c25fa38deb4efc5445f64af3ec17eae0eb660d2f,keras/models.py,Sequential,add,#Sequential#Any#,409

Before Change

                // to the input layer we just created.
                layer(x)

            if len(layer.inbound_nodes) != 1:
                raise ValueError("A layer added to a Sequential model must "
                                 "not already be connected somewhere else. "
                                 "Model received layer " + layer.name +
                                 " which has " +
                                 str(len(layer.inbound_nodes)) +
                                 " pre-existing inbound connections.")

            if len(layer.inbound_nodes[0].output_tensors) != 1:
                raise ValueError("All layers in a Sequential model "
                                 "should have a single output tensor. "
                                 "For multi-output layers, "

After Change

                    // In case of nested models: recover the first layer
                    // of the deepest model to infer input shape and dtype.
                    first_layer = layer.layers[0]
                    while isinstance(first_layer, (Model, Sequential)):
                        first_layer = first_layer.layers[0]
                    batch_shape = first_layer.batch_input_shape
                    dtype = first_layer.dtype
                else:
                    // We were passed a regular layer, and it should

Instances