# Serpent Canyon running IPXE on Ubuntu 22.04

![](https://hackmd.io/_uploads/B1bgyHzF2.png) ![](https://hackmd.io/_uploads/SknuZHMF3.png) ``` wget -c https://github.com/intel/xpumanager/releases/download/V1.2.13/xpumanager_1.2.13_20230629.055631.aeeedfec.u22.04_amd64.deb sudo apt install intel-gsc libmetee sudo dpkg -I xpumanager_1.2.13_20230629.055631.aeeedfec.u22.04_amd64.deb xpumcli dump -d 0 -m 1,2,8,18 ``` ``` [Install Kernel] sudo apt update sudo apt install vim git wget gpg cd Downloads/ mkdir v6.2.16 cd v6.2.16/ wget -c https://kernel.ubuntu.com/~kernel-ppa/mainline/v6.2.16/amd64/linux-headers-6.2.16-060216-generic_6.2.16-060216.202305171336_amd64.deb wget -c https://kernel.ubuntu.com/~kernel-ppa/mainline/v6.2.16/amd64/linux-headers-6.2.16-060216_6.2.16-060216.202305171336_all.deb wget -c https://kernel.ubuntu.com/~kernel-ppa/mainline/v6.2.16/amd64/linux-image-unsigned-6.2.16-060216-generic_6.2.16-060216.202305171336_amd64.deb wget -c https://kernel.ubuntu.com/~kernel-ppa/mainline/v6.2.16/amd64/linux-modules-6.2.16-060216-generic_6.2.16-060216.202305171336_amd64.deb sudo dpkg -i *deb git clone https://github.com/intel-gpu/intel-gpu-firmware.git cd intel-gpu-firmware sudo mkdir -p /lib/firmware/updates/i915/ sudo cp firmware/*.bin /lib/firmware/updates/i915/ sudo update-grub sudo reboot [Install required library w/o this IPUX can't detect XPU] wget -qO - https://repositories.intel.com/graphics/intel-graphics.key | sudo gpg --dearmor --output /usr/share/keyrings/intel-graphics.gpg echo "deb [arch=amd64,i386 signed-by=/usr/share/keyrings/intel-graphics.gpg] https://repositories.intel.com/graphics/ubuntu jammy arc" | sudo tee /etc/apt/sources.list.d/intel-gpu-jammy.list sudo apt-get install -y \ intel-opencl-icd intel-level-zero-gpu level-zero \ intel-media-va-driver-non-free libmfx1 libmfxgen1 libvpl2 \ libegl-mesa0 libegl1-mesa libegl1-mesa-dev libgbm1 libgl1-mesa-dev libgl1-mesa-dri \ libglapi-mesa libgles2-mesa-dev libglx-mesa0 libigdgmm12 libxatracker2 mesa-va-drivers \ mesa-vdpau-drivers mesa-vulkan-drivers va-driver-all vainfo hwinfo clinfo sudo ls #Install Intel® oneAPI Base Toolkit 2023.1 wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list sudo apt update sudo apt install intel-basekit # Intel® oneAPI Base Toolkit 2023.1 is installed to /opt/intel/oneapi/ export ONEAPI_ROOT=/opt/intel/oneapi # A DPC++ compiler patch is required to use with oneAPI Basekit 2023.1.0. Use the command below to download the patch package. wget https://registrationcenter-download.intel.com/akdlm/IRC_NAS/89283df8-c667-47b0-b7e1-c4573e37bd3e/2023.1-linux-hotfix.zip unzip 2023.1-linux-hotfix.zip cd 2023.1-linux-hotfix source ${ONEAPI_ROOT}/setvars.sh sudo -E bash installpatch.sh sudo apt install python3-venv cd python3 -m venv ipex source ipex/bin/activate python -m pip install torch==1.13.0a0+git6c9b55e torchvision==0.14.1a0 intel_extension_for_pytorch==1.13.120+xpu -f https://developer.intel.com/ipex-whl-stable-xpu python cifa10_ipex_fp32.py #cifa10_ipex_fp32.py import torch import torchvision ############# code changes ############### import intel_extension_for_pytorch as ipex ############# code changes ############### LR = 0.001 DOWNLOAD = True DATA = 'datasets/cifar10/' transform = torchvision.transforms.Compose([ torchvision.transforms.Resize((224, 224)), torchvision.transforms.ToTensor(), torchvision.transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)) ]) train_dataset = torchvision.datasets.CIFAR10( root=DATA, train=True, transform=transform, download=DOWNLOAD, ) train_loader = torch.utils.data.DataLoader( dataset=train_dataset, batch_size=128 ) model = torchvision.models.resnet50() criterion = torch.nn.CrossEntropyLoss() optimizer = torch.optim.SGD(model.parameters(), lr = LR, momentum=0.9) model.train() ######################## code changes ####################### model = model.to("xpu") criterion = criterion.to("xpu") model, optimizer = ipex.optimize(model, optimizer=optimizer) ######################## code changes ####################### for batch_idx, (data, target) in