Source code for numpynet.layers.base

class Layer:
    def __init__(self, trainable=True, name=None):
        self.trainable = trainable
        self.name = name
        self._built = False



    def build(self, input_shape):
        self._built = True




    def forward(self, x, training=False):
        raise NotImplementedError




    def backward(self, grad):
        raise NotImplementedError


    def __call__(self, x, training=False):
        return self.forward(x, training=training)

    @property
    def params(self):
        return {}

    @property
    def grads(self):
        return {}



    def get_config(self):
        return {"name": self.name, "trainable": self.trainable}




    def count_params(self):
        total = 0
        for p in self.params.values():
            total += p.size
        return total