Inception_v4

Quantized Inception_v4 model that could be supported by AMD Ryzen AI.

Model description

Inception_v4 was first introduced in the paper Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning.

The model implementaion is from TensorFlow-Slim.

How to use

Installation

Follow Ryzen AI Installation to prepare the environment for Ryzen AI. Run the following script to install pre-requisites for this model.

pip install -r requirements.txt

Data Preparation

Follow imagenet-1k to download dataset.

Download ImageNet validation synset labels file.

Create validation image list:

python create_image_list.py imagenet_2012_validation_synset_labels.txt

Model Evaluation

python eval_onnx.py --onnx_model inceptionv4_int8.onnx --ipu --provider_config Path\To\vaip_config.json --val_data_dir /Path/To/Your/Validation/Data --val_image_list val.txt

Performance

Metric Accuracy on IPU
Top1/Top5 79.92% / 95.02%
@article{Szegedy2016Inceptionv4IA,
  title={Inception-v4, Inception-ResNet and the Impact of Residual Connections on Learning},
  author={Christian Szegedy and Sergey Ioffe and Vincent Vanhoucke and Alexander A. Alemi},
  journal={arXiv:1602.07261},
  year={2016},
}
Downloads last month

-

Downloads are not tracked for this model. How to track
Inference Providers NEW
This model is not currently available via any of the supported Inference Providers.
The model cannot be deployed to the HF Inference API: The model has no library tag.

Dataset used to train amd/inception_v4