在numpy而不是tensorflow中计算keras度量

import numpy as np

y_true = np.array([0, 1, 0, 1, 1])  # 真实标签
y_pred = np.array([0, 1, 1, 1, 0])  # 预测标签

accuracy = np.mean(y_true == y_pred)

tp = np.sum((y_true == 1) & (y_pred == 1))  # 真正例
fp = np.sum((y_true == 0) & (y_pred == 1))  # 假正例
precision = tp / (tp + fp)

tp = np.sum((y_true == 1) & (y_pred == 1))  # 真正例
fn = np.sum((y_true == 1) & (y_pred == 0))  # 假反例
recall = tp / (tp + fn)

precision = tp / (tp + fp)  # 精确率
recall = tp / (tp + fn)  # 召回率
f1 = 2 * (precision * recall) / (precision + recall)