I was trying to use learn2learn’s QuickDraw but it seems like I’m getting errors when I attempt to apply transformations (resizing to 84x84, random crop) on it. The issue stems from when l2l’s quickdraw library attempts to apply transformations onto a quickdraw image (that is apparently in the form of a np.memmap/.npy record that PIL can’t understand) and so I get the following error:
Traceback (most recent call last):
File "/home/pzy2/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/dataloaders/maml_patricks_l2l.py", line 2300, in <module>
loop_through_l2l_indexable_benchmark_with_model_test()
File "/home/pzy2/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/dataloaders/maml_patricks_l2l.py", line 2259, in loop_through_l2l_indexable_benchmark_with_model_test
for benchmark in [quickdraw_l2l_tasksets()]: #hdb8_l2l_tasksets(),hdb9_l2l_tasksets(), delaunay_l2l_tasksets()]:#[dtd_l2l_tasksets(), cu_birds_l2l_tasksets(), fc100_l2l_tasksets()]:
File "/home/pzy2/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/dataloaders/maml_patricks_l2l.py", line 2216, in quickdraw_l2l_tasksets
_transforms: tuple[TaskTransform, TaskTransform, TaskTransform] = get_task_transforms_quickdraw(_datasets,
File "/home/pzy2/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/dataloaders/maml_patricks_l2l.py", line 2184, in get_task_transforms_quickdraw
train_transforms: TaskTransform = DifferentTaskTransformIndexableForEachDataset(train_dataset,
File "/home/pzy2/diversity-for-predictive-success-of-meta-learning/div_src/diversity_src/dataloaders/common.py", line 130, in __init__
self.indexable_dataset = MetaDataset(indexable_dataset)
File "learn2learn/data/meta_dataset.pyx", line 59, in learn2learn.data.meta_dataset.MetaDataset.__init__
File "learn2learn/data/meta_dataset.pyx", line 96, in learn2learn.data.meta_dataset.MetaDataset.create_bookkeeping
File "learn2learn/data/meta_dataset.pyx", line 65, in learn2learn.data.meta_dataset.MetaDataset.__getitem__
File "/home/pzy2/miniconda3/envs/metalearning3.9/lib/python3.9/site-packages/learn2learn/vision/datasets/quickdraw.py", line 511, in __getitem__
image = self.transform(image)
File "/home/pzy2/miniconda3/envs/metalearning3.9/lib/python3.9/site-packages/torchvision/transforms/transforms.py", line 60, in __call__
img = t(img)
File "/home/pzy2/miniconda3/envs/metalearning3.9/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/pzy2/miniconda3/envs/metalearning3.9/lib/python3.9/site-packages/torchvision/transforms/transforms.py", line 900, in forward
i, j, h, w = self.get_params(img, self.scale, self.ratio)
File "/home/pzy2/miniconda3/envs/metalearning3.9/lib/python3.9/site-packages/torchvision/transforms/transforms.py", line 859, in get_params
width, height = F._get_image_size(img)
File "/home/pzy2/miniconda3/envs/metalearning3.9/lib/python3.9/site-packages/torchvision/transforms/functional.py", line 67, in _get_image_size
return F_pil._get_image_size(img)
File "/home/pzy2/miniconda3/envs/metalearning3.9/lib/python3.9/site-packages/torchvision/transforms/functional_pil.py", line 26, in _get_image_size
raise TypeError("Unexpected type {}".format(type(img)))
TypeError: Unexpected type <class 'numpy.memmap'>
original: