Repository: pytorch
Issue: torch ones, zeros and empty operators with out= kwarg: SymIntArrayRef expected to contain only concrete integers
Labels: triaged,oncall: pt2,module: dynamic shapes

### 🐛 Describe the bug

torch ones, zeros and empty operators with out argument when used in torch.compile mode, reports error: SymIntArrayRef expected to contain only concrete integers

### Error logs

```
E0912 06:51:36.997000 1244 torch/_subclasses/fake_tensor.py:2017] [0/1] failed while attempting to run meta for aten.ones.out
E0912 06:51:36.997000 1244 torch/_subclasses/fake_tensor.py:2017] [0/1] Traceback (most recent call last):
E0912 06:51:36.997000 1244 torch/_subclasses/fake_tensor.py:2017] [0/1]   File "/usr/local/lib/python3.10/dist-packages/torch/_subclasses/fake_tensor.py", line 2013, in _dispatch_impl
E0912 06:51:36.997000 1244 torch/_subclasses/fake_tensor.py:2017] [0/1]     r = func(*args, **kwargs)
E0912 06:51:36.997000 1244 torch/_subclasses/fake_tensor.py:2017] [0/1]   File "/usr/local/lib/python3.10/dist-packages/torch/_ops.py", line 716, in __call__
E0912 06:51:36.997000 1244 torch/_subclasses/fake_tensor.py:2017] [0/1]     return self._op(*args, **kwargs)
E0912 06:51:36.997000 1244 torch/_subclasses/fake_tensor.py:2017] [0/1] RuntimeError: aten/src/ATen/RegisterCompositeExplicitAutograd.cpp:3324: SymIntArrayRef expected to contain only concrete integers
tensor([[1., 1., 1.],
        [1., 1., 1.]])
---------------------------------------------------------------------------
TorchRuntimeError                         Traceback (most recent call last)
[<ipython-input-3-8a1964a9495f>](https://localhost:8080/#) in <cell line: 13>()
     11 
     12 out2 = torch.empty(3, 4)
---> 13 opt_model((3, 4), out2)
     14 print(out2)

31 frames
[/usr/local/lib/python3.10/dist-packages/torch/_ops.py](https://localhost:8080/#) in __call__(self, *args, **kwargs)
    714     # that are named "self". This way, all the aten ops can be called by kwargs.
    715     def __call__(self, /, *args, **kwargs):
--> 716         return self._op(*args, **kwargs)
    717 
    718     # Use positional-only argument to avoid naming collision with aten ops arguments

TorchRuntimeError: Failed running call_function <built-in method ones of type object at 0x7914c7f93860>(*((s2, s3),), **{'out': FakeTensor(..., size=(s0, s1))}):
aten/src/ATen/RegisterCompositeExplicitAutograd.cpp:3324: SymIntArrayRef expected to contain only concrete integers

from user code:
   File "<ipython-input-3-8a1964a9495f>", line 4, in ones_fn
    return torch.ones(size, out=out)

Set TORCH_LOGS="+dynamo" and TORCHDYNAMO_VERBOSE=1 for more information


You can suppress this exception and fall back to eager by setting:
    import torch._dynamo
    torch._dynamo.config.suppress_errors = True
```

### Minified repro

torch.ones
```
import torch

def ones_fn(size, out):
  return torch.ones(size, out=out)

opt_model = torch.compile(ones_fn)

out1 = torch.empty(2, 3)
opt_model((2, 3), out1)
print(out1)

out2 = torch.empty(3, 4)
opt_model((3, 4), out2)
print(out2)
```
torch.zeros
```
import torch

def zeros_fn(size, out):
  return torch.zeros(size, out=out)

opt_model = torch.compile(zeros_fn)

out1 = torch.empty(2, 3)
opt_model((2, 3), out1)
print(out1)

out2 = torch.empty(3, 4)
opt_model((3, 4), out2)
print(out2)
```
torch.empty
```
import torch

def empty_fn(size, out):
  return torch.empty(size, out=out)

opt_model = torch.compile(empty_fn)

out1 = torch.empty(2, 3)
opt_model((2, 3), out1)
print(out1)

out2 = torch.empty(3, 4)
opt_model((3, 4), out2)
print(out2)
```


### Versions

```
Collecting environment information...
PyTorch version: 2.5.0.dev20240911+cpu
Is debug build: False
CUDA used to build PyTorch: Could not collect
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.3 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 3.30.3
Libc version: glibc-2.35

Python version: 3.10.12 (main, Jul 29 2024, 16:56:48) [GCC 11.4.0] (64-bit runtime)
Python platform: Linux-6.1.85+-x86_64-with-glibc2.35
Is CUDA available: False
CUDA runtime version: 12.2.140
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: Could not collect
Nvidia driver version: Could not collect
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.9.6
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.9.6
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):                               2
On-line CPU(s) list:                  0,1
Vendor ID:                            GenuineIntel
Model name:                           Intel(R) Xeon(R) CPU @ 2.20GHz
CPU family:                           6
Model:                                79
Thread(s) per core:                   2
Core(s) per socket:                   1
Socket(s):                            1
Stepping:                             0
BogoMIPS:                             4399.99
Flags:                                fpu vme de pse tsc msr pae mce cx8 apic sep mtrr pge mca cmov pat pse36 clflush mmx fxsr sse sse2 ss ht syscall nx pdpe1gb rdtscp lm constant_tsc rep_good nopl xtopology nonstop_tsc cpuid tsc_known_freq pni pclmulqdq ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single ssbd ibrs ibpb stibp fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm rdseed adx smap xsaveopt arat md_clear arch_capabilities
Hypervisor vendor:                    KVM
Virtualization type:                  full
L1d cache:                            32 KiB (1 instance)
L1i cache:                            32 KiB (1 instance)
L2 cache:                             256 KiB (1 instance)
L3 cache:                             55 MiB (1 instance)
NUMA node(s):                         1
NUMA node0 CPU(s):                    0,1
Vulnerability Gather data sampling:   Not affected
Vulnerability Itlb multihit:          Not affected
Vulnerability L1tf:                   Mitigation; PTE Inversion
Vulnerability Mds:                    Vulnerable; SMT Host state unknown
Vulnerability Meltdown:               Vulnerable
Vulnerability Mmio stale data:        Vulnerable
Vulnerability Reg file data sampling: Not affected
Vulnerability Retbleed:               Vulnerable
Vulnerability Spec rstack overflow:   Not affected
Vulnerability Spec store bypass:      Vulnerable
Vulnerability Spectre v1:             Vulnerable: __user pointer sanitization and usercopy barriers only; no swapgs barriers
Vulnerability Spectre v2:             Vulnerable; IBPB: disabled; STIBP: disabled; PBRSB-eIBRS: Not affected; BHI: Vulnerable (Syscall hardening enabled)
Vulnerability Srbds:                  Not affected
Vulnerability Tsx async abort:        Vulnerable

Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] optree==0.12.1
[pip3] torch==2.5.0.dev20240911+cpu
[pip3] torchaudio==2.4.0+cu121
[pip3] torchsummary==1.5.1
[pip3] torchvision==0.19.0+cu121
[conda] Could not collect
```

cc @ezyang @chauhang @penguinwu