Return this network as a ModelLayer so that it can be integrated into another Model. Examples -------- >>> from tensorlayer.layers import Input, Dense, Dropout >>> from tensorlayer.models import Model >>> ni = Input([None, 784]) >>> nn = Dense(n_units
(self)
| 545 | self.eval() |
| 546 | |
| 547 | def as_layer(self): |
| 548 | """Return this network as a ModelLayer so that it can be integrated into another Model. |
| 549 | |
| 550 | Examples |
| 551 | -------- |
| 552 | >>> from tensorlayer.layers import Input, Dense, Dropout |
| 553 | >>> from tensorlayer.models import Model |
| 554 | >>> ni = Input([None, 784]) |
| 555 | >>> nn = Dense(n_units=800, act=tf.nn.relu)(ni) |
| 556 | >>> nn = Dropout(keep=0.8)(nn) |
| 557 | >>> nn = Dense(n_units=10, act=tf.nn.relu)(nn) |
| 558 | >>> M_hidden = Model(inputs=ni, outputs=nn, name="mlp").as_layer() |
| 559 | >>> nn = M_hidden(ni) # use previously constructed model as layer |
| 560 | >>> nn = Dropout(keep=0.8)(nn) |
| 561 | >>> nn = Dense(n_units=10, act=tf.nn.relu)(nn) |
| 562 | >>> M_full = Model(inputs=ni, outputs=nn, name="mlp") |
| 563 | |
| 564 | """ |
| 565 | if self._outputs is None: |
| 566 | raise AttributeError("Dynamic network cannot be converted to Layer.") |
| 567 | |
| 568 | if self._model_layer is None: |
| 569 | self._model_layer = ModelLayer(self) |
| 570 | |
| 571 | return self._model_layer |
| 572 | |
| 573 | def _check_mode(self, is_train): |
| 574 | """Check whether this network is in a given mode. |