DebugModel.__init__
From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-10.)
DebugModel.__init__ has 11 facts recorded in Dontopedia across 2 references, with 2 live disagreements.
Mostly:rdf:type(2), has layer(2), method(1)
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| Predicate | Value | Ref |
|---|---|---|
| Rdf:type | Constructor | [1] |
| Rdf:type | Constructor | [2] |
| Has Layer | fc1 | [2] |
| Has Layer | fc2 | [2] |
| Method | __init__ | [2] |
| Calls | super(DebugModel, self).__init__ | [2] |
| Layer Type | nn.Linear | [2] |
| Fc1 Parameters | 512 input, 128 output | [2] |
| Fc2 Parameters | 128 input, 10 output | [2] |
| Invokes | Parent Init | [2] |
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References (2)
ctx:claims/beam/3273ae1c-32c6-4028-9a0a-b07bb3d1326a- full textbeam-chunktext/plain1 KB
doc:beam/3273ae1c-32c6-4028-9a0a-b07bb3d1326aShow excerpt
level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s', handlers=[ logging.FileHandler("debug_training.log"), logging.StreamHandler() ] ) # Define a custom dataset class for our queries class…
ctx:claims/beam/16ad261b-9fcf-4975-8708-5450c6d4ee02- full textbeam-chunktext/plain1 KB
doc:beam/16ad261b-9fcf-4975-8708-5450c6d4ee02Show excerpt
import json # Check if a GPU is available device = torch.device("cuda" if torch.cuda.is_available() else "cpu") print(f"Using device: {device}") # Configure logging logging.basicConfig( level=logging.INFO, format='%(asctime)s - %(…
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