Net neural network class
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)
Net neural network class is simple neural network.
Mostly:rdf:type(2), inherits from(2), has method(2)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (3)
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hasNetworkClassHas Network Class(1)
- Quantization Example
ex:quantization-example
hasPartOfHas Part of(1)
- Fc1 Layer
ex:fc1-layer
parentEntityParent Entity(1)
- Fc1 Layer
ex:fc1-layer
Other facts (10)
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 | Neural Network | [1] |
| Rdf:type | Neural Network Class | [2] |
| Inherits From | Nn Module | [1] |
| Inherits From | Nn Module | [2] |
| Has Method | Forward | [1] |
| Has Method | Forward Method | [2] |
| Description | simple neural network | [1] |
| Has Constructor | Init | [1] |
| Qualifier | simple | [1] |
| Has | Quantization Forward Method | [2] |
Timeline
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References (2)
ctx:claims/beam/88c02741-efbc-4d6e-8f20-338acfec5cf4- full textbeam-chunktext/plain1 KB
doc:beam/88c02741-efbc-4d6e-8f20-338acfec5cf4Show excerpt
1. **Baseline Performance**: Measure the baseline performance (accuracy, inference time, memory usage) of your unoptimized model. 2. **Quantization Evaluation**: - Apply quantization and measure the new performance metrics. - Compare …
ctx:claims/beam/16946ca8-b20f-438f-ba71-0fb513135469- full textbeam-chunktext/plain1 KB
doc:beam/16946ca8-b20f-438f-ba71-0fb513135469Show excerpt
def forward(self, x): x = torch.relu(self.fc1(x)) return x # Initialize the network and input tensor net = Net() input_tensor = torch.randn(1, 128) # Prepare the model for quantization net.qconfig = torch.quantization.…
See also
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