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torch2.0.1 No module named 'torch._six #1724
Comments
watching👁 |
Any fixes? I ran into this error EDIT: |
help, save my ass !!!!!! |
|
i fix this problem by downloading torch of 1.10.3 in other place, and then copy the _six.py to 2.,and modify init.py of 2. of torch module: add 'from _six import ***' into init.py. |
Just replace the original |
It seems like pytorch (>1.7) has abandoned the module "_six". The issue therefore exists. |
"_six" seems like serving to resolve the conflict of python 2 and python 3. Hope someone can provide a solution without editing code. |
you could change the source code like this
|
torch has stopped supporting six according to 94709. |
torch has stopped supporting six according to pytorch/pytorch#94709. |
hey thanks it works |
this saved my day. Thanks |
File "/opt/conda/lib/python3.8/site-packages/transformers/trainer.py", line 164, in
from apex import amp
File "/opt/conda/lib/python3.8/site-packages/apex/init.py", line 11, in
from . import amp
File "/opt/conda/lib/python3.8/site-packages/apex/amp/init.py", line 1, in
from .amp import init, half_function, float_function, promote_function,
File "/opt/conda/lib/python3.8/site-packages/apex/amp/amp.py", line 5, in
from .frontend import *
File "/opt/conda/lib/python3.8/site-packages/apex/amp/frontend.py", line 2, in
from ._initialize import _initialize
File "/opt/conda/lib/python3.8/site-packages/apex/amp/_initialize.py", line 2, in
from torch._six import string_classes
ModuleNotFoundError: No module named 'torch._six'
Environment
PyTorch version: 2.0.1+cu118
Is debug build: False
CUDA used to build PyTorch: 11.8
ROCM used to build PyTorch: N/A
OS: Ubuntu 20.04.4 LTS (x86_64)
GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
Clang version: Could not collect
CMake version: version 3.27.4
Libc version: glibc-2.31
Python version: 3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 06:04:10) [GCC 10.3.0] (64-bit runtime)
Python platform: Linux-5.16.20-1.el7.bzl.x86_64-x86_64-with-glibc2.10
Is CUDA available: True
CUDA runtime version: 11.7.99
CUDA_MODULE_LOADING set to: LAZY
GPU models and configuration:
GPU 0: NVIDIA GeForce RTX 3090
GPU 1: NVIDIA GeForce RTX 3090
Nvidia driver version: 530.41.03
cuDNN version: Probably one of the following:
/usr/lib/x86_64-linux-gnu/libcudnn.so.8.5.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_infer.so.8.5.0
/usr/lib/x86_64-linux-gnu/libcudnn_adv_train.so.8.5.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_infer.so.8.5.0
/usr/lib/x86_64-linux-gnu/libcudnn_cnn_train.so.8.5.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_infer.so.8.5.0
/usr/lib/x86_64-linux-gnu/libcudnn_ops_train.so.8.5.0
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
Byte Order: Little Endian
Address sizes: 46 bits physical, 48 bits virtual
CPU(s): 64
On-line CPU(s) list: 0-63
Thread(s) per core: 2
Core(s) per socket: 16
Socket(s): 2
NUMA node(s): 2
Vendor ID: GenuineIntel
CPU family: 6
Model: 85
Model name: Intel(R) Xeon(R) Gold 6226R CPU @ 2.90GHz
Stepping: 7
CPU MHz: 3900.000
CPU max MHz: 3900.0000
CPU min MHz: 1200.0000
BogoMIPS: 5800.00
Virtualization: VT-x
L1d cache: 1 MiB
L1i cache: 1 MiB
L2 cache: 32 MiB
L3 cache: 44 MiB
NUMA node0 CPU(s): 0-15,32-47
NUMA node1 CPU(s): 16-31,48-63
Vulnerability Itlb multihit: KVM: Mitigation: VMX disabled
Vulnerability L1tf: Not affected
Vulnerability Mds: Not affected
Vulnerability Meltdown: 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; Retpolines, IBPB conditional, IBRS_FW, STIBP conditional, RSB filling
Vulnerability Srbds: Not affected
Vulnerability Tsx async abort: Mitigation; TSX disabled
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 intel_ppin ssbd mba ibrs ibpb stibp ibrs_enhanced tpr_shadow vnmi flexpriority ept vpid ept_ad fsgsbase tsc_adjust bmi1 avx2 smep bmi2 erms invpcid 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 pku ospke avx512_vnni md_clear flush_l1d arch_capabilities
Versions of relevant libraries:
[pip3] numpy==1.22.4
[pip3] pytorch-quantization==2.1.2
[pip3] torch==2.0.1+cu118
[pip3] torch-tensorrt==1.2.0a0
[pip3] torchaudio==2.0.2+cu118
[pip3] torchtext==0.11.0a0
[pip3] torchvision==0.15.2+cu118
[conda] mkl 2020.4 h726a3e6_304 conda-forge
[conda] mkl-include 2020.4 h726a3e6_304 conda-forge
[conda] numpy 1.22.4 py38h99721a1_0 conda-forge
[conda] pytorch-quantization 2.1.2 pypi_0 pypi
[conda] torch 2.0.1+cu118 pypi_0 pypi
[conda] torch-tensorrt 1.2.0a0 pypi_0 pypi
[conda] torchaudio 2.0.2+cu118 pypi_0 pypi
[conda] torchtext 0.11.0a0 pypi_0 pypi
[conda] torchvision 0.15.2+cu118 pypi_0 pypi
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