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Optim.adam

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)

Optim.adam has 8 facts recorded in Dontopedia across 4 references, with 1 live disagreement.

8 facts·5 predicates·4 sources·1 in dispute

Mostly:rdf:type(3), rdfs:label(2), has learning rate(1)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Rdfs:labelrdfs:label

  • Adam[3]sourceall time · E23941de 32cc 40aa 8fa8 2ba2a21a03db
  • Adam[4]all time · 1ca59683 Ef7c 4511 A82b Ebdf3e48113e

Has Learning RatehasLearningRate

  • 0.001[1]sourceall time · 473b8b12 Bc82 4e33 85d3 1090ae8915bb

Has Learning Rate ParameterhasLearningRateParameter

  • 0.001[2]sourceall time · 1431835d Ed0f 4f5e A055 310bf86b145f

Is Constructor CallisConstructorCall

  • true[2]sourceall time · 1431835d Ed0f 4f5e A055 310bf86b145f

Inbound mentions (10)

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.

isInstanceIs Instance(2)

passedToPassed to(2)

rdf:typeRdf:type(2)

assignedFromAssigned From(1)

createdCreated(1)

implementedAsImplemented As(1)

valueValue(1)

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.

hasLearningRatebeam/473b8b12-bc82-4e33-85d3-1090ae8915bb
0.001
hasLearningRateParameterbeam/1431835d-ed0f-4f5e-a055-310bf86b145f
0.001
isConstructorCallbeam/1431835d-ed0f-4f5e-a055-310bf86b145f
true
labelbeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
Adam
labelbeam/1ca59683-ef7c-4511-a82b-ebdf3e48113e
Adam
typebeam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
ex:Optimizer
typebeam/473b8b12-bc82-4e33-85d3-1090ae8915bb
ex:Optimizer
typebeam/1ca59683-ef7c-4511-a82b-ebdf3e48113e
ex:PyTorchOptimizer

References (4)

4 references
  1. [1]beam-chunk2 facts
    customctx:claims/beam/473b8b12-bc82-4e33-85d3-1090ae8915bb
    • full textbeam-chunk
      text/plain1 KBdoc:beam/473b8b12-bc82-4e33-85d3-1090ae8915bb
      Show excerpt
      return x # Example usage: queries = [...] # List of queries labels = [...] # List of labels dataset = QueryDataset(queries, labels) data_loader = DataLoader(dataset, batch_size=64, shuffle=True, num_workers=4) model = Optimizat
  2. [2]beam-chunk2 facts
    customctx:claims/beam/1431835d-ed0f-4f5e-a055-310bf86b145f
    • full textbeam-chunk
      text/plain1 KBdoc:beam/1431835d-ed0f-4f5e-a055-310bf86b145f
      Show excerpt
      def worker(data_loader): local_model = MyModel() local_optimizer = optim.Adam(local_model.parameters(), lr=0.001) update_model(local_model, local_optimizer, data_loader) return local_model.state_dict(), local_optimizer.state
  3. [3]beam-chunk2 facts
    customctx:claims/beam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
    • full textbeam-chunk
      text/plain1 KBdoc:beam/e23941de-32cc-40aa-8fa8-2ba2a21a03db
      Show excerpt
      optimizer = optim.Adam(model.parameters(), lr=0.001) # Define the update logic def update_model(model, optimizer, data_loader): model.train() for data, _ in data_loader: data = data.to(device) optimizer.zero_grad()
  4. customctx:claims/beam/1ca59683-ef7c-4511-a82b-ebdf3e48113e

See also

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