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NVIDIA / vid2vid

Pytorch implementation of our method for high-resolution (e.g. 2048x1024) photorealistic video-to-video translation.
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'Segmentation fault (core dumped)' still exists. #20

Closed joe1chief closed 6 years ago

joe1chief commented 6 years ago

I downloaded the latest version (Aug 24th), and followed the steps in 'Read me' Paragraph 'Test', but I still get such error. My CUDA version is 9.0, PyTorch version is 4.1.

Can someone help me?

------------ Options -------------
aspect_ratio: 1.0
batchSize: 1
checkpoints_dir: ./checkpoints
dataroot: datasets/Cityscapes/test_A
dataset_mode: temporal
debug: False
display_id: 0
display_winsize: 512
feat_num: 3
fg: True
fg_labels: [26]
fineSize: 512
gpu_ids: [1, 2]
how_many: 300
input_nc: 3
isTrain: False
label_feat: False
label_nc: 35
loadSize: 2048
load_features: False
load_pretrain: 
max_dataset_size: inf
model: vid2vid
nThreads: 2
n_blocks: 9
n_blocks_local: 3
n_downsample_E: 3
n_downsample_G: 3
n_frames_G: 3
n_gpus_gen: 2
n_local_enhancers: 1
n_scales_spatial: 3
name: label2city_2048
ndf: 64
nef: 32
netE: simple
netG: composite
ngf: 128
no_first_img: False
no_flip: False
norm: batch
ntest: inf
output_nc: 3
phase: test
resize_or_crop: scaleWidth
results_dir: ./results/
serial_batches: False
tf_log: False
use_instance: True
use_real_img: False
use_single_G: True
which_epoch: latest
-------------- End ----------------
CustomDatasetDataLoader
dataset [TestDataset] was created
vid2vid
---------- Networks initialized -------------
-----------------------------------------------
Doing 28 frames
Segmentation fault (core dumped)
tcwang0509 commented 6 years ago

Can you first try if you can run flownet2 (https://github.com/NVIDIA/flownet2-pytorch)?

tsing90 commented 6 years ago

Exact same issue for me, flownet2 is well compiled. Will try pytorch 0.4.0 instead ...

kekedan commented 6 years ago

the same isuue,do you solve it ?

tsing90 commented 6 years ago

@kekedan pytorch 0.4.0 solved this issue

VisionU commented 5 years ago

This bug wastes me whole day to solve it. I try many methods and read the code deeply and repeatedly. The answer is so easy, pytorch 0.4.1 with CUDA 9.0 is not supported, your must download pytorch 0.4.0 and corresponding flownet2.