elmo.py 文件源码

def _load_projection(self):
        cnn_options = self._options['char_cnn']
        filters = cnn_options['filters']
        n_filters = sum(f[1] for f in filters)

        self._projection = torch.nn.Linear(n_filters, self.output_dim, bias=True)
        with h5py.File(cached_path(self._weight_file), 'r') as fin:
            weight = fin['CNN_proj']['W_proj'][...]
            bias = fin['CNN_proj']['b_proj'][...]
            self._projection.weight.data.copy_(torch.FloatTensor(numpy.transpose(weight)))
            self._projection.bias.data.copy_(torch.FloatTensor(bias))

            self._projection.weight.requires_grad = False
            self._projection.bias.requires_grad = False