enumerate(train_loader): ########## code changes ########## data = data.to("xpu") target = target.to("xpu") ########## code changes ########## optimizer.zero_grad() output = model(data) loss = criterion(output, target) loss.backward() optimizer.step() print(batch_idx) torch.save({ 'model_state_dict': model.state_dict(), 'optimizer_state_dict': optimizer.state_dict(), }, 'checkpoint.pth') Ref: https://raw.githubusercontent.com/intel/intel-extension-for-pytorch/master/scripts/collect_env.py ``` eapet@eapet-TANKDG2:~/Downloads$ sudo dpkg -I xpumanager_1.2.13_20230629.055631.aeeedfec.u22.04_amd64.deb [sudo] password for eapet: new Debian package, version 2.0. size 35326520 bytes: control archive=17908 bytes. 629 bytes, 15 lines control 54794 bytes, 575 lines md5sums 945 bytes, 34 lines * postinst #!/bin/bash 1117 bytes, 44 lines * prerm #!/bin/bash Architecture: amd64 Conflicts: xpu-smi Depends: level-zero (>= 1.7.9.1), intel-gsc (>=0.8.4), intel-level-zero-gpu (>=1.3.23726) Description: Intel(R) XPU Manager Intel(R) XPU Manager is a free and open-source tool for managing Intel data center GPUs. Homepage: https://github.com/intel/xpumanager Maintainer: Intel Corporation Package: xpumanager Priority: optional Recommends: intel-metrics-discovery (>=1.10.141), intel-metrics-library (>=1.0.76), libmfx-tools (>=22.5.0), intel-media-va-driver-non-free (>=22.5.0), libmfxgen1 (>=22.5.0) Section: devel Version: 1.2.13-20230629.055631.aeeedfec~u22.04 Installed-Size: 91901 ``` # logs eapet@eapet-NUC12SNKi72:~/Downloads$ wget -O- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB | gpg --dearmor | sudo tee /usr/share/keyrings/oneapi-archive-keyring.gpg > /dev/null --2023-07-04 20:28:57-- https://apt.repos.intel.com/intel-gpg-keys/GPG-PUB-KEY-INTEL-SW-PRODUCTS.PUB Resolving apt.repos.intel.com (apt.repos.intel.com)... 2001:b034:1c:382::4b23, 2001:b034:1c:380::4b23, 184.29.40.30 Connecting to apt.repos.intel.com (apt.repos.intel.com)|2001:b034:1c:382::4b23|:443... connected. HTTP request sent, awaiting response... 200 OK Length: 3796 (3.7K) [binary/octet-stream] Saving to: ‘STDOUT’ - 100%[===============================================================================================================>] 3.71K --.-KB/s in 0s 2023-07-04 20:28:57 (1.26 GB/s) - written to stdout [3796/3796] eapet@eapet-NUC12SNKi72:~/Downloads$ echo "deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main" | sudo tee /etc/apt/sources.list.d/oneAPI.list deb [signed-by=/usr/share/keyrings/oneapi-archive-keyring.gpg] https://apt.repos.intel.com/oneapi all main eapet@eapet-NUC12SNKi72:~/Downloads$ sudo apt update Hit:1 http://tw.archive.ubuntu.com/ubuntu jammy InRelease Hit:2 http://tw.archive.ubuntu.com/ubuntu jammy-updates InRelease Hit:3 http://tw.archive.ubuntu.com/ubuntu jammy-backports InRelease Get:4 https://apt.repos.intel.com/oneapi all InRelease [4447 B] Get:5 http://security.ubuntu.com/ubuntu jammy-security InRelease [110 kB] Get:6 https://apt.repos.intel.com/oneapi all/main amd64 Packages [292 kB] Get:7 https://apt.repos.intel.com/oneapi all/main all Packages [73.9 kB] Hit:8 https://repositories.intel.com/graphics/ubuntu jammy InRelease Hit:9 https://ppa.launchpadcontent.net/audio-recorder/ppa/ubuntu jammy InRelease Get:10 https://apt.repos.intel.com/oneapi all/main i386 Packages [103 kB] Fetched 585 kB in 2s (245 kB/s) Reading package lists... Done Building dependency tree... Done Reading state information... Done 209 packages can be upgraded. Run 'apt list --upgradable' to see them. eapet@eapet-NUC12SNKi72:~/Downloads$ sudo apt install intel-basekit Reading package lists... Done Building dependency tree... Done Reading state information... Done The following packages were automatically installed and are no longer required: libgl1-amber-dri libllvm15 Use 'sudo apt autoremove' to remove them. The following additional packages will be installed: intel-basekit-getting-started intel-oneapi-advisor intel-oneapi-ccl-2021.9.0 intel-oneapi-ccl-devel intel-oneapi-ccl-devel-2021.9.0 intel-oneapi-common-licensing