Question

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我正在编码一个拟进行模式识别的ANN。代码是从强制转换数组的模型复制而来的，我做了一点点更改，因此它从 tabulate 强制转换了表，表中的1是模式中的黑色像素，而0是白色像素。这是一种简单的模式，而图纸是B，C和D。但是现在，我被卡住了，因为当我运行它时，它会向我返回此错误：

TypeError：无法根据规则“安全”将数组数据从dtype（'float64'）转换为dtype（'

我试图通过关注其他用户的问题来解决它，但是那没有用。这是代码：

from numpy import exp, array, random, dot
import numpy as np
from tabulate import tabulate

class NeuralNetwork():
    def __init__(self):
        random.seed(1)

        self.synaptic_weights = 2 * random.random((5, 1)) - 1

     def __sigmoid(self, x):
        return 1 / (1 + exp(-x))

    def __sigmoid_derivate(self, x):
        return x * (1 - x)

    def train(self, training_set_inputs, training_set_outputs, number_of_training_iterations):
        for iteration in range(number_of_training_iterations):
            output = self.think(training_set_inputs)

            error = training_set_outputs - output

            adjustement = dot(training_set_inputs.T, error * self.__sigmoid_derivate(output))

            self.synaptic_weights += adjustement

    def think(self, inputs):
        return self.__sigmoid(dot(inputs, self.synaptic_weights))

if __name__ == "__main__":

    neural_network = NeuralNetwork()

    input1 = [[1, 1, 1, 1, 0],
              [1, 0, 0, 0, 1],
              [1, 0, 1, 1, 0],
              [1, 0, 0, 0, 1],
              [1, 1, 1, 1, 0]]

    input2 = [[0, 1, 1, 1, 1],
              [1, 0, 0, 0, 0],
              [1, 0, 0, 0, 0],
              [1, 0, 0, 0, 0],
              [0, 1, 1, 1, 1]]

    input3 = [[1, 1, 1, 1, 0],
              [1, 0, 0, 0, 1],
              [1, 0, 0, 0, 1],
              [1, 0, 0, 0, 1],
              [1, 1, 1, 1, 0]]

    input_n = [[0, 1, 1, 1, 0],
               [1, 0, 0, 0, 1],
               [1, 0, 0, 0, 0],
               [1, 0, 0, 0, 1],
               [0, 1, 1, 1, 0]]



    print ("Random starting synaptic weights: ")
    print (neural_network.synaptic_weights)

    training_set_inputs = array([[tabulate(input1)], [tabulate(input2)], [tabulate(input3)]])
    training_set_outputs = array([[1, 2, 3]])

    #1 = B || 2 = C || 3 = D

    print ("New synaptic weights after training: ")
    print (neural_network.synaptic_weights)

    print ("Considering new situation inputN -> ?: ")
    print (neural_network.think(tabulate(input_n)))

我想请你帮忙。谢谢！

TypeError：无法将数组数据从dtype（'float64'）转换为dtype（'<u32'）根据=“”到=“” the =“”规则=“”'safe'=“”

0 个答案: