Dontopedia

Linear Component

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

Linear Component has 9 facts recorded in Dontopedia across 1 reference, with 1 live disagreement.

9 facts·8 predicates·1 sources·1 in dispute

Mostly:ex:has parameter(2), rdf:type(1), ex:follows(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (1)

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.

ex:containsLayerEx:contains Layer(1)

Other facts (9)

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.

9 facts
PredicateValueRef
Ex:has ParameterIn Features[1]
Ex:has Parameter1[1]
Rdf:typeNeural Network Layer[1]
Ex:followsLstm Component[1]
Ex:has in Features64[1]
Ex:has Out Features1[1]
Ex:maps FromLstm Hidden Dimension[1]
Ex:maps toSingle Output[1]
Ex:transformsFiltered Output[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.

typebeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
ex:NeuralNetworkLayer
hasParameterbeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
ex:in_features
hasParameterbeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
1
followsbeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
ex:lstm-component
hasInFeaturesbeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
64
hasOutFeaturesbeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
1
mapsFrombeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
ex:lstm-hidden-dimension
mapsTobeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
ex:single-output
transformsbeam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
ex:filtered-output

References (1)

1 references
  1. ctx:claims/beam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
    • full textbeam-chunk
      text/plain1 KBdoc:beam/a7f1cd1a-35d3-48b4-be35-bbfe103ee0fe
      Show excerpt
      padded_sequences = [torch.tensor(seq, dtype=torch.float32) for seq in padded_sequences] ``` #### Step 3: Masking (Optional) If you want to ignore the padded parts during training, you can create a mask tensor. ```python # Create a mask t

See also

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