pytorch加载模型不是相同的softmax概率

import torch
import torch.nn as nn
import torch.nn.functional as F

class MyModel(nn.Module):
    def __init__(self):
        super(MyModel, self).__init__()
        self.fc1 = nn.Linear(input_size, hidden_size)
        self.fc2 = nn.Linear(hidden_size, output_size)

    def forward(self, x):
        x = F.relu(self.fc1(x))
        x = self.fc2(x)
        return x

model = MyModel()

model.load_state_dict(torch.load('model.pth'))

model.eval()

input_data = torch.tensor(input_data)  # 将输入数据转换为PyTorch张量
input_data = input_data.float()  # 将数据类型转换为float

output = model(input_data)
probabilities = F.softmax(output, dim=1)