import tensorflow as tf
from tensorflow.keras.layers import Layer
[docs]class SumLayer(Layer):
"""
Layer which adds all inputs together. All inputs must have compatible shapes
Example:
>>> # Create a model with just a SumLayer and two inputs
>>> input_1 = tf.keras.layers.Input(10)
>>> input_2 = tf.keras.layers.Input(10)
>>> sum_layer = mann.layers.SumLayer()([input_1, input_2])
>>> model = tf.keras.models.Model([input_1, input_2], sum_layer)
>>> model.compile()
>>> # Call the model
>>> data = np.arange(10).reshape((1, 10))
>>> model.predict([data, data])
array([[ 0., 2., 4., 6., 8., 10., 12., 14., 16., 18.]], dtype=float32)
"""
def __init__(self, **kwargs):
super(SumLayer, self).__init__(**kwargs)
[docs] def call(self, inputs):
"""
This is where the layer's logic lives and is called upon inputs
Parameters
----------
inputs : TensorFlow Tensor or Tensor-like
The inputs to the layer
Returns
-------
outputs : TensorFlow Tensor
The outputs of the layer's logic
"""
return tf.add_n(inputs)
[docs] def get_config(self):
return super().get_config().copy()
[docs] @classmethod
def from_config(cls, config):
return cls(**config)