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Massive savings. Thanks so much @ciscorn for providing the initial
code for choosing the dictionary.
This adds a bit of time to the build, both to find the dictionary
but also because (for reasons I don't fully understand), the binary
search in the compress() function no longer worked and had to be
replaced with a linear search.
I think this is because the intended invariant is that for codebook
entries that encode to the same number of bits, the entries are ordered
in ascending value. However, I mis-placed the transition from "words"
to "byte/char values" so the codebook entries for words are in word-order
rather than their code order.
Because this price is only paid at build time, I didn't care to determine
exactly where the correct fix was.
I also commented out a line to produce the "estimated total memory size"
-- at least on the unix build with TRANSLATION=ja, this led to a build
time KeyError trying to compute the codebook size for all the strings.
I think this occurs because some single unicode code point ('ァ') is
no longer present as itself in the compressed strings, due to always
being replaced by a word.
As promised, this seems to save hundreds of bytes in the German translation
on the trinket m0.
Testing performed:
- built trinket_m0 in several languages
- built and ran unix port in several languages (en, de_DE, ja) and ran
simple error-producing codes like ./micropython -c '1/0'
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Two problems: The lead byte for 3-byte sequences was wrong, and one
mid-byte was not even filled in due to a missing "++"!
Apparently this was broken ever since the first "Compress as unicode,
not bytes" commit, but I believed I'd "tested" it by running on the
Pinyin translation.
This rendered at least the Korean and Japanese translations completely
illegible, affecting 5.0 and all later releases.
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Now this gets filled in with values e.g., 128 (0x80) and 159 (0x9f).
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Compress common unicode bigrams by making code points in the range
0x80 - 0xbf (inclusive) represent them. Then, they can be greedily
encoded and the substituted code points handled by the existing Huffman
compression. Normally code points in the range 0x80-0xbf are not used
in Unicode, so we stake our own claim. Using the more arguably correct
"Private Use Area" (PUA) would mean that for scripts that only use
code points under 256 we would use more memory for the "values" table.
bigram means "two letters", and is also sometimes called a "digram".
It's nothing to do with "big RAM". For our purposes, a bigram represents
two successive unicode code points, so for instance in our build on
trinket m0 for english the most frequent are:
['t ', 'e ', 'in', 'd ', ...].
The bigrams are selected based on frequency in the corpus, but the
selection is not necessarily optimal, for these reasons I can think of:
* Suppose the corpus was just "tea" repeated 100 times. The
top bigrams would be "te", and "ea". However,
overlap, "te" could never be used. Thus, some bigrams might actually
waste space
* I _assume_ this has to be why e.g., bigram 0x86 "s " is more
frequent than bigram 0x85 " a" in English for Trinket M0, because
sequences like "can't add" would get the "t " digram and then
be unable to use the " a" digram.
* And generally, if a bigram is frequent then so are its constituents.
Say that "i" and "n" both encode to just 5 or 6 bits, then the huffman
code for "in" had better compress to 10 or fewer bits or it's a net
loss!
* I checked though! "i" is 5 bits, "n" is 6 bits (lucky guess)
but the bigram 0x83 also just 6 bits, so this one is a win of
5 bits for every "it" minus overhead. Yay, this round goes to team
compression.
* On the other hand, the least frequent bigram 0x9d " n" is 10 bits
long and its constituent code points are 4+6 bits so there's no
savings, but there is the cost of the table entry.
* and somehow 0x9f 'an' is never used at all!
With or without accounting for overlaps, there is some optimum number
of bigrams. Adding one more bigram uses at least 2 bytes (for the
entry in the bigram table; 4 bytes if code points >255 are in the
source text) and also needs a slot in the Huffman dictionary, so
adding bigrams beyond the optimim number makes compression worse again.
If it's an improvement, the fact that it's not guaranteed optimal
doesn't seem to matter too much. It just leaves a little more fruit
for the next sweep to pick up. Perhaps try adding the most frequent
bigram not yet present, until it doesn't improve compression overall.
Right now, de_DE is again the "fullest" build on trinket_m0. (It's
reclaimed that spot from the ja translation somehow) This change saves
104 bytes there, increasing free space about 6.8%. In the larger
(but not critically full) pyportal build it saves 324 bytes.
The specific number of bigrams used (32) was chosen as it is the max
number that fit within the 0x80..0xbf range. Larger tables would
require the use of 16 bit code points in the de_DE build, losing savings
overall.
(Side note: The most frequent letters in English have been said
to be: ETA OIN SHRDLU; but we have UAC EIL MOPRST in our corpus)
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Length was stored as a 16-bit number always. Most translations have
a max length far less. For example, US English translation lengths
always fit in just 8 bits. probably all languages fit in 9 bits.
This also has the side effect of reducing the alignment of
compressed_string_t from 2 bytes to 1.
testing performed: ran in german and english on pyruler, printed messages
looked right.
Firmware size, en_US
Before: 3044 bytes free in flash
After: 3408 bytes free in flash
Firmware size, de_DE (with #2967 merged to restore translations)
Before: 1236 bytes free in flash
After: 1600 bytes free in flash
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By treating each unicode code-point as a single entity for huffman
compression, the overall compression rate can be somewhat improved
without changing the algorithm. On the decompression side, when
compressed values above 127 are encountered, they need to be
converted from a 16-bit Unicode code point into a UTF-8 byte
sequence.
Doing this returns approximately 1.5kB of flash storage with the
zh_Latn_pinyin translation. (292 -> 1768 bytes remaining in my build
of trinket_m0)
Other "more ASCII" translations benefit less, and in fact
zh_Latn_pinyin is no longer the most constrained translation!
(de_DE 1156 -> 1384 bytes free in flash, I didn't check others
before pushing for CI)
English is slightly pessimized, 2840 -> 2788 bytes, probably mostly
because the "values" array was changed from uint8_t to uint16_t,
which is strictly not required for an all-ASCII translation. This
could probably be avoided in this case, but as English is not the
most constrained translation it doesn't really matter.
Testing performed: built for feather nRF52840 express and trinket m0
in English and zh_Latn_pinyin; ran and verified the localized
messages such as
Àn xià rènhé jiàn jìnrù REPL. Shǐyòng CTRL-D chóngxīn jiāzài.
and
Press any key to enter the REPL. Use CTRL-D to reload.
were properly displayed.
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This creates a common safe mode mechanic that ports can share.
As a result, the nRF52 now has safe mode support as well.
The common safe mode adds a 700ms delay at startup where a reset
during that window will cause a reset into safe mode. This window
is designated by a yellow status pixel and flashing the single led
three times.
A couple NeoPixel fixes are included for the nRF52 as well.
Fixes #1034. Fixes #990. Fixes #615.
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This saves code space in builds which use link-time optimization.
The optimization drops the untranslated strings and replaces them
with a compressed_string_t struct. It can then be decompressed to
a c string.
Builds without LTO work as well but include both untranslated
strings and compressed strings.
This work could be expanded to include QSTRs and loaded strings if
a compress method is added to C. Its tracked in #531.
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