(self)
| 210 | return ops_output |
| 211 | |
| 212 | def testFCWithoutBias(self): |
| 213 | output_dims = 2 |
| 214 | fc_without_bias = self.model.FCWithoutBias( |
| 215 | self.model.input_feature_schema.float_features, output_dims) |
| 216 | self.model.output_schema = fc_without_bias |
| 217 | |
| 218 | self.assertEqual( |
| 219 | schema.Scalar((np.float32, (output_dims, ))), |
| 220 | fc_without_bias |
| 221 | ) |
| 222 | |
| 223 | train_init_net, train_net = self.get_training_nets() |
| 224 | |
| 225 | init_ops = self.assertNetContainOps( |
| 226 | train_init_net, |
| 227 | [ |
| 228 | OpSpec("UniformFill", None, None), |
| 229 | ] |
| 230 | ) |
| 231 | |
| 232 | mat_mul_spec = OpSpec( |
| 233 | "MatMul", |
| 234 | [ |
| 235 | self.model.input_feature_schema.float_features(), |
| 236 | init_ops[0].output[0], |
| 237 | ], |
| 238 | fc_without_bias.field_blobs() |
| 239 | ) |
| 240 | |
| 241 | self.assertNetContainOps(train_net, [mat_mul_spec]) |
| 242 | |
| 243 | predict_net = self.get_predict_net() |
| 244 | self.assertNetContainOps(predict_net, [mat_mul_spec]) |
| 245 | |
| 246 | def testFCWithBootstrap(self): |
| 247 | output_dims = 1 |
nothing calls this directly
no test coverage detected