pytorch 线性回归数据集显示

谁践踏了优雅 2022-04-05 14:09 280阅读 0赞

法1：

import numpy as np
    import torch
    import matplotlib.pyplot as plt
    
    x_train = np.array([[3.3], [4.4], [5.5], [6.71], [6.93], [4.168],
                        [9.779], [6.182], [7.59], [2.167], [7.042],
                        [10.791], [5.313], [7.997], [3.1]], dtype=np.float32)
    
    y_train = np.array([[1.7], [2.76], [2.09], [3.19], [1.694], [1.573],
                        [3.366], [2.596], [2.53], [1.221], [2.827],
                        [3.465], [1.65], [2.904], [1.3]], dtype=np.float32)
    
    #x_train = torch.from_numpy(x_train)
    #y_train = torch.from_numpy(y_train)
    plt.plot(x_train, y_train, 'ro', label='Original data')
    
    #plt.plot(x_train.numpy(), y_train.numpy(), 'ro', label='Original data')
    plt.legend() 
    plt.show()

法2：

import numpy as np
    import torch
    import matplotlib.pyplot as plt
    
    x_train = np.array([[3.3], [4.4], [5.5], [6.71], [6.93], [4.168],
                        [9.779], [6.182], [7.59], [2.167], [7.042],
                        [10.791], [5.313], [7.997], [3.1]], dtype=np.float32)
    
    y_train = np.array([[1.7], [2.76], [2.09], [3.19], [1.694], [1.573],
                        [3.366], [2.596], [2.53], [1.221], [2.827],
                        [3.465], [1.65], [2.904], [1.3]], dtype=np.float32)
    
    x_train = torch.from_numpy(x_train)
    y_train = torch.from_numpy(y_train)
    
    
    plt.plot(x_train.numpy(), y_train.numpy(), 'ro', label='Original data')
    plt.legend() 
    plt.show()

运行结果：

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