eb8b70c825ef3e02818cbfa95c0f8a9ec4184275,theanolm/layers/dropoutlayer.py,DropoutLayer,create_structure,#DropoutLayer#,34

Before Change

        

        layer_input = self.input_layers[0].output
        self.output = tensor.switch(
            self.network.is_training,
            layer_input * self.network.random.binomial(
                layer_input.shape, p=0.5, n=1, dtype=layer_input.dtype),
            layer_input * 0.5)

After Change

        layer_input = self.input_layers[0].output
        // Pass rate is the probability of not dropping a unit.
        pass_rate = 1.0 - self.dropout_rate
        mask = self.network.random.binomial(
            layer_input.shape, p=pass_rate, n=1, dtype=layer_input.dtype)
        // Multiply the output by the inverse of the pass rate before dropping
        // units to compensate the scaling effect.
        scale_correction = 1.0 / pass_rate
        self.output = tensor.switch(
            self.network.is_training,
            layer_input * scale_correction * tensor.cast(mask, theano.config.floatX),
            layer_input)

Instances