commit 85b2e14: [Minor] Neural: Various fixes in neural module
Vsevolod Stakhov
vsevolod at highsecure.ru
Tue Feb 25 15:35:13 UTC 2020
Author: Vsevolod Stakhov
Date: 2020-02-25 15:28:37 +0000
URL: https://github.com/rspamd/rspamd/commit/85b2e14d5c882a66249faaaca3d90a2f998e8f57
[Minor] Neural: Various fixes in neural module
---
src/plugins/lua/neural.lua | 49 +++++++++++++++++++++++++++++++---------------
1 file changed, 33 insertions(+), 16 deletions(-)
diff --git a/src/plugins/lua/neural.lua b/src/plugins/lua/neural.lua
index cd870534f..e7f126398 100644
--- a/src/plugins/lua/neural.lua
+++ b/src/plugins/lua/neural.lua
@@ -200,6 +200,7 @@ local redis_maybe_lock_id = nil
-- key4 - profile as JSON
-- key5 - expire in seconds
-- key6 - current time
+-- key7 - old key
local redis_lua_script_save_unlock = [[
local now = tonumber(KEYS[6])
redis.call('ZADD', KEYS[2], now, KEYS[4])
@@ -207,6 +208,7 @@ local redis_lua_script_save_unlock = [[
redis.call('DEL', KEYS[1] .. '_spam')
redis.call('DEL', KEYS[1] .. '_ham')
redis.call('HDEL', KEYS[1], 'lock')
+ redis.call('HDEL', KEYS[7], 'lock')
redis.call('EXPIRE', KEYS[1], tonumber(KEYS[5]))
return 1
]]
@@ -470,8 +472,8 @@ local function ann_push_task_result(rule, task, verdict, score, set)
)
else
-- Negative result returned
- rspamd_logger.infox(task, "cannot learn %s ANN %s:%s: %s (%s vectors stored)",
- learn_type, rule.prefix, set.name, reason, -tonumber(nsamples))
+ rspamd_logger.infox(task, "cannot learn %s ANN %s:%s; redis_key: %s: %s (%s vectors stored)",
+ learn_type, rule.prefix, set.name, set.ann.redis_key, reason, -tonumber(nsamples))
end
else
if err then
@@ -485,22 +487,34 @@ local function ann_push_task_result(rule, task, verdict, score, set)
end
end
- if not set.ann then
- -- Need to create or load a profile corresponding to the current configuration
- set.ann = new_ann_profile(task, rule, set, 0)
- end
-- Check if we can learn
- lua_redis.exec_redis_script(redis_can_store_train_vec_id,
- {task = task, is_write = true},
- can_train_cb,
- {
- set.ann.redis_key,
- learn_type,
- tostring(train_opts.max_trains),
- tostring(math.random()),
- })
+ if set.can_store_vectors then
+ if not set.ann then
+ -- Need to create or load a profile corresponding to the current configuration
+ set.ann = new_ann_profile(task, rule, set, 0)
+ lua_util.debugm(N, task,
+ 'requested new profile for %s, set.ann is missing',
+ set.name)
+ end
+
+ lua_redis.exec_redis_script(redis_can_store_train_vec_id,
+ {task = task, is_write = true},
+ can_train_cb,
+ {
+ set.ann.redis_key,
+ learn_type,
+ tostring(train_opts.max_trains),
+ tostring(math.random()),
+ })
+ else
+ lua_util.debugm(N, task,
+ 'do not push data to key %s: train condition not satisfied; reason: not checked existing ANNs',
+ set.ann.redis_key)
+ end
else
- lua_util.debugm(N, task, 'do not push data: train condition not satisfied; reason: %s',
+ lua_util.debugm(N, task,
+ 'do not push data to key %s: train condition not satisfied; reason: %s',
+ set.ann.redis_key,
skip_reason)
end
end
@@ -719,6 +733,7 @@ local function spawn_train(worker, ev_base, rule, set, ann_key, ham_vec, spam_ve
profile_serialized,
tostring(rule.ann_expire),
tostring(os.time()),
+ ann_key, -- old key to unlock...
})
end
end
@@ -1108,10 +1123,12 @@ local function check_anns(worker, cfg, ev_base, rule, process_callback, what)
if err then
rspamd_logger.errx(cfg, 'cannot get ANNs list from redis: %s',
err)
+ set.can_store_vectors = true
elseif type(data) == 'table' then
lua_util.debugm(N, cfg, '%s: process element %s:%s',
what, rule.prefix, set.name)
process_callback(worker, ev_base, rule, set, fun.map(load_ann_profile, data))
+ set.can_store_vectors = true
end
end
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