例如,这是微不足道的,但是为此有一层吗?并不是真正的卷积...每个数据点只有一个“密集层”(权重)。
In [266]: X = np.random.randn(10, 3); W = np.random.randn(10, 3, 4); (X[:, :, None] * W).sum(axis=1).shape
Out[266]: (10, 4)
创建自己的图层:
警告:仅适用于固定批次大小,您需要在模型中定义
batch_shape
或batch_input_shape
!!!!
class SampleDense(Layer):
def __init__(self, units, **kwargs):
self.units = units
super(SampleDense, self).__init__(**kwargs)
def build(self, input_shape):
weight_shape = input_shape + (self.units,)
self.kernel = self.add_weight(name='kernel',
shape=weight_shape,
initializer='uniform',
trainable=True)
self.built = True
def call(self, inputs):
inputs = K.expand_dims(inputs, axis=-1)
outputs = inputs * self.kernel
outputs = K.sum(outputs, axis=-2)
return outputs
def compute_output_shape(self, input_shape):
return input_shape[:-1] + (self.units,)