TypeError: float() 参数必须是字符串或数字，而不是 'dict_values'，

Question

I was trying to plot the loss for my model, so coded like below, but I am getting below error:

TypeError: float() argument must be a string or a number, not 'dict_values'

code:

def fit(self, X, Y, epochs=1, learning_rate=1, initialise=True, display_loss=False):

    #initialise w,b
    if initialise:
        self.w = np.random.randn(1,X.shape[1])
        self.b = 0

    if display_loss:
        loss = {}

    for i in tqdm_notebook(range(epochs), total=epochs, unit='epoch'):
        dw = 0
        db = 0
        for x,y in zip(X,Y,):
            dw += self.grad_w(x,y)
            db += self.grad_b(x,y)

        self.w -= learning_rate * dw
        self.b -= learning_rate * db

        if display_loss:
            Y_pred = self.sigmoid(self.perceptron(X))
            loss[i] = mean_squared_error(Y_pred, Y)

    if display_loss:
        plt.plot(loss.values())
        plt.xlabel('Epochs')
        plt.ylabel('Mean Squared Error')
        plt.show()

def predict(self, X):
    Y_pred = []
    for x in X:
        y_pred = self.sigmoid(self.perceptron(x))
        Y_pred.append(y_pred)
    return np.array(Y_pred)

sn = SigmoidNeuron()
sn.fit(X_scaled_train, Y_scaled_train, epochs=1000, learning_rate=0.01, display_loss=True)

Answer 1

I got your error. This error occur if you are plotting the as it is... which you shouldn't do it.

You should change this dict_values to a list

which creates an array of type object and puts the dict_values object inside:

plt.plot(loss.values()) instead of this you should use

so your code should look like this:

    if display_loss:
        plt.plot(np.array(list(loss.values())).astype(float))
        plt.xlabel('Epochs')
        plt.ylabel('Mean Squared Error')
        plt.show()

so when you run the or with this sn.fit(X_scaled_train, Y_scaled_train, epochs=2000, learning_rate=0.015, display_loss=True)

then you will get the loss plotting image as loss_plotting .

I took reference of this snippet Float Arguments and dict_values with NumPy

Hope you get it...!