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author | Vsevolod Stakhov <vsevolod@highsecure.ru> | 2020-08-28 17:40:02 +0100 |
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committer | Vsevolod Stakhov <vsevolod@highsecure.ru> | 2020-08-28 17:40:02 +0100 |
commit | f3d8644e634acd8aee912a7871b30d7836709243 (patch) | |
tree | 1d42392ef71562e082a96e6c572463fccf13b5bd /src | |
parent | 545deadb7e1f392478e1537aee5d3b1c39b358f9 (diff) | |
download | rspamd-f3d8644e634acd8aee912a7871b30d7836709243.tar.gz rspamd-f3d8644e634acd8aee912a7871b30d7836709243.zip |
[Project] Neural: Further PCA fixes
Diffstat (limited to 'src')
-rw-r--r-- | src/plugins/lua/neural.lua | 20 |
1 files changed, 14 insertions, 6 deletions
diff --git a/src/plugins/lua/neural.lua b/src/plugins/lua/neural.lua index 225c9895b..d7410b225 100644 --- a/src/plugins/lua/neural.lua +++ b/src/plugins/lua/neural.lua @@ -114,7 +114,10 @@ end local redis_lua_script_vectors_len = [[ local prefix = KEYS[1] local locked = redis.call('HGET', prefix, 'lock') - if locked then return false end + if locked then + local host = redis.call('HGET', prefix, 'hostname') + return string.format('%s:%s', hostname, locked) + end local nspam = 0 local nham = 0 @@ -547,10 +550,10 @@ local function ann_push_task_result(rule, task, verdict, score, set) if err then rspamd_logger.errx(task, 'cannot check if we can train %s:%s : %s', rule.prefix, set.name, err) - elseif type(data) == 'userdata' then + elseif type(data) == 'string' then -- nil return value - rspamd_logger.infox(task, "cannot learn %s ANN %s:%s; redis_key: %s: locked for learning", - learn_type, rule.prefix, set.name, set.ann.redis_key) + rspamd_logger.infox(task, "cannot learn %s ANN %s:%s; redis_key: %s: locked for learning: %s", + learn_type, rule.prefix, set.name, set.ann.redis_key, data) else rspamd_logger.errx(task, 'cannot check if we can train %s:%s : type of Redis key %s is %s, expected table' .. 'please remove this key from Redis manually if you perform upgrade from the previous version', @@ -647,6 +650,7 @@ local function fill_scatter(inputs) inputs = rspamd_tensor.fromtable(inputs):transpose() local meanv = inputs:mean() + lua_util.debugm(N, 'means: %s', meanv) for i=1,nsamples do local col = rspamd_tensor.new(1, #inputs) @@ -662,6 +666,8 @@ local function fill_scatter(inputs) end end + lua_util.debugm(N, 'scatter matrix: %s', scatter_matrix) + return scatter_matrix end @@ -1004,7 +1010,7 @@ local function do_train_ann(worker, ev_base, rule, set, ann_key) { ann_key, tostring(os.time()), - tostring(rule.watch_interval * 2), + tostring(math.max(10.0, rule.watch_interval * 2)), rspamd_util.get_hostname() }) end @@ -1062,7 +1068,7 @@ local function load_new_ann(rule, ev_base, set, profile, min_diff) {set.prefix, tostring(rspamd_util.get_time()), profile_serialized} ) rspamd_logger.infox(rspamd_config, 'loaded ANN for %s:%s from %s; %s bytes compressed; version=%s', - rule.prefix, set.name, ann_key, #ann_data, profile.version) + rule.prefix, set.name, ann_key, #data[1], profile.version) else rspamd_logger.errx(rspamd_config, 'cannot unpack/deserialise ANN for %s:%s from Redis key %s', rule.prefix, set.name, ann_key) @@ -1079,6 +1085,8 @@ local function load_new_ann(rule, ev_base, set, profile, min_diff) if rule.max_inputs then -- We can use PCA set.ann.pca = rspamd_tensor.load(pca_data) + rspamd_logger.infox(rspamd_config, 'loaded PCA for ANN for %s:%s from %s; %s bytes compressed; version=%s', + rule.prefix, set.name, ann_key, #data[2], profile.version) else -- no need in pca, why is it there? rspamd_logger.warnx(rspamd_config, 'extra PCA for ANN for %s:%s from Redis key %s: no max inputs defined', |