[Rspamd] Slight changes to neural plugin
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@ -1,28 +1,14 @@
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rules {
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"LONG" {
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train {
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max_trains = 800;
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max_usages = 40;
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max_iterations = 25;
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learning_rate = 0.01,
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spam_score = 9;
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ham_score = -4;
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}
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symbol_spam = "NEURAL_SPAM_LONG";
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symbol_ham = "NEURAL_HAM_LONG";
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ann_expire = 31d;
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}
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"SHORT" {
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train {
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max_trains = 90;
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max_usages = 20;
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max_iterations = 15;
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learning_rate = 0.01,
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spam_score = 9;
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ham_score = -4;
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}
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symbol_spam = "NEURAL_SPAM_SHORT";
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symbol_ham = "NEURAL_HAM_SHORT";
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ann_expire = 7d;
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}
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servers = "31.47.234.2:6379";
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train {
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max_train = 1k; # Number of trains per epoch
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max_usages = 50; # Number of learn iterations while ANN data is valid
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spam_score = 12; # Score to learn spam
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ham_score = -7; # Score to learn ham
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learning_rate = 0.01; # Rate of learning (Torch only)
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max_iterations = 25; # Maximum iterations of learning (Torch only)
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}
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ann_expire = 80d;
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timeout = 20; # Increase redis timeout
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enabled = ${HAS_TORCH}; # Explicitly disable module when torch is disabled
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use_settings = false; # If enabled, then settings-id is used to dispatch networks
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@ -1,18 +1,10 @@
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symbols = {
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"NEURAL_SPAM_LONG" {
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weight = 4.2; # sample weight
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description = "Neural network spam (long)";
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"NEURAL_SPAM" {
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weight = 4.0; # sample weight
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description = "Neural network spam";
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}
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"NEURAL_HAM_LONG" {
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"NEURAL_HAM" {
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weight = -4.0; # sample weight
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description = "Neural network ham (long)";
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}
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"NEURAL_SPAM_SHORT" {
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weight = 3.0; # sample weight
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description = "Neural network spam (short)";
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}
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"NEURAL_HAM_SHORT" {
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weight = -2.0; # sample weight
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description = "Neural network ham (short)";
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description = "Neural network ham";
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}
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}
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