stsievert

stsievert

stsievert

stsievert

import numpy as np
from distributed import Client, as_completed
from sklearn.base import clone
from sklearn.svm import SVC
import dask.array as da
from time import sleep
from sklearn.base import BaseEstimator


def set_and_clone(x):

stsievert

distributed.core - ERROR - "('array-ce35610051c66c361205cb57db0700ff', 89, 7)"
Traceback (most recent call last):
  File "/Users/ssievert/anaconda3/envs/dask-master/lib/python3.6/site-packages/distributed/core.py", line 375, in handle_stream
    handler(**merge(extra, msg))
  File "/Users/ssievert/anaconda3/envs/dask-master/lib/python3.6/site-packages/distributed/scheduler.py", line 1355, in update_graph
    ts = self.tasks[key]
KeyError: "('array-ce35610051c66c361205cb57db0700ff', 89, 7)"
distributed.core - ERROR - "('array-ce35610051c66c361205cb57db0700ff', 89, 7)"
Traceback (most recent call last):
  File "/Users/ssievert/anaconda3/envs/dask-master/lib/python3.6/site-packages/distributed/core.py", line 375, in handle_stream

stsievert

import numpy as np
from sklearn.model_selection import cross_validate
from sklearn.linear_model import SGDClassifier
from sklearn.datasets import make_classification
import scipy.stats as stats
from sklearn.base import clone
from pprint import pprint
import sklearn.model_selection

stsievert

from __future__ import print_function
import socket
import sys
import time

# Create a TCP/IP socket
sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM)

# Connect the socket to the port where the server is listening
server_address = ('localhost', 10000)

stsievert

stsievert

stsievert

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