[Project] Rework rescore tool to the new architecture

3 files changed, 162 insertions, 34 deletions

diff --git a/lualib/rspamadm/corpus_test.lua b/lualib/rspamadm/corpus_test.lua
index 60aa2d7a9..07051a196 100644
--- a/lualib/rspamadm/corpus_test.lua
+++ b/lualib/rspamadm/corpus_test.lua
@@ -17,6 +17,7 @@ parser:option "-S --spam"
 parser:option "-n --conns"
       :description("Number of parallel connections")
       :argname("<N>")
+      :convert(tonumber)
       :default(10)
 parser:option "-o --output"
       :description("Output file")
@@ -25,6 +26,7 @@ parser:option "-o --output"
 parser:option "-t --timeout"
       :description("Timeout for client connections")
       :argname("<sec>")
+      :convert(tonumber)
       :default(60)
 parser:option "-c --connect"
       :description("Connect to specific host")
diff --git a/lualib/rspamadm/grep.lua b/lualib/rspamadm/grep.lua
index 0af83c1cf..b149a0337 100644
--- a/lualib/rspamadm/grep.lua
+++ b/lualib/rspamadm/grep.lua
@@ -38,7 +38,6 @@ parser:argument "input":args "*"
       :default("stdin")
 parser:flag "-S --sensitive"
       :description('Enable case-sensitivity in string search')
-      :default("false")
 parser:flag "-o --orphans"
       :description('Print orphaned logs')
 parser:flag "-P --partial"
diff --git a/lualib/rspamadm/rescore.lua b/lualib/rspamadm/rescore.lua
index e6df3b364..80b9630f4 100644
--- a/lualib/rspamadm/rescore.lua
+++ b/lualib/rspamadm/rescore.lua
@@ -1,12 +1,31 @@
+--[[
+Copyright (c) 2018, Vsevolod Stakhov <vsevolod@highsecure.ru>
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+]]--
+
+if not rspamd_config:has_torch() then
+  return
+end
+
 local torch = require "torch"
 local nn = require "nn"
 local lua_util = require "lua_util"
 local ucl = require "ucl"
 local logger = require "rspamd_logger"
-local getopt = require "getopt"
 local optim = require "optim"
 local rspamd_util = require "rspamd_util"
-
+local argparse = require "argparse"
 local rescore_utility = require "rescore_utility"
 
 local opts
@@ -15,6 +34,104 @@ local ignore_symbols = {
   ['DATE_IN_FUTURE'] = true,
 }
 
+local parser = argparse()
+    :name "rspamadm rescore"
+    :description "Estimate optimal symbol weights from log files"
+    :help_description_margin(37)
+
+parser:option "-l --log"
+      :description "Log file or files (from rescore)"
+      :argname("<log>")
+      :args "*"
+parser:option "-c --config"
+      :description "Path to config file"
+      :argname("<file>")
+      :default(rspamd_paths["CONFDIR"] .. "/" .. "rspamd.conf")
+parser:option "-o --output"
+      :description "Output file"
+      :argname("<file>")
+      :default("new.scores")
+parser:flag "-d --diff"
+      :description "Show differences in scores"
+parser:flag "-v --verbose"
+      :description "Verbose output"
+parser:flag "-z --freq"
+      :description "Display hit frequencies"
+parser:option "-i --iters"
+      :description "Learn iterations"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(10)
+parser:option "-b --batch"
+      :description "Batch size"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(100)
+parser:option "-d --decay"
+      :description "Decay rate"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(0.001)
+parser:option "-m --momentum"
+      :description "Learn momentum"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(0.1)
+parser:option "-t --threads"
+      :description "Number of threads to use"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(1)
+parser:option "-o --optim"
+      :description "Optimisation algorithm"
+      :argname("<alg>")
+      :convert {
+        LBFGS = "LBFGS",
+        ADAM = "ADAM",
+        ADAGRAD = "ADAGRAD",
+        SGD = "SGD",
+        NAG = "NAG"
+      }
+      :default "ADAM"
+parser:option "--ignore-symbol"
+      :description "Ignore symbol from logs"
+      :argname("<sym>")
+      :args "*"
+parser:option "--penalty-weight"
+      :description "Add new penalty weight to test"
+      :argname("<n>")
+      :convert(tonumber)
+      :args "*"
+parser:option "--learning-rate"
+      :description "Add new learning rate to test"
+      :argname("<n>")
+      :convert(tonumber)
+      :args "*"
+parser:option "--spam_action"
+      :description "Spam action"
+      :argname("<act>")
+      :default("reject")
+parser:option "--learning_rate_decay"
+      :description "Learn rate decay (for some algs)"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(0.0)
+parser:option "--weight_decay"
+      :description "Weight decay (for some algs)"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(0.0)
+parser:option "--l1"
+      :description "L1 regularization penalty"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(0.0)
+parser:option "--l2"
+      :description "L2 regularization penalty"
+      :argname("<n>")
+      :convert(tonumber)
+      :default(0.0)
+
 local function make_dataset_from_logs(logs, all_symbols, spam_score)
   -- Returns a list of {input, output} for torch SGD train
 
@@ -182,7 +299,8 @@ local function calculate_fscore_from_weights(logs, all_symbols, weights, thresho
 
   logs = update_logs(logs, new_symbol_scores)
 
-  local file_stats, _, all_fps, all_fns = rescore_utility.generate_statistics_from_logs(logs, threshold)
+  local file_stats, _, all_fps, all_fns =
+      rescore_utility.generate_statistics_from_logs(logs, threshold)
 
   return file_stats.fscore, all_fps, all_fns
 end
@@ -226,7 +344,7 @@ local function train(dataset, opt, model, criterion, epoch,
   local lbfgsState
   local sgdState
 
