Something wrong in executorch/extension/training /README.md #15991
Description
🐛 Describe the bug
In the "Run the model train script with CMAKE" part, the way to configure cmake is wrong. It shows that
"Use of 'EXECUTORCH_BUILD_EXTENSION_MODULE' requires
'EXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR'".
So we should run: cmake
-DCMAKE_INSTALL_PREFIX=cmake-out
-DCMAKE_BUILD_TYPE=Release
-DEXECUTORCH_BUILD_EXTENSION_DATA_LOADER=ON
-DEXECUTORCH_BUILD_EXTENSION_MODULE=ON
-DEXECUTORCH_BUILD_EXTENSION_FLAT_TENSOR=ON
-DEXECUTORCH_BUILD_EXTENSION_TENSOR=ON
-DEXECUTORCH_BUILD_EXTENSION_TRAINING=ON
-DEXECUTORCH_ENABLE_LOGGING=ON
-DPYTHON_EXECUTABLE=python
-Bcmake-out .
Versions
Collecting environment information...
PyTorch version: 2.7.1+cu126
Is debug build: False
CUDA used to build PyTorch: 12.6
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.6 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.2) 9.4.0
Clang version: 10.0.0-4ubuntu1
CMake version: version 3.16.3
Libc version: glibc-2.31
Python version: 3.10.12 | packaged by conda-forge | (main, Jun 23 2023, 22:40:32) [GCC 12.3.0] (64-bit runtime)
Python platform: Linux-5.4.0-216-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA A40
GPU 1: NVIDIA A40
GPU 2: NVIDIA A40
GPU 3: NVIDIA A100-PCIE-40GB
GPU 4: NVIDIA A40
GPU 5: NVIDIA A40
GPU 6: NVIDIA A40
GPU 7: NVIDIA A40
Nvidia driver version: 570.133.20
cuDNN version: Could not collect
Is XPU available: False
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
Byte Order: Little Endian
Address sizes: 46 bits physical, 57 bits virtual
CPU(s): 64
On-line CPU(s) list: 0-63
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 106
Model name: Intel(R) Xeon(R) Silver 4314 CPU @ 2.40GHz
Stepping: 6
Frequency boost: enabled
CPU MHz: 1065.310
CPU max MHz: 3400.0000
CPU min MHz: 800.0000
BogoMIPS: 4800.00
Virtualization: VT-x
L1d cache: 1.5 MiB
L1i cache: 1 MiB
L2 cache: 40 MiB
L3 cache: 48 MiB
NUMA node0 CPU(s): 0-15,32-47
NUMA node1 CPU(s): 16-31,48-63
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed: Not affected
Vulnerability Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Vulnerability Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Vulnerability Spectre v2: Mitigation; Enhanced / Automatic IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI SW loop, KVM SW loop
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Not affected
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 pni pclmulqdq dtes64 ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 invpcid_single ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid cqm rdt_a avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb intel_pt avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local wbnoinvd dtherm ida arat pln pts avx512vbmi umip pku ospke avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg tme avx512_vpopcntdq rdpid md_clear pconfig flush_l1d arch_capabilities
Versions of relevant libraries:
[pip3] flake8==4.0.1
[pip3] mkl-fft==1.3.1
[pip3] mkl-random==1.2.2
[pip3] mkl-service==2.4.0
[pip3] mypy-extensions==0.4.3
[pip3] numpy==1.24.4
[pip3] numpydoc==1.5.0
[pip3] nvidia-cublas-cu12==12.6.4.1
[pip3] nvidia-cuda-cupti-cu12==12.6.80
[pip3] nvidia-cuda-nvrtc-cu12==12.6.77
[pip3] nvidia-cuda-runtime-cu12==12.6.77
[pip3] nvidia-cudnn-cu12==9.5.1.17
[pip3] nvidia-cufft-cu12==11.3.0.4
[pip3] nvidia-curand-cu12==10.3.7.77
[pip3] nvidia-cusolver-cu12==11.7.1.2
[pip3] nvidia-cusparse-cu12==12.5.4.2
[pip3] nvidia-cusparselt-cu12==0.6.3
[pip3] nvidia-nccl-cu12==2.26.2
[pip3] nvidia-nvjitlink-cu12==12.6.85
[pip3] nvidia-nvtx-cu12==12.6.77
[pip3] onnxruntime-gpu==1.16.0
[pip3] optree==0.16.0
[pip3] pytorch-lightning==2.5.1
[pip3] torch==2.7.1
[pip3] torch-lr-scheduler==0.0.6
[pip3] torchaudio==2.7.1
[pip3] torchmetrics==1.6.3
[pip3] torchvision==0.22.1
[pip3] triton==3.3.1
[conda] blas 1.0 mkl anaconda
[conda] intel-openmp 2021.4.0 h06a4308_3561 anaconda
[conda] libblas 3.9.0 12_linux64_mkl conda-forge
[conda] libcblas 3.9.0 12_linux64_mkl conda-forge
[conda] liblapack 3.9.0 12_linux64_mkl conda-forge
[conda] mkl 2021.4.0 h06a4308_640 anaconda
[conda] mkl-service 2.4.0 py310h7f8727e_0 anaconda
[conda] mkl_fft 1.3.1 py310hd6ae3a3_0 anaconda
[conda] mkl_random 1.2.2 py310h00e6091_0 anaconda
[conda] numpy 1.24.4 pypi_0 pypi
[conda] numpydoc 1.5.0 py310h06a4308_0 anaconda
[conda] nvidia-cublas-cu12 12.6.4.1 pypi_0 pypi
[conda] nvidia-cuda-cupti-cu12 12.6.80 pypi_0 pypi
[conda] nvidia-cuda-nvrtc-cu12 12.6.77 pypi_0 pypi
[conda] nvidia-cuda-runtime-cu12 12.6.77 pypi_0 pypi
[conda] nvidia-cudnn-cu12 9.5.1.17 pypi_0 pypi
[conda] nvidia-cufft-cu12 11.3.0.4 pypi_0 pypi
[conda] nvidia-curand-cu12 10.3.7.77 pypi_0 pypi
[conda] nvidia-cusolver-cu12 11.7.1.2 pypi_0 pypi
[conda] nvidia-cusparse-cu12 12.5.4.2 pypi_0 pypi
[conda] nvidia-cusparselt-cu12 0.6.3 pypi_0 pypi
[conda] nvidia-nccl-cu12 2.26.2 pypi_0 pypi
[conda] nvidia-nvjitlink-cu12 12.6.85 pypi_0 pypi
[conda] nvidia-nvtx-cu12 12.6.77 pypi_0 pypi
[conda] optree 0.16.0 pypi_0 pypi
[conda] pytorch-lightning 2.5.1 pypi_0 pypi
[conda] tbb 2021.6.0 hdb19cb5_1 anaconda
[conda] tbb4py 2021.6.0 py310hdb19cb5_1 anaconda
[conda] torch 2.7.1 pypi_0 pypi
[conda] torch-lr-scheduler 0.0.6 pypi_0 pypi
[conda] torchaudio 2.7.1 pypi_0 pypi
[conda] torchmetrics 1.6.3 pypi_0 pypi
[conda] torchvision 0.22.1 pypi_0 pypi
[conda] triton 3.3.1 pypi_0 pypi