930f22933523259b1a152dc3174312357fb99fb9,tgen/nn.py,MaxPool1DLayer,connect,#MaxPool1DLayer#Any#,169

Before 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)


//         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), False)
//         // 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

        // do the max-pooling
        pooled = downsample.max_pool_2d(input_padded, (self.downscale_factor, 1), False)
        // remove the padded dimension + swap dimensions back
        output = pooled[:, :, 0].dimshuffle(1, 0)

        self.inputs.append(inputs)
        self.outputs.append(output)
        return output

Instances