Remove unnecessary epsilon fallback

allora-network · Aug 23, 2024 · 6564a7c · 6564a7c
1 parent 2fcf815
commit 6564a7c
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Showing 3 changed files with 13 additions and 21 deletions.
diff --git a/x/emissions/keeper/actor_utils/losses.go b/x/emissions/keeper/actor_utils/losses.go
@@ -149,7 +149,7 @@ func CloseReputerNonce(
 		return err
 	}
 
-	networkLossBundle, err := synth.CalcNetworkLosses(stakesByReputer, bundles, topic.Epsilon)
+	networkLossBundle, err := synth.CalcNetworkLosses(stakesByReputer, bundles)
 	if err != nil {
 		return err
 	}

diff --git a/x/emissions/keeper/inference_synthesis/network_losses.go b/x/emissions/keeper/inference_synthesis/network_losses.go
@@ -39,15 +39,14 @@ func RunningWeightedAvgUpdate(
 func convertMapOfRunningWeightedLossesToWorkerAttributedValue[T emissions.WorkerAttributedValue | emissions.WithheldWorkerAttributedValue](
 	runningWeightedLosses map[Worker]*RunningWeightedLoss,
 	sortedWorkers []Worker,
-	epsilon alloraMath.Dec,
 ) []*T {
 	weightedLosses := make([]*T, 0)
 	for _, worker := range sortedWorkers {
 		runningLoss, ok := runningWeightedLosses[worker]
 		if !ok {
 			continue
 		}
-		normalizedWeightedLoss, err := normalizeWeightedLoss(runningLoss, epsilon)
+		normalizedWeightedLoss, err := normalizeWeightedLoss(runningLoss)
 		if err != nil {
 			continue
 		}
@@ -63,7 +62,6 @@ func convertMapOfRunningWeightedLossesToWorkerAttributedValue[T emissions.Worker
 func CalcNetworkLosses(
 	stakesByReputer map[Worker]Stake,
 	reputerReportedLosses emissions.ReputerValueBundles,
-	epsilon alloraMath.Dec,
 ) (emissions.ValueBundle, error) {
 	// Make map from inferer to their running weighted-average loss
 	runningWeightedCombinedLoss := RunningWeightedLoss{alloraMath.ZeroDec(), alloraMath.ZeroDec()}
@@ -202,30 +200,30 @@ func CalcNetworkLosses(
 	sortedForecasters := alloraMath.GetSortedKeys(runningWeightedForecasterLosses)
 
 	// Normalize the combined loss
-	combinedValue, err := normalizeWeightedLoss(&runningWeightedCombinedLoss, epsilon)
+	combinedValue, err := normalizeWeightedLoss(&runningWeightedCombinedLoss)
 	if err != nil {
 		return emissions.ValueBundle{}, errorsmod.Wrapf(err, "Error normalizing combined loss")
 	}
 
 	// Normalize the naive loss
-	naiveValue, err := normalizeWeightedLoss(&runningWeightedNaiveLoss, epsilon)
+	naiveValue, err := normalizeWeightedLoss(&runningWeightedNaiveLoss)
 	if err != nil {
 		return emissions.ValueBundle{}, errorsmod.Wrapf(err, "Error normalizing naive loss")
 	}
 
