Repository: pytorch
Issue: convolution_backward has different size results on "CPU", FakeTensor
Labels: triaged,module: fakeTensor

### 🐛 Describe the bug

When the op `convolution_backward` is run using FakeTensors, the size of the third result is different from the one obtained without FakeTensors.

```python
import torch
from torch._subclasses.fake_tensor import FakeTensorMode

class ConvolutionBackwardModule(torch.nn.Module):
    def forward(self, grad_out, input_vec, weight):
        return torch.ops.aten.convolution_backward(
            grad_out,
            input_vec,
            weight,
            bias_sizes=[4],
            stride=[2, 2],
            padding=[1, 1],
            dilation=[1, 1],
            transposed=False,
            output_padding=[0, 0],
            groups=1,
            output_mask=[True, True, True])

example_args = [torch.rand(1, 2, 4, 4), torch.rand(1, 2, 8, 8),
                torch.rand(2, 2, 3, 3)]
module = ConvolutionBackwardModule()
results = module(*example_args)

with FakeTensorMode():
    example_args = [torch.rand(1, 2, 4, 4), torch.rand(1, 2, 8, 8),
                    torch.rand(2, 2, 3, 3)]
    module = ConvolutionBackwardModule()
    results_fake = module(*example_args)

    assert results[2].shape == results_fake[2].shape
```

In the above example, the FakeTensor version produces a tensor of shape `[4]`, while the regular version produces a tensor of shape `[2]`.

### Versions

```
PyTorch version: 2.3.0.dev20240122+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A

OS: Debian GNU/Linux rodete (x86_64)
GCC version: (Debian 13.2.0-5) 13.2.0
Clang version: 16.0.6 (16)
CMake version: version 3.27.7
Libc version: glibc-2.37

Python version: 3.11.6 (main, Oct  8 2023, 05:06:43) [GCC 13.2.0] (64-bit runtime)
Python platform: Linux-6.5.13-1rodete2-amd64-x86_64-with-glibc2.37
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:                      46 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             96
On-line CPU(s) list:                0-95
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) CPU @ 2.00GHz
CPU family:                         6
Model:                              85
Thread(s) per core:                 2
Core(s) per socket:                 24
Socket(s):                          2
Stepping:                           3
BogoMIPS:                           4000.38
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 vmx ssse3 fma cx16 pcid sse4_1 sse4_2 x2apic movbe popcnt aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch invpcid_single pti ssbd ibrs ibpb stibp tpr_shadow flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm mpx avx512f avx512dq rdseed adx smap clflushopt clwb avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves arat vnmi md_clear arch_capabilities
Virtualization:                     VT-x
Hypervisor vendor:                  KVM
Virtualization type:                full
L1d cache:                          1.5 MiB (48 instances)
L1i cache:                          1.5 MiB (48 instances)
L2 cache:                           48 MiB (48 instances)
L3 cache:                           77 MiB (2 instances)
NUMA node(s):                       2
NUMA node0 CPU(s):                  0-23,48-71
NUMA node1 CPU(s):                  24-47,72-95
Vulnerability Gather data sampling: Not affected
Vulnerability Itlb multihit:        Not affected
Vulnerability L1tf:                 Mitigation; PTE Inversion; VMX flush not necessary, SMT vulnerable
Vulnerability Mds:                  Mitigation; Clear CPU buffers; SMT Host state unknown
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Vulnerable: Clear CPU buffers attempted, no microcode; SMT Host state unknown
Vulnerability Retbleed:             Mitigation; IBRS
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; IBRS, IBPB conditional, STIBP conditional, RSB filling, PBRSB-eIBRS Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Mitigation; Clear CPU buffers; SMT Host state unknown

Versions of relevant libraries:
[pip3] mypy-extensions==1.0.0
[pip3] numpy==1.26.1
[pip3] torch==2.3.0.dev20240122+cpu
[pip3] torchvision==0.18.0.dev20240122+cpu
[conda] Could not collect
```

cc @eellison