class for managing distributed
execution.
prompt_adapter_config (Optional): The configuration related to serving
prompt_adapter_config (Optional): The configuration related to serving
prompt adapters.
log_stats: Whether to log statistics.
usage_context: Specified entry point, used for usage info collection.
@@ -1605,15 +1605,15 @@ def check_health(self) -> None:
def start_profile(self) -> None:
# using type instead of isinstance to check to avoid capturing
# inherited classes (MultiprocessingGPUExecutor)
if type(self.model_executor) == GPUExecutor:
if type(self.model_executor) == GPUExecutor: # noqa: E721
self.model_executor.start_profile()
else:
self.model_executor._run_workers("start_profile")

def stop_profile(self) -> None:
# using type instead of isinstance to check to avoid capturing
# inherited classes (MultiprocessingGPUExecutor)
if type(self.model_executor) == GPUExecutor:
if type(self.model_executor) == GPUExecutor: # noqa: E721
self.model_executor.stop_profile()
else:
self.model_executor._run_workers("stop_profile")
Original file line number Diff line number Diff line change
@@ -67,9 +67,9 @@ def __call__(self, input_ids: List[int],
instruction = self._guide.get_next_instruction(
state=self._fsm_state[seq_id])

if type(instruction) == Generate:
if type(instruction) == Generate: # noqa: E721
allowed_tokens = instruction.tokens
elif type(instruction) == Write:
elif type(instruction) == Write: # noqa: E721
# TODO: support fast forward tokens
allowed_tokens = [instruction.tokens[0]]
else:
6 changes: 3 additions & 3 deletions vllm/model_executor/layers/quantization/awq_marlin.py
Original file line number Diff line number Diff line change
@@ -110,9 +110,9 @@ def get_scaled_act_names(self) -> List[str]:
def is_awq_marlin_compatible(cls, quant_config: Dict[str, Any]):
# Extract data from quant config.
quant_method = quant_config.get("quant_method", "").lower()
num_bits = quant_config.get("bits", None)
group_size = quant_config.get("group_size", None)
has_zp = quant_config.get("zero_point", None)
num_bits = quant_config.get("bits")
group_size = quant_config.get("group_size")
has_zp = quant_config.get("zero_point")

if quant_method != "awq":
return False
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
from typing import Any, Dict, List, Optional
from typing import Any, Dict, List, Optional, cast

import torch
from pydantic import BaseModel
@@ -79,8 +79,8 @@ def get_quant_method(
@classmethod
def from_config(cls, config: Dict[str, Any]) -> "CompressedTensorsConfig":
target_scheme_map: Dict[str, Any] = dict()
ignore: List[str] = config.get("ignore", None)
quant_format: str = config.get("format", None)
ignore = cast(List[str], config.get("ignore"))
quant_format = cast(str, config.get("format"))

# The quant_config has multiple config_groups, each containing
# an input_activations key with details about how the activations are
@@ -200,7 +200,7 @@ def _is_fp8_w8a16(self, weight_quant: BaseModel,
is_per_tensor_or_channel_weight = (weight_quant.strategy in [
QuantizationStrategy.TENSOR, QuantizationStrategy.CHANNEL
])
if not (is_symmetric_weight and is_static_weight
if not (is_symmetric_weight and is_static_weight # noqa: SIM103
and is_per_tensor_or_channel_weight):
return False

@@ -333,7 +333,7 @@ def create_weights(self, layer: torch.nn.Module,
output_size: int, params_dtype: torch.dtype,
**extra_weight_attrs):
"""
Use the CompressedTensorsScheme associated with each layer to create
Use the CompressedTensorsScheme associated with each layer to create
the necessary parameters for the layer. See LinearMethodBase for param
details
"""
@@ -352,8 +352,8 @@ def apply(self,
x: torch.Tensor,
bias: Optional[torch.Tensor] = None):
"""
Use the output of create_weights and the CompressedTensorsScheme
associated with the layer to apply the forward pass with the
Use the output of create_weights and the CompressedTensorsScheme
associated with the layer to apply the forward pass with the
layer input. See LinearMethodBase for param details
"""
8 changes: 4 additions & 4 deletions vllm/model_executor/layers/quantization/gptq_marlin.py
Original file line number Diff line number Diff line change
@@ -132,10 +132,10 @@ def get_scaled_act_names(self) -> List[str]:
def is_gptq_marlin_compatible(cls, quant_config: Dict[str, Any]):
# Extract data from quant config.
quant_method = quant_config.get("quant_method", "").lower()
num_bits = quant_config.get("bits", None)
group_size = quant_config.get("group_size", None)
sym = quant_config.get("sym", None)
desc_act = quant_config.get("desc_act", None)
num_bits = quant_config.get("bits")
group_size = quant_config.get("group_size")
sym = quant_config.get("sym")
desc_act = quant_config.get("desc_act")

if quant_method != "gptq":
return False
4 changes: 1 addition & 3 deletions vllm/model_executor/model_loader/tensorizer.py
Original file line number Diff line number Diff line change
@@ -408,9 +408,7 @@ def is_vllm_tensorized(tensorizer_config: "TensorizerConfig") -> bool:
"inferred as vLLM models, so setting vllm_tensorized=True is "
"only necessary for models serialized prior to this change.")
return True
if (".vllm_tensorized_marker" in deserializer):
return True
return False
return ".vllm_tensorized_marker" in deserializer


def serialize_vllm_model(
2 changes: 1 addition & 1 deletion vllm/model_executor/models/minicpmv.py
Original file line number Diff line number Diff line change
@@ -884,7 +884,7 @@ def __new__(
version = str(config.version).split(".")
version = tuple([int(x) for x in version])
# Dispatch class based on version
instance_class = _SUPPORT_VERSION.get(version, None)
instance_class = _SUPPORT_VERSION.get(version)
if instance_class is None:
raise ValueError(
"Currently, MiniCPMV only supports versions 2.0, 2.5, and 2.6")
5 changes: 1 addition & 4 deletions vllm/spec_decode/draft_model_runner.py
Original file line number Diff line number Diff line change
@@ -183,10 +183,7 @@ def supports_gpu_multi_step(self, execute_model_req: ExecuteModelRequest):
return False

# TODO: Add soft-tuning prompt adapter support
if self.prompt_adapter_config:
return False

return True
return not self.prompt_adapter_config

@torch.inference_mode()
def execute_model(
7 changes: 2 additions & 5 deletions vllm/spec_decode/metrics.py
Original file line number Diff line number Diff line change
@@ -104,13 +104,10 @@ def _should_collect_rejsample_metrics(self, now: float) -> bool:
if self._rank != 0:
return False

if (now - self._last_metrics_collect_time <
self._rejsample_metrics_collect_interval_s):
return False
return True
return now - self._last_metrics_collect_time >= self._rejsample_metrics_collect_interval_s # noqa: E501

def _copy_rejsample_metrics_async(self) -> torch.cuda.Event:
"""Copy rejection/typical-acceptance sampling metrics
"""Copy rejection/typical-acceptance sampling metrics
(number of accepted tokens, etc) to CPU asynchronously.
Returns a CUDA event recording when the copy is complete.
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