Dontopedia

complexity_scorer

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-09.)

complexity_scorer has 9 facts recorded in Dontopedia across 3 references, with 1 live disagreement.

9 facts·6 predicates·3 sources·1 in dispute

Mostly:rdf:type(3), has method(1), has attribute(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (3)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

fedToFed to(1)

roleInTeamRole in Team(1)

teamRoleTeam Role(1)

Other facts (8)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

8 facts
PredicateValueRef
Rdf:typeScorer[1]
Rdf:typePy Torch Module[2]
Rdf:typeNeural Network Model[3]
Has MethodScore[1]
Has AttributeScores[1]
Used forEvaluation[1]
Has Parameterstrue[2]
ReceivesBatch Inputs[3]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

typebeam/f54bef6c-8fc0-483e-bd86-e318e44c14f4
ex:Scorer
hasMethodbeam/f54bef6c-8fc0-483e-bd86-e318e44c14f4
ex:score
hasAttributebeam/f54bef6c-8fc0-483e-bd86-e318e44c14f4
ex:scores
usedForbeam/f54bef6c-8fc0-483e-bd86-e318e44c14f4
ex:evaluation
typebeam/f6bdd424-985a-4eea-a1d8-a4f7ec22cc5b
ex:PyTorchModule
hasParametersbeam/f6bdd424-985a-4eea-a1d8-a4f7ec22cc5b
true
typebeam/815302c1-8846-46c0-b5a2-8475c92165b2
ex:NeuralNetworkModel
labelbeam/815302c1-8846-46c0-b5a2-8475c92165b2
complexity_scorer
receivesbeam/815302c1-8846-46c0-b5a2-8475c92165b2
ex:batch-inputs

References (3)

3 references
  1. ctx:claims/beam/f54bef6c-8fc0-483e-bd86-e318e44c14f4
  2. ctx:claims/beam/f6bdd424-985a-4eea-a1d8-a4f7ec22cc5b
    • full textbeam-chunk
      text/plain1 KBdoc:beam/f6bdd424-985a-4eea-a1d8-a4f7ec22cc5b
      Show excerpt
      def forward(self, x): x = torch.relu(self.fc1(x)) x = self.fc2(x) return x # Initialize scorer, optimizer, and loss function scorer = ComplexityScorer() optimizer = optim.Adam(scorer.parameters(), lr=1e-5) loss_
  3. ctx:claims/beam/815302c1-8846-46c0-b5a2-8475c92165b2
    • full textbeam-chunk
      text/plain1 KBdoc:beam/815302c1-8846-46c0-b5a2-8475c92165b2
      Show excerpt
      optimizer.step() # Zero gradients optimizer.zero_grad() # Validation loop scorer.eval() val_losses = [] with torch.no_grad(): for batch_inputs, batch_targets in val_loader: outpu

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