ce597a0b10658043b6d6d8ffed3fff4a6ebbc1ea,stellargraph/layer/appnp.py,APPNP,__init__,#APPNP#Any#Any#Any#Any#Any#Any#Any#Any#,54

Before Change

        //gather the nodes from the output indices - inputs = [all node predictions, output node indices]
        self._layers.append(
            Lambda(lambda inputs:
               K.expand_dims(
                   K.gather(
                       K.squeeze(inputs[0], 0),
                       tf.cast(K.squeeze(inputs[1], 0), tf.int32)
                    ),
                    0
               )
            )
        )

    def __call__(self, x):
        

After Change

        if not isinstance(approx_iter, int) or approx_iter <= 0:
            raise ValueError("approx_iter should be a positive integer")

        if (transport_probability > 1.0) or (transport_probability < 0.0):
            raise ValueError("transport_probability should be between 0 and 1 (inclusive)")

        self.layer_sizes = layer_sizes
        self.transport_probability = transport_probability
        self.activations = activations
        self.bias = bias
        self.dropout = dropout
        self.kernel_regularizer = kernel_regularizer
        self.generator = generator
        self.support = 1
        self.method = generator.method
        self.approx_iter = approx_iter

        // Check if the generator is producing a sparse matrix
        self.use_sparse = generator.use_sparse
        if self.method == "none":

Instances