8000 [NJT] NestedTensor repr has contiguous=True while the NJT isn't contiguous · Issue #153237 · pytorch/pytorch · GitHub
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[NJT] NestedTensor repr has contiguous=True while the NJT isn't contiguous #153237

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mdeff opened this issue May 9, 2025 · 2 comments
Closed

[NJT] NestedTensor repr has contiguous=True while the NJT isn't contiguous #153237

mdeff opened this issue May 9, 2025 · 2 comments
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actionable module: nestedtensor NestedTensor tag see issue #25032 triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module

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@mdeff
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mdeff commented May 9, 2025 •
edited by pytorch-bot bot
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🐛 Describe the bug

import torch
x = torch.nested.nested_tensor(
    [
        torch.randn((12, 4)),
        torch.randn((12, 6)),
    ],
    layout=torch.jagged,
)
assert x.is_contiguous()
print(x)  # prints contiguous=True, as expected

x = x.transpose(1, 2)
assert not x.is_contiguous()
print(x)  # still prints contiguous=True, while x is not contiguous anymore

Versions

PyTorch 2.7.0+cu126 from PyPI.

Full collect_env.py output 
Collecting environment information...
PyTorch version: 2.7.0+cu126
Is debug build: False
CUDA used to build PyTorch: 12.6
ROCM used to build PyTorch: N/A

OS: Ubuntu 22.04.4 LTS (x86_64)
GCC version: (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
Clang version: Could not collect
CMake version: Could not collect
Libc version: glibc-2.35

Python version: 3.12.0 | packaged by conda-forge | (main, Oct  3 2023, 08:43:22) [GCC 12.3.0] (64-bit runtime)
Python platform: Linux-5.15.0-113-generic-x86_64-with-glibc2.35
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 2080 Ti
Nvidia driver version: 535.161.08
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:                      46 bits physical, 48 bits virtual
Byte Order:                         Little Endian
CPU(s):                             8
On-line CPU(s) list:                0-7
Vendor ID:                          GenuineIntel
Model name:                         Intel(R) Xeon(R) W-2123 CPU @ 3.60GHz
CPU family:                         6
Model:                              85
Thread(s) per core:                 2
Core(s) per socket:                 4
Socket(s):                          1
Stepping:                           4
CPU max MHz:                        3900.0000
CPU min MHz:                        1200.0000
BogoMIPS:                           7200.00
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 pni pclmulqdq dtes64 monitor ds_cpl vmx smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm pcid dca sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb cat_l3 cdp_l3 invpcid_single pti intel_ppin ssbd mba ibrs ibpb stibp tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 hle avx2 smep bmi2 erms invpcid rtm cqm mpx rdt_a avx512f avx512dq rdseed adx smap clflushopt clwb intel_pt avx512cd avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves cqm_llc cqm_occup_llc cqm_mbm_total cqm_mbm_local dtherm ida arat pln pts hwp hwp_act_window hwp_epp hwp_pkg_req md_clear flush_l1d arch_capabilities
Virtualization:                     VT-x
L1d cache:                          128 KiB (4 instances)
L1i cache:                          128 KiB (4 instances)
L2 cache:                           4 MiB (4 instances)
L3 cache:                           8.3 MiB (1 instance)
NUMA node(s):                       1
NUMA node0 CPU(s):                  0-7
Vulnerability Gather data sampling: Mitigation; Microcode
Vulnerability Itlb multihit:        KVM: Mitigation: VMX disabled
Vulnerability L1tf:                 Mitigation; PTE Inversion; VMX conditional cache flushes, SMT vulnerable
Vulnerability Mds:                  Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Meltdown:             Mitigation; PTI
Vulnerability Mmio stale data:      Mitigation; Clear CPU buffers; SMT vulnerable
Vulnerability Retbleed:             Mitigation; IBRS
Vulnerability Spec rstack overflow: Not affected
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; IBRS; IBPB conditional; STIBP conditional; RSB filling; PBRSB-eIBRS Not affected; BHI Not affected
Vulnerability Srbds:                Not affected
Vulnerability Tsx async abort:      Mitigation; Clear CPU buffers; SMT vulnerable

Versions of relevant libraries:
[pip3] Could not collect
[conda] Could not collect

cc @cpuhrsch @jbschlosser @bhosmer @drisspg @soulitzer @davidberard98 @YuqingJ
@malfet malfet added the module: nestedtensor NestedTensor tag see issue #25032 label May 9, 2025
@jbschlosser
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Thanks for the report @mdeff, this is definitely wrong. We'd accept a PR fixing the repr of NJT to properly reflect its contiguity.

@jbschlosser jbschlosser added actionable triaged This issue has been looked at a team member, and triaged and prioritized into an appropriate module labels May 12, 2025
@simonzgx
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Hi @jbschlosser ,
I'd like to address this bug. It seems that we just need to modify the line of code by changing the condition for the contiguous property of NestedTensor from self._lengths is None to self.is_contiguous(), correct?

@simonzgx simonzgx mentioned this issue May 14, 2025
Closed
@mdeff mdeff mentioned this issue May 16, 2025
Open
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[Torch][NT] Fix NestedTensor contiguous check condition. (#153237) simonzgx/pytorch
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