File size: 1,276 Bytes
e4e6259 e4820c4 1063c0e e4820c4 1063c0e e4820c4 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 |
---
datasets:
- ILSVRC/imagenet-1k
- uoft-cs/cifar100
base_model:
- microsoft/resnet-18
pipeline_tag: image-classification
tags:
- arxiv:1512.03385
---
# 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](https://gitlab.eclipse.org/groups/eclipse/aidge/-/issues). 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] |