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Error message:
RuntimeError: Error(s) in loading state_dict for KAN:
Missing key(s) in state_dict: "biases.3.weight", "act_fun.3.grid", "act_fun.3.coef", "act_fun.3.scale_base", "act_fun.3.scale_sp", "act_fun.3.mask", "symbolic_fun.3.mask", "symbolic_fun.3.affine".
size mismatch for biases.0.weight: copying a param with shape torch.Size([1, 1]) from checkpoint, the shape in current model is torch.Size([1, 2]).
size mismatch for biases.1.weight: copying a param with shape torch.Size([1, 4]) from checkpoint, the shape in current model is torch.Size([1, 10]).
size mismatch for biases.2.weight: copying a param with shape torch.Size([1, 5]) from checkpoint, the shape in current model is torch.Size([1, 1]).
size mismatch for act_fun.0.grid: copying a param with shape torch.Size([10, 5]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.0.coef: copying a param with shape torch.Size([10, 6]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.0.scale_base: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.0.scale_sp: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.0.mask: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.1.grid: copying a param with shape torch.Size([4, 5]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.1.coef: copying a param with shape torch.Size([4, 6]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.1.scale_base: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.1.scale_sp: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.1.mask: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.2.grid: copying a param with shape torch.Size([20, 5]) from checkpoint, the shape in current model is torch.Size([10, 7]).
size mismatch for act_fun.2.coef: copying a param with shape torch.Size([20, 6]) from checkpoint, the shape in current model is torch.Size([10, 7]).
size mismatch for act_fun.2.scale_base: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([10]).
size mismatch for act_fun.2.scale_sp: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([10]).
size mismatch for act_fun.2.mask: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([10]).
size mismatch for symbolic_fun.0.mask: copying a param with shape torch.Size([1, 10]) from checkpoint, the shape in current model is torch.Size([2, 10]).
size mismatch for symbolic_fun.0.affine: copying a param with shape torch.Size([1, 10, 4]) from checkpoint, the shape in current model is torch.Size([2, 10, 4]).
size mismatch for symbolic_fun.1.mask: copying a param with shape torch.Size([4, 1]) from checkpoint, the shape in current model is torch.Size([10, 2]).
size mismatch for symbolic_fun.1.affine: copying a param with shape torch.Size([4, 1, 4]) from checkpoint, the shape in current model is torch.Size([10, 2, 4]).
size mismatch for symbolic_fun.2.mask: copying a param with shape torch.Size([5, 4]) from checkpoint, the shape in current model is torch.Size([1, 10]).
size mismatch for symbolic_fun.2.affine: copying a param with shape torch.Size([5, 4, 4]) from checkpoint, the shape in current model is torch.Size([1, 10, 4]).
Error message:
RuntimeError: Error(s) in loading state_dict for KAN:
Missing key(s) in state_dict: "biases.3.weight", "act_fun.3.grid", "act_fun.3.coef", "act_fun.3.scale_base", "act_fun.3.scale_sp", "act_fun.3.mask", "symbolic_fun.3.mask", "symbolic_fun.3.affine".
size mismatch for biases.0.weight: copying a param with shape torch.Size([1, 1]) from checkpoint, the shape in current model is torch.Size([1, 2]).
size mismatch for biases.1.weight: copying a param with shape torch.Size([1, 4]) from checkpoint, the shape in current model is torch.Size([1, 10]).
size mismatch for biases.2.weight: copying a param with shape torch.Size([1, 5]) from checkpoint, the shape in current model is torch.Size([1, 1]).
size mismatch for act_fun.0.grid: copying a param with shape torch.Size([10, 5]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.0.coef: copying a param with shape torch.Size([10, 6]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.0.scale_base: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.0.scale_sp: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.0.mask: copying a param with shape torch.Size([10]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.1.grid: copying a param with shape torch.Size([4, 5]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.1.coef: copying a param with shape torch.Size([4, 6]) from checkpoint, the shape in current model is torch.Size([20, 7]).
size mismatch for act_fun.1.scale_base: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.1.scale_sp: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.1.mask: copying a param with shape torch.Size([4]) from checkpoint, the shape in current model is torch.Size([20]).
size mismatch for act_fun.2.grid: copying a param with shape torch.Size([20, 5]) from checkpoint, the shape in current model is torch.Size([10, 7]).
size mismatch for act_fun.2.coef: copying a param with shape torch.Size([20, 6]) from checkpoint, the shape in current model is torch.Size([10, 7]).
size mismatch for act_fun.2.scale_base: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([10]).
size mismatch for act_fun.2.scale_sp: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([10]).
size mismatch for act_fun.2.mask: copying a param with shape torch.Size([20]) from checkpoint, the shape in current model is torch.Size([10]).
size mismatch for symbolic_fun.0.mask: copying a param with shape torch.Size([1, 10]) from checkpoint, the shape in current model is torch.Size([2, 10]).
size mismatch for symbolic_fun.0.affine: copying a param with shape torch.Size([1, 10, 4]) from checkpoint, the shape in current model is torch.Size([2, 10, 4]).
size mismatch for symbolic_fun.1.mask: copying a param with shape torch.Size([4, 1]) from checkpoint, the shape in current model is torch.Size([10, 2]).
size mismatch for symbolic_fun.1.affine: copying a param with shape torch.Size([4, 1, 4]) from checkpoint, the shape in current model is torch.Size([10, 2, 4]).
size mismatch for symbolic_fun.2.mask: copying a param with shape torch.Size([5, 4]) from checkpoint, the shape in current model is torch.Size([1, 10]).
size mismatch for symbolic_fun.2.affine: copying a param with shape torch.Size([5, 4, 4]) from checkpoint, the shape in current model is torch.Size([1, 10, 4]).
Code:
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