predict_no_batches.py

#!/usr/bin/env python
# coding: utf-8

"""
prediction code without batches
see http://fastml.com/how-to-get-predictions-from-pylearn2/
author: Zygmunt Zając
"""

import sys
import os
import numpy as np
import cPickle as pickle

from pylearn2.utils import serial
from theano import tensor as T
from theano import function

try:
	model_path = sys.argv[1]
	test_path = sys.argv[2]
	out_path = sys.argv[3]
except IndexError:
	print "Usage: predict.py <model file> <test file> <output file>"
	print "       predict.py saved_clf.pkl saved_tst.pkl results.csv\n"
	quit()
	
print "loading model..."

try:
	model = serial.load(model_path)
except Exception, e:
	print model_path + "doesn't seem to be a valid model path, got this error when trying to load it:"
	print e

print "setting up symbolic expressions..."

X = model.get_input_space().make_theano_batch()
Y = model.fprop(X)
Y = T.argmax(Y, axis=1)

f = function([X], Y)

print "loading data and predicting..."

x = pickle.load(open(test_path, 'rb'))
y = f(x)

print "writing predictions..."

out = open(out_path, 'w')
out.write('id,label\n')

for i in xrange(y.shape[0]):
	p = y[i]
	out.write('{},{}\n'.format(i + 1, p))
	
out.close()