intel-oneapi-common-licensing-2023.1.0 intel-oneapi-common-vars intel-oneapi-compiler-cpp-eclipse-cfg intel-oneapi-compiler-dpcpp-cpp intel-oneapi-compiler-dpcpp-cpp-2023.1.0 intel-oneapi-compiler-dpcpp-cpp-common-2023.1.0 intel-oneapi-compiler-dpcpp-cpp-runtime-2023.1.0 intel-oneapi-compiler-dpcpp-eclipse-cfg intel-oneapi-compiler-shared-2023.1.0 intel-oneapi-compiler-shared-common-2023.1.0 intel-oneapi-compiler-shared-runtime-2023.1.0 intel-oneapi-condaindex intel-oneapi-dal-2023.1.0 intel-oneapi-dal-common-2023.1.0 intel-oneapi-dal-common-devel-2023.1.0 intel-oneapi-dal-devel intel-oneapi-dal-devel-2023.1.0 intel-oneapi-dev-utilities intel-oneapi-dev-utilities-2021.9.0 intel-oneapi-dev-utilities-eclipse-cfg intel-oneapi-diagnostics-utility intel-oneapi-dnnl intel-oneapi-dnnl-devel intel-oneapi-dpcpp-cpp-2023.1.0 intel-oneapi-dpcpp-ct intel-oneapi-dpcpp-ct-2023.1.0 intel-oneapi-dpcpp-ct-eclipse-cfg intel-oneapi-dpcpp-debugger intel-oneapi-dpcpp-debugger-2023.1.0 intel-oneapi-dpcpp-debugger-eclipse-cfg intel-oneapi-icc-eclipse-plugin-cpp-2023.1.0 intel-oneapi-ipp-2021.8.0 intel-oneapi-ipp-common-2021.8.0 intel-oneapi-ipp-common-devel-2021.8.0 intel-oneapi-ipp-devel intel-oneapi-ipp-devel-2021.8.0 intel-oneapi-ippcp-2021.7.0 intel-oneapi-ippcp-common-2021.7.0 intel-oneapi-ippcp-common-devel-2021.7.0 intel-oneapi-ippcp-devel intel-oneapi-ippcp-devel-2021.7.0 intel-oneapi-libdpstd-devel intel-oneapi-libdpstd-devel-2022.1.0 intel-oneapi-mkl-2023.1.0 intel-oneapi-mkl-common-2023.1.0 intel-oneapi-mkl-common-devel-2023.1.0 intel-oneapi-mkl-devel intel-oneapi-mkl-devel-2023.1.0 intel-oneapi-mpi-2021.9.0 intel-oneapi-mpi-devel-2021.9.0 intel-oneapi-openmp-2023.1.0 intel-oneapi-openmp-common-2023.1.0 intel-oneapi-tbb-2021.9.0 intel-oneapi-tbb-common-2021.9.0 intel-oneapi-tbb-common-devel-2021.9.0 intel-oneapi-tbb-devel intel-oneapi-tbb-devel-2021.9.0 intel-oneapi-vtune intel-oneapi-vtune-eclipse-plugin-vtune libssl-dev libssl3 Suggested packages: libssl-doc The following NEW packages will be installed: intel-basekit intel-basekit-getting-started intel-oneapi-advisor intel-oneapi-ccl-2021.9.0 intel-oneapi-ccl-devel intel-oneapi-ccl-devel-2021.9.0 intel-oneapi-common-licensing intel-oneapi-common-licensing-2023.1.0 intel-oneapi-common-vars intel-oneapi-compiler-cpp-eclipse-cfg intel-oneapi-compiler-dpcpp-cpp intel-oneapi-compiler-dpcpp-cpp-2023.1.0 intel-oneapi-compiler-dpcpp-cpp-common-2023.1.0 intel-oneapi-compiler-dpcpp-cpp-runtime-2023.1.0 intel-oneapi-compiler-dpcpp-eclipse-cfg intel-oneapi-compiler-shared-2023.1.0 intel-oneapi-compiler-shared-common-2023.1.0 intel-oneapi-compiler-shared-runtime-2023.1.0 intel-oneapi-condaindex intel-oneapi-dal-2023.1.0 intel-oneapi-dal-common-2023.1.0 intel-oneapi-dal-common-devel-2023.1.0 intel-oneapi-dal-devel intel-oneapi-dal-devel-2023.1.0 intel-oneapi-dev-utilities intel-oneapi-dev-utilities-2021.9.0 intel-oneapi-dev-utilities-eclipse-cfg intel-oneapi-diagnostics-utility intel-oneapi-dnnl intel-oneapi-dnnl-devel intel-oneapi-dpcpp-cpp-2023.1.0 intel-oneapi-dpcpp-ct intel-oneapi-dpcpp-ct-2023.1.0 intel-oneapi-dpcpp-ct-eclipse-cfg intel-oneapi-dpcpp-debugger intel-oneapi-dpcpp-debugger-2023.1.0 intel-oneapi-dpcpp-debugger-eclipse-cfg intel-oneapi-icc-eclipse-plugin-cpp-2023.1.0 intel-oneapi-ipp-2021.8.0 intel-oneapi-ipp-common-2021.8.0 intel-oneapi-ipp-common-devel-2021.8.0 intel-oneapi-ipp-devel intel-oneapi-ipp-devel-2021.8.0 intel-oneapi-ippcp-2021.7.0 intel-oneapi-ippcp-common-2021.7.0 intel-oneapi-ippcp-common-devel-2021.7.0 intel-oneapi-ippcp-devel intel-oneapi-ippcp-devel-2021.7.0 intel-oneapi-libdpstd-devel intel-oneapi-libdpstd-devel-2022.1.0 intel-oneapi-mkl-2023.1.0 intel-oneapi-mkl-common-2023.1.0 intel-oneapi-mkl-common-devel-2023.1.0 intel-oneapi-mkl-devel intel-oneapi-mkl-devel-2023.1.0 intel-oneapi-mpi-2021.9.0 intel-oneapi-mpi-devel-2021.9.0 intel-oneapi-openmp-2023.1.0 intel-oneapi-openmp-common-2023.1.0 intel-oneapi-tbb-2021.9.0 intel-oneapi-tbb-common-2021.9.0 intel-oneapi-tbb-common-devel-2021.9.0 intel-oneapi-tbb-devel intel-oneapi-tbb-devel-2021.9.0 