How to use _activate method in pyatom

Best Python code snippet using pyatom_python

Layers.py

Source:Layers.py Github

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...5 def __init__(self, shape):6 self.shape = shape7 def activate(self, x, w, bias=None, predict=False):8 if bias is None:9 return self._activate(tf.matmul(x, w), predict)10 return self._activate(tf.matmul(x, w) + bias, predict)11 @abstractmethod12 def _activate(self, x, predict):13 pass14# Activation Layers15class Tanh(Layer):16 def _activate(self, x, predict):17 return tf.tanh(x)18class Sigmoid(Layer):19 def _activate(self, x, predict):20 return tf.nn.sigmoid(x)21class ELU(Layer):22 def _activate(self, x, predict):23 return tf.nn.elu(x)24class ReLU(Layer):25 def _activate(self, x, predict):26 return tf.nn.relu(x)27class Softplus(Layer):28 def _activate(self, x, predict):29 return tf.nn.softplus(x)30class Identical(Layer):31 def _activate(self, x, predict):32 return x33class CF0910(Layer):34 def _activate(self, x, predict):35 return tf.minimum(tf.maximum(x, 0), 6)36# Cost Layers37class CostLayer(Layer):38 def _activate(self, x, y):39 pass40 def calculate(self, y, y_pred):41 return self._activate(y.astype(np.float32), y_pred)42class CrossEntropy(CostLayer):43 def _activate(self, x, y):44 return tf.reduce_mean(tf.nn.softmax_cross_entropy_with_logits(logits=x, labels=y))45class MSE(CostLayer):46 def _activate(self, x, y):...

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