Closed Promootheus closed 9 months ago
Here is what happening:
1) Some python packages (onnx & pycocotools) are not available as pre-built binaries for your OS (Arch linux)
2) So pip
attempts to compile them using compiler and build tools available on your machine.
3) As the error suggests, there is a failure in installing these libraries.
There could be a number of reasons, starting from build-essential
package is not installed or unsupported compiler version. Unfortunately, log you provided is truncated and does not provide much information what exactly caused this error. You may want to run pip install pycocotools
from command line (respecting venv) and providing output of that command here.
Try installing it with Python version <3.11
Answer more responsibly, the answers are not helpful
Answer more responsibly, the answers are not helpful
I finally found the best way to install super-gradients in windows10 with vscode.
1, first you should create .venv with python version=3.10
2, install visual c++ building tools https://stackoverflow.com/questions/70726826/could-not-install-pycocotools-in-windows10
3, install pycocotools-2.0-cp310-cp310-win_amd64.whl this whl not in pypl or in any other whl website. ( I forget where to download it now and who make this whl. I share it in my google driver https://drive.google.com/file/d/1r2andfVBitZvAnvkJjxkdsqAnWwfpux9/view?usp=sharing)
this whl will solve any dependency conflicts with pycootools, finally it will be uninstall when you install super-gradients.
4, pip install super-gradients
💡 Your Question
Error below
note: This error originates from a subprocess, and is likely not a problem with pip. ERROR: Failed building wheel for onnx Running setup.py clean for onnx Building wheel for future (setup.py) ... done Created wheel for future: filename=future-0.18.3-py3-none-any.whl size=492024 sha256=9bb0ddfa9716d134642af02a842aeb2fd2ce1629c3127b93ed2a6945f695140e Stored in directory: /tmp/pip-ephem-wheel-cache-cwmjfnjt/wheels/da/19/ca/9d8c44cd311a955509d7e13da3f0bea42400c469ef825b580b Successfully built termcolor treelib coverage future Failed to build pycocotools onnx ERROR: Could not build wheels for pycocotools, onnx, which is required to install pyproject.toml-based projects
Arch Linux Python 3.11.5 Name: onnxruntime Version: 1.15.1 Name: onnxruntime-gpu Version: 1.15.1 Name: Cython Version: 3.0.2 Name: pycocotools Version: 2.0
Versions
Collecting environment information... PyTorch version: 2.0.1+cu117 Is debug build: False CUDA used to build PyTorch: 11.7 ROCM used to build PyTorch: N/A
OS: Arch Linux (x86_64) GCC version: (GCC) 13.2.1 20230801 Clang version: 16.0.6 CMake version: version 3.27.2 Libc version: glibc-2.38
Python version: 3.11.5 (main, Aug 28 2023, 20:02:58) [GCC 13.2.1 20230801] (64-bit runtime) Python platform: Linux-6.4.12-arch1-1-x86_64-with-glibc2.38 Is CUDA available: True CUDA runtime version: 12.2.91 CUDA_MODULE_LOADING set to: LAZY GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090 Nvidia driver version: 535.104.05 cuDNN version: Probably one of the following: /usr/lib/libcudnn.so.8.9.2 /usr/lib/libcudnn_adv_infer.so.8.9.2 /usr/lib/libcudnn_adv_train.so.8.9.2 /usr/lib/libcudnn_cnn_infer.so.8.9.2 /usr/lib/libcudnn_cnn_train.so.8.9.2 /usr/lib/libcudnn_ops_infer.so.8.9.2 /usr/lib/libcudnn_ops_train.so.8.9.2 HIP runtime version: N/A MIOpen runtime version: N/A Is XNNPACK available: True
CPU: Architecture: x86_64 CPU op-mode(s): 32-bit, 64-bit Address sizes: 43 bits physical, 48 bits virtual Byte Order: Little Endian CPU(s): 24 On-line CPU(s) list: 0-23 Vendor ID: AuthenticAMD Model name: AMD Ryzen Threadripper 1920X 12-Core Processor CPU family: 23 Model: 1 Thread(s) per core: 2 Core(s) per socket: 12 Socket(s): 1 Stepping: 1 Frequency boost: enabled CPU(s) scaling MHz: 73% CPU max MHz: 3500.0000 CPU min MHz: 2200.0000 BogoMIPS: 6989.71 Flags: fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ht syscall nx mmxext fxsr_opt pdpe1gb rdtscp lm constant_tsc rep_good nopl nonstop_tsc cpuid extd_apicid amd_dcm aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb hw_pstate ssbd ibpb vmmcall fsgsbase bmi1 avx2 smep bmi2 rdseed adx smap clflushopt sha_ni xsaveopt xsavec xgetbv1 clzero irperf xsaveerptr arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif overflow_recov succor smca sev Virtualization: AMD-V L1d cache: 384 KiB (12 instances) L1i cache: 768 KiB (12 instances) L2 cache: 6 MiB (12 instances) L3 cache: 32 MiB (4 instances) NUMA node(s): 2 NUMA node0 CPU(s): 0-5,12-17 NUMA node1 CPU(s): 6-11,18-23 Vulnerability Gather data sampling: Not affected 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: Mitigation; untrained return thunk; SMT vulnerable Vulnerability Spec rstack overflow: Mitigation; safe RET 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; Retpolines, IBPB conditional, STIBP disabled, RSB filling, PBRSB-eIBRS Not affected Vulnerability Srbds: Not affected Vulnerability Tsx async abort: Not affected
Versions of relevant libraries: [pip3] flake8==6.0.0 [pip3] numpy==1.25.2 [pip3] torch==2.0.1 [pip3] torchvision==0.15.2 [pip3] triton==2.0.0 [conda] numpy 1.22.3 py310h4ef5377_2 conda-forge