DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
>dxdispatch.exe -i 1000 ssd-12.onnx
...
2022-08-09 16:05:18.4763276 [W:onnxruntime:, graph.cc:3559 onnxruntime::Graph::CleanUnusedInitializersAndNodeArgs] Removing initializer 'backbone.model.layer2.0.4.bn1.num_batches_tracked'. It is not used by any node and should be removed from the model.
2022-08-09 16:05:18.4793944 [W:onnxruntime:, graph.cc:3559 onnxruntime::Graph::CleanUnusedInitializersAndNodeArgs] Removing initializer 'backbone.model.layer2.0.4.bn2.num_batches_tracked'. It is not used by any node and should be removed from the model.
2022-08-09 16:05:18.6571438 [E:onnxruntime:, sequential_executor.cc:364 onnxruntime::SequentialExecutor::Execute] Non-zero status code returned while running Unsqueeze node. Name:'Unsqueeze_scores' Status Message: D:\a\_work\1\s\onnxruntime\core\providers\dml\DmlExecutionProvider\src\MLOperatorAuthorImpl.cpp(1758)\onnxruntime.dll!00007FFF5FAC6064: (caller: 00007FFF5FF1655E) Exception(2) tid(5364) 8007023E {Application Error}
The exception %s (0x
Failed to execute dispatchable: Non-zero status code returned while running Unsqueeze node. Name:'Unsqueeze_scores' Status Message: D:\a\_work\1\s\onnxruntime\core\providers\dml\DmlExecutionProvider\src\MLOperatorAuthorImpl.cpp(1758)\onnxruntime.dll!00007FFF5FAC6064: (caller: 00007FFF5FF1655E) Exception(2) tid(5364) 8007023E {Application Error}
The exception %s (0x
The new functionality of dx-dispatch to quickly benchmark onnx model is very useful. However, it doesn't seem to work with some of the models.
Here are some examples from onnxzoo:
Model path: https://github.com/onnx/models/tree/main/vision/object_detection_segmentation/yolov4/model
Model path: https://github.com/onnx/models/tree/main/vision/object_detection_segmentation/ssd/model
Model path: https://github.com/onnx/models/tree/main/vision/classification/mobilenet/model For this one batch_size:1 works