fix: persistent styling between ruff and yapf (#279)

openllm-python/src/openllm/serialisation/__init__.py

@@ -30,12 +30,19 @@ import cloudpickle
 import fs
 
 import openllm
+
 from bentoml._internal.models.model import CUSTOM_OBJECTS_FILENAME
-from openllm_core._typing_compat import M, ParamSpec, T
+from openllm_core._typing_compat import M
+from openllm_core._typing_compat import ParamSpec
+from openllm_core._typing_compat import T
+
 if t.TYPE_CHECKING:
   import bentoml
 
-  from . import constants as constants, ggml as ggml, transformers as transformers
+  from . import constants as constants
+  from . import ggml as ggml
+  from . import transformers as transformers
+
 P = ParamSpec('P')
 
 def load_tokenizer(llm: openllm.LLM[t.Any, T], **tokenizer_attrs: t.Any) -> T:
@@ -44,7 +51,8 @@ def load_tokenizer(llm: openllm.LLM[t.Any, T], **tokenizer_attrs: t.Any) -> T:
   By default, it will try to find the bentomodel whether it is in store..
   If model is not found, it will raises a ``bentoml.exceptions.NotFound``.
   '''
-  from .transformers._helpers import infer_tokenizers_from_llm, process_config
+  from .transformers._helpers import infer_tokenizers_from_llm
+  from .transformers._helpers import process_config
 
   config, *_ = process_config(llm._bentomodel.path, llm.__llm_trust_remote_code__)
   bentomodel_fs = fs.open_fs(llm._bentomodel.path)

openllm-python/src/openllm/serialisation/constants.py

@@ -1,4 +1,5 @@
 from __future__ import annotations
+
 FRAMEWORK_TO_AUTOCLASS_MAPPING = {
     'pt': ('AutoModelForCausalLM', 'AutoModelForSeq2SeqLM'),
     'tf': ('TFAutoModelForCausalLM', 'TFAutoModelForSeq2SeqLM'),

openllm-python/src/openllm/serialisation/ggml.py

@@ -7,7 +7,9 @@ import typing as t
 
 import bentoml
 import openllm
-if t.TYPE_CHECKING: from openllm_core._typing_compat import M
+
+if t.TYPE_CHECKING:
+  from openllm_core._typing_compat import M
 
 _conversion_strategy = {'pt': 'ggml'}
 

openllm-python/src/openllm/serialisation/transformers/__init__.py

@@ -5,15 +5,23 @@ import logging
 import typing as t
 
 from huggingface_hub import snapshot_download
-from simple_di import Provide, inject
+from simple_di import Provide
+from simple_di import inject
 
 import bentoml
 import openllm
+
 from bentoml._internal.configuration.containers import BentoMLContainer
 from bentoml._internal.models.model import ModelOptions
 
-from ._helpers import check_unintialised_params, infer_autoclass_from_llm, infer_tokenizers_from_llm, make_model_signatures, process_config, update_model
+from ._helpers import check_unintialised_params
+from ._helpers import infer_autoclass_from_llm
+from ._helpers import infer_tokenizers_from_llm
+from ._helpers import make_model_signatures
+from ._helpers import process_config
+from ._helpers import update_model
 from .weights import HfIgnore
+
 if t.TYPE_CHECKING:
   import types
 
@@ -24,7 +32,9 @@ if t.TYPE_CHECKING:
   import vllm
 
   from bentoml._internal.models import ModelStore
-  from openllm_core._typing_compat import DictStrAny, M, T
+  from openllm_core._typing_compat import DictStrAny
+  from openllm_core._typing_compat import M
+  from openllm_core._typing_compat import T
 else:
   vllm = openllm.utils.LazyLoader('vllm', globals(), 'vllm')
   autogptq = openllm.utils.LazyLoader('autogptq', globals(), 'auto_gptq')

openllm-python/src/openllm/serialisation/transformers/_helpers.py

@@ -4,16 +4,24 @@ import typing as t
 
 import openllm
 import openllm_core
-from bentoml._internal.models.model import ModelInfo, ModelSignature
-from openllm.serialisation.constants import FRAMEWORK_TO_AUTOCLASS_MAPPING, HUB_ATTRS
+
+from bentoml._internal.models.model import ModelInfo
+from bentoml._internal.models.model import ModelSignature
+from openllm.serialisation.constants import FRAMEWORK_TO_AUTOCLASS_MAPPING
+from openllm.serialisation.constants import HUB_ATTRS
+
 if t.TYPE_CHECKING:
   import torch
   import transformers
+
   from transformers.models.auto.auto_factory import _BaseAutoModelClass
 
   import bentoml
+
   from bentoml._internal.models.model import ModelSignaturesType
-  from openllm_core._typing_compat import DictStrAny, M, T
+  from openllm_core._typing_compat import DictStrAny
+  from openllm_core._typing_compat import M
+  from openllm_core._typing_compat import T
 else:
   transformers, torch = openllm_core.utils.LazyLoader('transformers', globals(), 'transformers'), openllm_core.utils.LazyLoader('torch', globals(), 'torch')
 

openllm-python/src/openllm/serialisation/transformers/weights.py

@@ -2,10 +2,14 @@ from __future__ import annotations
 import typing as t
 
 import attr
+
 from huggingface_hub import HfApi
+
 if t.TYPE_CHECKING:
   import openllm
-  from openllm_core._typing_compat import M, T
+
+  from openllm_core._typing_compat import M
+  from openllm_core._typing_compat import T
 
 def has_safetensors_weights(model_id: str, revision: str | None = None) -> bool:
   return any(s.rfilename.endswith('.safetensors') for s in HfApi().model_info(model_id, revision=revision).siblings)