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#!/usr/bin/env python
import cPickle
import sys
import os
import importlib
import csv
from blocks.model import Model
if __name__ == "__main__":
if len(sys.argv) != 2:
print >> sys.stderr, 'Usage: %s config' % sys.argv[0]
sys.exit(1)
model_name = sys.argv[1]
config = importlib.import_module('.%s' % model_name, 'config')
model_config = config.Model(config)
stream = config.Stream(config)
inputs = stream.inputs()
outputs = model_config.predict.outputs
req_vars_test = model_config.predict.inputs + ['trip_id']
test_stream = stream.test(req_vars_test)
model = Model(model_config.predict(**inputs))
with open(os.path.join('model_data', "{}.pkl".format(model_name))) as f:
parameters = cPickle.load(f)
model.set_param_values(parameters)
if 'destination' in outputs:
dest_outfile = open(os.path.join('output', 'test-dest-output-%s.csv' % model_name), 'w')
dest_outcsv = csv.writer(dest_outfile)
dest_outcsv.writerow(["TRIP_ID", "LATITUDE", "LONGITUDE"])
if 'duration' in outputs:
time_outfile = open(os.path.join('output', 'test-time-output-%s.csv' % model_name), 'w')
time_outcsv = csv.writer(time_outfile)
time_outcsv.writerow(["TRIP_ID", "TRAVEL_TIME"])
function = model.get_theano_function()
for d in test_stream.get_epoch_iterator(as_dict=True):
input_values = [d[k.name] for k in model.inputs]
output_values = function(*input_values)
if 'destination' in outputs:
destination = output_values[outputs.index('destination')]
dest_outcsv.writerow([d['trip_id'][0], destination[0, 0], destination[0, 1]])
if 'duration' in outputs:
duration = output_values[outputs.index('duration')]
time_outcsv.writerow([d['trip_id'][0], int(round(duration[0]))])
if 'destination' in outputs:
dest_outfile.close()
if 'duration' in outputs:
time_outfile.close()
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