TinghuiWang /
pyActLearn
| @@ 50-59 (lines=10) @@ | ||
| 47 | self.summaries = [] |
|
| 48 | # Create Layers |
|
| 49 | for i in range(len(layers)): |
|
| 50 | if i == 0: |
|
| 51 | # First Layer |
|
| 52 | self.inner_layers.append( |
|
| 53 | HiddenLayer(num_features, layers[i], x=self.x, name=('Hidden%d' % i), activation_fn=activation_fn) |
|
| 54 | ) |
|
| 55 | else: |
|
| 56 | # inner Layer |
|
| 57 | self.inner_layers.append( |
|
| 58 | HiddenLayer(layers[i-1], layers[i], x=self.inner_layers[i-1].y, |
|
| 59 | name=('Hidden%d' % i), activation_fn=activation_fn) |
|
| 60 | ) |
|
| 61 | self.summaries += self.inner_layers[i].summaries |
|
| 62 | if num_classes == 1: |
|
| @@ 48-56 (lines=9) @@ | ||
| 45 | self.tuning_optimizer = tuning_optimizer |
|
| 46 | # Create Layers |
|
| 47 | for i in range(len(layers)): |
|
| 48 | if i == 0: |
|
| 49 | # First Layer |
|
| 50 | self.inner_layers.append( |
|
| 51 | AutoencoderLayer(num_features, layers[i], x=self.x, name=('Hidden%d' % i)) |
|
| 52 | ) |
|
| 53 | else: |
|
| 54 | # inner Layer |
|
| 55 | self.inner_layers.append( |
|
| 56 | AutoencoderLayer(layers[i-1], layers[i], x=self.inner_layers[i-1].y, name=('Hidden%d' % i)) |
|
| 57 | ) |
|
| 58 | self.summaries += self.inner_layers[i].summaries |
|
| 59 | self.encode_opts.append( |
|
