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[HamdiAbed]

What is the correct way to change embedding sizes in Tiny or Small supernet? what is the criteria of selecting the embedding sizes. I got this error almost every time I try to set EMBED_DIM in the supernet-T.yaml

qkv = self.qkv(x).reshape([B, N, 3, self.sample_num_heads, -1]).permute(2, 0, 3, 1, 4)
RuntimeError: shape '[16, 32, 3, 3, -1]' is invalid for input of size 61440