When I used 128*128 for training, the following errors have been shown
[rank0]: context_feats, context, rgb_features = self.encoder.encode_images(
[rank0]: File "/home/sly/FlowRAM/diffuser_actor/utils/encoder.py", line 185, in encode_images
[rank0]: rgb_features = rgb_features[self.feature_map_pyramid[0]] # flow-8 都是256的 original
[rank0]: File "/home/sly/anaconda3/envs/flowram/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1962, in getattr
[rank0]: raise AttributeError(
[rank0]: AttributeError: 'Encoder' object has no attribute 'feature_map_pyramid'. Did you mean: 'feature_pyramid'?
In encoder.py if 128128,then feature_map_pyramid realled coarse_feature_map, but even I used coarse_feature_map, still new errors about tensor shape existed, could you plz try using 128128 with your code?
if self.image_size == (128, 128):
print("self.image_size=",self.image_size)
# Coarse RGB features are the 2nd layer of the feature pyramid
# at 1/4 resolution (32x32)
# Fine RGB features are the 1st layer of the feature pyramid
# at 1/2 resolution (64x64)
self.coarse_feature_map = ['res5', 'res1', 'res1', 'res1']
self.downscaling_factor_pyramid = [4, 2, 2, 2]
elif self.image_size == (256, 256):
# Coarse RGB features are the 3rd layer of the feature pyramid
# at 1/8 resolution (32x32)
# Fine RGB features are the 1st layer of the feature pyramid
# at 1/2 resolution (128x128)
self.feature_map_pyramid = ['res3', 'res1', 'res1', 'res1']
self.downscaling_factor_pyramid = [8, 2, 2, 2]
Or could you plz provide 256*256 dataset, only one task data is fine, I just want to run your code no need to check the final performance. Thanks in advance!!
When I used 128*128 for training, the following errors have been shown
[rank0]: context_feats, context, rgb_features = self.encoder.encode_images(
[rank0]: File "/home/sly/FlowRAM/diffuser_actor/utils/encoder.py", line 185, in encode_images
[rank0]: rgb_features = rgb_features[self.feature_map_pyramid[0]] # flow-8 都是256的 original
[rank0]: File "/home/sly/anaconda3/envs/flowram/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1962, in getattr
[rank0]: raise AttributeError(
[rank0]: AttributeError: 'Encoder' object has no attribute 'feature_map_pyramid'. Did you mean: 'feature_pyramid'?
In encoder.py if 128128,then feature_map_pyramid realled coarse_feature_map, but even I used coarse_feature_map, still new errors about tensor shape existed, could you plz try using 128128 with your code?
if self.image_size == (128, 128):
print("self.image_size=",self.image_size)
# Coarse RGB features are the 2nd layer of the feature pyramid
# at 1/4 resolution (32x32)
# Fine RGB features are the 1st layer of the feature pyramid
# at 1/2 resolution (64x64)
self.coarse_feature_map = ['res5', 'res1', 'res1', 'res1']
self.downscaling_factor_pyramid = [4, 2, 2, 2]
elif self.image_size == (256, 256):
# Coarse RGB features are the 3rd layer of the feature pyramid
# at 1/8 resolution (32x32)
# Fine RGB features are the 1st layer of the feature pyramid
# at 1/2 resolution (128x128)
self.feature_map_pyramid = ['res3', 'res1', 'res1', 'res1']
self.downscaling_factor_pyramid = [8, 2, 2, 2]
Or could you plz provide 256*256 dataset, only one task data is fine, I just want to run your code no need to check the final performance. Thanks in advance!!