-  local batch_size = opt.batch_size
+  local batch_size = opt.batch
 
   logger.messagex("trainer epoch #%s, %s batch", epoch, batch_size)
 
@@ -300,7 +418,7 @@ local function train(dataset, opt, model, criterion, epoch,
     end
 
     -- optimize on current mini-batch
-    if opt.optimization == 'LBFGS' then
+    if opt.optim == 'LBFGS' then
 
       -- Perform LBFGS step:
       lbfgsState = lbfgsState or {
@@ -315,7 +433,7 @@ local function train(dataset, opt, model, criterion, epoch,
       logger.messagex(' - nb of iterations: ' .. lbfgsState.nIter)
       logger.messagex(' - nb of function evalutions: ' .. lbfgsState.funcEval)
 
-    elseif opt.optimization == 'ADAM' then
+    elseif opt.optim == 'ADAM' then
       sgdState = sgdState or {
         learningRate = tonumber(opts.learning_rate),-- opt.learningRate,
         momentum = tonumber(opts.momentum), -- opt.momentum,
@@ -323,7 +441,7 @@ local function train(dataset, opt, model, criterion, epoch,
         weightDecay = tonumber(opts.weight_decay),
       }
       optim.adam(feval, parameters, sgdState)
-    elseif opt.optimization == 'ADAGRAD' then
+    elseif opt.optim == 'ADAGRAD' then
       sgdState = sgdState or {
         learningRate = tonumber(opts.learning_rate),-- opt.learningRate,
         momentum = tonumber(opts.momentum), -- opt.momentum,
@@ -331,7 +449,7 @@ local function train(dataset, opt, model, criterion, epoch,
         weightDecay = tonumber(opts.weight_decay),
       }
       optim.adagrad(feval, parameters, sgdState)
-    elseif opt.optimization == 'SGD' then
+    elseif opt.optim == 'SGD' then
       sgdState = sgdState or {
         learningRate = tonumber(opts.learning_rate),-- opt.learningRate,
         momentum = tonumber(opts.momentum), -- opt.momentum,
@@ -339,7 +457,7 @@ local function train(dataset, opt, model, criterion, epoch,
         weightDecay = tonumber(opts.weight_decay),
       }
       optim.sgd(feval, parameters, sgdState)
-    elseif opt.optimization == 'NAG' then
+    elseif opt.optim == 'NAG' then
       sgdState = sgdState or {
         learningRate = tonumber(opts.learning_rate),-- opt.learningRate,
         momentum = tonumber(opts.momentum), -- opt.momentum,
@@ -348,7 +466,8 @@ local function train(dataset, opt, model, criterion, epoch,
       }
       optim.nag(feval, parameters, sgdState)
     else
-      error('unknown optimization method')
+      logger.errx('unknown optimization method: %s', opt.optim)
+      os.exit(1)
     end
   end
 
@@ -363,19 +482,6 @@ local function train(dataset, opt, model, criterion, epoch,
   confusion:zero()
 end
 
-
-local default_opts = {
-  verbose = true,
-  iters = 10,
-  threads = 1,
-  batch_size = 1000,
-  optimization = 'ADAM',
-  learning_rate_decay = 0.001,
-  momentum = 0.1,
-  l1 = 0.0,
-  l2 = 0.0,
-}
-
 local learning_rates = {
   0.01
 }
@@ -393,11 +499,27 @@ local function get_threshold()
       or actions['reject']), actions['reject']
 end
 
-return function (args, cfg)
-  opts = default_opts
-  opts = lua_util.override_defaults(opts, getopt.getopt(args, 'i:'))
+local function handler(args)
+  opts = parser:parse(args)
+  if not opts['log'] then
+    parser:error('no log specified')
+  end
+
+  local _r,err = rspamd_config:load_ucl(opts['config'])
+
+  if not _r then
+    logger.errx('cannot parse %s: %s', opts['config'], err)
+    os.exit(1)
+  end
+
+  _r,err = rspamd_config:parse_rcl({'logging', 'worker'})
+  if not _r then
+    logger.errx('cannot process %s: %s', opts['config'], err)
+    os.exit(1)
+  end
+
   local threshold,reject_score = get_threshold()
-  local logs = rescore_utility.get_all_logs(cfg["logdir"])
+  local logs = rescore_utility.get_all_logs(opts['log'])
 
   if opts['ignore-symbol'] then
     local function add_ignore(s)
@@ -446,14 +568,12 @@ return function (args, cfg)
     end
   end
 
-  if opts['i'] then opts['iters'] = opts['i'] end
-
   local all_symbols = rescore_utility.get_all_symbols(logs, ignore_symbols)
   local original_symbol_scores = rescore_utility.get_all_symbol_scores(rspamd_config,
       ignore_symbols)
 
   -- Display hit frequencies
-  if opts['z'] then
+  if opts['freq'] then
       local _, all_symbols_stats = rescore_utility.generate_statistics_from_logs(logs, threshold)
       local t = {}
       for _, symbol_stats in pairs(all_symbols_stats) do table.insert(t, symbol_stats) end
@@ -580,11 +700,11 @@ return function (args, cfg)
 
   new_symbol_scores = stitch_new_scores(all_symbols, new_symbol_scores)
 
-  if cfg["output"] then
-    write_scores(new_symbol_scores, cfg["output"])
+  if opts["output"] then
+    write_scores(new_symbol_scores, opts["output"])
   end
 
-  if cfg["diff"] then
+  if opts["diff"] then
     print_score_diff(new_symbol_scores, original_symbol_scores)
   end
 
@@ -616,3 +736,10 @@ return function (args, cfg)
       end
   end
 end
+
+
+return {
+  handler = handler,
+  description = parser._description,
+  name = 'rescore'
+}
\ No newline at end of file