dtype
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
dtype has 11 facts recorded in Dontopedia across 4 references, with 3 live disagreements.
Mostly:rdf:type(3), value(2), has value(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (4)
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.
containsContains(1)
- Constructor Arguments
ex:constructor-arguments
hasParameterHas Parameter(1)
- Field Schema Params
ex:field-schema-params
setsParameterSets Parameter(1)
- Quantized Net Definition
ex:quantized_net-definition
takesArgumentTakes Argument(1)
- Quantize Dynamic
ex:quantize-dynamic
Other facts (8)
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.
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Parameter | [2] |
| Rdf:type | Parameter | [3] |
| Rdf:type | Parameter | [4] |
| Value | np.float32 | [2] |
| Value | Data Type Int64 | [3] |
| Has Value | Torch Qint8 | [1] |
| Used in | Lil Matrix Initialization | [2] |
| Parameter Value | Torch Qint8 | [4] |
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.
References (4)
ctx:claims/beam/5a883f10-cd51-4320-9b90-c929f1dad36d- full textbeam-chunktext/plain1 KB
doc:beam/5a883f10-cd51-4320-9b90-c929f1dad36dShow 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…
ctx:claims/beam/306c29bb-24f7-454f-9101-afe06f337d8ectx:claims/beam/58335043-7a28-4310-8bc8-6b38b5011f99- full textbeam-chunktext/plain1 KB
doc:beam/58335043-7a28-4310-8bc8-6b38b5011f99Show excerpt
Here's how you can set up and use Milvus to store and retrieve document embeddings: ### Step-by-Step Guide 1. **Install Milvus**: - Install Milvus using Docker or from source. - Ensure you have a running Milvus instance. 2. **Desig…
ctx:claims/beam/893846b7-2485-431d-970b-b70aaf9c7c59
See also
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