2
def compileActivation(self, net, layerNum):
variable = net.x if layerNum == 0 else net.varArrayA[layerNum - 1]
#print tf.expand_dims(net.dropOutVectors[layerNum], 1)
#print net.varWeights[layerNum]['w'].get_shape().as_list()
z = tf.matmul((net.varWeights[layerNum]['w']), (variable * (tf.expand_dims(net.dropOutVectors[layerNum], 1) if self.dropout else 1.0))) + tf.expand_dims(net.varWeights[layerNum]['b'], 1)
a = self.activation(z, self.pool_size)
net.varArrayA.append(a)
我正在运行,其计算z
,并将其传递到S形激活的激活功能相同的等级。 当我尝试执行上面的功能,我得到以下错误:TensorFlow错误:TensorShape()必须具有
ValueError: Shapes TensorShape([Dimension(-2)]) and TensorShape([Dimension(None), Dimension(None)]) must have the same rank
的theano当量计算z
工作就好了:
z = T.dot(net.varWeights[layerNum]['w'], variable * (net.dropOutVectors[layerNum].dimshuffle(0, 'x') if self.dropout else 1.0)) + net.varWeights[layerNum]['b'].dimshuffle(0, 'x')
该代码看起来在语法上是正确的,但似乎'net'中的某个对象具有损坏的形状。特别是'TensorShape([Dimension(-2)])'永远不会出现,并且在TensorFlow 0.7.0中进行测试,所以如果升级,您可能会收到更有帮助的错误消息。 – mrry
谢谢。我会尝试升级 –