Runtime Error in Elastic-Transform

[N-Friederich]

🐛 Describe the bug

When executing the elastic transformation, a runtime error occurs, more precisely in the forward pass during padding.
MRE:

import torch
import torchvision.transforms.v2 as transforms_v2

x = torch.rand([1,1,20,64])
transforms_v2.ElasticTransform(alpha=50.0)(x)

RuntimeError: Argument #6: Padding size should be less than the corresponding input dimension, but got: padding (20, 20) at dimension 2 of input [1, 1, 20, 64]

Versions

Collecting environment information...
PyTorch version: 2.4.0
Is debug build: False
CUDA used to build PyTorch: 12.4
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: version 3.22.1
Libc version: glibc-2.35

Python version: 3.11.9 | packaged by conda-forge | (main, Apr 19 2024, 18:36:13) [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 3090
Nvidia driver version: 555.42.06
cuDNN version: Could not collect
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True

CPU:
Architektur: x86_64
CPU Operationsmodus: 32-bit, 64-bit
Adressgrößen: 46 bits physical, 48 bits virtual
Byte-Reihenfolge: Little Endian
CPU(s): 32
Liste der Online-CPU(s): 0-31
Anbieterkennung: GenuineIntel
Modellname: 13th Gen Intel(R) Core(TM) i9-13900
Prozessorfamilie: 6
Modell: 183
Thread(s) pro Kern: 2
Kern(e) pro Socket: 24
Sockel: 1
Stepping: 1
Maximale Taktfrequenz der CPU: 5600,0000
Minimale Taktfrequenz der CPU: 800,0000
BogoMIPS: 3993.60
Markierungen: 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 smx est tm2 ssse3 sdbg fma cx16 xtpr pdcm sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand lahf_lm abm 3dnowprefetch cpuid_fault epb ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid 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 umip pku ospke waitpkg gfni vaes vpclmulqdq tme rdpid movdiri movdir64b fsrm md_clear serialize pconfig arch_lbr flush_l1d arch_capabilities
Virtualisierung: VT-x
L1d Cache: 896 KiB (24 instances)
L1i Cache: 1,3 MiB (24 instances)
L2 Cache: 32 MiB (12 instances)
L3 Cache: 36 MiB (1 instance)
NUMA-Knoten: 1
NUMA-Knoten0 CPU(s): 0-31
Schwachstelle Gather data sampling: Not affected
Schwachstelle Itlb multihit: Not affected
Schwachstelle L1tf: Not affected
Schwachstelle Mds: Not affected
Schwachstelle Meltdown: Not affected
Schwachstelle Mmio stale data: Not affected
Schwachstelle Retbleed: Not affected
Schwachstelle Spec rstack overflow: Not affected
Schwachstelle Spec store bypass: Mitigation; Speculative Store Bypass disabled via prctl and seccomp
Schwachstelle Spectre v1: Mitigation; usercopy/swapgs barriers and __user pointer sanitization
Schwachstelle Spectre v2: Mitigation; Enhanced IBRS; IBPB conditional; RSB filling; PBRSB-eIBRS SW sequence; BHI BHI_DIS_S
Schwachstelle Srbds: Not affected
Schwachstelle Tsx async abort: Not affected

Versions of relevant libraries:
[pip3] numpy==1.24.3
[pip3] torch==2.4.0
[pip3] torch-tb-profiler==0.4.3
[pip3] torchaudio==2.4.0
[pip3] torchinfo==1.8.0
[pip3] torchvision==0.19.0
[pip3] triton==3.0.0
[conda] blas 1.0 mkl
[conda] libblas 3.9.0 12_linux64_mkl conda-forge
[conda] libcblas 3.9.0 12_linux64_mkl conda-forge
[conda] liblapack 3.9.0 12_linux64_mkl conda-forge
[conda] liblapacke 3.9.0 12_linux64_mkl conda-forge
[conda] libopenvino-pytorch-frontend 2024.2.0 he02047a_1 conda-forge
[conda] mkl 2021.4.0 h06a4308_640
[conda] mkl-service 2.4.0 py311h5eee18b_0
[conda] mkl_fft 1.3.1 py311h30b3d60_0
[conda] mkl_random 1.2.2 py311hba01205_0
[conda] numpy 1.24.3 py311hc206e33_0
[conda] numpy-base 1.24.3 py311hfd5febd_0
[conda] pytorch 2.4.0 py3.11_cuda12.4_cudnn9.1.0_0 pytorch
[conda] pytorch-cuda 12.4 hc786d27_6 pytorch
[conda] pytorch-mutex 1.0 cuda pytorch
[conda] torch-tb-profiler 0.4.3 pypi_0 pypi
[conda] torchaudio 2.4.0 py311_cu124 pytorch
[conda] torchinfo 1.8.0 pyhd8ed1ab_0 conda-forge
[conda] torchtriton 3.0.0 py311 pytorch
[conda] torchvision 0.19.0 py311_cu124 pytorch

[NicolasHug]

Hi @N-Friederich ,

It looks like your image is too small for sigma to be supported. It should work if you set sigma to 0.