How to parallel a function taking two arguments and return a dictionary in DASK

Question

I have a function batch_opt taking two arguments (integer i and pandas dataframe train) and return a python dictionary. When I was trying to parallelize the computation using DASK in Python, I got the type error of Delayed objects are immutable. I am new to DASK. Can anyone help me out here? Thanks.

results = []
for i in range(0, 2):
    validation_res = delayed(batch_opt)(i, train)
    results.append(validation_res) 

start = time.time()
res = compute(*results)
print(time.time() - start)

Trace:

TypeError                                 Traceback (most recent call last)
    <ipython-input-19-8463f64dec56> in <module>
          5 
          6 start = time.time()
    ----> 7 res = compute(*results)
          8 print(time.time() - start)

~/.conda/envs/odop/lib/python3.8/site-packages/dask/base.py in compute(*args, **kwargs)
    568         postcomputes.append(x.__dask_postcompute__())
    569 
--> 570     results = schedule(dsk, keys, **kwargs)
    571     return repack([f(r, *a) for r, (f, a) in zip(results, postcomputes)])
    572 

~/.conda/envs/odop/lib/python3.8/site-packages/dask/threaded.py in get(dsk, result, cache, num_workers, pool, **kwargs)
     77             pool = MultiprocessingPoolExecutor(pool)
     78 
---> 79     results = get_async(
     80         pool.submit,
     81         pool._max_workers,

~/.conda/envs/odop/lib/python3.8/site-packages/dask/local.py in get_async(submit, num_workers, dsk, result, cache, get_id, rerun_exceptions_locally, pack_exception, raise_exception, callbacks, dumps, loads, chunksize, **kwargs)
    505                             _execute_task(task, data)  # Re-execute locally
    506                         else:
--> 507                             raise_exception(exc, tb)
    508                     res, worker_id = loads(res_info)
    509                     state["cache"][key] = res

~/.conda/envs/odop/lib/python3.8/site-packages/dask/local.py in reraise(exc, tb)
    313     if exc.__traceback__ is not tb:
    314         raise exc.with_traceback(tb)
--> 315     raise exc
    316 
    317 

~/.conda/envs/odop/lib/python3.8/site-packages/dask/local.py in execute_task(key, task_info, dumps, loads, get_id, pack_exception)
    218     try:
    219         task, data = loads(task_info)
--> 220         result = _execute_task(task, data)
    221         id = get_id()
    222         result = dumps((result, id))

~/.conda/envs/odop/lib/python3.8/site-packages/dask/core.py in _execute_task(arg, cache, dsk)
    117         # temporaries by their reference count and can execute certain
    118         # operations in-place.
--> 119         return func(*(_execute_task(a, cache) for a in args))
    120     elif not ishashable(arg):
    121         return arg

<ipython-input-7-e3af5748e1cf> in batch_opt(i, train)
     22         test.loc[:, 'seg'] = test.apply(lambda x: proc.assign_trxn(x), axis = 1)
     23         test_policy_res, test_metrics_res = opt.analyze_result(fa_m, x, test, cum_to_day, cur_policy, policy)
---> 24         validation_res[(train_mon_yr_batch, test_mon_yr)] = {'train_policy': train_policy_res, 'train_result': train_metrics_res, 'test_policy': test_policy_res, 'test_result': test_metrics_res}
     25     return validation_res

~/.conda/envs/odop/lib/python3.8/site-packages/dask/delayed.py in __setitem__(self, index, val)
    564 
    565     def __setitem__(self, index, val):
--> 566         raise TypeError("Delayed objects are immutable")
    567 
    568     def __iter__(self):

TypeError: Delayed objects are immutable