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While run the demo.sh, error msg is here:
Namespace(G_GAN=1, G_VGG=1, G_nn=1, batch_size_t=128, batch_size_v=16, beta1=0.5, dataroot=False, dataset='MPV', dataset_mode='regular', decay_iters=10, epoch=200, face_L1=10, face_gan=3, face_img_L1=1, face_residual=False, face_vgg=1, fine_height=256, fine_width=192, forward='normal', forward_save_path='end2end', gan_mode='lsgan', gpu_ids=[0], grid_size=5, init_gain=0.02, init_type='normal', input_nc_D_app=6, input_nc_D_face=6, input_nc_D_parsing=56, input_nc_G_app=26, input_nc_G_face=6, input_nc_G_parsing=36, isdemo=False, isval=False, joint=False, joint_G_parsing=1, joint_all=False, joint_parse_loss=False, lambda_L1=1, lr=0.0002, mask=1, mask_tvloss=False, momentum=0.9, n_layers_D=3, ndf=64, netD_app='resnet_blocks', netD_face='resnet_blocks', netD_parsing='basic', netG_app='treeresnet', netG_face='treeresnet', netG_parsing='unet_256', ngf=64, no_dropout=False, norm='instance', num_workers=1, output_nc_app=4, output_nc_face=3, output_nc_parsing=20, pool_size=100, print_freq=10, resume_D_app='', resume_D_face='', resume_D_parse='', resume_G_app='pretrained_checkpoint/app.tar', resume_G_face='pretrained_checkpoint/face.tar', resume_G_parse='pretrained_checkpoint/parsing.tar', resume_gmm='pretrained_checkpoint/step_009000.pth', save_epoch_freq=1, save_time=False, size=(256, 192), start_epoch=0, suffix='', train_mode='parsing', use_gmm=False, val_freq=200, warp_cloth=False, weight_decay=0.0001) initialization method [normal] initialization method [normal] initialize network with normal initialize network with normal initialize network with normal ==================== ==================== ==================== ==================== ==>loaded model Traceback (most recent call last): File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\IPython\core\interactiveshell.py", line 3343, in run_code exec(code_obj, self.user_global_ns, self.user_ns) File "<ipython-input-2-692ce522c4fa>", line 1, in <module> runfile('E:/Code/Python/Down-to-the-Last-Detail-Virtual-Try-on-with-Detail-Carving/demo.py', wdir='E:/Code/Python/Down-to-the-Last-Detail-Virtual-Try-on-with-Detail-Carving') File "D:\Program Files\JetBrains\PyCharm 2020.3.2\plugins\python\helpers\pydev\_pydev_bundle\pydev_umd.py", line 197, in runfile pydev_imports.execfile(filename, global_vars, local_vars) # execute the script File "D:\Program Files\JetBrains\PyCharm 2020.3.2\plugins\python\helpers\pydev\_pydev_imps\_pydev_execfile.py", line 18, in execfile exec(compile(contents+"\n", file, 'exec'), glob, loc) File "E:/Code/Python/Down-to-the-Last-Detail-Virtual-Try-on-with-Detail-Carving/demo.py", line 176, in <module> forward(opt, paths, 4, opt.forward_save_path) File "E:/Code/Python/Down-to-the-Last-Detail-Virtual-Try-on-with-Detail-Carving/demo.py", line 96, in forward for i, result in enumerate(val_dataloader): File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\torch\utils\data\dataloader.py", line 337, in __next__ return self._process_next_batch(batch) File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\torch\utils\data\dataloader.py", line 359, in _process_next_batch raise batch.exc_type(batch.exc_msg) RuntimeError: Traceback (most recent call last): File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\torch\utils\data\dataloader.py", line 106, in _worker_loop samples = collate_fn([dataset[i] for i in batch_indices]) File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\torch\utils\data\dataloader.py", line 106, in <listcomp> samples = collate_fn([dataset[i] for i in batch_indices]) File "E:\Code\Python\Down-to-the-Last-Detail-Virtual-Try-on-with-Detail-Carving\data\demo_dataset.py", line 87, in __getitem__ source_parse_shape = self.transforms['1'](source_parse_shape) # [-1,1] File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\torchvision\transforms\transforms.py", line 61, in __call__ img = t(img) File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\torchvision\transforms\transforms.py", line 166, in __call__ return F.normalize(tensor, self.mean, self.std, self.inplace) File "D:\ProgramData\Anaconda3\envs\torch\lib\site-packages\torchvision\transforms\functional.py", line 217, in normalize tensor.sub_(mean[:, None, None]).div_(std[:, None, None]) RuntimeError: The expanded size of the tensor (1) must match the existing size (3) at non-singleton dimension 0
The text was updated successfully, but these errors were encountered:
Hi @wangvm, did you solve it ? 🥺🥺🥺 I encounter the same issue when running train.sh any idea of how to solve it ??? 🥺🥺
thank you !
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While run the demo.sh, error msg is here:
The text was updated successfully, but these errors were encountered: