path: root/views/debug.haml

- require 'zipf'
!!!
%html
  %head
    %title Debug view (Session ##{session_key})
  %link(rel="stylesheet" type="text/css" href="debug.css")
  %script{:src => "http://postedit.cl.uni-heidelberg.de/js/jquery.min.js"}
  %script{:src => "http://postedit.cl.uni-heidelberg.de/js/jquery.tablesorter.min.js"}
  %script{:src => "http://postedit.cl.uni-heidelberg.de/js/debug.js"}
  %body
    %h1 Debug view
    %div#floater
      - if pairwise_ranking_data["kbest"].empty?
        %p.red
          %strong No data to show!
      %ul
        %li
          %a{ :href => "#controls" } Controls
        %li
          %a{ :href => "#post_edit" } Post-edit
        %li
          %a{ :href => "#grammar" } Grammar
        %li
          %a{ :href => "#weights" } Weights
        %li
          %a{ :href => "#kbest" } K-best

      %p.tiny Session: ##{session_key}

    /=#########################################################################
    %h2#controls Controls
    %h3 Reset
    %p
      %strong [Server reply]
      %span#control_reply
    %ul
      %li
        %a.ajax{:tgt => "/reset_progress",       :href => "#controls"} Reset progress
      %li
        %a.ajax{:tgt => "/reset_weights",        :href => "#controls"} Reset weights
      %li
        %a.ajax{:tgt => "/reset_learning_rates", :href => "#controls"} Reset learning rates
      %li
        %a.ajax{:tgt => "/reset_extractor",       :href => "#controls"} Reset extractor
      %li
        %a.ajax{:tgt => "/reset_new_rules",       :href => "#controls"} Reset new rules
      %li
        %a.ajax{:tgt => "/shutdown",              :href => "#controls"} Initiate shutdown
    %h3 Learning rates & weights
    %p Set default weight or rate for specific features:
    %select#features_type
      %option{ :value => "/set_weights" } Weight
      %option{ :value => "/set_learning_rates" } Rate
    %input#features{ :value => "Feature", :style => "text-align:center; width:20em" }
    %input#features_value{ :value => "1e-05", :style => "text-align:right; width:5em" }
    %button#set_features
      Set
    %p Set rate for feature groups:
    %select#feature_groups
      %option{ :value => "R" } rule ids
      %option{ :value => "RB" } rule bigrams 
      %option{ :value => "Shape" } rule shapes
    %input#feature_groups_value{ :value => "1e-05", :style => "text-align:right; width:5em" }
    %button#set_feature_groups
      Set rate


    /=#########################################################################
    %h2#post_edit Post-edit


    %p#original_svg_b64 #{data["original_svg"][progress]}
    %p Before:
    %div#original_svg

    %p#svg_b64 #{data["svg"][progress]}
    %p After:
    %div#svg

    %table
      %tr
        %td.noborder
          %strong Progress:
        %td.left.noborder #{[0,progress].max}
      %tr
        %td.noborder
          %strong MT Input:
        %td.left.noborder #{data["source_segments"][[0,progress].max]}
      %tr
        %td.noborder
          %strong Raw source:
        %td.left.noborder #{data["raw_source_segments"][[0,progress].max]}
      %tr
        %td.noborder
          %strong Post-edit:
        %td.left.noborder #{data["post_edits_raw"][progress]}
      %tr
        %td.noborder
          %strong Post-edit (processed):
        %td.left.noborder #{data["post_edits"][progress]}
      %tr
        %td.noborder
          %strong Original MT:
        %td.left.noborder #{data["mt_raw"][progress]}
      %tr
        %td.noborder
          %strong Displayed MT:
        %td.left.noborder #{data["mt"][progress]}
      %tr
        %td.noborder
          %strong Best match (BLEU=#{(pairwise_ranking_data["best_match_score"]*100).round(2)}%):
        %td.left.noborder #{pairwise_ranking_data["best_match"]}

    %h3 Metadata
    %p <strong>K:</strong>                      #{pairwise_ranking_data["samples_size"]}
    %p <strong>Number of updates:</strong>      #{pairwise_ranking_data["num_up"]}
    %p <strong>Updated features:</strong>       #{pairwise_ranking_data["updated_features"]}
    %p <strong>Duration:</strong>               #{data["durations"][progress]}ms
    %p <strong>Updated:</strong>                #{data["updated"][progress]}

    %h3 Derivation
    %p
      %a{:onclick => "$('#derivation').toggle()"} Show/hide original raw derivation.
    %pre#derivation{:style => "display:none"} #{data["derivations"][progress]}

    %h3 Client reply
    %p
      %a{:onclick => "$('#client_reply').toggle()"} Show/hide raw JSON client reply.
    - if data["feedback"][progress]
      - client_reply = JSON.parse(data["feedback"][progress])
      - client_reply["svg"] = "omitted"
      - client_reply["original_svg"] = "omitted"
      %pre#client_reply{ :style => "display:none" } #{JSON.pretty_generate(client_reply)}

    %p.up
      %a{ :href => "#" } ^ up

    /=#########################################################################
    %h2#grammar Grammar

    %h3
      New Rules
    %p Including OOV fixes.
    %table.sortable
      %thead
        %th Source
        %th
        %th Target
      %tbody
        - additional_rules.each do |rule_string|
          - nt, src, tgt, f, a = splitpipe(rule_string)
          %tr
            %td #{src}
            %td.big &#8611;
            %td #{tgt}

    %h3
      Known rules
    %table.sortable
      %thead
        %th Source
        %th
        %th Target
      %tbody
        - rejected_rules.each do |rule_string|
          - nt, src, tgt, f, a = splitpipe(rule_string)
          %tr
            %td #{src}
            %td.big &#8611;
            %td #{tgt}

    %p.up
      %a{ :href => "#" } ^ up

    /=#########################################################################
    %h2#weights Weights

    %p N.B. that updates are only done if the post-edit is different from the original 1-best output of the decoder.

