RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 28 but got size 29 for tensor number 1 in the list.

[jasonwongw]

First,It's a great job to get the content in the image to follow the content in the video.
Secondly, I want to train on my own dataset, but there is an error during the training process, can you help me?
Finally，This is really an amazing project.

[jasonwongw]

Here are my settings(fashion-256.yaml) and i‘ve a question. Does the resolution for critical point detectors and dense motion have to be 64×64?

dataset_params:
root_dir: data\fashion
frame_shape: [512, 512, 3]
id_sampling: False
augmentation_params:
flip_param:
horizontal_flip: True
time_flip: True
jitter_param:
hue: 0.1

model_params:
common_params:
num_kp: 10
num_channels: 3
estimate_jacobian: True
kp_detector_params:
temperature: 0.1
block_expansion: 32
max_features: 1024
scale_factor: 0.5
num_blocks: 5
generator_params:
block_expansion: 64
max_features: 512
num_down_blocks: 2
num_bottleneck_blocks: 6
estimate_occlusion_map: True
dense_motion_params:
block_expansion: 64
max_features: 1024
num_blocks: 5
scale_factor: 0.5
discriminator_params:
scales: [1]
block_expansion: 32
max_features: 512
num_blocks: 4

train_params:
num_epochs: 100
num_repeats: 1
epoch_milestones: [60, 90]
lr_generator: 2.0e-4
lr_discriminator: 2.0e-4
lr_kp_detector: 2.0e-4
batch_size: 1
scales: [1, 0.5, 0.25, 0.125]
checkpoint_freq: 50
transform_params:
sigma_affine: 0.05
sigma_tps: 0.005
points_tps: 5
loss_weights:
generator_gan: 1
discriminator_gan: 1
feature_matching: [10, 10, 10, 10]
perceptual: [10, 10, 10, 10, 10]
equivariance_value: 10
equivariance_jacobian: 10

reconstruction_params:
num_videos: 1000
format: '.mp4'

animate_params:
num_pairs: 50
format: '.mp4'
normalization_params:
adapt_movement_scale: False
use_relative_movement: True
use_relative_jacobian: True

visualizer_params:
kp_size: 5
draw_border: True
colormap: 'gist_rainbow'

[jasonwongw]

D:\Anaconda\envs\pytorch\lib\site-packages\torch\functional.py:504: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at C:\actions-runner_work\pytorch\p
ytorch\builder\windows\pytorch\aten\src\ATen\native\TensorShape.cpp:3191.)
return _VF.meshgrid(tensors, **kwargs) # type: ignore[attr-defined]
Use predefined train-test split.
Training...
D:\Anaconda\envs\pytorch\lib\site-packages\torchvision\models_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.
warnings.warn(
D:\Anaconda\envs\pytorch\lib\site-packages\torchvision\models_utils.py:223: UserWarning: Arguments other than a weight enum or None for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior
is equivalent to passing weights=VGG19_Weights.IMAGENET1K_V1. You can also use weights=VGG19_Weights.DEFAULT to get the most up-to-date weights.
warnings.warn(msg)
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:\Users\jiewang\AppData\Roaming\Python\Python38\site-packages\skimage\io\manage_plugins.py:23: UserWarning: Your installed pillow version is < 7.1.0. Several security issues (CVE-2020-11538, CVE-2020-10379, CVE-2020-10994, CVE-202
0-10177) have been fixed in pillow 7.1.0 or higher. We recommend to upgrade this library.
from .collection import imread_collection_wrapper
C:\Users\jiewang\AppData\Roaming\Python\Python38\site-packages\skimage\io\manage_plugins.py:23: UserWarning: Your installed pillow version is < 7.1.0. Several security issues (CVE-2020-11538, CVE-2020-10379, CVE-2020-10994, CVE-20
20-10177) have been fixed in pillow 7.1.0 or higher. We recommend to upgrade this library.
from .collection import imread_collection_wrapper
C:\Users\jiewang\AppData\Roaming\Python\Python38\site-packages\skimage\io\manage_plugins.py:23: UserWarning: Your installed pillow version is < 7.1.0. Several security issues (CVE-2020-11538, CVE-2020-10379, CVE-2020-10994, CVE-20
20-10177) have been fixed in pillow 7.1.0 or higher. We recommend to upgrade this library.
from .collection import imread_collection_wrapper
C:\Users\jiewang\AppData\Roaming\Python\Python38\site-packages\skimage\io\manage_plugins.py:23: UserWarning: Your installed pillow version is < 7.1.0. Several security issues (CVE-2020-11538, CVE-2020-10379, CVE-2020-10994, CVE-20
20-10177) have been fixed in pillow 7.1.0 or higher. We recommend to upgrade this library.
from .collection import imread_collection_wrapper
C:\Users\jiewang\AppData\Roaming\Python\Python38\site-packages\skimage\io\manage_plugins.py:23: UserWarning: Your installed pillow version is < 7.1.0. Several security issues (CVE-2020-11538, CVE-2020-10379, CVE-2020-10994, CVE-20
20-10177) have been fixed in pillow 7.1.0 or higher. We recommend to upgrade this library.
from .collection import imread_collection_wrapper
C:\Users\jiewang\AppData\Roaming\Python\Python38\site-packages\skimage\io\manage_plugins.py:23: UserWarning: Your installed pillow version is < 7.1.0. Several security issues (CVE-2020-11538, CVE-2020-10379, CVE-2020-10994, CVE-20
20-10177) have been fixed in pillow 7.1.0 or higher. We recommend to upgrade this library.
from .collection import imread_collection_wrapper
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Traceback (most recent call last):
File "run.py", line 81, in
train(config, generator, discriminator, kp_detector, opt.checkpoint, log_dir, dataset, opt.device_ids)
File "D:\pycharmproject\first-order-model-master\train.py", line 51, in train
losses_generator, generated = generator_full(x)
File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\nn\parallel\data_parallel.py", line 169, in forward
return self.module(*inputs[0], **kwargs[0])
File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\pycharmproject\first-order-model-master\modules\model.py", line 152, in forward
kp_source = self.kp_extractor(x['source'])
File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\pycharmproject\first-order-model-master\modules\keypoint_detector.py", line 53, in forward
feature_map = self.predictor(x)
File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\pycharmproject\first-order-model-master\modules\util.py", line 198, in forward
return self.decoder(self.encoder(x))
File "D:\Anaconda\envs\pytorch\lib\site-packages\torch\nn\modules\module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "D:\pycharmproject\first-order-model-master\modules\util.py", line 182, in forward
out = torch.cat([out, skip], dim=1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 28 but got size 29 for tensor number 1 in the list.

[Qia98]

I met the same problem, did you solve it? It looks like a data set format problem

[rbrbrbrbb]

I met the same problem