5,337
edits
TensorFlow: Difference between revisions
→Custom Layers
| Line 104: | Line 104: | ||
w_pad,h_pad = self.padding | w_pad,h_pad = self.padding | ||
return tf.pad(x, [[0,0], [h_pad,h_pad], [w_pad,w_pad], [0,0] ], 'REFLECT') | return tf.pad(x, [[0,0], [h_pad,h_pad], [w_pad,w_pad], [0,0] ], 'REFLECT') | ||
</syntaxhighlight> | |||
}} | |||
{{ hidden | BilinearUpsample | | |||
<syntaxhighlight lang="python"> | |||
class BilinearUpsample(layers.Layer): | |||
def __init__(self): | |||
super().__init__() | |||
self.input_spec = [keras.layers.InputSpec(ndim=4)] | |||
def compute_output_shape(self, shape): | |||
return shape[0], 2 * shape[1], 2 * shape[2], shape[3] | |||
def call(self, inputs, training=None, mask=None): | |||
new_height = int(2 * inputs.shape[1]) | |||
new_width = int(2 * inputs.shape[2]) | |||
return tf.image.resize_images(inputs, [new_height, new_width]) | |||
</syntaxhighlight> | </syntaxhighlight> | ||
}} | }} | ||