From 06e6935ba97be2b7353751e8d4c09b6727e37f40 Mon Sep 17 00:00:00 2001 From: Ruonan Wang <105281011+rnwang04@users.noreply.github.com> Date: Fri, 3 Feb 2023 17:29:58 +0800 Subject: [PATCH] Nano: update troubleshooting guide (#7285) * update troubshooting guide * update based on comment --- .../source/doc/Nano/Overview/troubshooting.md | 18 +++++++++++++----- 1 file changed, 13 insertions(+), 5 deletions(-) diff --git a/docs/readthedocs/source/doc/Nano/Overview/troubshooting.md b/docs/readthedocs/source/doc/Nano/Overview/troubshooting.md index 0ffa24aa..21109a27 100644 --- a/docs/readthedocs/source/doc/Nano/Overview/troubshooting.md +++ b/docs/readthedocs/source/doc/Nano/Overview/troubshooting.md @@ -3,9 +3,9 @@ Refer to this section for common issues faced while using BigDL-Nano. ## Installation -### Why I fail to install openvino==2022.2 when ``pip install bgdl-nano[inference]``? +### Why I fail to install openvino-dev==2022.2 when ``pip install bigdl-nano[inference]``? -Please check your system first as openvino 2022.x does not support centos anymore. Refer [OpenVINO release notes](https://www.intel.com/content/www/us/en/developer/articles/release-notes/openvino-relnotes-2021.html) for more details. +Please check your system first as openvino-dev 2022.2 does not support centos. Refer [this](https://pypi.org/project/openvino-dev/) for more details. You can install bigdl-nano[inference] >= 2.2 instead, as bigdl-nano[inference] >= 2.2 use openvino-dev >= 2022.3 which supports centos again. ## Inference @@ -15,7 +15,7 @@ Please make sure you use context manager provided by ``InferenceOptimizer.get_co ### ``assert precision in list(self.cur_config['ops'].keys())`` when using ipex quantization with inc on machine with BF16 instruction set -It's known issue for [Intel® Neural Compressor](https://github.com/intel/neural-compressor) that they don't deal with BF16 op well at version 1.13.1 . This will be fixed when next stable version releases. +It's known issue for [Intel® Neural Compressor](https://github.com/intel/neural-compressor) that they don't deal with BF16 op well at version 1.13.1 . This has been fixed in version 2.0. You can install bigdl-nano[inference] >= 2.2 to fix this problem. ### Why my output is not bf16 dtype when using bf16+ipex related methods? @@ -41,7 +41,7 @@ If you accelerate the model with ``accelerator=None`` by ``InferenceOptimizer.tr ### Why my bf16 model is slower than fp32 model? -You can first check whether your machine supports the bf16 instruction set first by ``lscpu | grep "avx512"``. If there is no ``avx512_bf16`` in the output, then, without instruction set support, the performance of bf16 cannot be guaranteed, and generally, its performance will deteriorate. +You can first check whether your machine supports the bf16 instruction set first by ``lscpu | grep "bf16"``. If there is no ``avx512_bf16`` or ``amx_bf16`` in the output, then, without instruction set support, the performance of bf16 cannot be guaranteed, and generally, its performance will deteriorate. ### ``INVALID_ARGUMENT : Got invalid dimensions for input`` or ``[ PARAMETER_MISMATCH ] Can not clone with new dims.`` when do inference with OpenVINO / ONNXRuntime accelerated model @@ -62,4 +62,12 @@ Please check first if you use `patch_cuda(disable_jit=True)` command of Nano, if ### How to cope with out-of-memory during workload with Intel® Extension for PyTorch* -If you found the workload runs with Intel® Extension for PyTorch* occupies a remarkably large amount of memory, you can try to reduce the occupied memory size by setting `weights_prepack=False` when calling `InferenceOptimizer.trace` \ `InferenceOptimizer.quantize`. \ No newline at end of file +If you found the workload runs with Intel® Extension for PyTorch* occupies a remarkably large amount of memory, you can try to reduce the occupied memory size by setting `weights_prepack=False` when calling `InferenceOptimizer.trace` \ `InferenceOptimizer.quantize`. + +### RuntimeError: Check 'false' failed at src/frontends/common/src/frontend.cpp + +You may see this error when you do inference with accelerator=`OpenVINO` in keras. It only occurs when you use `intel-tensorflow` >= 2.8 and you forget `source bigdl-nano-init`. The way to solve this problem is just `source bigdl-nano-init` or `source bigdl-nano-init -j`. + +### TypeError: deprecated() got an unexpected keyword argument 'name' + +If a version problem caused by too low cryptography version. You can fix it by just `pip install cryptography==38.0.0` .