def forward(self, x, sampled_values, label):
sampled_candidates, _, _ = sampled_values<EOL>label = label.reshape(shape=(-<NUM_LIT:1>,))<EOL>ids = nd.concat(sampled_candidates, label, dim=<NUM_LIT:0>)<EOL>weight = self.weight.row_sparse_data(ids)<EOL>bias = self.bias.data(ids.context)<EOL>w_all = nd.Embedding(data=ids, weight=weight, **self._kwargs)<EOL>b_all = nd.take(bias, indices=ids)<EOL>out, new_targets = self._dense(x, sampled_values, label, w_all, b_all)<EOL>return out, new_targets<EOL>
Forward computation.