def traverse(self, right_idx=0, right_widx=0, fsent=None, rules=None, nodememo=None):
''' helper called by dump(); returns a string; figure out span'''
if nodememo is None:
nodememo = {}
if id(self) in nodememo:
return
deds = [(ded.dcost.dot(weights), ded) for ded in self.deds]
deds.sort()
deds = [x for _, x in deds[:max_edges_per_node]]
self.deds = deds # prune!
nedges = len(deds) # accumulating number of edges, recursively
self.i = right_idx
self.wi = right_widx
for dedid, ded in enumerate(deds):
try:
rule = rules[ded.ruleid]
except:
print >> sys.stderr, "WARNING: rule %d not found" % ded.ruleid
## assuming it's a one-word UNKNOWN rule
## TODO: check with lattice
unkword = fsent[self.wi]
rule = 'UNKNOWN("@UNKNOWN@") -> "%s"' % unkword # in reverse order
rules[ded.ruleid] = rule
print >> sys.stderr, " covering " + unkword
self.x = rule.split("(", 1)[0] # non-terminal label
# analyse RHS (chinese side)
lhs, rhs = rule.split(" -> ", 1) ## -> might be a word
# deal with lhs; convert to ded.lhsstr = ["...", "...", Item(...), "..."]
varid = 0
lhsstr = []
for child in ded.rule.e:
if sym.isvar(child):
lhsstr.append(ded.ants[varid])
varid += 1
else:
lhsstr.append(quoteattr(sym.tostring(child)))
# will be used in _dump()
ded.lhsstr = lhsstr
vars = []
chars_in_gap = 0
words_in_gap = 0
for it in reversed(rhs.split()): ## from RIGHT to LEFT!! N.B. can't split(" ")
if it[0] == "x":
#variable:
var = int(it[1:])
vars.append((var, chars_in_gap, words_in_gap))
chars_in_gap = 0
words_in_gap = 0
else:
# strip off quotes "..."
it = it[1:-1]
# calculate char-length
if it == foreign_sentence_tag: # <foreign-sentence>:
# glue symbol is not counted!
chars_in_gap += 0
words_in_gap += 0
else:
# 1 for word, len(...) for char
chars_in_gap += len(words_to_chars(it, encode_back=True))
words_in_gap += 1
accumu = self.i ## left boundary
waccumu = self.wi
for i, c_gap, w_gap in vars:
##for sub in ded.ants:
sub = ded.ants[i]
if id(sub) not in nodememo:
sub.traverse(accumu + c_gap, waccumu + w_gap, fsent, rules, nodememo)
# accumulating # of edges (if first seen)
nedges += nodememo[id(sub)][1]
## don't accumulate subs now; will do in another visit
## s += subs
accumu = sub.j
waccumu = sub.wj
tmp_j = (ded.ants[vars[-1][0]].j if vars != [] else self.i) + chars_in_gap
if self.j is not None and self.j != tmp_j:
assert False, "@sentence %d, node #%s, %d %d != %d %s rule %d" % \
(opts.sentid, self.nodeid, self.i, self.j, tmp_j, self.x, ded.ruleid)
self.j = tmp_j
tmp_wj = (ded.ants[vars[-1][0]].wj if vars != [] else self.wi) + words_in_gap ##
self.wj = tmp_wj
self.id = len(nodememo) + 1
nodememo[id(self)] = (self.id, nedges)
def dump(self, rules=None, sid=1, fsent="<foreign-sentence>", byline="", reflines=[]):
nodememo = {} # to keep track of sizes (# of nodes, # of edges)
# forest id, foreign sentence (TODO: refs)
fsent = fsent.split(" ")
s = "%s\t%s\n" % (sid, " ".join(fsent)) + \
"%d\n" % len(reflines) + \
"".join(reflines)
flen = len(words_to_chars(fsent, encode_back=True))
fwlen = len(fsent)
reversed_fsent = list(reversed(fsent)) ## RIGHT TO LEFT
if byline != "":
self.traverse(0, 0, reversed_fsent, rules, nodememo)
## swap back
self.adjust_spans(flen, fwlen)
byline = byline.split(" ")
byline_flen = self.i
byline_fwlen = self.wi
byline_f = fsent[:byline_fwlen]
print >> logs, "clen (non-byline) = %d (%d)" % (flen, self.j - self.i)
print >> logs, "wlen (non-byline) = %d (%d)" % (fwlen, self.wj - self.wi)
print >> logs, "BYLINE = " + " ".join(byline_f) + \
" ### %d chars, %d words" % (byline_flen, byline_fwlen)
assert len(words_to_chars(byline_f)) == byline_flen, "@sentence %d, BYLINE Error" % opts.sentid ## check consistency
## new rule/edge
## TOP("by" "line" x0:TOP) -> "BY" "LINE" x0 ### id=-1
byline_e = " ".join('"%s"' % w for w in byline)
lhs = "TOP(" + byline_e + " x0:%s)" % self.x # "TOP"
rhs = " ".join('"%s"' % w for w in byline_f) + " x0"
# byline rule, id=-1
rid = -1
rules[rid] = "%s -> %s ### id=%d" % (lhs, rhs, rid)
## make david-style LHS
david_lhs = []
for w in byline:
david_lhs.append(sym.fromstring(w))
david_lhs.append(sym.setindex(dummylabel, 1))
ded = Deduction([self], rule.Rule(rid, rule.Phrase(david_lhs), rule.Phrase(david_lhs)),\
svector.Vector())
ded.lhsstr = byline_e.split() + [self] ## N.B.: dont forget "..."
ded.ruleid = rid
# new node on top of TOP
oldtop = self
self = Item(self.x, 0, flen, deds=[ded])
self.x = oldtop.x
self.wi = 0
self.wj = fwlen
self.id = len(nodememo)+1
nodememo[id(self)] = (self.id, nodememo[id(oldtop)][1]+1) #edges
else:
# establish node spans
self.traverse(0, 0, reversed_fsent, rules, nodememo)
# swap i,j
self.adjust_spans(flen, fwlen)
## lhuang: the following is from hope.py
## be very careful about weights interpolation
sg = sgml.Sentence(fsent)
sg.fwords = fsent
sg.refs = [refline.split(" ") for refline in reflines]
if sg.refs:
theoracle.input(sg, verbose=False)
# 1-best
self.reweight(weights)
output(self, "1-best @ %s" % sid, onebestbleus, onebestscores)
base_oracleweights = theoracle.make_weights(additive=True)
# we use the in-place operations because oracleweights might be
# a subclass of Vector
for relative in []:#[opts.hope]:
oracleweights = theoracle.make_weights(additive=True)
oracleweights *= relative
# interpolation: taking modelcost into account
oracleweights += weights
# compute oracle
self.rescore(theoracle.models, oracleweights, add=True)
# TODO: why??
output(self, "hope%s " % relative, hopebleus[relative], hopescores[relative])
# right boundary should match sentence length (in chars)
assert self.j == flen and self.wj == fwlen, \
"@sentence %d, Boundary Mismatch at %s\t%s" % (opts.sentid, sid, fsent) + \
"self.j=%d, flen=%d; self.wj=%d, fwlen=%d" % (self.j, flen, self.wj, fwlen)
s += "%d\t%d\n" % nodememo[id(self)] + \
self._dump(rules, deriv=self.viterbi_deriv())
return s
