Examples: query, "exact match", wildcard*, wild?ard, wild*rd
Fuzzy search: cake~ (finds cakes, bake)
Term boost: "red velvet"^4, chocolate^2
Field grouping: tags:(+work -"fun-stuff")
Escaping: Escape characters +-&|!(){}[]^"~*?:\ with \, e.g. \+
Range search: properties.timestamp:[1587729413488 TO *] (inclusive), properties.title:{A TO Z}(excluding A and Z)
Combinations: chocolate AND vanilla, chocolate OR vanilla, (chocolate OR vanilla) NOT "vanilla pudding"
Field search: properties.title:"The Title" AND text
Unanswered
Hi Guys! Love Using Trains And Love The Great Support In This Channel. Say I Have Two Different Training Experiments Which Report Every 20 Iteration, But The Batch Size Between Them Is Different, Resulting In Different Number Of Iterations Per Epoch. I Wo


So obviously the straight forward solution is to report normalize the step value when reporting to TB, i.e. int(step/batch_size). Which makes sense as I suppose the batch size is known and is part of the hyper-parameters. Normalization itself can be done when comparing experiments in the UI, and in the backend can do that, if given the correct normalization parameter. I think this feature request should actually be posted on GitHub, as it is not as simple as one might think (the UI needs to allow you to select parameter for comparison, then the question is do we normalize all the scalars or just a few etc.)
Anyhow if we have enough people interested we can definitely add it :)

  
  
Posted 4 years ago
158 Views
0 Answers
4 years ago
one year ago