357d1611c7a222b55a5b4f2b3399bde14a9ac0ea,tgen/nn.py,MaxPool1DLayer,connect,#MaxPool1DLayer#Any#,167

Before Change

    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)

After Change

//             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

Instances