 	// Convert the running weighted averages to WorkerAttributedValue/WithheldWorkerAttributedValue for inferers and forecasters
-	infererLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WorkerAttributedValue](runningWeightedInfererLosses, sortedInferers, epsilon)
-	forecasterLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WorkerAttributedValue](runningWeightedForecasterLosses, sortedForecasters, epsilon)
-	oneOutInfererLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WithheldWorkerAttributedValue](runningWeightedOneOutInfererLosses, sortedInferers, epsilon)
-	oneOutForecasterLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WithheldWorkerAttributedValue](runningWeightedOneOutForecasterLosses, sortedForecasters, epsilon)
-	oneInForecasterLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WorkerAttributedValue](runningWeightedOneInForecasterLosses, sortedForecasters, epsilon)
+	infererLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WorkerAttributedValue](runningWeightedInfererLosses, sortedInferers)
+	forecasterLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WorkerAttributedValue](runningWeightedForecasterLosses, sortedForecasters)
+	oneOutInfererLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WithheldWorkerAttributedValue](runningWeightedOneOutInfererLosses, sortedInferers)
+	oneOutForecasterLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WithheldWorkerAttributedValue](runningWeightedOneOutForecasterLosses, sortedForecasters)
+	oneInForecasterLosses := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WorkerAttributedValue](runningWeightedOneInForecasterLosses, sortedForecasters)
 	oneOutInfererForecasterLosses := make([]*emissions.OneOutInfererForecasterValues, 0)
 	for _, forecaster := range sortedForecasters {
 		innerMap, ok := runningWeightedOneOutInfererForecasterLosses[forecaster]
 		if !ok {
 			continue
 		}
-		oneOutInfererValues := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WithheldWorkerAttributedValue](innerMap, sortedInferers, epsilon)
+		oneOutInfererValues := convertMapOfRunningWeightedLossesToWorkerAttributedValue[emissions.WithheldWorkerAttributedValue](innerMap, sortedInferers)
 		oneOutInfererForecasterLosses = append(oneOutInfererForecasterLosses, &emissions.OneOutInfererForecasterValues{
 			Forecaster:          forecaster,
 			OneOutInfererValues: oneOutInfererValues,
@@ -248,7 +246,6 @@ func CalcNetworkLosses(
 
 func normalizeWeightedLoss(
 	runningWeightedLossData *RunningWeightedLoss,
-	epsilon alloraMath.Dec,
 ) (alloraMath.Dec, error) {
 	if runningWeightedLossData.SumWeight.IsZero() {
 		return alloraMath.Dec{}, errorsmod.Wrapf(emissions.ErrFractionDivideByZero, "Sum weight for combined naive loss is 0")
@@ -259,9 +256,5 @@ func normalizeWeightedLoss(
 		return alloraMath.Dec{}, err
 	}
 
-	if normalizedWeightedLoss.IsZero() {
-		normalizedWeightedLoss = epsilon
-	}
-
 	return normalizedWeightedLoss, nil
 }
diff --git a/x/emissions/keeper/inference_synthesis/network_losses_test.go b/x/emissions/keeper/inference_synthesis/network_losses_test.go
@@ -370,7 +370,7 @@ func (s *InferenceSynthesisTestSuite) TestCalcNetworkLosses() {
 
 	for _, tc := range tests {
 		s.Run(tc.name, func() {
-			output, err := inferencesynthesis.CalcNetworkLosses(tc.stakesByReputer, tc.reportedLosses, tc.epsilon)
+			output, err := inferencesynthesis.CalcNetworkLosses(tc.stakesByReputer, tc.reportedLosses)
 			if tc.expectedError != nil {
 				require.Error(err)
 				require.EqualError(err, tc.expectedError.Error())
@@ -418,7 +418,6 @@ func (s *InferenceSynthesisTestSuite) TestCalcNetworkLossesFromCsv() {
 	epochGet := testutil.GetSimulatedValuesGetterForEpochs()
 	epoch301Get := epochGet[301]
 	topicId := uint64(1)
-	epsilon := alloraMath.MustNewDecFromString("1e-4")
 
 	reputer0 := s.addrs[0].String()
 	reputer1 := s.addrs[1].String()
@@ -481,7 +480,7 @@ func (s *InferenceSynthesisTestSuite) TestCalcNetworkLossesFromCsv() {
 	)
 	s.Require().NoError(err)
 
-	networkLosses, err := inferencesynthesis.CalcNetworkLosses(stakesByReputer, reportedLosses, epsilon)
+	networkLosses, err := inferencesynthesis.CalcNetworkLosses(stakesByReputer, reportedLosses)
 	s.Require().NoError(err)
 
 	expectedNetworkLosses, err := testutil.GetNetworkLossFromCsv(
@@ -579,7 +578,7 @@ func (s *InferenceSynthesisTestSuite) TestCalcNetworkLossesCombined() {
 
 	for _, tc := range tests {
 		s.Run(tc.name, func() {
-			output, err := inferencesynthesis.CalcNetworkLosses(tc.stakesByReputer, tc.reportedLosses, tc.epsilon)
+			output, err := inferencesynthesis.CalcNetworkLosses(tc.stakesByReputer, tc.reportedLosses)
 			if tc.expectedError != nil {
 				require.Error(err)
 				require.EqualError(err, tc.expectedError.Error())