intel-oneapi-vtune intel-oneapi-vtune-eclipse-plugin-vtune libssl-dev The following packages will be upgraded: libssl3 1 upgraded, 67 newly installed, 0 to remove and 208 not upgraded. Need to get 2832 MB of archives. After this operation, 14.9 GB of additional disk space will be used. Do you want to continue? [Y/n] Get:1 http://tw.archive.ubuntu.com/ubuntu jammy-updates/main amd64 libssl3 amd64 3.0.2-0ubuntu1.10 [1901 kB] Get:2 http://tw.archive.ubuntu.com/ubuntu jammy-updates/main amd64 libssl-dev amd64 3.0.2-0ubuntu1.10 [2372 kB] Get:3 https://apt.repos.intel.com/oneapi all/main all intel-basekit-getting-started all 2023.1.0-46401 [3760 B] Get:4 https://apt.repos.intel.com/oneapi all/main all intel-oneapi-common-licensing-2023.1.0 all 2023.1.0-43473 [30.5 kB] Get:5 https://apt.repos.intel.com/oneapi all/main all intel-oneapi-common-vars all 2023.1.0-43473 [11.6 kB] Get:6 https://apt.repos.intel.com/oneapi all/main all intel-oneapi-common-licensing all 2023.1.0-43473 [2148 B] Get:7 https://apt.repos.intel.com/oneapi all/main all intel-oneapi-dpcpp-ct-eclipse-cfg all 2023.1.0-44450 [2012 B] Get:8 https://apt.repos.intel.com/oneapi all/main amd64 intel-oneapi-dpcpp-ct-2023.1.0 amd64 2023.1.0-44450 [30.6 MB] Get:9 https://apt.repos.intel.com/oneapi all/main amd64 intel-oneapi-dpcpp-ct amd64 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amd64 2023.1.0-46343 [221 kB] Get:68 https://apt.repos.intel.com/oneapi all/main amd64 intel-basekit amd64 2023.1.0-46401 [2132 B] Fetched 2832 MB in 20min 11s (2339 kB/s) Extracting templates from packages: 100% Preconfiguring packages ... 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Setting up libssl-dev:amd64 (3.0.2-0ubuntu1.10) ... Setting up intel-oneapi-condaindex (2023.1.0-43291) ... Setting up intel-basekit-getting-started (2023.1.0-46401) ... Setting up intel-oneapi-common-vars (2023.1.0-43473) ... Setting up intel-oneapi-libdpstd-devel-2022.1.0 (2022.1.0-43490) ... Setting up intel-oneapi-dal-common-2023.1.0 (2023.1.0-46349) ... Setting up intel-oneapi-dpcpp-debugger-eclipse-cfg (2023.1.0-43513) ... Setting up intel-oneapi-advisor (2023.1.0-43480) ... Setting up intel-oneapi-mpi-2021.9.0 (2021.9.0-43482) ... Setting up intel-oneapi-ippcp-common-2021.7.0 (2021.7.0-43492) ... Setting up intel-oneapi-ippcp-2021.7.0 (2021.7.0-43492) ... Setting up intel-oneapi-compiler-cpp-eclipse-cfg (2023.1.0-46305) ... Setting up intel-oneapi-openmp-common-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-vtune (2023.1.0-44286) ... C compiler version: 11.3.0 Make version: 4.3 Kernel version: 6.2.16-060216-generic Cleaning workspaces ... Done Building socperf driver ... warning: the compiler differs from the one used to build the kernel The kernel was built by: x86_64-linux-gnu-gcc-12 (Ubuntu 12.2.0-17ubuntu1) 12.2.0 You are using: gcc (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0 gcc: error: unrecognized command-line option ‘-ftrivial-auto-var-init=zero’ make[3]: *** [scripts/Makefile.build:252: /opt/intel/oneapi/vtune/2023.1.0/sepdk/src/socperf/src/socperfdrv.o] Error 1 make[3]: *** Waiting for unfinished jobs.... gcc: error: unrecognized command-line option ‘-ftrivial-auto-var-init=zero’ make[3]: *** [scripts/Makefile.build:252: /opt/intel/oneapi/vtune/2023.1.0/sepdk/src/socperf/src/control.o] Error 1 gcc: error: unrecognized command-line option ‘-ftrivial-auto-var-init=zero’ make[3]: *** [scripts/Makefile.build:252: /opt/intel/oneapi/vtune/2023.1.0/sepdk/src/socperf/src/utility.o] Error 1 gcc: error: unrecognized command-line option ‘-ftrivial-auto-var-init=zero’ make[3]: *** [scripts/Makefile.build:252: /opt/intel/oneapi/vtune/2023.1.0/sepdk/src/socperf/src/pmu_list.o] Error 1 make[2]: *** [Makefile:2027: /opt/intel/oneapi/vtune/2023.1.0/sepdk/src/socperf/src] Error 2 make[1]: *** [Makefile:145: default] Error 2 make: *** [Makefile:210: default] Error 2 Failed to build the drivers Warning: the following driver(s) were not found loaded in the kernel: sep5. Warning: no vtsspp driver was found loaded in the kernel. Warning: skipping