I'm trying to use multiprocessing to map a Boost-wrapped function over multiple cores. This works fine in python 2.7, but is failing in python 3.8. I know the o
Problem I'm trying to load a file using PyTorch, but the error states archive/data.pkl does not exist. Code import torch cachefile = 'cacheddata.pth' torch.load
While using: with open("data_file.pickle", "rb") as pfile: raw_data = pickle.load(pfile) I get the error: AttributeError: Can't get attribute '_unpickle
I have my data in multiple pickle files stored on disk. I want to use tensorflow's tf.data.Dataset to load my data into training pipeline. My code goes: def _p
I have a big (several Gigs) nested dictionary of this structure: { string1: {string1_1: int1_1, string1_2: int1_2, ...}, string2: {string2_1: int2_1, strin
I am trying to I am tring to delete stop words via spark,the code is as follow from nltk.corpus import stopwords from pyspark.context import SparkContext from
I have successfully read the csv file from Amazon S3. But I have .pkl file of sentiment model. I want to load this .pkl file to predict sentiment. Here is my co
I ran this code on cmd and I face this error. _pickle.UnpicklingError: NEWOBJ class argument isn't a type object my app.py goes like this: # -*- coding: utf-8 -
I have read in a number of threads that Python pickle/cPickle cannot pickle lambda functions. However the following code works, using Python 2.7.6: import cPic
I'm working on an application that is a "predictive-model-as-a-service", structured as follows: train a model offline periodically upload model parameters to a
I got exceptions like UnicodeDecodeError raised when pickling (a list of) objects of EventFrame with a member participants that was an empty set. class EventFr
I'm applying some parallelization to my code, in which I use classes. I knew that is not possible to pickle a class method without any other approach different
I'm trying to pickle a pandas dataframe to my local directory so I can work on it in another jupyter notebook. The write appears to go successful at first but w