Dontopedia

torch.qint8

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

torch.qint8 has 3 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

3 facts·1 predicates·2 sources·1 in dispute
Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (2)

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.

hasValueHas Value(1)

parameterValueParameter Value(1)

Other facts (2)

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.

2 facts
PredicateValueRef
Rdf:typePy Torch Data Type[1]
Rdf:typeData Format[2]

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/5a883f10-cd51-4320-9b90-c929f1dad36d
ex:PyTorchDataType
typebeam/893846b7-2485-431d-970b-b70aaf9c7c59
ex:DataFormat
labelbeam/893846b7-2485-431d-970b-b70aaf9c7c59
torch.qint8

References (2)

2 references
  1. ctx:claims/beam/5a883f10-cd51-4320-9b90-c929f1dad36d
    • full textbeam-chunk
      text/plain1 KBdoc:beam/5a883f10-cd51-4320-9b90-c929f1dad36d
      Show excerpt
      quantized_net = torch.quantization.quantize_dynamic(net, {nn.Linear}, dtype=torch.qint8) # Example usage: output = quantized_net(input_tensor) print(output) ``` Can you help me evaluate the trade-offs between different optimization techniq
  2. ctx:claims/beam/893846b7-2485-431d-970b-b70aaf9c7c59

See also

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