Remove use of `julia_kwargs`

pysr/sr.py

@@ -575,11 +575,6 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         before passing to the symbolic regression code. None means no
         feature selection; an int means select that many features.
         Default is `None`.
-    julia_kwargs : dict
-        Keyword arguments to pass to `julia.core.Julia(...)` to initialize
-        the Julia runtime. The default, when `None`, is to set `threads` equal
-        to `procs`, and `optimize` to 3.
-        Default is `None`.
     **kwargs : dict
         Supports deprecated keyword arguments. Other arguments will
         result in an error.
@@ -743,7 +738,6 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         extra_jax_mappings: Optional[Dict[Callable, str]] = None,
         denoise: bool = False,
         select_k_features: Optional[int] = None,
-        julia_kwargs: Optional[Dict] = None,
         **kwargs,
     ):
         # Hyperparameters
@@ -843,7 +837,6 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         # Pre-modelling transformation
         self.denoise = denoise
         self.select_k_features = select_k_features
-        self.julia_kwargs = julia_kwargs
 
         # Once all valid parameters have been assigned handle the
         # deprecated kwargs
@@ -878,6 +871,12 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
                         "PySR repository root.\n"
                         "You should now be able to use the custom julia project.",
                     )
+                elif k == "julia_kwargs":
+                    warnings.warn(
+                        "The `julia_kwargs` parameter has been deprecated. To pass custom "
+                        "keyword arguments to the julia backend, you should use environment variables. "
+                        "See the Julia documentation for more information.",
+                    )
                 else:
                     raise TypeError(
                         f"{k} is not a valid keyword argument for PySRRegressor."
@@ -1300,16 +1299,6 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
             > 0
         )
 
-        julia_kwargs = {}
-        if self.julia_kwargs is not None:
-            for key, value in self.julia_kwargs.items():
-                julia_kwargs[key] = value
-        if "optimize" not in julia_kwargs:
-            julia_kwargs["optimize"] = 3
-        if "threads" not in julia_kwargs and packed_modified_params["multithreading"]:
-            julia_kwargs["threads"] = self.procs
-        packed_modified_params["julia_kwargs"] = julia_kwargs
-
         return packed_modified_params
 
     def _validate_and_set_fit_params(
@@ -1551,7 +1540,6 @@ class PySRRegressor(MultiOutputMixin, RegressorMixin, BaseEstimator):
         batch_size = mutated_params["batch_size"]
         update_verbosity = mutated_params["update_verbosity"]
         progress = mutated_params["progress"]
-        julia_kwargs = mutated_params["julia_kwargs"]
 
         # Start julia backend processes
         if not already_ran and update_verbosity != 0: