Merge pull request #3398 from jepler/better-dictionary-compression
compression: Implement @ciscorn's dictionary approach
This commit is contained in:
Scott Shawcroft
GitHub
commit
750bc1e04a
@ -12,10 +12,14 @@ from __future__ import print_function
|
||||
import re
|
||||
import sys
|
||||
|
||||
from math import log
|
||||
import collections
|
||||
import gettext
|
||||
import os.path
|
||||
|
||||
sys.stdout.reconfigure(encoding='utf-8')
|
||||
sys.stderr.reconfigure(errors='backslashreplace')
|
||||
|
||||
py = os.path.dirname(sys.argv[0])
|
||||
top = os.path.dirname(py)
|
||||
|
||||
@ -100,77 +104,173 @@ def translate(translation_file, i18ns):
|
||||
translations.append((original, translation))
|
||||
return translations
|
||||
|
||||
def frequent_ngrams(corpus, sz, n):
|
||||
return collections.Counter(corpus[i:i+sz] for i in range(len(corpus)-sz)).most_common(n)
|
||||
class TextSplitter:
|
||||
def __init__(self, words):
|
||||
words.sort(key=lambda x: len(x), reverse=True)
|
||||
self.words = set(words)
|
||||
self.pat = re.compile("|".join(re.escape(w) for w in words) + "|.", flags=re.DOTALL)
|
||||
|
||||
def encode_ngrams(translation, ngrams):
|
||||
if len(ngrams) > 32:
|
||||
start = 0xe000
|
||||
def iter_words(self, text):
|
||||
s = []
|
||||
words = self.words
|
||||
for m in self.pat.finditer(text):
|
||||
t = m.group(0)
|
||||
if t in words:
|
||||
if s:
|
||||
yield (False, "".join(s))
|
||||
s = []
|
||||
yield (True, t)
|
||||
else:
|
||||
start = 0x80
|
||||
for i, g in enumerate(ngrams):
|
||||
translation = translation.replace(g, chr(start + i))
|
||||
return translation
|
||||
s.append(t)
|
||||
if s:
|
||||
yield (False, "".join(s))
|
||||
|
||||
def decode_ngrams(compressed, ngrams):
|
||||
if len(ngrams) > 32:
|
||||
start, end = 0xe000, 0xf8ff
|
||||
else:
|
||||
start, end = 0x80, 0x9f
|
||||
return "".join(ngrams[ord(c) - start] if (start <= ord(c) <= end) else c for c in compressed)
|
||||
def iter(self, text):
|
||||
for m in self.pat.finditer(text):
|
||||
yield m.group(0)
|
||||
|
||||
def iter_substrings(s, minlen, maxlen):
|
||||
len_s = len(s)
|
||||
maxlen = min(len_s, maxlen)
|
||||
for n in range(minlen, maxlen + 1):
|
||||
for begin in range(0, len_s - n + 1):
|
||||
yield s[begin : begin + n]
|
||||
|
||||
def compute_huffman_coding(translations, compression_filename):
|
||||
texts = [t[1] for t in translations]
|
||||
words = []
|
||||
|
||||
start_unused = 0x80
|
||||
end_unused = 0xff
|
||||
max_ord = 0
|
||||
for text in texts:
|
||||
for c in text:
|
||||
ord_c = ord(c)
|
||||
max_ord = max(ord_c, max_ord)
|
||||
if 0x80 <= ord_c < 0xff:
|
||||
end_unused = min(ord_c, end_unused)
|
||||
max_words = end_unused - 0x80
|
||||
|
||||
values_type = "uint16_t" if max_ord > 255 else "uint8_t"
|
||||
max_words_len = 160 if max_ord > 255 else 255
|
||||
|
||||
sum_len = 0
|
||||
while True:
|
||||
# Until the dictionary is filled to capacity, use a heuristic to find
|
||||
# the best "word" (2- to 9-gram) to add to it.
|
||||
#
|
||||
# The TextSplitter allows us to avoid considering parts of the text
|
||||
# that are already covered by a previously chosen word, for example
|
||||
# if "the" is in words then not only will "the" not be considered
|
||||
# again, neither will "there" or "wither", since they have "the"
|
||||
# as substrings.
|
||||
extractor = TextSplitter(words)
|
||||
counter = collections.Counter()
|
||||
for t in texts:
|
||||
for (found, word) in extractor.iter_words(t):
|
||||
if not found:
|
||||
for substr in iter_substrings(word, minlen=2, maxlen=9):
|
||||
counter[substr] += 1
|
||||
|
||||
# Score the candidates we found. This is an empirical formula only,
|
||||
# chosen for its effectiveness.
|
||||
scores = sorted(
|
||||
(
|
||||
(s, (len(s) - 1) ** log(max(occ - 2, 1)), occ)
|
||||
for (s, occ) in counter.items()
|
||||
),
|
||||
key=lambda x: x[1],
|
||||
reverse=True,
|
||||
)
|
||||
|
||||
# Do we have a "word" that occurred 5 times and got a score of at least
|
||||
# 5? Horray. Pick the one with the highest score.
|
||||
word = None
|
||||
for (s, score, occ) in scores:
|
||||
if occ < 5:
|
||||
continue
|
||||
if score < 5:
|
||||
break
|
||||
word = s
|
||||
break
|
||||
|
||||
# If we can successfully add it to the dictionary, do so. Otherwise,
|
||||
# we've filled the dictionary to capacity and are done.
|
||||
if not word:
|
||||
break
|
||||
if sum_len + len(word) - 2 > max_words_len:
|
||||
break
|
||||
if len(words) == max_words:
|
||||
break
|
||||
words.append(word)
|
||||
sum_len += len(word) - 2
|
||||
|
||||
extractor = TextSplitter(words)
|
||||
counter = collections.Counter()
|
||||
for t in texts:
|
||||
for atom in extractor.iter(t):
|
||||
counter[atom] += 1
|
||||
cb = huffman.codebook(counter.items())
|
||||
|
||||
word_start = start_unused
|
||||
word_end = word_start + len(words) - 1
|
||||
print("// # words", len(words))
|
||||
print("// words", words)
|
||||
|
||||
def compute_huffman_coding(translations, qstrs, compression_filename):
|
||||
all_strings = [x[1] for x in translations]
|
||||
all_strings_concat = "".join(all_strings)
|
||||
ngrams = [i[0] for i in frequent_ngrams(all_strings_concat, 2, 32)]
|
||||
all_strings_concat = encode_ngrams(all_strings_concat, ngrams)
|
||||
counts = collections.Counter(all_strings_concat)
|
||||
cb = huffman.codebook(counts.items())
|
||||
values = []
|
||||
length_count = {}
|
||||
renumbered = 0
|
||||
last_l = None
|
||||
last_length = None
|
||||
canonical = {}
|
||||
for ch, code in sorted(cb.items(), key=lambda x: (len(x[1]), x[0])):
|
||||
values.append(ch)
|
||||
l = len(code)
|
||||
if l not in length_count:
|
||||
length_count[l] = 0
|
||||
length_count[l] += 1
|
||||
if last_l:
|
||||
renumbered <<= (l - last_l)
|
||||
canonical[ch] = '{0:0{width}b}'.format(renumbered, width=l)
|
||||
s = C_ESCAPES.get(ch, ch)
|
||||
print("//", ord(ch), s, counts[ch], canonical[ch], renumbered)
|
||||
for atom, code in sorted(cb.items(), key=lambda x: (len(x[1]), x[0])):
|
||||
values.append(atom)
|
||||
length = len(code)
|
||||
if length not in length_count:
|
||||
length_count[length] = 0
|
||||
length_count[length] += 1
|
||||
if last_length:
|
||||
renumbered <<= (length - last_length)
|
||||
canonical[atom] = '{0:0{width}b}'.format(renumbered, width=length)
|
||||
# print(f"atom={repr(atom)} code={code}", file=sys.stderr)
|
||||
if len(atom) > 1:
|
||||
o = words.index(atom) + 0x80
|
||||
s = "".join(C_ESCAPES.get(ch1, ch1) for ch1 in atom)
|
||||
else:
|
||||
s = C_ESCAPES.get(atom, atom)
|
||||
o = ord(atom)
|
||||
print("//", o, s, counter[atom], canonical[atom], renumbered)
|
||||
renumbered += 1
|
||||
last_l = l
|
||||
last_length = length
|
||||
lengths = bytearray()
|
||||
print("// length count", length_count)
|
||||
print("// bigrams", ngrams)
|
||||
|
||||
for i in range(1, max(length_count) + 2):
|
||||
lengths.append(length_count.get(i, 0))
|
||||
print("// values", values, "lengths", len(lengths), lengths)
|
||||
ngramdata = [ord(ni) for i in ngrams for ni in i]
|
||||
print("// estimated total memory size", len(lengths) + 2*len(values) + 2 * len(ngramdata) + sum((len(cb[u]) + 7)//8 for u in all_strings_concat))
|
||||
|
||||
print("//", values, lengths)
|
||||
values_type = "uint16_t" if max(ord(u) for u in values) > 255 else "uint8_t"
|
||||
max_translation_encoded_length = max(len(translation.encode("utf-8")) for original,translation in translations)
|
||||
values = [(atom if len(atom) == 1 else chr(0x80 + words.index(atom))) for atom in values]
|
||||
print("//", values, lengths)
|
||||
max_translation_encoded_length = max(
|
||||
len(translation.encode("utf-8")) for (original, translation) in translations)
|
||||
|
||||
wends = list(len(w) - 2 for w in words)
|
||||
for i in range(1, len(wends)):
|
||||
wends[i] += wends[i - 1]
|
||||
|
||||
with open(compression_filename, "w") as f:
|
||||
f.write("const uint8_t lengths[] = {{ {} }};\n".format(", ".join(map(str, lengths))))
|
||||
f.write("const {} values[] = {{ {} }};\n".format(values_type, ", ".join(str(ord(u)) for u in values)))
|
||||
f.write("#define compress_max_length_bits ({})\n".format(max_translation_encoded_length.bit_length()))
|
||||
f.write("const {} bigrams[] = {{ {} }};\n".format(values_type, ", ".join(str(u) for u in ngramdata)))
|
||||
if len(ngrams) > 32:
|
||||
bigram_start = 0xe000
|
||||
else:
|
||||
bigram_start = 0x80
|
||||
bigram_end = bigram_start + len(ngrams) - 1 # End is inclusive
|
||||
f.write("#define bigram_start {}\n".format(bigram_start))
|
||||
f.write("#define bigram_end {}\n".format(bigram_end))
|
||||
return values, lengths, ngrams
|
||||
f.write("const {} words[] = {{ {} }};\n".format(values_type, ", ".join(str(ord(c)) for w in words for c in w)))
|
||||
f.write("const uint8_t wends[] = {{ {} }};\n".format(", ".join(str(p) for p in wends)))
|
||||
f.write("#define word_start {}\n".format(word_start))
|
||||
f.write("#define word_end {}\n".format(word_end))
|
||||
|
||||
return (values, lengths, words, canonical, extractor)
|
||||
|
||||
def decompress(encoding_table, encoded, encoded_length_bits):
|
||||
values, lengths, ngrams = encoding_table
|
||||
(values, lengths, words, _, _) = encoding_table
|
||||
dec = []
|
||||
this_byte = 0
|
||||
this_bit = 7
|
||||
@ -218,7 +318,8 @@ def decompress(encoding_table, encoded, encoded_length_bits):
|
||||
searched_length += lengths[bit_length]
|
||||
|
||||
v = values[searched_length + bits - max_code]
|
||||
v = decode_ngrams(v, ngrams)
|
||||
if v >= chr(0x80) and v < chr(0x80 + len(words)):
|
||||
v = words[ord(v) - 0x80]
|
||||
i += len(v.encode('utf-8'))
|
||||
dec.append(v)
|
||||
return ''.join(dec)
|
||||
@ -226,66 +327,32 @@ def decompress(encoding_table, encoded, encoded_length_bits):
|
||||
def compress(encoding_table, decompressed, encoded_length_bits, len_translation_encoded):
|
||||
if not isinstance(decompressed, str):
|
||||
raise TypeError()
|
||||
values, lengths, ngrams = encoding_table
|
||||
decompressed = encode_ngrams(decompressed, ngrams)
|
||||
(_, _, _, canonical, extractor) = encoding_table
|
||||
|
||||
enc = bytearray(len(decompressed) * 3)
|
||||
#print(decompressed)
|
||||
#print(lengths)
|
||||
current_bit = 7
|
||||
current_byte = 0
|
||||
|
||||
code = len_translation_encoded
|
||||
bits = encoded_length_bits + 1
|
||||
for i in range(bits - 1, 0, -1):
|
||||
if len_translation_encoded & (1 << (i - 1)):
|
||||
enc[current_byte] |= 1 << current_bit
|
||||
if current_bit == 0:
|
||||
current_bit = 7
|
||||
#print("packed {0:0{width}b}".format(enc[current_byte], width=8))
|
||||
current_byte += 1
|
||||
else:
|
||||
current_bit -= 1
|
||||
|
||||
for c in decompressed:
|
||||
#print()
|
||||
#print("char", c, values.index(c))
|
||||
start = 0
|
||||
end = lengths[0]
|
||||
bits = 1
|
||||
compressed = None
|
||||
code = 0
|
||||
while compressed is None:
|
||||
s = start
|
||||
e = end
|
||||
#print("{0:0{width}b}".format(code, width=bits))
