Hi, I’m facing the same error… also using Windows.
It was working fine until a couple of weeks ago; it’s something to do with cloudpickle, here’s the full trace of the error I get:
---------------------------------------------------------------------------
IndexError Traceback (most recent call last)
Cell In[38], line 9
7 p = pm.Beta("p", alpha=1, beta=1)
8 y = pm.Binomial("y", n=10, p=p, observed=[1,1,0,0])
----> 9 idata = pm.sample()
File ~\anaconda3\envs\H2\Lib\site-packages\pymc\sampling\mcmc.py:546, in sample(draws, step, init, n_init, initvals, trace, chains, cores, tune, progressbar, model, random_seed, discard_tuned_samples, compute_convergence_checks, callback, jitter_max_retries, return_inferencedata, keep_warning_stat, idata_kwargs, mp_ctx, **kwargs)
544 _print_step_hierarchy(step)
545 try:
--> 546 _mp_sample(**sample_args, **parallel_args)
547 except pickle.PickleError:
548 _log.warning("Could not pickle model, sampling singlethreaded.")
File ~\anaconda3\envs\H2\Lib\site-packages\pymc\sampling\mcmc.py:900, in _mp_sample(draws, tune, step, chains, cores, random_seed, start, progressbar, traces, model, callback, mp_ctx, **kwargs)
897 # We did draws += tune in pm.sample
898 draws -= tune
--> 900 sampler = ps.ParallelSampler(
901 draws=draws,
902 tune=tune,
903 chains=chains,
904 cores=cores,
905 seeds=random_seed,
906 start_points=start,
907 step_method=step,
908 progressbar=progressbar,
909 mp_ctx=mp_ctx,
910 )
911 try:
912 try:
File ~\anaconda3\envs\H2\Lib\site-packages\pymc\sampling\parallel.py:401, in ParallelSampler.__init__(self, draws, tune, chains, cores, seeds, start_points, step_method, progressbar, mp_ctx)
399 step_method_pickled = None
400 if mp_ctx.get_start_method() != "fork":
--> 401 step_method_pickled = cloudpickle.dumps(step_method, protocol=-1)
403 self._samplers = [
404 ProcessAdapter(
405 draws,
(...)
414 for chain, seed, start in zip(range(chains), seeds, start_points)
415 ]
417 self._inactive = self._samplers.copy()
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle_fast.py:73, in dumps(obj, protocol, buffer_callback)
69 with io.BytesIO() as file:
70 cp = CloudPickler(
71 file, protocol=protocol, buffer_callback=buffer_callback
72 )
---> 73 cp.dump(obj)
74 return file.getvalue()
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle_fast.py:602, in CloudPickler.dump(self, obj)
600 def dump(self, obj):
601 try:
--> 602 return Pickler.dump(self, obj)
603 except RuntimeError as e:
604 if "recursion" in e.args[0]:
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle_fast.py:692, in CloudPickler.reducer_override(self, obj)
690 return _class_reduce(obj)
691 elif isinstance(obj, types.FunctionType):
--> 692 return self._function_reduce(obj)
693 else:
694 # fallback to save_global, including the Pickler's
695 # dispatch_table
696 return NotImplemented
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle_fast.py:565, in CloudPickler._function_reduce(self, obj)
563 return NotImplemented
564 else:
--> 565 return self._dynamic_function_reduce(obj)
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle_fast.py:546, in CloudPickler._dynamic_function_reduce(self, func)
544 """Reduce a function that is not pickleable via attribute lookup."""
545 newargs = self._function_getnewargs(func)
--> 546 state = _function_getstate(func)
547 return (types.FunctionType, newargs, state, None, None,
548 _function_setstate)
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle_fast.py:157, in _function_getstate(func)
139 def _function_getstate(func):
140 # - Put func's dynamic attributes (stored in func.__dict__) in state. These
141 # attributes will be restored at unpickling time using
(...)
144 # unpickling time by iterating over slotstate and calling setattr(func,
145 # slotname, slotvalue)
146 slotstate = {
147 "__name__": func.__name__,
148 "__qualname__": func.__qualname__,
(...)
154 "__closure__": func.__closure__,
155 }
--> 157 f_globals_ref = _extract_code_globals(func.__code__)
158 f_globals = {k: func.__globals__[k] for k in f_globals_ref if k in
159 func.__globals__}
161 closure_values = (
162 list(map(_get_cell_contents, func.__closure__))
163 if func.__closure__ is not None else ()
164 )
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle.py:334, in _extract_code_globals(co)
330 names = co.co_names
331 # We use a dict with None values instead of a set to get a
332 # deterministic order (assuming Python 3.6+) and avoid introducing
333 # non-deterministic pickle bytes as a results.
--> 334 out_names = {names[oparg]: None for _, oparg in _walk_global_ops(co)}
336 # Declaring a function inside another one using the "def ..."
337 # syntax generates a constant code object corresponding to the one
338 # of the nested function's As the nested function may itself need
339 # global variables, we need to introspect its code, extract its
340 # globals, (look for code object in it's co_consts attribute..) and
341 # add the result to code_globals
342 if co.co_consts:
File ~\anaconda3\envs\H2\Lib\site-packages\cloudpickle\cloudpickle.py:334, in <dictcomp>(.0)
330 names = co.co_names
331 # We use a dict with None values instead of a set to get a
332 # deterministic order (assuming Python 3.6+) and avoid introducing
333 # non-deterministic pickle bytes as a results.
--> 334 out_names = {names[oparg]: None for _, oparg in _walk_global_ops(co)}
336 # Declaring a function inside another one using the "def ..."
337 # syntax generates a constant code object corresponding to the one
338 # of the nested function's As the nested function may itself need
339 # global variables, we need to introspect its code, extract its
340 # globals, (look for code object in it's co_consts attribute..) and
341 # add the result to code_globals
342 if co.co_consts:
IndexError: tuple index out of range