thread_local_overrides.overrides["usage_tracker"] = copy.deepcopy(parent_overrides["usage_tracker"])

try:
    index, outcome = f.result()
except Exception:
    pass

original = thread_local_overrides.get()
new_overrides = {**original, **parent_overrides.copy()}
if parent_overrides.get("usage_tracker"):
    new_overrides["usage_tracker"] = copy.deepcopy(parent_overrides["usage_tracker"])
token = thread_local_overrides.set(new_overrides)

except Exception as e:
    logger.error(f"Worker failed: {e}")
    if self.provide_traceback:
        traceback.print_exc()

import dspy
import mlflow

mlflow.dspy.autolog()  # Enables usage_tracker, triggering the bug

class ProcessItem(dspy.Module):
    def __init__(self):
        self.predictor = dspy.ChainOfThought("item -> result")

    def forward(self, item):
        return self.predictor(item=item)

class GetItems(dspy.Module):
    def __init__(self):
        self.predictor = dspy.ChainOfThought("objective -> task_items: list[str]")

    def forward(self, objective):
        return self.predictor(objective=objective)

class Pipeline(dspy.Module):
    def __init__(self):
        self.get_items = GetItems()
        self.process_item = ProcessItem()

    def forward(self, objective):
        result = self.get_items(objective=objective)

        parallel = dspy.Parallel(num_threads=4, provide_traceback=True)
        results = parallel([
            (self.process_item, {"item": item})
            for item in result.task_items
        ])
        return dspy.Prediction(results=results)  # Returns [None, None, None, ...] before fix

lm = dspy.LM("azure/gpt-4")
dspy.configure(lm=lm)

pipeline = Pipeline()
results = pipeline("do something")
print(results)