multiprocessing

问题 I am very new to Python, thus am possibly asking a simple question. I am wrting a multiprocess code with Python: from multiprocessing import Process from multiprocessing import Queue class myClass(object): def __init__(self): self.__i = 0 self.__name = 'rob' return def target_func(self, name, q): self.__name = name print 'Hello', self.__name self.__i += 1 print self.__i q.put([self.__i, self.__name]) return def name(self): return self.__name def i(self): return self.__i if __name__ == '__main

问题 I am very new to Python, thus am possibly asking a simple question. I am wrting a multiprocess code with Python: from multiprocessing import Process from multiprocessing import Queue class myClass(object): def __init__(self): self.__i = 0 self.__name = 'rob' return def target_func(self, name, q): self.__name = name print 'Hello', self.__name self.__i += 1 print self.__i q.put([self.__i, self.__name]) return def name(self): return self.__name def i(self): return self.__i if __name__ == '__main

问题 I come here because I have an issue with my Jupiter's Python3 notebook. I need to create a function that uses the multiprocessing library. Before to implement it, I make some tests. I found a looooot of different examples but the issue is everytime the same : my code is executed but nothing happens in the notebook's interface : The code i try to run on jupyter is this one : import os from multiprocessing import Process, current_process def doubler(number): """ A doubling function that can be

问题 I come here because I have an issue with my Jupiter's Python3 notebook. I need to create a function that uses the multiprocessing library. Before to implement it, I make some tests. I found a looooot of different examples but the issue is everytime the same : my code is executed but nothing happens in the notebook's interface : The code i try to run on jupyter is this one : import os from multiprocessing import Process, current_process def doubler(number): """ A doubling function that can be

问题 I have a simple code: path = [filepath1, filepath2, filepath3] def umap_embedding(filepath): file = np.genfromtxt(filepath,delimiter=' ') if len(file) > 20000: file = file[np.random.choice(file.shape[0], 20000, replace=False), :] neighbors = len(file)//200 if neighbors >= 2: neighbors = neighbors else: neighbors = 2 embedder = umap.UMAP(n_neighbors=neighbors, min_dist=0.1, metric='correlation', n_components=2) embedder.fit(file) embedded = embedder.transform(file) name = 'file' np.savetxt

问题 I have a simple code: path = [filepath1, filepath2, filepath3] def umap_embedding(filepath): file = np.genfromtxt(filepath,delimiter=' ') if len(file) > 20000: file = file[np.random.choice(file.shape[0], 20000, replace=False), :] neighbors = len(file)//200 if neighbors >= 2: neighbors = neighbors else: neighbors = 2 embedder = umap.UMAP(n_neighbors=neighbors, min_dist=0.1, metric='correlation', n_components=2) embedder.fit(file) embedded = embedder.transform(file) name = 'file' np.savetxt

问题 I have a piece of code below where the joblib.Parallel() returns a list. import numpy as np from joblib import Parallel, delayed lst = [[0.0, 1, 2], [3, 4, 5], [6, 7, 8]] arr = np.array(lst) w, v = np.linalg.eigh(arr) def proj_func(i): return np.dot(v[:,i].reshape(-1, 1), v[:,i].reshape(1, -1)) proj = Parallel(n_jobs=-1)(delayed(proj_func)(i) for i in range(len(w))) Instead of a list, how do I return a generator using joblib.Parallel() ? Edit: I have updated the code as suggested by

问题 I wrote a script that I deploy in an HPC node with 112 cores, thus starting 112 processes up to completing 400 needed ( node_combinations is a list of 400 tuples). The relevant snippet of code is below: # Parallel Path Probability Calculation # ===================================== node_combinations = [(i, j) for i in g.nodes for j in g.nodes] pool = Pool() start = datetime.datetime.now() logging.info("Start time: %s", start) print("Start time: ", start) pool.starmap(g._print_probability_path

问题 I wrote a script that I deploy in an HPC node with 112 cores, thus starting 112 processes up to completing 400 needed ( node_combinations is a list of 400 tuples). The relevant snippet of code is below: # Parallel Path Probability Calculation # ===================================== node_combinations = [(i, j) for i in g.nodes for j in g.nodes] pool = Pool() start = datetime.datetime.now() logging.info("Start time: %s", start) print("Start time: ", start) pool.starmap(g._print_probability_path

问题 I encounter a multiprocessing problem. The code is included below. The code can execute as expected, but when uncommenting self.queue = multiprocessing.Queue() , this program will exit immediately and it seems that the subprocess can't be started successfully. I don't know what happened. Could someone help me out? Many Thanks! import multiprocessing import time class Test: def __init__(self): self.pool = multiprocessing.Pool(1) #self.queue = multiprocessing.Queue() def subprocess(self): for i