SOCWATCH driver unload, not built Warning: the following driver(s) were not found loaded in the kernel: socperf3. The PAX service is not loaded anymore. Creating group vtune ... done PYTHON is set to python3 ERROR: sep5 driver "sep5-x32_64-6.2.16-060216-genericsmp.ko" was not found in directory "." ! This means you may need to build sep5 driver from the provided driver sources. Please see the driver README for instructions. Note: Ensure that the driver is built for kernel version 6.2.16-060216-generic Configuring sep5 boot script with the following options: driver files = /opt/intel/oneapi/vtune/2023.1.0/sepdk/src/. Creating systemd load script /usr/local/sbin/sep5-load.sh ... done. Creating systemd boot config file /lib/systemd/system/sep5.service ... done. Configuring autoload of sep5.service service ... Created symlink /etc/systemd/system/multi-user.target.wants/sep5.service → /lib/systemd/system/sep5.service. Job for sep5.service failed because the control process exited with error code. See "systemctl status sep5.service" and "journalctl -xeu sep5.service" for details. WARNING: systemctl start returned error 1 ... done. Setting up intel-oneapi-mpi-devel-2021.9.0 (2021.9.0-43482) ... Setting up intel-oneapi-tbb-common-2021.9.0 (2021.9.0-43484) ... Setting up intel-oneapi-ipp-common-2021.8.0 (2021.8.0-46345) ... Setting up intel-oneapi-dpcpp-debugger-2023.1.0 (2023.1.0-43513) ... Setting up intel-oneapi-compiler-dpcpp-eclipse-cfg (2023.1.0-46305) ... Setting up intel-oneapi-compiler-shared-common-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-openmp-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-tbb-common-devel-2021.9.0 (2021.9.0-43484) ... Setting up intel-oneapi-dev-utilities-eclipse-cfg (2021.9.0-44447) ... Setting up intel-oneapi-dal-common-devel-2023.1.0 (2023.1.0-46349) ... Setting up intel-oneapi-mkl-common-2023.1.0 (2023.1.0-46342) ... Setting up intel-oneapi-ippcp-common-devel-2021.7.0 (2021.7.0-43492) ... Setting up intel-oneapi-tbb-2021.9.0 (2021.9.0-43484) ... Setting up intel-oneapi-ipp-2021.8.0 (2021.8.0-46345) ... Setting up intel-oneapi-libdpstd-devel (2022.1.0-43490) ... Setting up intel-oneapi-ippcp-devel-2021.7.0 (2021.7.0-43492) ... Setting up intel-oneapi-diagnostics-utility (2022.3.0-43897) ... Setting up intel-oneapi-mkl-common-devel-2023.1.0 (2023.1.0-46342) ... Setting up intel-oneapi-ipp-common-devel-2021.8.0 (2021.8.0-46345) ... Setting up intel-oneapi-dpcpp-ct-eclipse-cfg (2023.1.0-44450) ... Setting up intel-oneapi-ccl-2021.9.0 (2021.9.0-43543) ... Setting up intel-oneapi-compiler-shared-runtime-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-compiler-dpcpp-cpp-common-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-ippcp-devel (2021.7.0-43492) ... Setting up intel-oneapi-ccl-devel-2021.9.0 (2021.9.0-43543) ... Setting up intel-oneapi-dpcpp-debugger (2023.1.0-43513) ... Setting up intel-oneapi-ccl-devel (2021.9.0-43543) ... Setting up intel-oneapi-dpcpp-ct-2023.1.0 (2023.1.0-44450) ... Setting up intel-oneapi-ipp-devel-2021.8.0 (2021.8.0-46345) ... Setting up intel-oneapi-dpcpp-ct (2023.1.0-44450) ... Setting up intel-oneapi-tbb-devel-2021.9.0 (2021.9.0-43484) ... Setting up intel-oneapi-dev-utilities-2021.9.0 (2021.9.0-44447) ... Setting up intel-oneapi-tbb-devel (2021.9.0-43484) ... Setting up intel-oneapi-compiler-shared-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-compiler-dpcpp-cpp-runtime-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-dev-utilities (2021.9.0-44447) ... Setting up intel-oneapi-dal-2023.1.0 (2023.1.0-46349) ... Setting up intel-oneapi-ipp-devel (2021.8.0-46345) ... Setting up intel-oneapi-dal-devel-2023.1.0 (2023.1.0-46349) ... Setting up intel-oneapi-dal-devel (2023.1.0-46349) ... Setting up intel-oneapi-dpcpp-cpp-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-dnnl (2023.1.0-46343) ... Setting up intel-oneapi-mkl-2023.1.0 (2023.1.0-46342) ... Setting up intel-oneapi-compiler-dpcpp-cpp-2023.1.0 (2023.1.0-46305) ... Setting up intel-oneapi-compiler-dpcpp-cpp (2023.1.0-46305) ... Setting