Pickled Object created by Python 3.6 cannot be loaded in Python 3.7 #738
Closed
Description
I'm new to sacred, and I am running into an issue trying to load an object created by a different python version.
I run my experiments on a SLurm cluster (Python 3.6.1) through my academic institution, and save out a dictionary of results using pickle. However, when I try to then load the pickled data on my laptop (which runs Python 3.7) I get the following error:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-11-a7579d7c1c2b> in <module>
2 # elbos = pickle.load(open("./poisson_lds_elbos.pkl", "rb"))
3 # posterior = pickle.load(open("./poisson_lds_posterior.pkl", "rb"))
----> 4 results = pickle.load(open("./lds_fit_results_poisson_rotational_orthog.pkl", "rb"))
5 lds = results["lds"]
6 elbos = results["elbos"]
~/anaconda3/envs/ssm/lib/python3.7/site-packages/sacred/config/custom_containers.py in _readonly(self, *args, **kwargs)
171
172 def _readonly(self, *args, **kwargs):
--> 173 raise SacredError(self.message, filter_traceback="always")
174
175
AttributeError: 'ReadOnlyList' object has no attribute 'message'
Here is the script which I ran to create the object:
import numpy as np
import matplotlib.pyplot as plt
import ssm
import pickle
from scipy.io import loadmat
from sacred import Experiment
ex = Experiment('poisson_lds_pjpca')
def load_data(path, sqrt=True):
struct = loadmat(path)
spikes = struct["binned"]
spikes = spikes.astype(int)
if sqrt:
spikes = np.sqrt(spikes)
spikes = np.swapaxes(spikes, -1, -2)
return [x for x in spikes]
@ex.config
def cfg():
data_path = "./binned_start-60_end190_width10_all_units.mat"
datas = load_data(data_path, sqrt=False)
D = 10
N = datas[0].shape[-1]
dynamics = "rotational"
emissions = "poisson_orthog"
masks = None
num_iters = 50
method = "laplace_em"
results_path = "lds_fit_results_poisson_rotational_orthog.pkl"
@ex.automain
def run(N, D, data_path, datas, dynamics, emissions, masks, num_iters, method, results_path):
ex.add_resource(data_path)
lds = ssm.LDS(N, D, dynamics=dynamics, emissions=emissions)
elbos, posterior = lds.fit(datas, num_iters=num_iters, method=method, masks=masks)
results = dict(lds=lds,
posterior=posterior,
elbos=elbos,
datas=datas)
print("saving results to %s" % results_path)
pickle.dump(results, open(results_path, "wb"))
ex.add_artifact(results_path)
return elbosIs there something obviously wrong with saving data using Pickle during a Sacred experiment? Or perhaps this is a bug?