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Increase completion model token lookback to 100
In moving to a pointer mixture network from a traditional language model I had initially decreased model lookback to 50 tokens to facilitate faster model training iteration. Now that we've landed on a configuration that works well, increasing lookback to 100 tokens improves accuracy further. I also went ahead and followed a recommendation from Jacob to oversample Flutter sources since they're greatly underrrepresented in our training corpus compared to our users' code at prediction time. Change-Id: I885ddb606270394198f3aca2554e381f4465bdae Reviewed-on: https://dart-review.googlesource.com/c/sdk/+/124083 Reviewed-by: Brian Wilkerson <brianwilkerson@google.com> Commit-Queue: Ari Aye <ariaye@google.com>
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4 changed files with 5 additions and 5 deletions
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DEPS
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DEPS
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@ -427,7 +427,7 @@ deps = {
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"packages": [
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{
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"package": "dart/language_model",
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"version": "9fJQZ0TrnAGQKrEtuL3-AXbUfPzYxqpN_OBHr9P4hE4C",
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"version": "lIRt14qoA1Cocb8j3yw_Fx5cfYou2ddam6ArBm4AI6QC",
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}
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],
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"dep_type": "cipd",
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@ -14,7 +14,7 @@ import 'package:analysis_server/src/services/completion/dart/language_model.dart
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import 'package:analyzer/dart/analysis/features.dart';
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/// Number of lookback tokens.
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const int _LOOKBACK = 50;
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const int _LOOKBACK = 100;
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/// Minimum probability to prioritize model-only suggestion.
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const double _MODEL_RELEVANCE_CUTOFF = 0.5;
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@ -20,7 +20,7 @@ void main() {
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final tokens =
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tokenize('if (list == null) { return; } for (final i = 0; i < list.');
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final response = await ranking.makeRequest('predict', tokens);
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expect(response['data']['length'], greaterThan(0.85));
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expect(response['data']['length'], greaterThan(0.9));
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});
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}
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@ -11,7 +11,7 @@ import 'package:test/test.dart';
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final directory = path.join(File.fromUri(Platform.script).parent.path, '..',
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'..', '..', '..', 'language_model', 'lexeme');
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const expectedLookback = 50;
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const expectedLookback = 100;
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void main() {
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if (sizeOf<IntPtr>() == 4) {
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@ -46,7 +46,7 @@ void main() {
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final suggestions = model.predictWithScores(tokens);
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final best = suggestions.entries.first;
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expect(best.key, 'length');
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expect(best.value, greaterThan(0.85));
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expect(best.value, greaterThan(0.9));
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});
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test('predict when no previous tokens', () {
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