---
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]