Repository: pytorch
Issue: torch.nn.functional.pad() with value type bool
Labels: oncall: jit

### 🐛 Describe the bug

```
@torch.jit.script
def fn():
    a = torch.zeros(10, dtype=torch.bool)
    a = F.pad(a, (1,1), value=True)
    return a
```

Error:
```
aten::pad(Tensor self, SymInt[] pad, str mode="constant", float? value=None) -> Tensor:
Expected a value of type 'Optional[float]' for argument 'value' but instead found type 'bool'.
:
  File ..., line ...
def fn():
    a = torch.zeros(10, dtype=torch.bool)
    a = F.pad(a, (1,1), value=True)
        ~~~~~ <--- HERE
    return a
```

### 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 22.04.2 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 3.27.1
Libc version: glibc-2.35

Python version: 3.10.12 (main, Jun 11 2023, 05:26:28) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.2.0-26-generic-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
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:                   45 bits physical, 48 bits virtual
Byte Order:                      Little Endian
CPU(s):                          8
On-line CPU(s) list:             0-7
Vendor ID:                       GenuineIntel
Model name:                      11th Gen Intel(R) Core(TM) i9-11950H @ 2.60GHz
CPU family:                      6
Model:                           141
Thread(s) per core:              1
Core(s) per socket:              1
Socket(s):                       8
Stepping:                        1
BogoMIPS:                        5222.40
Flags:                           fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss syscall nx pdpe1gb rdtscp lm constant_tsc arch_perfmon rep_good nopl xtopology tsc_reliable nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat avx512vbmi umip avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid fsrm avx512_vp2intersect flush_l1d arch_capabilities
Hypervisor vendor:               VMware
Virtualisation type:             full
L1d cache:                       384 KiB (8 instances)
L1i cache:                       256 KiB (8 instances)
L2 cache:                        10 MiB (8 instances)
L3 cache:                        192 MiB (8 instances)
NUMA node(s):                    1
NUMA node0 CPU(s):               0-7
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Mitigation; PTE Inversion
Vulnerability Mds:               Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Meltdown:          Mitigation; PTI
Vulnerability Mmio stale data:   Not affected
Vulnerability Retbleed:          Mitigation; IBRS
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; IBRS, 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] numpy==1.24.4
[pip3] pytorch-lightning==2.0.6
[pip3] recurrent-memory-transformer-pytorch==0.5.3
[pip3] torch==2.0.1
[pip3] torchaudio==2.0.2
[pip3] torchmetrics==1.0.3
[pip3] triton==2.0.0
[conda] Could not collect

cc @EikanWang @jgong5 @wenzhe-nrv @sanchitintel