Dontopedia

GradScaler

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GradScaler has 6 facts recorded in Dontopedia across 1 reference.

6 facts·5 predicates·1 sources

Mostly:uses class(1), used for(1), rdf:type(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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containsContains(1)

hasComponentHas Component(1)

Other facts (5)

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5 facts
PredicateValueRef
Uses ClassGradScaler[1]
Used formixed precision training[1]
Rdf:typeGradient Scaler[1]
Used for Purposemixed precision training[1]
Enablesmixed precision training[1]

Timeline

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usesClassbeam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
GradScaler
usedForbeam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
mixed precision training
typebeam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
ex:GradientScaler
labelbeam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
GradScaler
usedForPurposebeam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
mixed precision training
enablesbeam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
mixed precision training

References (1)

1 references
  1. ctx:claims/beam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
    • full textbeam-chunk
      text/plain1 KBdoc:beam/25baff9e-41da-45c5-b4cd-7ddac9cf5c32
      Show excerpt
      loader = DataLoader(dataset, batch_size=16, shuffle=True) # Reduced batch size optimizer = optim.Adam(model.parameters(), lr=0.001) scaler = GradScaler() # For mixed precision training for epoch in range(10): train

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