From 8473f8ba4ee5f46f2f41f397e5be9d2c04e6e7d2 Mon Sep 17 00:00:00 2001
From: Patrick Simianer <p@simianer.de>
Date: Fri, 26 Jun 2015 15:21:55 +0200
Subject: debug view

---
 views/debug.haml | 50 +++++++++++++++++++++++++++++++++++++-------------
 1 file changed, 37 insertions(+), 13 deletions(-)

diff --git a/views/debug.haml b/views/debug.haml
index 8dcac13..fc5629b 100644
--- a/views/debug.haml
+++ b/views/debug.haml
@@ -5,7 +5,20 @@
     %title debug view (for session ##{session_key})
   %link(rel="stylesheet" type="text/css" href="debug.css")
   %body
-    %h1 debug view (for session ##{session_key})
+    %h1 debug view
+    %p (for session ##{session_key})
+    %p
+      %a{:href => "/reset", :target => "_blank"} reset progress,
+      %a{:href => "/reset_weights", :target => "_blank"} reset weights,
+      %a{:href => "/shutdown", :target => "_blank"} shutdown,
+      %span learning rate
+      %select
+        - [1000,100,10,1,0.1,0.01,0.001,0.0001,0.00001,0.000001].each do |i|
+          %option{:value => i, :onclick => "window.open(\"http://\"+window.location.host+\"/set_learning_rate/#{i}\");"} #{i}
+      %span , learning rate (sparse)
+      %select
+        - [1000,100,10,1,0.1,0.01,0.001,0.0001,0.00001,0.000001].each do |i|
+          %option{:value => i, :onclick => "window.open(\"http://\"+window.location.host+\"/set_sparse_learning_rate/#{i}\");"} #{i}
     %table
       %tr
         %td.noborder
@@ -28,6 +41,7 @@
     %p <strong>number of updates:</strong> #{data["num_up"]}
     %p <strong>updated features:</strong> #{data["updated_features"]}
     %p <strong>learning rate:</strong> #{data["learning_rate"]}
+    %p <strong>learning rate (sparse):</strong> #{data["learning_rate_sparse"]}
     %h2 k-best
     %p bleu | model score | original rank | \|e\| | translation \n features
     %p.red update needed
@@ -40,11 +54,11 @@
         -if b
           %li.red
             %strong #{"%.2f"%(k[0].to_f*100)} | #{k[1]} | #{k[2]} | #{k[4].split.size} |#{k[4]} <br/>
-            %pre #{k[3]}
+            %p{:style=>"font-size:80%"} #{k[3]}
         - else
           %li
             %strong #{"%.2f"%(k[0].to_f*100)} | #{k[1]} | #{k[2]} | #{k[4].split.size} | #{k[4]} <br/>
-            %pre #{k[3]}
+            %p{:style=>"font-size:80%"} #{k[3]}
         - if [9,89].include? j
           %hr
     %h2 weight updates
@@ -55,41 +69,48 @@
         %th after
         %th diff
         %th raw diff
+      - data["weights_before"].default = 0
       - data["weights_after"].keys.each.sort { |a,b| a[0] <=> b[0] }.each do |k|
         %tr
           %td.noborder <strong> #{k} </strong>
           %td #{"%+.3f"%data["weights_before"][k].round(4)}
           %td #{"%+.3f"%data["weights_after"][k].round(4)}
-          - diff = data["weights_before"][k].abs-data["weights_after"][k].abs
+          - diff = data["weights_after"][k]-data["weights_before"][k]
           - if diff < 0
             %td.red #{"%+.3f"%(diff).round(4)}
           - elsif diff > 0
             %td.green #{"%+.3f"%(diff).round(4)}
           - else
             %td #{"%+.3f"%(diff).round(4)}
-          %td #{"%+.1f"%((data["weights_before"][k].abs-data["weights_after"][k].abs)/data["learning_rate"]).round(2)}
+          - if !k.start_with? "R:"
+            %td #{"%+.1f"%((data["weights_after"][k]-data["weights_before"][k])/data["learning_rate"]).round(2)}
+          - else
+            %td #{"%+.1f"%((data["weights_after"][k]-data["weights_before"][k])/data["learning_rate_sparse"]).round(2)}
     %h3 dense features explained
     %table
       %tr
         %td.noborder EgivenFCoherent (TM)
         %td.left -log10[ c(e, f) / sample c(f) ]
       %tr
-        %td.noborder Glue (per edge/rule) (dyn)
-        %td.left absolute count of used rules from glue grammar
+        %td.noborder Glue
+        %td.left absolute number of rules used from glue grammar
       %tr
-        %td.noborder IsSingletonF/E (per edge/rule) (TM)
+        %td.noborder IsSingletonF/E (TM)
         %td.left true|false (1|0) (sum)
       %tr
-        %td.noborder IsSingletonFE (per edge/rule) (TM)
+        %td.noborder IsSingletonFE (TM)
         %td.left true|false (1|0) (sum)
       %tr
         %td.noborder LanguageModel
         %td.left -log?[ score ]
       %tr
-        %td.noborder MaxLexFgivenE
+        %td.noborder LanguageModel_OOV
+        %td.left abs. count of OOV unigrams
+      %tr
+        %td.noborder MaxLexFgivenE (TM)
         %td.left Sum_f -log10(maxScore) (maxScore = max_e(ttable(f))
       %tr
-        %td.noborder MaxLexEgivenF
+        %td.noborder MaxLexEgivenF (TM)
         %td.left Sum_e -log10(maxScore) (maxScore = max_f(ttable(e))
       %tr
         %td.noborder PassThrough
@@ -98,9 +119,12 @@
         %td.noborder SampleCountF
         %td.left log10 [ sample c(f) ]
       %tr
-        %td.noborder WordPenalty (per edge/rule) (dyn)
+        %td.noborder WordPenalty
         %td.left log_10(e)*|e| = 1/log(10) * |e| (*-1) = -0.43429448190325176*|e|
       %tr
-        %td.noborder SourceWordPenalty (per edge/rule) (dyn)
+        %td.noborder SourceWordPenalty (per edge/rule)
         %td.left ^^^ (|e| <=> |f|)
+      %tr
+        %td.noborder R:*
+        %td.left rule indicator features, sum over full derivation per rule
 
-- 
cgit v1.2.3