`group_sparsity` regularization results in an error with different conv types

[mohammadbashiri]

The group_sparsity regularizer of the Stacked2dCore the convolution layers are referred to as conv, but that does not generalize to other conv layer types like ds_conv for instance.

neuralpredictors/neuralpredictors/layers/cores/conv2d.py

Lines 247 to 257 in 7f1b303

	def group_sparsity(self):
	"""
	Sparsity regularization on the filters of all the conv2d layers except the first one.
	"""
	ret = 0
	for feature in self.features[1:]:
	ret = ret + feature.conv.weight.pow(2).sum(3, keepdim=True).sum(2, keepdim=True).sqrt().mean()
	return ret / ((self.num_layers - 1) if self.num_layers > 1 else 1)
	def regularizer(self):
	return self.group_sparsity() * self.gamma_hidden + self.gamma_input * self.laplace()