[CI][RFC] Replace black-jupyter with ruff-format (#37210)
Co-authored-by: Alison Shao <a.shao@wustl.edu>
This commit is contained in:
co-authored by
Alison Shao
parent
2641e427be
commit
28262c20df
@@ -129,9 +129,9 @@ class OpenAI(BaseBackend):
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if key not in self.spec_kwargs:
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self.spec_kwargs[key] = value
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else:
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assert (
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value == self.spec_kwargs[key]
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), "sampling parameters should be consistent if turn on api speculative execution."
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assert value == self.spec_kwargs[key], (
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"sampling parameters should be consistent if turn on api speculative execution."
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)
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self.spec_format.append(
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{"text": "", "stop": params["stop"], "name": spec_var_name}
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)
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@@ -180,9 +180,9 @@ class OpenAI(BaseBackend):
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)
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# Keep the returned list (or string) as is.
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elif sampling_params.dtype in [str, "str", "string"]:
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assert (
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not self.is_chat_model
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), "constrained type not supported on chat model"
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assert not self.is_chat_model, (
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"constrained type not supported on chat model"
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)
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kwargs = sampling_params.to_openai_kwargs()
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kwargs.pop("stop")
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comp = openai_completion(
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@@ -200,9 +200,9 @@ class OpenAI(BaseBackend):
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else:
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comp = '"' + comp + '"'
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elif sampling_params.dtype in [int, "int"]:
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assert (
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not self.is_chat_model
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), "constrained type not supported on chat model"
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assert not self.is_chat_model, (
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"constrained type not supported on chat model"
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)
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kwargs = sampling_params.to_openai_kwargs()
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kwargs.pop("stop")
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comp = openai_completion(
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@@ -133,18 +133,14 @@ class RuntimeEndpoint(BaseBackend):
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dtype_regex = None
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if sampling_params.dtype in ["int", int]:
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dtype_regex = REGEX_INT
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sampling_params.stop.extend([" ", "\n"])
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elif sampling_params.dtype in ["float", float]:
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dtype_regex = REGEX_FLOAT
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sampling_params.stop.extend([" ", "\n"])
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elif sampling_params.dtype in ["str", str]:
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dtype_regex = REGEX_STR
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elif sampling_params.dtype in ["bool", bool]:
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dtype_regex = REGEX_BOOL
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else:
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raise RuntimeError(f"Invalid dtype: {sampling_params.dtype}")
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@@ -12,7 +12,6 @@ class ChoicesDecision:
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class ChoicesSamplingMethod(ABC):
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@property
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def requires_unconditional_logprobs(self) -> bool:
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return False
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@@ -30,7 +29,6 @@ class ChoicesSamplingMethod(ABC):
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class TokenLengthNormalized(ChoicesSamplingMethod):
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def __call__(
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self,
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*,
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@@ -54,7 +52,6 @@ token_length_normalized = TokenLengthNormalized()
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class GreedyTokenSelection(ChoicesSamplingMethod):
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def __call__(
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self,
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*,
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@@ -108,7 +105,6 @@ greedy_token_selection = GreedyTokenSelection()
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class UnconditionalLikelihoodNormalized(ChoicesSamplingMethod):
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@property
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def requires_unconditional_logprobs(self) -> bool:
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return True
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@@ -624,9 +624,9 @@ class StreamExecutor:
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self.meta_info[name] = meta_info
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self.variable_event[name].set()
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else:
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assert (
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self.num_api_spec_tokens is None
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), "stream is not supported with api speculative execution"
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assert self.num_api_spec_tokens is None, (
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"stream is not supported with api speculative execution"
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)
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generator = self.backend.generate_stream(
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self, sampling_params=sampling_params
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)
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@@ -531,7 +531,6 @@ class SglRoleEnd(SglExpr):
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class SglSelect(SglExpr):
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def __init__(
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self,
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name: str,
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