Repository: pytorch
Issue: Met error "we don't have an op for aten::full but it isn't a special case." when running microsoft/Florence-2-base
Labels: oncall: jit

### 🐛 Describe the bug

When running the florence-2 base model, it throw the following error:
```
RuntimeError: 0 INTERNAL ASSERT FAILED at "../torch/csrc/jit/ir/alias_analysis.cpp":616, please report a bug to PyTorch. We don't have an op for aten::full but it isn't a special case.  Argument types: int[], bool, NoneType, NoneType, Device, bool,

Candidates:
        aten::full.names(int[] size, Scalar fill_value, *, str[]? names, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
        aten::full(SymInt[] size, Scalar fill_value, *, ScalarType? dtype=None, Layout? layout=None, Device? device=None, bool? pin_memory=None) -> Tensor
        aten::full.names_out(int[] size, Scalar fill_value, *, str[]? names, Tensor(a!) out) -> Tensor(a!)
        aten::full.out(SymInt[] size, Scalar fill_value, *, Tensor(a!) out) -> Tensor(a!)
```

### Versions

PyTorch version: 2.1.2+cu121
Is debug build: False
CUDA used to build PyTorch: 12.1
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.5 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: 14.0.0-1ubuntu1.1
CMake version: version 3.22.1
Libc version: glibc-2.35

Python version: 3.10.14 | packaged by conda-forge | (main, Mar 20 2024, 12:45:18) [GCC 12.3.0] (64-bit runtime)
Python platform: Linux-5.15.0-121-generic-x86_64-with-glibc2.35
Is CUDA available: True
CUDA runtime version: 12.6.68
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA RTX A6000
GPU 1: NVIDIA RTX A6000

Nvidia driver version: 560.35.03
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:                        43 bits physical, 48 bits virtual
Byte Order:                           Little Endian
CPU(s):                               128
On-line CPU(s) list:                  0-127
Vendor ID:                            AuthenticAMD
Model name:                           AMD Ryzen Threadripper PRO 3995WX 64-Cores
CPU family:                           23
Model:                                49
Thread(s) per core:                   2
Core(s) per socket:                   64
Socket(s):                            1
Stepping:                             0
Frequency boost:                      enabled
CPU max MHz:                          4308.3979
CPU min MHz:                          2200.0000
BogoMIPS:                             5389.79
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 aperfmperf rapl pni pclmulqdq monitor ssse3 fma cx16 sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand lahf_lm cmp_legacy svm extapic cr8_legacy abm sse4a misalignsse 3dnowprefetch osvw ibs skinit wdt tce topoext perfctr_core perfctr_nb bpext perfctr_llc mwaitx cpb cat_l3 cdp_l3 hw_pstate ssbd mba ibpb stibp vmmcall fsgsbase bmi1 avx2 smep bmi2 cqm rdt_a rdseed adx smap clflushopt clwb sha_ni xsaveopt xsavec xgetbv1 cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local clzero irperf xsaveerptr rdpru wbnoinvd amd_ppin arat npt lbrv svm_lock nrip_save tsc_scale vmcb_clean flushbyasid decodeassists pausefilter pfthreshold avic v_vmsave_vmload vgif v_spec_ctrl umip rdpid overflow_recov succor smca sme sev sev_es
Virtualization:                       AMD-V
L1d cache:                            2 MiB (64 instances)
L1i cache:                            2 MiB (64 instances)
L2 cache:                             32 MiB (64 instances)
L3 cache:                             256 MiB (16 instances)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0-127
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 Reg file data sampling: Not affected
Vulnerability Retbleed:               Mitigation; untrained return thunk; SMT enabled with STIBP protection
Vulnerability Spec rstack overflow:   Mitigation; safe RET
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; Retpolines; IBPB conditional; STIBP always-on; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Not affected

Versions of relevant libraries:
[pip3] Aimet==1.34.0.0.207.0.44+torch.gpu
[pip3] AimetCommon==1.34.0.0.207.0.44+torch.gpu
[pip3] AimetTorch==1.34.0.0.207.0.44+torch.gpu
[pip3] numpy==1.23.5
[pip3] onnx==1.16.1
[pip3] onnxruntime==1.18.1
[pip3] onnxruntime_extensions==0.12.0
[pip3] onnxscript==0.1.0.dev20240923
[pip3] onnxsim==0.4.36
[pip3] torch==2.1.2+cu121
[pip3] torchvision==0.16.2+cu121
[pip3] triton==2.1.0
[conda] aimet                     1.34.0.0.207.0.44+torch.gpu          pypi_0    pypi
[conda] aimetcommon               1.34.0.0.207.0.44+torch.gpu          pypi_0    pypi
[conda] aimettorch                1.34.0.0.207.0.44+torch.gpu          pypi_0    pypi
[conda] numpy                     1.23.5                   pypi_0    pypi
[conda] torch                     2.1.2+cu121              pypi_0    pypi
[conda] torchvision               0.16.2+cu121             pypi_0    pypi
[conda] triton                    2.1.0                    pypi_0    pypi

cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel