Resnet18
This is an exported version of Resnet18 from Aidge.
The original version trained on Imagenet and the finetuned version on CIFAR100.
Aidge support
Note: We tested this network for the following features. If you encounter any error please open an issue. Features not tested in CI may not be functional.
| Feature | Tested in CI |
|---|---|
| ONNX import | ✔ |
| Backend CPU | ✔ |
| Export CPP | ❌ |
Model
- Operators: 171 (11 types)
- Add: 8
- BatchNorm2D: 20
- Conv2D: 3
- FC: 1
- Flatten: 1
- GlobalAveragePooling: 1
- Identity: 3
- PaddedConv2D: 17
- PaddedMaxPooling2D: 1
- Producer: 99
- ReLU: 17
CIFAR100
- Opset: 18
- Source: PyTorch
- Input
- size: [N, 3, 224, 224]
- format: [N, C, H, W]
- preprocessing:
- ?
- Output
- size: [N, 100]
ImageNet1k
- Opset: 8
- Source: ?
- Input
- size: [N, 3, 224, 224]
- format: [N, C, H, W]
- preprocessing:
- ?
- Output
- size: [N, 1000]
Model tree for EclipseAidge/resnet18
Base model
microsoft/resnet-18