|
||||
# Binary search!
|
||||
while e > s:
|
||||
midpoint = (s + e) // 2
|
||||
#print(s, e, midpoint)
|
||||
if values[midpoint] == c:
|
||||
compressed = code + (midpoint - start)
|
||||
#print("found {0:0{width}b}".format(compressed, width=bits))
|
||||
break
|
||||
elif c < values[midpoint]:
|
||||
e = midpoint
|
||||
else:
|
||||
s = midpoint + 1
|
||||
code += end - start
|
||||
code <<= 1
|
||||
start = end
|
||||
end += lengths[bits]
|
||||
bits += 1
|
||||
#print("next bit", bits)
|
||||
|
||||
for i in range(bits - 1, 0, -1):
|
||||
if compressed & (1 << (i - 1)):
|
||||
for atom in extractor.iter(decompressed):
|
||||
for b in canonical[atom]:
|
||||
if b == "1":
|
||||
enc[current_byte] |= 1 << current_bit
|
||||
if current_bit == 0:
|
||||
current_bit = 7
|
||||
#print("packed {0:0{width}b}".format(enc[current_byte], width=8))
|
||||
current_byte += 1
|
||||
else:
|
||||
current_bit -= 1
|
||||
|
||||
if current_bit != 7:
|
||||
current_byte += 1
|
||||
return enc[:current_byte]
|
||||
@ -452,7 +519,7 @@ if __name__ == "__main__":
|
||||
if args.translation:
|
||||
i18ns = sorted(i18ns)
|
||||
translations = translate(args.translation, i18ns)
|
||||
encoding_table = compute_huffman_coding(translations, qstrs, args.compression_filename)
|
||||
encoding_table = compute_huffman_coding(translations, args.compression_filename)
|
||||
print_qstr_data(encoding_table, qcfgs, qstrs, translations)
|
||||
else:
|
||||
print_qstr_enums(qstrs)
|
||||
|
||||
@ -47,13 +47,22 @@ STATIC int put_utf8(char *buf, int u) {
|
||||
if(u <= 0x7f) {
|
||||
*buf = u;
|
||||
return 1;
|
||||
} else if(bigram_start <= u && u <= bigram_end) {
|
||||
int n = (u - 0x80) * 2;
|
||||
// (note that at present, entries in the bigrams table are
|
||||
// guaranteed not to represent bigrams themselves, so this adds
|
||||
} else if(word_start <= u && u <= word_end) {
|
||||
uint n = (u - word_start);
|
||||
size_t pos = 0;
|
||||
if (n > 0) {
|
||||
pos = wends[n - 1] + (n * 2);
|
||||
}
|
||||
int ret = 0;
|
||||
// note that at present, entries in the words table are
|
||||
// guaranteed not to represent words themselves, so this adds
|
||||
// at most 1 level of recursive call
|
||||
int ret = put_utf8(buf, bigrams[n]);
|
||||
return ret + put_utf8(buf + ret, bigrams[n+1]);
|
||||
for(; pos < wends[n] + (n + 1) * 2; pos++) {
|
||||
int len = put_utf8(buf, words[pos]);
|
||||
buf += len;
|
||||
ret += len;
|
||||
}
|
||||
return ret;
|
||||
} else if(u <= 0x07ff) {
|
||||
*buf++ = 0b11000000 | (u >> 6);
|
||||
*buf = 0b10000000 | (u & 0b00111111);
|
||||
|
||||
@ -43,6 +43,19 @@
|
||||
// (building the huffman encoding on UTF-16 code points gave better
|
||||
// compression than building it on UTF-8 bytes)
|
||||
//
|
||||
// - code points starting at 128 (word_start) and potentially extending
|
||||
// to 255 (word_end) (but never interfering with the target
|
||||
// language's used code points) stand for dictionary entries in a
|
||||
// dictionary with size up to 256 code points. The dictionary entries
|
||||
// are computed with a heuristic based on frequent substrings of 2 to
|
||||
// 9 code points. These are called "words" but are not, grammatically
|
||||
// speaking, words. They're just spans of code points that frequently
|
||||
// occur together.
|
||||
//
|
||||
// - dictionary entries are non-overlapping, and the _ending_ index of each
|
||||
// entry is stored in an array. Since the index given is the ending
|
||||
// index, the array is called "wends".
|
||||
//
|
||||
// The "data" / "tail" construct is so that the struct's last member is a
|
||||
// "flexible array". However, the _only_ member is not permitted to be
|
||||
// a flexible member, so we have to declare the first byte as a separte
|
||||
|
||||
Loading…
Reference in New Issue
Block a user