forked from TensorLayer/tensorlayer3
58 lines
1.4 KiB
Python
58 lines
1.4 KiB
Python
#! /usr/bin/python
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# -*- coding: utf-8 -*-
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import tensorlayer as tl
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from tensorlayer import logging
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from tensorlayer.layers.core import Module
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__all__ = [
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'Scale',
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]
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class Scale(Module):
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"""The :class:`Scale` class is to multiple a trainable scale value to the layer outputs. Usually be used on the output of binary net.
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Parameters
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----------
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init_scale : float
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The initial value for the scale factor.
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name : a str
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A unique layer name.
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Examples
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----------
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>>> inputs = tl.layers.Input([8, 3])
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>>> dense = tl.layers.Dense(n_units=10, in_channels=3)(inputs)
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>>> outputs = tl.layers.Scale(init_scale=0.5)(dense)
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"""
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def __init__(
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self,
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init_scale=0.05,
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name='scale',
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):
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super(Scale, self).__init__(name)
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self.init_scale = init_scale
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self.build((None, ))
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self._built = True
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logging.info("Scale %s: init_scale: %f" % (self.name, self.init_scale))
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def __repr__(self):
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s = '{classname}('
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s += 'init_scale={init_scale},'
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s += 'name={name}'
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s += ")"
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return s.format(classname=self.__class__.__name__, **self.__dict__)
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def build(self, inputs_shape):
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self.scale = self._get_weights("scale", shape=[1], init=tl.initializers.constant(value=self.init_scale))
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# @tf.function
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def forward(self, inputs):
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outputs = inputs * self.scale
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return outputs
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