def __init__()

in adaptive_io.py [0:0]

• 22 lines of code
• 2 McCabe index (conditional complexity)

    def __init__(self, n_tokens, d_embed, d_proj, cutoffs, div_val=4):
        super(ProjectedAdaptiveLogSoftmax, self).__init__()

        self.n_tokens = n_tokens
        self.d_embed = d_embed
        self.d_proj = d_proj

        assert 0 < min(cutoffs) <= max(cutoffs) < n_tokens
        self.cutoffs = cutoffs + [n_tokens]
        self.cutoff_ends = [0] + self.cutoffs
        self.div_val = div_val
        assert self.div_val > 1
        assert len(self.cutoffs) > 1

        self.shortlist_size = self.cutoffs[0]
        self.n_clusters = len(self.cutoffs) - 1
        self.head_size = self.shortlist_size + self.n_clusters

        # clusters parameters
        self.cluster_proj = nn.Linear(self.d_embed, self.n_clusters)

        self.out_layers = nn.ModuleList()
        self.out_projs = nn.ParameterList()

        # output layers / projections
        for i in range(len(self.cutoffs)):
            l_idx, r_idx = self.cutoff_ends[i], self.cutoff_ends[i + 1]
            d_emb_i = d_embed // (div_val ** i)
            self.out_projs.append(nn.Linear(d_emb_i, d_proj).weight)
            self.out_layers.append(nn.Linear(d_emb_i, r_idx - l_idx))