torch pollutes libgomp symbols when import _C
Labels: oncall: binaries, triaged, module: openmp, module: third_party

### 🐛 Describe the bug

In torch `__init__.py`, the _C library is imported with the `RTLD_GLOBAL` mode. It pollutes the global symbols provided by libgomp. When importing other libraries later, symbols and functions from libgomp are resolved to the libgomp library provided by pytorch. This name pollution causes bugs when using pytorch and libraries that rely on libgomp. One may receive segfault or strange results due to version conflicts in libgomp.

I noticed that in `__init__.py`, this behavior is controlled by the variable `USE_GLOBAL_DEPS`. Disabling this option can solve the problem. Is there a way to configure this variable at runtime?

### 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: Ubuntu 20.04.2 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 3.27.4
Libc version: glibc-2.31

Python version: 3.10.10 (main, Mar 21 2023, 18:45:11) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.11.0-36-generic-x86_64-with-glibc2.31
Is CUDA available: True
CUDA runtime version: 10.1.243
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce GTX 1050 Ti
Nvidia driver version: 470.199.02
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
Byte Order:                      Little Endian
Address sizes:                   46 bits physical, 48 bits virtual
CPU(s):                          28
On-line CPU(s) list:             0-27
Thread(s) per core:              2
Core(s) per socket:              14
Socket(s):                       1
NUMA node(s):                    1
Vendor ID:                       GenuineIntel
CPU family:                      6
Model:                           85
Model name:                      Intel(R) Core(TM) i9-7940X CPU @ 3.10GHz
Stepping:                        4
CPU MHz:                         3100.000
CPU max MHz:                     4400.0000
CPU min MHz:                     1200.0000
BogoMIPS:                        6199.99
Virtualization:                  VT-x
L1d cache:                       448 KiB
L1i cache:                       448 KiB
L2 cache:                        14 MiB
L3 cache:                        19.3 MiB
NUMA node0 CPU(s):               0-27
Vulnerability Itlb multihit:     KVM: Mitigation: VMX disabled
Vulnerability L1tf:              Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable
Vulnerability Mds:               Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown:          Mitigation; PTI
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; Full generic retpoline, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Mitigation; Clear CPU buffers; SMT vulnerable
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 rd
tscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr p
dcm 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 cdp_l3 invpcid_single pti ssbd mb
a ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clf
lushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window h
wp_epp hwp_pkg_req md_clear flush_l1d arch_capabilities

Versions of relevant libraries:
[pip3] numpy==1.25.2
[pip3] torch==2.0.1
[pip3] triton==2.0.0
[conda] cudatoolkit               10.1.243             h6bb024c_0  
[conda] mkl                       2019.0                      118  
[conda] mkl-service               1.1.2            py37h90e4bf4_5  
[conda] mkl_fft                   1.0.4            py37h4414c95_1  
[conda] mkl_random                1.0.1            py37h4414c95_1  
[conda] numpy                     1.21.6                    <pip>
[conda] numpy                     1.15.4           py37h99e49ec_0  
[conda] numpy-base                1.15.4           py37h2f8d375_0  
[conda] numpydoc                  0.8.0                    py37_0  
[conda] pytorch                   1.3.1           py3.7_cuda10.1.243_cudnn7.6.3_0    pytorch

cc @seemethere @malfet