Model Compatibility#
In the Ryzen AI workflow, the quantized model is converted into ONNX format for deployment. Currently, the IPU supports a subset of ONNX operators. However, with the Vitis AI ONNX Execution Provider (VAI EP), the neural network is automatically partitioned into multiple subgraphs. The subgraph(s) containing IPU-supported operators are executed on the IPU, while the remaining subgraph(s) containing IPU-incompatible operators are executed on the CPU. This “Model Parallel” deployment technique across the CPU and IPU is fully automated. VAI EP manages it and is transparent to the end-user.
The current list of the IPU-supported ONNX operators is as follows:
Add
And
Average pool
BatchNorm
Clip
Concat
Conv
ConvTranspose
Gemm
GlobalAveragePool
GlobalMaxPool
Identity
LayerNorm
LSTM
Max
MaxPool
Mul
Pad
Prelu
Relu
Resize
RNN
Sigmoid
Slice
Softmax
Split
Squeeze
Unsqueeze
Upsample
Spacetodepth