encode the features of `Data` to tensors. Args: data: A `Data` object. Returns: A Tensor.
(self, data)
| 185 | self._fused_int_mapping[spec.dimension] = ib |
| 186 | |
| 187 | def forward(self, data): |
| 188 | """ encode the features of `Data` to tensors. |
| 189 | Args: |
| 190 | data: A `Data` object. |
| 191 | Returns: |
| 192 | A Tensor. |
| 193 | """ |
| 194 | outputs = [] |
| 195 | if self._float_fg: |
| 196 | float_outputs = self._float_fg(data.float_attrs) |
| 197 | outputs.append(float_outputs) |
| 198 | |
| 199 | if self._int_fg: |
| 200 | ints = [data.int_attrs[:,i] for i in self._int_mapping] |
| 201 | int_outputs = self._int_fg(ints) |
| 202 | outputs.append(int_outputs) |
| 203 | |
| 204 | if self._fused_int_fg: |
| 205 | fused_inputs = [] |
| 206 | for dim, ib in self._fused_int_mapping.items(): |
| 207 | fused_inputs.append([data.int_attrs[:,i] for i in ib.index_list]) |
| 208 | fused_int_outputs = self._fused_int_fg(fused_inputs) |
| 209 | outputs.append(fused_int_outputs) |
| 210 | |
| 211 | if self._string_fg: |
| 212 | string_outputs = self._string_fg(data.string_attrs) |
| 213 | outputs.append(string_outputs) |
| 214 | |
| 215 | return tf.concat(outputs, -1) |
no test coverage detected