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Self.fc1

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

Self.fc1 has 7 facts recorded in Dontopedia across 3 references, with 1 live disagreement.

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

Mostly:rdf:type(2), has output size(1), has input size(1)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Has Output SizehasOutputSize

  • 128[2]all time · B424bd38 46a8 4f5b 8589 C66c43eca88e

Has Input SizehasInputSize

  • 512[2]all time · B424bd38 46a8 4f5b 8589 C66c43eca88e

Nn:linearnn:Linear

  • Nn.linear[2]all time · B424bd38 46a8 4f5b 8589 C66c43eca88e

Assigned ValueassignedValue

Is InstanceisInstance

  • Nn.linear[3]all time · Cb8cd140 2b8c 41c2 8160 68d7bc0c4c91

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.

appliedToApplied to(1)

definesAttributeDefines Attribute(1)

hasAttributeHas Attribute(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.

7 undated
—
assignedValuebeam/343d7abc-9aa0-4e2b-8884-910c760bfe88
ex:linear-layer
—
hasInputSizebeam/b424bd38-46a8-4f5b-8589-c66c43eca88e
512
—
hasOutputSizebeam/b424bd38-46a8-4f5b-8589-c66c43eca88e
128
—
isInstancebeam/cb8cd140-2b8c-41c2-8160-68d7bc0c4c91
ex:nn.Linear
—
Linearbeam/b424bd38-46a8-4f5b-8589-c66c43eca88e
ex:nn.Linear
—
typebeam/b424bd38-46a8-4f5b-8589-c66c43eca88e
ex:LinearLayer
—
typebeam/343d7abc-9aa0-4e2b-8884-910c760bfe88
ex:ModuleAttribute

References (3)

3 references
  1. [1]beam-chunk2 facts
    customctx:claims/beam/343d7abc-9aa0-4e2b-8884-910c760bfe88
    • full textbeam-chunk
      text/plain1 KBdoc:beam/343d7abc-9aa0-4e2b-8884-910c760bfe88
      Show excerpt
      self.fc1 = nn.Linear(512, 128) self.fc2 = nn.Linear(128, 10) def forward(self, x): x = torch.relu(self.fc1(x)) x = self.fc2(x) return x # Initialize the model and optimizer model = MyModel() opt…
  2. [2]B424bd38 46a8 4f5b 8589 C66c43eca88e4 facts
    customctx:claims/beam/b424bd38-46a8-4f5b-8589-c66c43eca88e
  3. [3]Cb8cd140 2b8c 41c2 8160 68d7bc0c4c911 fact
    customctx:claims/beam/cb8cd140-2b8c-41c2-8160-68d7bc0c4c91

See also

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