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Tf.math.ceil

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

Tf.math.ceil has 6 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

6 facts·5 predicates·2 sources·1 in dispute

Mostly:rdf:type(2), called with(1), applied to(1)

Maturity scale raw canonical shape-checked rule-derived certified

Rdf:typein disputerdf:type

Called WithcalledWith

Applied toappliedTo

Operation TypeoperationType

Rounds UproundsUp

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.

operandOfOperand of(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.

appliedTobeam/04bd25c0-df3e-4304-bfa4-8ddd9781d277
ex:context_size-calculation
calledWithbeam/2d91ade4-2b08-48f8-8245-9ae483489b3b
ex:seq_len_times_0.5
operationTypebeam/04bd25c0-df3e-4304-bfa4-8ddd9781d277
ex:mathematical-function
typebeam/04bd25c0-df3e-4304-bfa4-8ddd9781d277
ex:function
typebeam/2d91ade4-2b08-48f8-8245-9ae483489b3b
ex:TensorFlowFunction
roundsUpbeam/04bd25c0-df3e-4304-bfa4-8ddd9781d277
ex:context_size-value

References (2)

2 references
  1. [1]beam-chunk4 facts
    customctx:claims/beam/04bd25c0-df3e-4304-bfa4-8ddd9781d277
    • full textbeam-chunk
      text/plain1 KBdoc:beam/04bd25c0-df3e-4304-bfa4-8ddd9781d277
      Show excerpt
      Here's an example of how you can implement these strategies using Keras: ```python import tensorflow as tf from tensorflow.keras.layers import Embedding, LSTM, Input, Lambda, Masking from tensorflow.keras.models import Model import numpy a
  2. customctx:claims/beam/2d91ade4-2b08-48f8-8245-9ae483489b3b

See also

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