def main(args, _in, _out):
parts = args.matcher_fn.split(".")
module = __import__(".".join(parts[:-1]), fromlist=[""])
matcher = getattr(module, parts[-1])
with open(args.f, "r") as f:
_dict = list(load_dict(f))
raw = list(load_raw(_in))
from rank.util.feature import vw_model
bow = list(compute_bow(raw, _dict, matcher, args.max_dist, args.multi))
_out.write("{0}".format(vw_model(bow_string(bow), args.label)))
def main(args, _in, _out):
parts = args.matcher_fn.split(".")
module = __import__(".".join(parts[:-1]), fromlist=[""])
matcher = getattr(module, parts[-1])
with open(args.f, "r") as f:
_dict = list(load_dict(f))
raw = list(load_raw(_in))
from rank.util.feature import vw_model
bow = list(compute_bow(raw, _dict, matcher, args.max_dist, args.multi))
_out.write("{0}".format(vw_model(bow_string(bow), args.label)))
def main(args, _in, _out):
import pandas as pd
from rank.util.feature import parse_bow, vw_model
with open(args.m, "r") as f:
mask = list(map(lambda x: x.strip(), f.read().split("\n")))
data = [parse_bow(line)
for line in map(lambda x: x.strip(), _in.read().split("\n"))
if len(line) > 0
]
df = pd.DataFrame(data)
filtered = df[mask]
for label, line in zip(df["label"], filtered.values):
_out.write("{0}\n".format(vw_model(" ".join(
map(lambda x: "{0}:{1}".format(*x), zip(filtered.columns, line))), label)
))
def main(args, _in, _out):
import pandas as pd
from rank.util.feature import parse_bow, vw_model
with open(args.m, "r") as f:
mask = list(map(lambda x: x.strip(), f.read().split("\n")))
data = [
parse_bow(line) for line in map(lambda x: x.strip(),
_in.read().split("\n"))
if len(line) > 0
]
df = pd.DataFrame(data)
filtered = df[mask]
for label, line in zip(df["label"], filtered.values):
_out.write("{0}\n".format(
vw_model(
" ".join(
map(lambda x: "{0}:{1}".format(*x),
zip(filtered.columns, line))), label)))
