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--- |
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datasets: |
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- ILSVRC/imagenet-1k |
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- uoft-cs/cifar100 |
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base_model: |
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- microsoft/resnet-18 |
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pipeline_tag: image-classification |
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tags: |
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- arxiv:1512.03385 |
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--- |
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# Resnet18 |
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This is an exported version of Resnet18 from Aidge. |
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The original version trained on Imagenet and the finetuned version on CIFAR100. |
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## Aidge support |
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> Note: We tested this network for the following features. If you encounter any error please open an [issue](https://gitlab.eclipse.org/groups/eclipse/aidge/-/issues). Features not tested in CI may not be functional. |
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| Feature | Tested in CI | |
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| :---------: | :----------: | |
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| ONNX import | ✔ | |
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| Backend CPU | ✔ | |
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| Export CPP | ❌ | |
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## Model |
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* Operators: 171 (11 types) |
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- Add: 8 |
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- BatchNorm2D: 20 |
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- Conv2D: 3 |
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- FC: 1 |
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- Flatten: 1 |
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- GlobalAveragePooling: 1 |
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- Identity: 3 |
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- PaddedConv2D: 17 |
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- PaddedMaxPooling2D: 1 |
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- Producer: 99 |
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- ReLU: 17 |
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## CIFAR100 |
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* Opset: 18 |
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* Source: PyTorch |
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* **Input** |
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* size: [N, 3, 224, 224] |
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* format: [N, C, H, W] |
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* preprocessing: |
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* ? |
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* **Output** |
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* size: [N, 100] |
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## ImageNet1k |
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* Opset: 8 |
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* Source: ? |
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* **Input** |
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* size: [N, 3, 224, 224] |
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* format: [N, C, H, W] |
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* preprocessing: |
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* ? |
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* **Output** |
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* size: [N, 1000] |
