Repository: pytorch
Issue: Cannot use `checkpoint_sequential` with `torch.compile`
Labels: oncall: distributed,module: checkpoint,triaged,oncall: pt2,pt2d-triage-nov2024

## Issue description

I have a number of classes that derive directly from `nn.Sequential`, when I `torch.compile` models containing these classes and attempt to use them in conjunction with `checkpoint_sequential` execution immediately aborts with a TypeError exception (@ line 352 in torch/utils/checkpoint.py):

```
    segment_size = len(functions) // segments
TypeError: object of type 'OptimizedModule' has no len()
```

I could imagine that perhaps the two are not meant to interoperate, but it's not clear whether that's the case.

I have seen this with both the stable 2.0.0 CUDA 11.7 release as well as the nightly CUDA 11.8 release (system info below)

## Code example

I have managed to reproduce the issue in a minimal way with this code snippet:

```python
import torch
import torch.nn as nn
import torch.utils.checkpoint as ckpt
import collections

class Sequence(nn.Sequential):
    def __init__(self) -> None:
        builder = collections.OrderedDict()
        builder['linear_1'] = nn.Linear(32, 32)
        builder['linear_2'] = nn.Linear(32, 32)
        super(Sequence, self).__init__(builder)

m = Sequence()
n = torch.compile(m)
x = torch.randn(32)
y = ckpt.checkpoint_sequential(n, segments=2, input=x, use_reentrant=False)
```

## System Info
```
Collecting environment information...
PyTorch version: 2.1.0.dev20230406+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A

OS: Arch Linux (x86_64)
GCC version: (GCC) 12.2.1 20230201
Clang version: 15.0.7
CMake version: Could not collect
Libc version: glibc-2.37

Python version: 3.10.10 (main, Mar  5 2023, 22:26:53) [GCC 12.2.1 20230201] (64-bit runtime)
Python platform: Linux-6.2.9-arch1-1-x86_64-with-glibc2.37
Is CUDA available: True
CUDA runtime version: Could not collect
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration: GPU 0: NVIDIA GeForce RTX 3090
Nvidia driver version: 530.41.03
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:                   39 bits physical, 48 bits virtual
Byte Order:                      Little Endian
CPU(s):                          12
On-line CPU(s) list:             0-11
Vendor ID:                       GenuineIntel
Model name:                      12th Gen Intel(R) Core(TM) i5-12400F
CPU family:                      6
Model:                           151
Thread(s) per core:              2
Core(s) per socket:              6
Socket(s):                       1
Stepping:                        5
CPU(s) scaling MHz:              35%
CPU max MHz:                     5600.0000
CPU min MHz:                     800.0000
BogoMIPS:                        4993.00
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 rdtscp lm constant_tsc art arch_perfmon pebs bts rep_good nopl xtopology nonstop_tsc cpuid aperfmperf tsc_known_freq pni pclmulqdq dtes64 monitor ds_cpl vmx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l2 invpcid_single cdp_l2 ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid rdt_a rdseed adx smap clflushopt clwb intel_pt sha_ni xsaveopt xsavec xgetbv1 xsaves split_lock_detect avx_vnni dtherm ida arat pln pts hwp hwp_notify hwp_act_window hwp_epp hwp_pkg_req hfi umip pku ospke waitpkg gfni vaes vpclmulqdq rdpid movdiri movdir64b fsrm md_clear serialize arch_lbr flush_l1d arch_capabilities
Virtualization:                  VT-x
L1d cache:                       288 KiB (6 instances)
L1i cache:                       192 KiB (6 instances)
L2 cache:                        7.5 MiB (6 instances)
L3 cache:                        18 MiB (1 instance)
NUMA node(s):                    1
NUMA node0 CPU(s):               0-11
Vulnerability Itlb multihit:     Not affected
Vulnerability L1tf:              Not affected
Vulnerability Mds:               Not affected
Vulnerability Meltdown:          Not affected
Vulnerability Mmio stale data:   Not affected
Vulnerability Retbleed:          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; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence
Vulnerability Srbds:             Not affected
Vulnerability Tsx async abort:   Not affected

Versions of relevant libraries:
[pip3] numpy==1.24.1
[pip3] pytorch-triton==2.1.0+46672772b4
[pip3] torch==2.1.0.dev20230406+cu118
[pip3] torchaudio==2.1.0.dev20230406+cu118
[pip3] torchdata==0.7.0.dev20230406
[pip3] torchvision==0.16.0.dev20230406+cu118
[conda] Could not collect
```

cc @H-Huang @awgu @kwen2501 @wanchaol @fegin @fduwjj @wz337 @wconstab @d4l3k @c-p-i-o @soulitzer @chauhang @penguinwu @mrshenli @pritamdamania87 @zhaojuanmao @satgera @rohan-varma @gqchen @aazzolini @osalpekar @jiayisuse @XilunWu @tianyu-l @yf225 @ezyang @msaroufim @bdhirsh @anijain2305 @zou3519 @soumith @ngimel