up intel-oneapi-dnnl-devel (2023.1.0-46343) ... Setting up intel-oneapi-mkl-devel-2023.1.0 (2023.1.0-46342) ... Setting up intel-oneapi-mkl-devel (2023.1.0-46342) ... Setting up intel-basekit (2023.1.0-46401) ... Processing triggers for libc-bin (2.35-0ubuntu3.1) ... eapet@eapet-NUC12SNKi72:~$ python3 -m venv ipex eapet@eapet-NUC12SNKi72:~$ source ipex/bin/activate (ipex) eapet@eapet-NUC12SNKi72:~$ python -m pip install torch==1.13.0a0+git6c9b55e torchvision==0.14.1a0 intel_extension_for_pytorch==1.13.120+xpu -f https://developer.intel.com/ipex-whl-stable-xpu Looking in links: https://developer.intel.com/ipex-whl-stable-xpu DEPRECATION: The HTML index page being used (https://www.intel.com/content/dam/develop/external/us/en/documents/ipex/whl-stable-xpu.html) is not a proper HTML 5 document. This is in violation of PEP 503 which requires these pages to be well-formed HTML 5 documents. Please reach out to the owners of this index page, and ask them to update this index page to a valid HTML 5 document. pip 22.2 will enforce this behaviour change. Discussion can be found at https://github.com/pypa/pip/issues/10825 Collecting torch==1.13.0a0+git6c9b55e Downloading https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/torch-1.13.0a0%2Bgit6c9b55e-cp310-cp310-linux_x86_64.whl (138.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 138.6/138.6 MB 5.7 MB/s eta 0:00:00 Collecting torchvision==0.14.1a0 Downloading https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/torchvision-0.14.1a0%2B5e8e2f1-cp310-cp310-linux_x86_64.whl (728 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 728.8/728.8 KB 651.5 kB/s eta 0:00:00 Collecting intel_extension_for_pytorch==1.13.120+xpu Downloading https://intel-extension-for-pytorch.s3.amazonaws.com/ipex_stable/xpu/intel_extension_for_pytorch-1.13.120%2Bxpu-cp310-cp310-linux_x86_64.whl (474.7 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 474.7/474.7 MB 3.8 MB/s eta 0:00:00 Collecting typing-extensions Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB) Collecting numpy Using cached numpy-1.25.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (17.6 MB) Collecting requests Using cached requests-2.31.0-py3-none-any.whl (62 kB) Collecting pillow!=8.3.*,>=5.3.0 Using cached Pillow-10.0.0-cp310-cp310-manylinux_2_28_x86_64.whl (3.4 MB) Collecting psutil Downloading psutil-5.9.5-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (282 kB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 282.1/282.1 KB 1.2 MB/s eta 0:00:00 Collecting charset-normalizer<4,>=2 Using cached charset_normalizer-3.1.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (199 kB) Collecting urllib3<3,>=1.21.1 Using cached urllib3-2.0.3-py3-none-any.whl (123 kB) Collecting idna<4,>=2.5 Using cached idna-3.4-py3-none-any.whl (61 kB) Collecting certifi>=2017.4.17 Using cached certifi-2023.5.7-py3-none-any.whl (156 kB) Installing collected packages: urllib3, typing-extensions, psutil, pillow, numpy, idna, charset-normalizer, certifi, torch, requests, intel_extension_for_pytorch, torchvision Successfully installed certifi-2023.5.7 charset-normalizer-3.1.0 idna-3.4 intel_extension_for_pytorch-1.13.120+xpu numpy-1.25.0 pillow-10.0.0 psutil-5.9.5 requests-2.31.0 torch-1.13.0a0+git6c9b55e torchvision-0.14.1a0+5e8e2f1 typing-extensions-4.7.1 urllib3-2.0.3 (ipex) eapet@eapet-NUC12SNKi72:~$ python Downloads/collect_env.py /home/eapet/ipex/lib/python3.10/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: warn(f"Failed to load image Python extension: {e}") Collecting environment information... PyTorch version: 1.13.0a0+git6c9b55e PyTorch CXX11 ABI: Yes IPEX version: 1.13.120+xpu IPEX commit: c2a37012e Build type: Release OS: Ubuntu 22.04.2 LTS (x86_64) GCC version: (Ubuntu 11.3.0-1ubuntu1~22.04.1) 11.3.0 Clang version: N/A IGC version: 2023.1.0 (2023.1.0.20230320) CMake version: N/A Libc version: glibc-2.35 Python version: 3.10.6 (main, May 29 2023, 11:10:38) [GCC 11.3.0] (64-bit runtime) Python platform: Linux-6.2.16-060216-generic-x86_64-with-glibc2.35 Is XPU available: True