Method _add_ops

caffe2/python/layers/fc.py:171–204

Args: params : the weight and bias, passed by either add_ops or add_train_ops function version : fp16 or fp32, might support in8 in the future.

(self, net, params, version)

            raise Exception("unsupported FC type version {}".format(version))

    def _add_ops(self, net, params, version):
        """
        Args:
            params : the weight and bias,
                passed by either add_ops or add_train_ops function
            version : fp16 or fp32, might support in8 in the future.
        """
        if self.clip_args is not None:
            clipped_params = [net.NextScopedBlob(
                'clipped_%s' % str(p)) for p in params]
            for p, cp in zip(params, clipped_params):
                net.Clip([p], [cp], **self.clip_args)
            params = clipped_params

        if self.output_dim_vec is None or len(self.output_dim_vec) == 1:
            self._insert_fc_ops(net, params, self.output_schema.field_blobs(), version)
        else:
            w_vec = params[:int(len(params) / 2)]
            b_vec = params[int(len(params) / 2):]

            assert len(w_vec) == len(b_vec)

            output_blob_vec = []

            for i in range(len(self.output_dim_vec)):
                output_blob = net.NextScopedBlob(
                    'output_sub_{}'.format(i))
                insert_ret = self._insert_fc_ops(
                    net, [w_vec[i], b_vec[i]], [output_blob], version
                )
                output_blob_vec.append(insert_ret)
            net.Concat(output_blob_vec,
                       self.output_schema.field_blobs() +
                       [self.output_schema.field_blobs()[0] + "_concat_dims"])

    def add_ops(self, net):
        """Both the predict net and the eval net will call this function