Repository: pytorch
Issue: torch.utils.cpp_extension.load recompiling every time
Labels: module: cpp-extensions,triaged

### 🐛 Describe the bug

When I run `torch.utils.cpp_extension.load`, it will recompile every single time, regardless of whether or not the source files actually changed. For example, when I run

```
myext = torch.utils.cpp_extension.load(
    name='myext',
    sources='./images2triplanes.cu',
    build_directory='build/',
    with_cuda=True,
    extra_cuda_cflags=['-O3'],
    keep_intermediates=True,
    verbose=True
)
```
The stdout will print `Emitting ninja build file build/build.ninja...` every single time, even though a `build/myext.so` file is already present and I did not touch the source files. In principle, `load(...)` should not re-compile the files if there is no change to the source code and the .so is already present.

The likely cause is that the [JIT_EXTENSION_VERSIONER](https://github.com/pytorch/pytorch/blob/e620c3e814ee85f252d62b2ca07090a2b7253131/torch/utils/cpp_extension.py#L249) object which stores the existing version numbers for pytorch extensions is just a local variable which obviously does not persist between runs. As a result [this if-statement](https://github.com/pytorch/pytorch/blob/e620c3e814ee85f252d62b2ca07090a2b7253131/torch/utils/cpp_extension.py#L1694) will always be triggered on the first `cpp_extension.load(...)` call because `old_version` will be `None`

I observed this issue in Pytorch nightly, Pytorch 2.2, and 2.1

### Versions

Collecting environment information...
PyTorch version: 2.4.0.dev20240418
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Pop!_OS 22.04 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: version 3.28.3
Libc version: glibc-2.35

Python version: 3.10.14 (main, Mar 21 2024, 16:24:04) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-6.6.10-76060610-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.1.66
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090
Nvidia driver version: 545.29.06
cuDNN version: Could not collect
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:                      46 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) i7-12700K
CPU family:                         6
Model:                              151
Thread(s) per core:                 2
Core(s) per socket:                 12
Socket(s):                          1
Stepping:                           2
CPU max MHz:                        5000.0000
CPU min MHz:                        800.0000
BogoMIPS:                           7219.20
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 sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l2 cdp_l2 ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdt_a rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect user_shstk avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi vnmi umip pku ospke waitpkg gfni vaes vpclmulqdq tme rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr ibt flush_l1d arch_capabilities
Virtualization:                     VT-x
L1d cache:                          512 KiB (12 instances)
L1i cache:                          512 KiB (12 instances)
L2 cache:                           12 MiB (9 instances)
L3 cache:                           25 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-19
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:             Not affected
Vulnerability Spec rstack overflow: 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 / Automatic IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Not affected

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.4.0.dev20240418
[pip3] torchaudio==2.2.0.dev20240418
[pip3] torchvision==0.19.0.dev20240418
[pip3] triton==3.0.0
[conda] blas                      1.0                         mkl  
[conda] libjpeg-turbo             2.0.0                h9bf148f_0    pytorch-nightly
[conda] mkl                       2023.1.0         h213fc3f_46344  
[conda] mkl-service               2.4.0           py310h5eee18b_1  
[conda] mkl_fft                   1.3.8           py310h5eee18b_0  
[conda] mkl_random                1.2.4           py310hdb19cb5_0  
[conda] numpy                     1.26.4          py310h5f9d8c6_0  
[conda] numpy-base                1.26.4          py310hb5e798b_0  
[conda] pytorch                   2.4.0.dev20240418 py3.10_cuda12.1_cudnn8.9.2_0    pytorch-nightly
[conda] pytorch-cuda              12.1                 ha16c6d3_5    pytorch-nightly
[conda] pytorch-mutex             1.0                        cuda    pytorch-nightly
[conda] torchaudio                2.2.0.dev20240418     py310_cu121    pytorch-nightly
[conda] torchtriton               3.0.0+989adb9a29           py310    pytorch-nightly
[conda] torchvision               0.19.0.dev20240418     py310_cu121    pytorch-nightly

cc @malfet @zou3519