DPCPP runtime version: 2023.1.0 MKL version: 2023.1.0 GPU models and configuration: [0] _DeviceProperties(name='Intel(R) Arc(TM) A770M Graphics', platform_name='Intel(R) Level-Zero', dev_type='gpu, support_fp64=0, total_memory=15473MB, max_compute_units=512) [1] _DeviceProperties(name='Intel(R) Graphics [0x46a6]', platform_name='Intel(R) Level-Zero', dev_type='gpu, support_fp64=0, total_memory=25313MB, max_compute_units=96) Intel OpenCL ICD version: 23.17.26241.21-647~22.04 Level Zero version: 1.3.26241.21-647~22.04 CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 39 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 20 On-line CPU(s) list: 0-19 Vendor ID: GenuineIntel Model name: 12th Gen Intel(R) Core(TM) i7-12700H CPU family: 6 Model: 154 Thread(s) per core: 2 Core(s) per socket: 14 Socket(s): 1 Stepping: 3 CPU max MHz: 4700.0000 CPU min MHz: 400.0000 BogoMIPS: 5376.00 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe syscall nx pdpe1gb rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr ibt flush_l1d arch_capabilities Virtualization: VT-x L1d cache: 544 KiB (14 instances) L1i cache: 704 KiB (14 instances) L2 cache: 11.5 MiB (8 instances) L3 cache: 24 MiB (1 instance) NUMA node(s): 1 NUMA node0 CPU(s): 0-19 Vulnerability Itlb multihit: Not affected Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Not affected Vulnerability Retbleed: Not affected Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization Vulnerability Spectre v2: Mitigation; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected Versions of relevant libraries: [pip3] intel-extension-for-pytorch==1.13.120+xpu [pip3] numpy==1.25.0 [pip3] torch==1.13.0a0+git6c9b55e [pip3] torchvision==0.14.1a0+5e8e2f1 [conda] N/A (ipex) eapet@eapet-NUC12SNKi72:~$ (ipex) eapet@eapet-NUC12SNKi72:~$ (ipex) eapet@eapet-NUC12SNKi72:~$ python Python 3.10.6 (main, May 29 2023, 11:10:38) [GCC 11.3.0] on linux Type "help", "copyright", "credits" or "license" for more information. >>> import torch >>> import torchvision /home/eapet/ipex/lib/python3.10/site-packages/torchvision/io/image.py:13: UserWarning: Failed to load image Python extension: warn(f"Failed to load image Python extension: {e}") >>> ############# code changes ############### >>> import intel_extension_for_pytorch as ipex >>> ############# code changes ############### >>> >>> LR = 0.001 >>> DOWNLOAD = True >>> DATA = 'datasets/cifar10/' >>> >>> transform = torchvision.transforms.Compose([ ... torchvision.transforms.Resize((224, 224)), ... torchvision.transforms.ToTensor(), ... torchvision.transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5)) ... ]) >>> train_dataset = torchvision.datasets.CIFAR10( ... root=DATA, ... train=True, ... transform=transform, ... download=DOWNLOAD, ... ) Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to datasets/cifar10/cifar-10-python.tar.gz 100.0% Extracting datasets/cifar10/cifar-10-python.tar.gz to datasets/cifar10/ >>> train_loader = torch.utils.data.DataLoader( ... dataset=train_dataset, ... batch_size=128 ... ) >>> >>> model = torchvision.models.resnet50() >>> criterion = torch.nn.CrossEntropyLoss() >>> optimizer = torch.optim.SGD(model.parameters(), lr = LR, momentum=0.9) >>> model.train() ResNet( (conv1): Conv2d(3, 64, kernel_size=(7, 7), stride=(2, 2), padding=(3, 3), bias=False) (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (maxpool): MaxPool2d(kernel_size=3, stride=2, padding=1, dilation=1, ceil_mode=False) (layer1): Sequential( (0): Bottleneck( (conv1): Conv2d(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(64, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) (layer2): Sequential( (0): Bottleneck( (conv1): Conv2d(256, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(256, 512, kernel_size=(1, 1), stride=(2, 2), bias=False) (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (3): Bottleneck( (conv1): Conv2d(512, 128, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(128, 128, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(128, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) (layer3): Sequential( (0): Bottleneck( (conv1): Conv2d(512, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(512, 1024, kernel_size=(1, 1), stride=(2, 2), bias=False) (1): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (3): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (4): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (5): Bottleneck( (conv1): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(256, 1024, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) (layer4): Sequential( (0): Bottleneck( (conv1): Conv2d(1024, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False) (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) (downsample): Sequential( (0): Conv2d(1024, 2048, kernel_size=(1, 1), stride=(2, 2), bias=False) (1): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) ) ) (1): Bottleneck( (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) (2): Bottleneck( (conv1): Conv2d(2048, 512, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv2): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False) (bn2): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (conv3): Conv2d(512, 2048, kernel_size=(1, 1), stride=(1, 1), bias=False) (bn3): BatchNorm2d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True) (relu): ReLU(inplace=True) ) ) (avgpool): AdaptiveAvgPool2d(output_size=(1, 1)) (fc): Linear(in_features=2048, out_features=1000, bias=True) ) >>> ######################## code changes ####################### >>> model = model.to("xpu") >>> criterion = criterion.to("xpu") >>> model, optimizer = ipex.optimize(model, optimizer=optimizer) /home/eapet/ipex/lib/python3.10/site-packages/intel_extension_for_pytorch/frontend.py:484: UserWarning: Split Master Weight feature is not supported on XPU for now, disabled. warnings.warn("Split Master Weight feature is not supported on XPU for now, disabled.") /home/eapet/ipex/lib/python3.10/site-packages/intel_extension_for_pytorch/frontend.py:494: UserWarning: To reduce device memory usage on XPU, optimization are done inplace, setting the inplace argument to True. warnings.warn( /home/eapet/ipex/lib/python3.10/site-packages/intel_extension_for_pytorch/frontend.py:500: UserWarning: Weight Prepack and Sample Input are both disabled on XPU. The Onednn Layout is automatically applied. warnings.warn( >>> ######################## code changes ####################### >>> >>> for batch_idx, (data, target) in enumerate(train_loader): ... ########## code changes ########## ... data = data.to("xpu") ... target = target.to("xpu") ... ########## code changes ########## ... optimizer.zero_grad() ... output = model(data) ... loss = criterion(output, target) ... loss.backward() ... optimizer.step() ... print(batch_idx) ... torch.save({ File "<stdin>", line 12 torch.save({ ^^^^^ SyntaxError: invalid syntax >>> 'model_state_dict': model.state_dict(), File "<stdin>", line 1 'model_state_dict': model.state_dict(), IndentationError: unexpected indent >>> 'optimizer_state_dict': optimizer.state_dict(), File "<stdin>", line 1 'optimizer_state_dict': optimizer.state_dict(), IndentationError: unexpected indent >>> }, 'checkpoint.pth') File "<stdin>", line 1 }, 'checkpoint.pth') IndentationError: unexpected indent >>> >>> >>> >>> for batch_idx, (data, target) in enumerate(train_loader): ... ########## code changes ########## ... data = data.to("xpu") ... target = target.to("xpu") ... ########## code changes ########## ... optimizer.zero_grad() ... output = model(data) ... loss = criterion(output, target) ... loss.backward() ... optimizer.step() ... print(batch_idx) ... 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 ^CTraceback (most recent call last): File "<stdin>", line 9, in <module> File "/home/eapet/ipex/lib/python3.10/site-packages/torch/_tensor.py", line 488, in backward torch.autograd.backward( File "/home/eapet/ipex/lib/python3.10/site-packages/torch/autograd/__init__.py", line 197, in backward Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass KeyboardInterrupt >>> exit() (ipex) eapet@eapet-NUC12SNKi72:~$ ```