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Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

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hello,may i ask you a question? when i read your code,"main.py",i was confused about the meaning of the parameter test_num_updates ? can you explain it to me? it seems a...

why instead of `unused = task_metalearn((self.inputa[0], self.inputb[0], self.labela[0], self.labelb[0]), False)` you haven't used the following: `unused = self.forward(self.inputa[0], weights, reuse=reuse) ` ?

In the omniglot dataset, images are in black and white mode. When resizing in that mode, resampling is useless as gray tones are not allowed. As you specified a resample...

Is it possible to create a tests file to highlight basic usage scenarios? For example, in sklearn, a simple regression task looks like... ```python import matplotlib.pyplot as plt from sklearn.linear_model...