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Datasets, Transforms and Models specific to Computer Vision
https://pytorch.org/vision
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Error while using `download_file_from_google_drive` #8275

Closed david20571015 closed 8 months ago

david20571015 commented 8 months ago

🐛 Describe the bug

I met an error while trying to download https://drive.google.com/file/d/1badu11NqxGf6qM3PTTooQDJvQbejgbTv/view from https://github.com/switchablenorms/CelebAMask-HQ by torchvision.datasets.utils.download_file_from_google_drive

UserWarning: We detected some HTML elements in the downloaded file. This most likely means that the download triggered an unhandled API response by GDrive. Please report this to torchvision at https://github.com/pytorch/vision/issues including the response:

<!DOCTYPE html><html><head><title>Google Drive - Virus scan warning</title><meta http-equiv="content-type" content="text/html; charset=utf-8"/><style nonce="a316ajj4g-eflupDC1Jt9w">.goog-link-button{position:relative;color:#15c;text-decoration:underline;cursor:pointer}.goog-link-button-disabled{color:#ccc;text-decoration:none;cursor:default}body{color:#222;font:normal 13px/1.4 arial,sans-serif;margin:0}.grecaptcha-badge{visibility:hidden}.uc-main{padding-top:50px;text-align:center}#uc-dl-icon{display:inline-block;margin-top:16px;padding-right:1em;vertical-align:top}#uc-text{display:inline-block;max-width:68ex;text-align:left}.uc-error-caption,.uc-warning-caption{color:#222;font-size:16px}#uc-download-link{text-decoration:none}.uc-name-size a{color:#15c;text-decoration:none}.uc-name-size a:visited{color:#61c;text-decoration:none}.uc-name-size a:active{color:#d14836;text-decoration:none}.uc-footer{color:#777;font-size:11px;padding-bottom:5ex;padding-top:5ex;text-align:center}.uc-footer a{color:#15c}.uc-footer a:visited{color:#61c}.uc-footer a:active{color:#d14836}.uc-footer-divider{color:#ccc;width:100%}.goog-inline-block{position:relative;display:-moz-inline-box;display:inline-block}* html .goog-inline-block{display:inline}*:first-child+html .goog-inline-block{display:inline}sentinel{}</style><link rel="icon" href="//ssl.gstatic.com/docs/doclist/images/drive_2022q3_32dp.png"/></head><body><div class="uc-main"><div id="uc-dl-icon" class="image-container"><div class="drive-sprite-aux-download-file"></div></div><div id="uc-text"><p class="uc-warning-caption">Google Drive can't scan this file for viruses.</p><p class="uc-warning-subcaption"><span class="uc-name-size"><a href="/open?id=1badu11NqxGf6qM3PTTooQDJvQbejgbTv">CelebAMask-HQ.zip</a> (2.9G)</span> is too large for Google to scan for viruses. Would you still like to download this file?</p><form id="download-form" action="https://drive.usercontent.google.com/download" method="get"><input type="submit" id="uc-download-link" class="goog-inline-block jfk-button jfk-button-action" value="Download anyway"/><input type="hidden" name="id" value="1badu11NqxGf6qM3PTTooQDJvQbejgbTv"><input type="hidden" name="export" value="download"><input type="hidden" name="confirm" value="t"><input type="hidden" name="uuid" value="19ebee42-9335-42ed-b652-68b7f0208782"></form></div></div><div class="uc-footer"><hr class="uc-footer-divider"></div></body></html>

Code for reproduce:

from torchvision.datasets.utils import download_file_from_google_drive

download_file_from_google_drive('1badu11NqxGf6qM3PTTooQDJvQbejgbTv', '.',
                                'CelebAMask-HQ.zip')

Versions

PyTorch version: 2.2.0 Is debug build: False CUDA used to build PyTorch: 11.8 ROCM used to build PyTorch: N/A

OS: Ubuntu 20.04.6 LTS (x86_64) GCC version: (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 Clang version: Could not collect CMake version: version 3.16.3 Libc version: glibc-2.31

Python version: 3.11.7 | packaged by conda-forge | (main, Dec 23 2023, 14:43:09) [GCC 12.3.0] (64-bit runtime) Python platform: Linux-5.4.0-153-generic-x86_64-with-glibc2.31 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 GPU 1: NVIDIA GeForce RTX 3090 GPU 2: NVIDIA GeForce RTX 3090 GPU 3: NVIDIA GeForce RTX 3090 GPU 4: NVIDIA GeForce RTX 3090 GPU 5: NVIDIA GeForce RTX 3090 GPU 6: NVIDIA GeForce RTX 3090 GPU 7: NVIDIA GeForce RTX 3090

Nvidia driver version: 530.41.03 cuDNN version: Probably one of the following: /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn.so.8.0.4 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.0.4 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.0.4 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.0.4 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.0.4 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.0.4 /usr/local/cuda-11.0/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.0.4 /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn.so.8.1.0 /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.1.0 /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.1.0 /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.1.0 /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.1.0 /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.1.0 /usr/local/cuda-11.2/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.1.0 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn.so.8.6.0 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_adv_infer.so.8.6.0 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_adv_train.so.8.6.0 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_cnn_infer.so.8.6.0 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_cnn_train.so.8.6.0 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_ops_infer.so.8.6.0 /usr/local/cuda-11.8/targets/x86_64-linux/lib/libcudnn_ops_train.so.8.6.0 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: 2811.520 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: Split huge pages Vulnerability L1tf: Not affected Vulnerability Mds: Not affected Vulnerability Meltdown: Not affected Vulnerability Mmio stale data: Mitigation; Clear CPU buffers; SMT vulnerable Vulnerability Retbleed: Mitigation; Enhanced IBRS 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; Enhanced IBRS, IBPB conditional, RSB filling, PBRSB-eIBRS SW sequence 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 hwp hwp_act_window hwp_epp hwp_pkg_req pku ospke avx512_vnni md_clear flush_l1d arch_capabilities

Versions of relevant libraries: [pip3] numpy==1.26.4 [pip3] pytorch-lightning==2.1.3 [pip3] torch==2.2.0 [pip3] torchmetrics==1.2.1 [pip3] torchvision==0.17.0 [pip3] triton==2.2.0 [conda] blas 1.0 mkl conda-forge [conda] ffmpeg 4.3 hf484d3e_0 pytorch [conda] libblas 3.9.0 16_linux64_mkl conda-forge [conda] libcblas 3.9.0 16_linux64_mkl conda-forge [conda] liblapack 3.9.0 16_linux64_mkl conda-forge [conda] mkl 2022.1.0 hc2b9512_224
[conda] numpy 1.26.4 py311h64a7726_0 conda-forge [conda] pytorch 2.2.0 py3.11_cuda11.8_cudnn8.7.0_0 pytorch [conda] pytorch-cuda 11.8 h7e8668a_5 pytorch [conda] pytorch-lightning 2.1.3 pyhd8ed1ab_0 conda-forge [conda] pytorch-mutex 1.0 cuda pytorch [conda] torchmetrics 1.2.1 pyhd8ed1ab_0 conda-forge [conda] torchtriton 2.2.0 py311 pytorch [conda] torchvision 0.17.0 py311_cu118 pytorch

NicolasHug commented 8 months ago

Thank you for the report @david20571015 . This is the same issue as in https://github.com/pytorch/vision/issues/8204#issuecomment-1935737815 so I'll close this one. Please see my message there for the recommended temporary fix and the future plan. Thank you

NicolasHug commented 8 months ago

Hi @david20571015 , torchvision 0.17.1 is out and the download util should now be fixed. For it to work, you'll need to pip install gdown