b68db1aaf6abe4d2cea8321cc6f1564228dd60f5,deepchem/models/tensorgraph/models/seqtoseq.py,AspuruGuzikAutoEncoder,_create_encoder,#AspuruGuzikAutoEncoder#Any#Any#,501
Before Change
prev_layer = layers.Dense(
self._decoder_dimension, in_layers=prev_layer, activation_fn=tf.nn.relu)
prev_layer = layers.BatchNorm(prev_layer)
if self._variational:
self._embedding_mean = layers.Dense(
self._embedding_dimension,
in_layers=prev_layer,
name="embedding_mean")
self._embedding_stddev = layers.Dense(
self._embedding_dimension, in_layers=prev_layer, name="embedding_std")
prev_layer = layers.CombineMeanStd(
[self._embedding_mean, self._embedding_stddev], training_only=True)
return prev_layer
def _create_decoder(self, n_layers, dropout):
Create the decoder layers.
After Change
def _create_encoder(self, n_layers, dropout):
Create the encoder as a tf.keras.Model.
input = self._create_features()
gather_indices = Input(shape=(2,), dtype=tf.int32)
prev_layer = input
for i in range(len(self._filter_sizes)):
filter_size = self._filter_sizes[i]
kernel_size = self._kernel_sizes[i]
if dropout > 0.0:
prev_layer = Dropout(rate=dropout)(prev_layer)
prev_layer = Conv1D(
filters=filter_size, kernel_size=kernel_size,
activation=tf.nn.relu)(prev_layer)
prev_layer = Flatten()(prev_layer)
prev_layer = Dense(
self._decoder_dimension, activation=tf.nn.relu)(prev_layer)
prev_layer = BatchNormalization()(prev_layer)
return tf.keras.Model(inputs=[input, gather_indices], outputs=prev_layer)
def _create_decoder(self, n_layers, dropout):
Create the decoder as a tf.keras.Model.
In pattern: SUPERPATTERN
Frequency: 3
Non-data size: 7
Instances
Project Name: deepchem/deepchem
Commit Name: b68db1aaf6abe4d2cea8321cc6f1564228dd60f5
Time: 2019-05-31
Author: peastman@stanford.edu
File Name: deepchem/models/tensorgraph/models/seqtoseq.py
Class Name: AspuruGuzikAutoEncoder
Method Name: _create_encoder
Project Name: stellargraph/stellargraph
Commit Name: 59266e34e076ed25852bccf5ce13025b5408406f
Time: 2019-05-28
Author: andrew.docherty@data61.csiro.au
File Name: stellargraph/layer/gcn.py
Class Name: GCN
Method Name: node_model
Project Name: deepchem/deepchem
Commit Name: b68db1aaf6abe4d2cea8321cc6f1564228dd60f5
Time: 2019-05-31
Author: peastman@stanford.edu
File Name: deepchem/models/tensorgraph/models/seqtoseq.py
Class Name: SeqToSeq
Method Name: _create_encoder