4807d3523ea77a38461d1458fc18749a88814d37,tgen/nn.py,MaxPool1DLayer,connect,#MaxPool1DLayer#Any#,168

Before Change

    def connect(self, inputs):
        // swap dimensions (we are going to max-pool over the sentence/DA, not over embedding
        // dimensions) + pad one more dimension that we won"t use
        input_padded = T.shape_padright(inputs.dimshuffle(1, 0), 1)
        // do the max-pooling
        pooled = downsample.max_pool_2d(input_padded, (self.downscale_factor, 1), self.ignore_border)
        // remove the padded dimension + swap dimensions back
        output = pooled[:, :, 0].dimshuffle(1, 0)
        self.inputs.append(inputs)
        self.outputs.append(output)
        return output

After Change

        self.params = []  // no parameters here

    def connect(self, inputs):
        if self.stride > 1:
            output = T.max(T.reshape(inputs,
                                     (inputs.shape[0] / self.stride,
                                      inputs.shape[1] * self.stride)),
                           axis=0)
        else:
            output = T.max(inputs, axis=0)
        self.inputs.append(inputs)
        self.outputs.append(output)
        return output

Instances