RuntimeError: input and target shapes do not match: input [2 x 17 x 6 x 9], target [2 x 17] at /pytorch/aten/src/THCUNN/generic/MSECriterion.cu:12

[BugTan]

/usr/bin/python3.6 /home/bugtan/code/GANimation/train.py --data_dir /home/bugtan/code/GANimation/ck_dataset --name experiment_ck --batch_size 2
------------ Options -------------
D_adam_b1: 0.5
D_adam_b2: 0.999
G_adam_b1: 0.5
G_adam_b2: 0.999
aus_file: aus_openface.pkl
batch_size: 2
checkpoints_dir: ./checkpoints
cond_nc: 17
data_dir: /home/bugtan/code/GANimation/ck_dataset
dataset_mode: aus
display_freq_s: 300
do_saturate_mask: False
gpu_ids: [0]
image_size: 128
images_folder: imgs
is_train: True
lambda_D_cond: 4000
lambda_D_gp: 10
lambda_D_prob: 1
lambda_cyc: 10
lambda_mask: 0.1
lambda_mask_smooth: 1e-05
load_epoch: 0
lr_D: 0.0001
lr_G: 0.0001
model: ganimation
n_threads_test: 1
n_threads_train: 4
name: experiment_ck
nepochs_decay: 10
nepochs_no_decay: 20
num_iters_validate: 1
poses_g_sigma: 0.06
print_freq_s: 60
save_latest_freq_s: 3600
serial_batches: False
test_ids_file: test_ids.csv
train_G_every_n_iterations: 5
train_ids_file: train_ids.csv
-------------- End ----------------
./checkpoints/experiment_ck
Dataset AusDataset was created
Dataset AusDataset was created
#train images = 8791
#test images = 4
Network generator_wasserstein_gan was created
Network discriminator_wasserstein_gan was created
Model GANimation was created
Exception ignored in: <bound method _DataLoaderIter.del of <torch.utils.data.dataloader._DataLoaderIter object at 0x7f8e651aea90>>
Traceback (most recent call last):
File "/home/bugtan/.local/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 399, in del
self._shutdown_workers()
File "/home/bugtan/.local/lib/python3.6/site-packages/torch/utils/data/dataloader.py", line 378, in _shutdown_workers
self.worker_result_queue.get()
File "/usr/lib/python3.6/multiprocessing/queues.py", line 337, in get
return _ForkingPickler.loads(res)
File "/home/bugtan/.local/lib/python3.6/site-packages/torch/multiprocessing/reductions.py", line 151, in rebuild_storage_fd
fd = df.detach()
File "/usr/lib/python3.6/multiprocessing/resource_sharer.py", line 58, in detach
return reduction.recv_handle(conn)
File "/usr/lib/python3.6/multiprocessing/reduction.py", line 182, in recv_handle
return recvfds(s, 1)[0]
File "/usr/lib/python3.6/multiprocessing/reduction.py", line 153, in recvfds
msg, ancdata, flags, addr = sock.recvmsg(1, socket.CMSG_LEN(bytes_size))
ConnectionResetError: [Errno 104] Connection reset by peer
Traceback (most recent call last):
File "/home/bugtan/code/GANimation/train.py", line 141, in
Train()
File "/home/bugtan/code/GANimation/train.py", line 27, in init
self._train()
File "/home/bugtan/code/GANimation/train.py", line 40, in _train
self._train_epoch(i_epoch)
File "/home/bugtan/code/GANimation/train.py", line 69, in _train_epoch
self._model.optimize_parameters(keep_data_for_visuals=do_visuals, train_generator=train_generator)
File "/home/bugtan/code/GANimation/models/ganimation.py", line 207, in optimize_parameters
loss_D, fake_imgs_masked = self._forward_D()
File "/home/bugtan/code/GANimation/models/ganimation.py", line 280, in _forward_D
self._loss_d_cond = self._criterion_D_cond(d_real_img_cond, self._real_cond) / self._B * self._opt.lambda_D_cond
File "/home/bugtan/.local/lib/python3.6/site-packages/torch/nn/modules/module.py", line 477, in call
result = self.forward(*input, **kwargs)
File "/home/bugtan/.local/lib/python3.6/site-packages/torch/nn/modules/loss.py", line 421, in forward
return F.mse_loss(input, target, reduction=self.reduction)
File "/home/bugtan/.local/lib/python3.6/site-packages/torch/nn/functional.py", line 1716, in mse_loss
return _pointwise_loss(lambda a, b: (a - b) ** 2, torch._C._nn.mse_loss, input, target, reduction)
File "/home/bugtan/.local/lib/python3.6/site-packages/torch/nn/functional.py", line 1674, in _pointwise_loss
return lambd_optimized(input, target, reduction)
RuntimeError: input and target shapes do not match: input [2 x 17 x 6 x 9], target [2 x 17] at /pytorch/aten/src/THCUNN/generic/MSECriterion.cu:12

Anyone can help me solve this question?

[Blade6570]

Resize the training images to 128x128x3

[joyyang1997]

@Blade6570 Shall I do resize before I extract AU?

[Blade6570]

@joyyang1997 no need. extract AU and then resize it to 128x128. hope it helps.