---
datasets:
- ylecun/mnist
metrics:
- accuracy
pipeline_tag: image-classification
library_name: torch
---

# LeNet

Toy model mainly used to showcase Aidge in various tutorial, for example: https://eclipse.dev/aidge/source/Tutorial/101_first_step.html

## 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  |      ❌      |

## MNIST

* **Input**
    * size: [N, 1, 28, 28]
    * format: [N, C, H, W]
    * preprocessing: `None`
* **Output**
    * size: [N, 10]

### ONNX attributes

* Opset: <opset>
* Source: PyTorch
* Operators: 22 (6 types)
  - Conv2D: 2
  - FC: 3
  - Flatten: 1
  - MaxPooling2D: 2
  - Producer: 10
  - ReLU: 4

### Benchmark

> Coming soon