model.to(device)
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
model.to(device) has 21 facts recorded in Dontopedia across 8 references, with 2 live disagreements.
21 facts·12 predicates·8 sources·2 in dispute
Mostly:rdf:type(5), applied to(1), uses argument(1)
Maturity scale
raw canonical shape-checked rule-derived certifiedInbound mentions (5)
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)
- Move to Gpu Section
ex:move-to-gpu-section
isCodeElementIs Code Element(1)
- Code Element
ex:code-element
recommendsFunctionRecommends Function(1)
- Section 1 Device Compatibility
ex:section-1-device-compatibility
usesMethodUses Method(1)
- Model Gpu Movement
ex:model-gpu-movement
usesSyntaxUses Syntax(1)
- Model Gpu Move
ex:model-gpu-move
Other facts (16)
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.
16 facts
| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Method Call | [1] |
| Rdf:type | Py Torch Function | [2] |
| Rdf:type | Method Call | [3] |
| Rdf:type | Method | [5] |
| Rdf:type | Function Call | [8] |
| Applied to | Model | [1] |
| Uses Argument | Device Variable | [1] |
| Called on | Model Variable | [3] |
| Has Argument | Device Variable | [3] |
| Applies | Scoring Model | [4] |
| Belongs to List | Pytorch Operations | [6] |
| Requires | Device Variable | [6] |
| Transfers | Model to Gpu | [7] |
| Purpose | Leverage Faster Matrix Operations | [8] |
| Belong to | Move to Gpu Section | [8] |
| Defines | Device Movement Step | [8] |
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/c470eab1-38ce-41c3-9d0a-f012e744b156
ex:MethodCall
—
labelbeam/c470eab1-38ce-41c3-9d0a-f012e744b156
model.to(device)
—
appliedTobeam/c470eab1-38ce-41c3-9d0a-f012e744b156
ex:model
—
usesArgumentbeam/c470eab1-38ce-41c3-9d0a-f012e744b156
ex:device-variable
—
typebeam/4e8f3c99-86d7-4749-a146-b0408a009f88
ex:PyTorchFunction
—
typebeam/2b55433d-f10b-4ba8-ac07-7b8a156dc333
ex:MethodCall
—
labelbeam/2b55433d-f10b-4ba8-ac07-7b8a156dc333
model device transfer
—
calledOnbeam/2b55433d-f10b-4ba8-ac07-7b8a156dc333
ex:model-variable
—
hasArgumentbeam/2b55433d-f10b-4ba8-ac07-7b8a156dc333
ex:device-variable
—
appliesbeam/1dd18c5a-82f0-4898-9740-49697f0d9016
ex:ScoringModel
—
typebeam/bb661926-a23e-4f89-b0a0-8fd1c07034c4
ex:Method
—
labelbeam/bb661926-a23e-4f89-b0a0-8fd1c07034c4
model.to(device)
—
labelbeam/2d5078e9-d244-454c-b9a1-551fc675b359
model.to(device)
—
belongsToListbeam/2d5078e9-d244-454c-b9a1-551fc675b359
ex:pytorch-operations
—
requiresbeam/2d5078e9-d244-454c-b9a1-551fc675b359
ex:device-variable
—
transfersbeam/50866f1c-f63e-42f0-a70c-005f7877c981
ex:model-to-gpu
—
typebeam/893846b7-2485-431d-970b-b70aaf9c7c59
ex:FunctionCall
—
labelbeam/893846b7-2485-431d-970b-b70aaf9c7c59
model.to(device)
—
purposebeam/893846b7-2485-431d-970b-b70aaf9c7c59
ex:leverage-faster-matrix-operations
—
belongTobeam/893846b7-2485-431d-970b-b70aaf9c7c59
ex:move-to-gpu-section
—
definesbeam/893846b7-2485-431d-970b-b70aaf9c7c59
ex:device-movement-step
References (8)
8 references
ctx:claims/beam/c470eab1-38ce-41c3-9d0a-f012e744b156- full textbeam-chunktext/plain1 KB
doc:beam/c470eab1-38ce-41c3-9d0a-f012e744b156Show excerpt
```python def retrieve(queries): # Tokenize the queries inputs = tokenizer(queries, padding=True, truncation=True, return_tensors="pt") # Perform retrieval using the LLM outputs = model(**inputs…
ctx:claims/beam/4e8f3c99-86d7-4749-a146-b0408a009f88- full textbeam-chunktext/plain1 KB
doc:beam/4e8f3c99-86d7-4749-a146-b0408a009f88Show excerpt
- Ensure that both the model and the input data are on the same device (either CPU or GPU). - Use `model.to(device)` and `input_data.to(device)` to move the model and data to the desired device. 2. **Gradient Calculation**: - When…
ctx:claims/beam/2b55433d-f10b-4ba8-ac07-7b8a156dc333- full textbeam-chunktext/plain1 KB
doc:beam/2b55433d-f10b-4ba8-ac07-7b8a156dc333Show excerpt
- Use tools like `torch.utils.benchmark` to measure and compare the performance of different configurations. ### Example with Error Handling Here's an example with error handling: ```python import torch import torch.nn as nn class Sc…
ctx:claims/beam/1dd18c5a-82f0-4898-9740-49697f0d9016ctx:claims/beam/bb661926-a23e-4f89-b0a0-8fd1c07034c4- full textbeam-chunktext/plain1 KB
doc:beam/bb661926-a23e-4f89-b0a0-8fd1c07034c4Show excerpt
1. **Data Loading and Preprocessing**: - Use `DataLoader` with `num_workers` to enable multi-threaded data loading. - Ensure data is moved to the GPU using `.to(device)`. 2. **Model and Optimizer Initialization**: - Move the model…
ctx:claims/beam/2d5078e9-d244-454c-b9a1-551fc675b359ctx:claims/beam/50866f1c-f63e-42f0-a70c-005f7877c981- full textbeam-chunktext/plain1 KB
doc:beam/50866f1c-f63e-42f0-a70c-005f7877c981Show excerpt
2. **Model and Optimizer Initialization**: - Move the model to the GPU using `model.to(device)`. - Use `Adam` optimizer with a learning rate of `0.001`. 3. **Batch Processing**: - Process batches in the loop, ensuring efficient gr…
ctx:claims/beam/893846b7-2485-431d-970b-b70aaf9c7c59
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.