flag_bootstrapped = True
if i % 1000 == 0:
print "processed %s jobs so far" % i
i = 0
for i in range(len(X)):
env.start(job_process(i))
i = i + 1
simulate(env)
if arguments['--interactive'] == True:
print(arguments)
from IPython import embed
embed()
if tool == "sgd":
array_to_file(
pred, arguments["<output_folder>"] + "/prediction_%s_%s_%s" %
(tool, loss, penalty))
elif tool == "passive-aggressive":
array_to_file(
pred,
arguments["<output_folder>"] + "/prediction_%s_%s" % (tool, loss))
#interactive?
if arguments['--interactive'] == True:
print(arguments)
from IPython import embed
embed()
model.partial_fit(np.array([j]),np.array([yf[i]]))
#print('5: time is %s,i= %s' % (env.now, i))
if not flag_bootstrapped:
flag_bootstrapped=True
if i % 1000==0:
print "processed %s jobs so far" %i
i=0
for i in range(len(X)):
env.start(job_process(i))
i=i+1
simulate(env)
if arguments['--interactive']==True:
print(arguments)
from IPython import embed
embed()
if tool=="sgd":
array_to_file(pred,arguments["<output_folder>"]+"/prediction_%s_%s_%s" %(tool,loss,penalty))
elif tool=="passive-aggressive":
array_to_file(pred,arguments["<output_folder>"]+"/prediction_%s_%s" %(tool,loss))
#interactive?
if arguments['--interactive']==True:
print(arguments)
from IPython import embed
embed()
yield env.timeout(wait_time + run_time)
#print('4: time is %s,i= %s' % (env.now, i))
model.partial_fit(np.array([j]), np.array([yf[i]]))
#print('5: time is %s,i= %s' % (env.now, i))
if not flag_bootstrapped:
flag_bootstrapped = True
if i % 1000 == 0:
print "processed %s jobs so far" % i
i = 0
for i in range(len(X)):
env.start(job_process(i))
i = i + 1
simulate(env)
if arguments['--interactive'] == True:
print(arguments)
from IPython import embed
embed()
array_to_file(pred, "prediction_sgd")
#interactive?
if arguments['--interactive'] == True:
print(arguments)
from IPython import embed
embed()
yield env.timeout(wait_time+run_time)
#print('4: time is %s,i= %s' % (env.now, i))
model.partial_fit(np.array([j]),np.array([yf[i]]))
#print('5: time is %s,i= %s' % (env.now, i))
if not flag_bootstrapped:
flag_bootstrapped=True
if i % 1000==0:
print "processed %s jobs so far" %i
i=0
for i in range(len(X)):
env.start(job_process(i))
i=i+1
simulate(env)
if arguments['--interactive']==True:
print(arguments)
from IPython import embed
embed()
array_to_file(pred,"prediction_sgd")
#interactive?
if arguments['--interactive']==True:
print(arguments)
from IPython import embed
embed()
