Aniket Srivastav
Aniket Srivastav
yes. `images[labels].shape` shows shape` (1, 256, 256, 3)`
Yes, the output of the predict function is NxC. But I have modified it to take only a single image. You can get the code from [here]( https://github.com/notAI-tech/NudeNet). Just place...
Thanks, I have removed the batch size limitations. But I am still getting the same error while running the `explainer.explain()` function. `onnxruntime.capi.onnxruntime_pybind11_state.InvalidArgument: [ONNXRuntimeError] : 2 : INVALID_ARGUMENT : Invalid rank...
Yes, changing the input shape to (256,256,3) seems to be working without any error but the program is getting killed. Is it because the data (features) is too big for...
It gets killed after 10-20 sec. Number of parameters in the model: 20865582.0 The CPU Memory usage is almost 90% EDIT: Also, I ran a similar TensorFlow based cat classification...
The imagenet model takes almost 4GB of RAM out of 8GB. The current ONNX model takes 100% of RAM consumption before it gets killed. SO I think it might be...
Hi @jklaise, I tried the same code on a 16GB RAM system and it worked and I got the explainer segmentation. The RAM memory consumption was ~9.62 GB and it...
Hi @cliveseldon, I will use the HTTP endpoints but how do I fix the `payload too large` error.
I am using triton and kfserving.
I am using the default istio setting. and I am also using kubeflow for deployment. I am able to run the prediction function with the same istio setting but gets...