state_dict
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
state_dict has 14 facts recorded in Dontopedia across 7 references, with 1 live disagreement.
Mostly:rdf:type(7), method of(1), loaded from(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (7)
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.
acceptsParameterAccepts Parameter(1)
- Torch Save
ex:torch-save
addsComplexityToAdds Complexity to(1)
- Running Statistics
ex:running-statistics
createsCreates(1)
- Save Model
ex:save_model
deserializesDeserializes(1)
- Torch Load
ex:torch-load
hasStateHas State(1)
- Model
ex:model
serializesSerializes(1)
- Torch Save
ex:torch-save
usesUses(1)
- Model Loading
ex:model-loading
Other facts (13)
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 | Py Torch Component | [1] |
| Rdf:type | Model Weights | [2] |
| Rdf:type | Model Weights | [3] |
| Rdf:type | Dictionary | [4] |
| Rdf:type | Model State | [5] |
| Rdf:type | Dictionary | [6] |
| Rdf:type | Py Torch State Dict | [7] |
| Method of | Reranking Model | [1] |
| Loaded From | Model Path | [2] |
| Contains | Learned Weights | [2] |
| State of | Model | [3] |
| Contains Key | Model State Dict Key | [6] |
| Contains Value | Model State Dict Value | [6] |
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 (7)
ctx:claims/beam/6fee7420-d7a9-4f8e-bc28-9cd1591ad95d- full textbeam-chunktext/plain1 KB
doc:beam/6fee7420-d7a9-4f8e-bc28-9cd1591ad95dShow excerpt
avg_val_loss = total_val_loss / len(val_loader) print(f"Validation Loss: {avg_val_loss:.4f}") return model ``` ### Example Usage Here's how you can use the above components to integrate your reranking logi…
ctx:claims/beam/fa097ab4-7c54-4d7c-bce6-50883cbc7667ctx:claims/beam/5fb76548-eadb-49e2-aa62-01f144546c00- full textbeam-chunktext/plain1 KB
doc:beam/5fb76548-eadb-49e2-aa62-01f144546c00Show excerpt
3. **Check for Errors**: If an error occurs during the update, load the saved state to roll back to the previous version. 4. **Log Rollback Failures**: Log any issues encountered during the rollback process. Here's a Python script demonstr…
ctx:claims/beam/5c01f8e0-e02b-4cf2-b48b-9c494bf07dc5ctx:claims/beam/9151b445-41b5-4d53-900d-4199adc168c1- full textbeam-chunktext/plain1 KB
doc:beam/9151b445-41b5-4d53-900d-4199adc168c1Show excerpt
model = MyModel().to(device) optimizer = optim.Adam(model.parameters(), lr=0.001) # Define the update logic def update_model(model, optimizer, data_loader): model.train() for data, _ in data_loader: data = data.to(device) …
ctx:claims/beam/facb10e4-23ac-48a9-95ff-5135145b239a- full textbeam-chunktext/plain1 KB
doc:beam/facb10e4-23ac-48a9-95ff-5135145b239aShow excerpt
- Print periodic status updates to monitor the progress of saving the model. ### Additional Considerations: - **Compression**: - If you are concerned about disk space usage, you can compress the saved model files using libraries like…
ctx:claims/beam/343d7abc-9aa0-4e2b-8884-910c760bfe88- full textbeam-chunktext/plain1 KB
doc:beam/343d7abc-9aa0-4e2b-8884-910c760bfe88Show 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…
See also
Keep researching
Missing something or suspicious of what's here? Kick off a research session — a Claude agent will investigate, cite its sources, and file new facts into a dedicated context you can review before accepting into the shared view.