Description
🐛 Describe the bug
Test TestSimpleDecoder::test_dimension_order fails in my environment. We suspect this is related to torch versions. Specifically, when running pytest test -vvv, I get:
> assert frame.is_contiguous(memory_format=expected_memory_format)
E assert False
E + where False = <built-in method is_contiguous of Tensor object at 0x7fc40c0a48f0>(memory_format=torch.channels_last)
E + where <built-in method is_contiguous of Tensor object at 0x7fc40c0a48f0> = tensor([[[[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]],\n\n [[0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n ...,\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0],\n [0, 0, 0, ..., 0, 0, 0]]]], dtype=torch.uint8).is_contiguous
test/decoders/test_simple_video_decoder.py:419: AssertionError
___________________________________________________________________________________ TestSimpleDecoder.test_dimension_order[<lambda>3-NHWC] ____________________________________________________________________________________
Versions
Collecting environment information...
PyTorch version: 2.4.0
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: CentOS Stream 9 (x86_64)
GCC version: (GCC) 11.4.1 20231218 (Red Hat 11.4.1-3)
Clang version: Could not collect
CMake version: version 3.26.4
Libc version: glibc-2.34
Python version: 3.11.9 (main, Apr 19 2024, 16:48:06) [GCC 11.2.0] (64-bit runtime)
Python platform: Linux-5.19.0-0_fbk21_hardened_12633_g4db063a1bcb5-x86_64-with-glibc2.34
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: 40 bits physical, 57 bits virtual
Byte Order: Little Endian
CPU(s): 56
On-line CPU(s) list: 0-55
Vendor ID: GenuineIntel
Model name: Intel Xeon Processor (Icelake)
CPU family: 6
Model: 134
Thread(s) per core: 2
Core(s) per socket: 28
Socket(s): 1
Stepping: 0
BogoMIPS: 2000.00
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 arch_perfmon rep_good nopl xtopology cpuid tsc_known_freq pni pclmulqdq vmx ssse3 fma cx16 pdcm pcid sse4_1 sse4_2 x2apic movbe popcnt tsc_deadline_timer aes xsave avx f16c rdrand hypervisor lahf_lm abm 3dnowprefetch cpuid_fault invpcid_single ssbd ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid avx512f avx512dq rdseed adx smap avx512ifma clflushopt clwb avx512cd sha_ni avx512bw avx512vl xsaveopt xsavec xgetbv1 xsaves avx_vnni avx512_bf16 wbnoinvd arat avx512vbmi umip pku ospke waitpkg avx512_vbmi2 gfni vaes vpclmulqdq avx512_vnni avx512_bitalg avx512_vpopcntdq rdpid cldemote movdiri movdir64b fsrm md_clear arch_capabilities
Virtualization: VT-x
Hypervisor vendor: KVM
Virtualization type: full
L1d cache: 1.8 MiB (56 instances)
L1i cache: 1.8 MiB (56 instances)
L2 cache: 112 MiB (28 instances)
L3 cache: 16 MiB (1 instance)
NUMA node(s): 1
NUMA node0 CPU(s): 0-55
Vulnerability Itlb multihit: Not affected
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: Not affected
Vulnerability Mmio stale data: Vulnerable
Vulnerability Retbleed: 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
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled
Versions of relevant libraries:
[pip3] numpy==1.26.4
[pip3] torch==2.4.0
[pip3] torchvision==0.19.0
[conda] blas 1.0 mkl
[conda] libjpeg-turbo 2.0.0 h9bf148f_0 pytorch
[conda] mkl 2023.1.0 h213fc3f_46344
[conda] mkl-service 2.4.0 py311h5eee18b_1
[conda] mkl_fft 1.3.8 py311h5eee18b_0
[conda] mkl_random 1.2.4 py311hdb19cb5_0
[conda] numpy 1.26.4 py311h08b1b3b_0
[conda] numpy-base 1.26.4 py311hf175353_0
[conda] pytorch 2.4.0 py3.11_cpu_0 pytorch
[conda] pytorch-mutex 1.0 cpu pytorch
[conda] torchcodec 0.0.1.dev0 pypi_0 pypi
[conda] torchvision 0.19.0 py311_cpu pytorch