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How to use test_tagging method in locust

Best Python code snippet using locust

grader.py

Source:grader.py

2from tagger import *3from collections import defaultdict4def read_data_test(path):5    return open(path, 'r').read().split('\n')6def test_tagging(test_file):7	pred = np.asarray(read_data_test(test_file+'.pred'))8	soln = np.asarray(read_data_test(test_file+'.soln')[:-1])9	acc = np.sum(pred==soln) / len(soln)10	pct = min(acc, tagging_threshold) / tagging_threshold11	return pct12def almost_equal(a, b, diff=1e-4):13	if a == -np.inf:14		return b == -np.inf15	return np.abs(a-b) < diff16def array_almost_equal(a, b, diff=1e-4):17	if a.shape != b.shape:18		return False19	a_flat = a.flatten()20	b_flat = b.flatten()21	for i in range(a_flat.shape[0]):22		if not almost_equal(a_flat[i], b_flat[i]):23			return False24	return True25scheme = {26	'prior': 14,27	'transition':14,28	'emission':14,29	'tagging_small':35,30	'tagging_large':2331}32tagging_threshold = 0.8533test_names = list(scheme.keys())34if __name__ == '__main__':35	prior, transition, emission = train_HMM('data/train-public')36	results = defaultdict(float)37	solutions = np.load('soln.npz')38	# Prior Tests39	try:40		assert(array_almost_equal(prior, solutions['prior']))41		results['prior'] = scheme['prior']42	except Exception:43		pass44	# Transition Tests45	try:46		assert(array_almost_equal(transition, solutions['transition']))47		results['transition'] = scheme['transition']48	except Exception:49		pass50	# Emission Tests51	try:52		assert(array_almost_equal(np.asarray([emission[(key[0], key[1])] for key in solutions['emission_key']]), solutions['emission_val']))53		results['emission'] = scheme['emission']54	except Exception:55		pass56	# Tagging tests57	# Small58	try:59		results['tagging_small'] = test_tagging('data/test-public-small') * scheme['tagging_small']60	except Exception:61		pass62	# Large63	try:64		results['tagging_large'] = test_tagging('data/test-public-large') * scheme['tagging_large']65	except Exception:66		pass67	for t in test_names:68		print(t+": %.1f/%.1f" % (results[t], scheme[t]))...

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