def make_eq(q, a, VERBOSE, TRAIN):
#wps = open(q).readlines()
#answs = open(a).readlines()
#VERBOSE=True
wps = q
for k in range(len(wps)):
if VERBOSE:
for i in range(len(wps)):
print(i, wps[i])
k = int(input())
print(k)
#First preprocessing, tokenize slightly
problem = utils.preprocess_problem(wps[k])
print(problem)
story = utils.parse_stanford_nlp(problem)
sets = makesets.makesets(story['sentences'])
EF.main(sets, k, a[k], sys.argv[1])
sets = [x for x in sets
if makesets.floatcheck(x[1].num)
or x[1].num == 'x']
print(sets)
for z in sets:
z[1].details()
def make_eq(q, a, VERBOSE, TRAIN):
#wps = open(q).readlines()
#answs = open(a).readlines()
#VERBOSE=True
wps = q
for k in range(len(wps)):
if VERBOSE:
for i in range(len(wps)):
print(i, wps[i])
k = int(input())
print(k)
#First preprocessing, tokenize slightly
problem = utils.preprocess_problem(wps[k])
print(problem)
story = utils.parse_stanford_nlp(problem)
sets = makesets.makesets(story['sentences'])
EF.main(sets, k, a[k], sys.argv[1])
sets = [
x for x in sets if makesets.floatcheck(x[1].num) or x[1].num == 'x'
]
print(sets)
for z in sets:
z[1].details()
def make_eq(q, a, VERBOSE, TRAIN):
wps = q
for k in range(len(wps)):
if VERBOSE:
for i in range(len(wps)):
print(i, wps[i])
k = int(input())
print(k)
#First preprocessing, tokenize slightly
problem = utils.preprocess_problem(wps[k])
print(problem)
story = utils.parse_stanford_nlp(problem)
with open("s_data/" + str(k) + ".pickle", 'wb') as f:
pickle.dump(story, f)
return sets
def bug():
print("bug")
ip = 0
while ip == 0:
inp = input()
if inp == 0:
ip = 1
else:
exec(inp)
if __name__ == "__main__":
q, a, e = utils.parse_inp(sys.argv[1])
wps = q
while True:
for i in range(len(q)):
print(i, q[i])
k = input()
k = int(k)
problem = wps[k].lower()
print(problem)
story = utils.parse_stanford_nlp(problem)
sets = makesets(story["sentences"])
for s in sets:
s[1].details()
input()
return sets
def bug():
print("bug")
ip = 0
while ip == 0:
inp = input()
if inp == 0:
ip = 1
else:
exec(inp)
if __name__ == "__main__":
q, a, e = utils.parse_inp(sys.argv[1])
wps = q
while True:
for i in range(len(q)):
print(i, q[i])
k = input()
k = int(k)
problem = wps[k].lower()
print(problem)
story = utils.parse_stanford_nlp(problem)
sets = makesets(story["sentences"])
for s in sets:
s[1].details()
input()
