diff --git a/src/mistralai/models/completiontrainingparametersin.py b/src/mistralai/models/completiontrainingparametersin.py index 1f74bb9d..1610095d 100644 --- a/src/mistralai/models/completiontrainingparametersin.py +++ b/src/mistralai/models/completiontrainingparametersin.py @@ -46,7 +46,8 @@ class CompletionTrainingParametersIn(BaseModel): @model_serializer(mode="wrap") def serialize_model(self, handler): - optional_fields = [ + # Use tuple/lists for fastest membership test, all fields are a small, fixed set + optional_fields = { "training_steps", "learning_rate", "weight_decay", @@ -54,36 +55,39 @@ def serialize_model(self, handler): "epochs", "seq_len", "fim_ratio", - ] - nullable_fields = [ + } + nullable_fields = { "training_steps", "weight_decay", "warmup_fraction", "epochs", "seq_len", "fim_ratio", - ] - null_default_fields = [] + } + null_default_fields = set() serialized = handler(self) + # Precompute fields set and other invariants local to the method for perf + pydantic_fields_set = self.__pydantic_fields_set__ + + # Micro-optimize reference lookups & minimize attribute access in loop + model_fields = type(self).model_fields m = {} - for n, f in type(self).model_fields.items(): + # Avoid repeatedly calling .get/.pop when iterating: iterate directly on model_fields + for n, f in model_fields.items(): k = f.alias or n - val = serialized.get(k) - serialized.pop(k, None) + # Use pop once, default None if not present + val = serialized.pop(k, None) optional_nullable = k in optional_fields and k in nullable_fields - is_set = ( - self.__pydantic_fields_set__.intersection({n}) - or k in null_default_fields - ) # pylint: disable=no-member + is_set = n in pydantic_fields_set or k in null_default_fields # pylint: disable=no-member if val is not None and val != UNSET_SENTINEL: m[k] = val elif val != UNSET_SENTINEL and ( - not k in optional_fields or (optional_nullable and is_set) + k not in optional_fields or (optional_nullable and is_set) ): m[k] = val