(self)
| 345 | train_init_net, train_net = self.get_training_nets() |
| 346 | |
| 347 | def testFCTransposed(self): |
| 348 | input_dim = 10 |
| 349 | output_dim = 30 |
| 350 | max_length = 20 |
| 351 | input_record = self.new_record( |
| 352 | schema.Struct( |
| 353 | ('history_sequence', schema.Scalar((np.float32, (max_length, |
| 354 | input_dim)))), |
| 355 | ) |
| 356 | ) |
| 357 | fc_transposed_out = self.model.FC( |
| 358 | input_record.history_sequence, output_dim, |
| 359 | axis=2, transposed=True) |
| 360 | self.model.output_schema = fc_transposed_out |
| 361 | self.assertEqual( |
| 362 | schema.Scalar((np.float32, (max_length, output_dim))), |
| 363 | fc_transposed_out |
| 364 | ) |
| 365 | |
| 366 | train_init_net, train_net = self.get_training_nets() |
| 367 | |
| 368 | def testFCTransposedWithMaxFCSize(self): |
| 369 | input_dim = 10 |
nothing calls this directly
no test coverage detected