[ci skip] Update Keras version in writing-your-own-keras-layers.md
For simple, stateless custom operations, you are probably better off using `layers.core.Lambda` layers. But for any custom operation that has trainable weights, you should implement your own layer.
-Here is the skeleton of a Keras layer, **as of Keras 1.2.0** (if you have an older version, please upgrade). There are only three methods you need to implement:
+Here is the skeleton of a Keras layer, **as of Keras 2.0** (if you have an older version, please upgrade). There are only three methods you need to implement:
- `build(input_shape)`: this is where you will define your weights. This method must set `self.built = True`, which can be done by calling `super([Layer], self).build()`.
- `call(x)`: this is where the layer's logic lives. Unless you want your layer to support masking, you only have to care about the first argument passed to `call`: the input tensor.