    %h3 Weight updates
    %table.sortable
      %thead
        %tr
          %th Feature
          %th Before
          %th After
          %th Diff.
          %th Raw diff.
          %th Rate
      %tbody
        - if pairwise_ranking_data["update_raw"]
          - raw_update = SparseVector.from_kv(pairwise_ranking_data["update_raw"])
          - pairwise_ranking_data["weights_before"].default = 0
          - pairwise_ranking_data["weights_after"].keys.each.sort { |a,b| a <=> b }.each do |k|
            - diff = pairwise_ranking_data["weights_after"][k] - pairwise_ranking_data["weights_before"][k]
            - if diff != 0.0
              %tr
                %td.left <strong> #{k} </strong>
                %td.right #{"%+.3f" % pairwise_ranking_data["weights_before"][k]}
                %td.right #{"%+.3f" % pairwise_ranking_data["weights_after"][k]}
                - rdiff = diff.round 3
                - if diff < 0
                  %td.right.red #{rdiff}
                - elsif diff > 0
                  %td.right.green #{rdiff}
                %td.right #{"%+.1f"%(raw_update[k])}
                %td.right
                  - if pairwise_ranking_data["learning_rates"].has_key? k
                    #{pairwise_ranking_data["learning_rates"][k].round 10}
                  - elsif k.start_with? "R:"
                    #{pairwise_ranking_data["learning_rate_R"].round 10}
                  - elsif k.start_with? "RBS:" or k.start_with? "RBT:"
                    #{pairwise_ranking_data["learning_rate_RB"].round 10}
                  - elsif k.start_with? "Shape_"
                    #{pairwise_ranking_data["learning_rate_Shape"].round 10}
                  - else
                    ERROR: unknown key #{k}

    %p
      %a{ :onclick => "$('#features').toggle()" } Explanations
    %table#features{ :style => "display:none" }
      %tr
        %td EgivenFCoherent
        %td.left -log10[ c(e, f) / sample c(f) ]
      %tr
        %td NewRule
        %td.left New rules extracted from post-edits (this is the only feature of those rules)
      %tr
        %td KnownRule
        %td.left Added to already existing rules if they could be also be extracted from post-edits
      %tr
        %td OOVFix
        %td.left Manually added rules for OOV items
      %tr
        %td Glue
        %td.left Absolute number of rules used from glue grammar
      %tr
        %td IsSingletonF/E
        %td.left true|false (1|0) (sum)
      %tr
        %td IsSingletonFE
        %td.left true|false (1|0) (sum)
      %tr
        %td LanguageModel
        %td.left -log10[ score ]
      %tr
        %td LanguageModel_OOV
        %td.left Absolute count of OOV unigrams
      %tr
        %td MaxLexFgivenE
        %td.left Sum_f -log10(maxScore) (maxScore = max_e(ttable(f))
      %tr
        %td MaxLexEgivenF
        %td.left Sum_e -log10(maxScore) (maxScore = max_f(ttable(e))
      %tr
        %td PassThrough
        %td.left Absolute count of applied PassThrough rules
      %tr
        %td SampleCountF
        %td.left log10 [ sample c(f) ]
      %tr
        %td WordPenalty
        %td.left log_10(e)*|e| = 1/log(10) * |e| (*-1) = -0.43429448190325176*|e|
      %tr
        %td SourceWordPenalty
        %td.left As WordPenalty (|e| <=> |f|)
      %tr
        %td R:*
        %td.left Rule indicator features (sum of rule applications)
      %tr
        %td Shape_*
        %td.left Indicator features for rule shapes (39 in total)
      %tr
        %td IsSupportedOnline
        %td.left Rules with support from local context (Denkowski)

    %p.up
      %a{ :href => "#" } ^ up

    /=#########################################################################
    %h2#kbest K-best list
    %p
      %span.red In red:
      %span Update needed, i.e. "any of the above hypotheses has a lower model score" (in default order).
    %table.sortable
      %thead
        %tr
          %th.center{:style => "width:5%"}  Rank
          %th.center{:style => "width:5%"}  BLEU score
          %th.center{:style => "width:5%"}  Model score
          %th.center{:style => "width:5%"}  Original rank
          %th.center{:style => "width:5%"}  Token count
          %th.center{:style => "width:75%"} Translation
      %tbody
        - kbest = []
        - pairwise_ranking_data["kbest"].each { |i| x=splitpipe(i); kbest << [ x[0].to_f, x[1].to_f, x[2].to_i, x[3], x[4] ] }
        - kbest.sort! { |i,j| j[0] <=> i[0] }
        - kbest.each_with_index do |k,j|
          - add_class = ""
          - if kbest[0,j].map { |l| l[0]>k[0] && l[1]<k[1] }.include? true
            - add_class = "red"
          %tr{:class => "#{add_class}"}
            %td.center #{j+1}
            %td.center #{"%.2f"%(k[0].to_f*100)}
            %td.center #{k[1]}
            %td.center #{k[2]+1}
            %td.center #{k[4].split.size}
            %td
              %p #{k[4]}
              %p.toggle
                %a.tiny Features
              %table.kbest_features.small.mono.black{:style => "display:none"}
                %tr
                  %th Feature
                  %th Value
                - k[3].split.sort.each do |i|
                  - k,_,v = i.rpartition "="
                  %tr
                    %td #{k}
                    %td #{v}

    %p.up
      %a{ :href => "#" } ^ up