(self)
| 366 | train_init_net, train_net = self.get_training_nets() |
| 367 | |
| 368 | def testFCTransposedWithMaxFCSize(self): |
| 369 | input_dim = 10 |
| 370 | output_dim = 30 |
| 371 | max_length = 20 |
| 372 | input_record = self.new_record( |
| 373 | schema.Struct( |
| 374 | ('history_sequence', schema.Scalar((np.float32, (max_length, |
| 375 | input_dim)))), |
| 376 | ) |
| 377 | ) |
| 378 | fc_transposed_out = self.model.FC( |
| 379 | input_record.history_sequence, output_dim, |
| 380 | max_fc_size=input_dim * output_dim // 2, |
| 381 | axis=2, transposed=True) |
| 382 | self.model.output_schema = fc_transposed_out |
| 383 | self.assertEqual( |
| 384 | schema.Scalar((np.float32, (max_length, output_dim))), |
| 385 | fc_transposed_out |
| 386 | ) |
| 387 | |
| 388 | train_init_net, train_net = self.get_training_nets() |
| 389 | |
| 390 | def testSparseLookupSumPoolingWithEviction(self): |
| 391 | # Create test embedding table of 1 row |
nothing calls this directly
no test coverage detected