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                                            bills

Rpc call error when using TensorFlow Serving Predict API

No use in more than one params, oh! I feel that the product is not as good as PPT

BUG: Unexpected exception TypeError("_post_eval_hook() got an unexpected keyword argument 'accuracy'") happened during tuning.

The tensorflow adaptor not has accuracy params, So raise the execption, You have pass it, So tensorboard in NIC is not avaliable now!

Quantization AssertionError "inputs len must equal with input_tensor"

I have the same error? but I don't know how to reslove ``` (tf2) [root@VM-117-232-centos /data/home/guirongguo/neural-compressor/examples/tensorflow/image_recognition/SavedModel/quantization/ptq_2]# bash run_tuning.sh --input_model=origin_model.pb --output_model=origin_model_tune.pb --dataset_location=./ + main --input_model=origin_model.pb --output_model=origin_model_tune.pb --dataset_location=./ + init_params --input_model=origin_model.pb --output_model=origin_model_tune.pb...

CPU inference is much slower than with ONNX Runtime directly

I use Triton ORT 21.09-py3 I also have the same problem too. When I run pref the cpu is about 100%, but the QPS is not have a ideal accelerate.

Is There has some tools to get model's FLOPS/FLOPs and MACs for Onnx model?

I try many tools but always report error, very sad