How do I call a trained model in PyTorch?

To invoke the trained model, follow these steps:

1. Import the necessary libraries and modules.

import torch
import torch.nn as nn

1. Defining the structure of the model:

class YourModel(nn.Module):
    def __init__(self):
        super(YourModel, self).__init__()
        # 定义模型的结构

    def forward(self, x):
        # 定义模型的前向传播逻辑
        return x

1. Create model objects:

model = YourModel()

1. Load pre-trained model parameters.

model.load_state_dict(torch.load('path/to/your/trained/model.pth'))

Make sure to replace ‘path/to/your/trained/model.pth’ with the actual path to your trained model parameter file.

1. Set the model to evaluation mode.

model.eval()

The model is now loaded and ready for inference. You can use the model to make predictions, for example:

input_data = torch.randn(1, 3, 224, 224)  # 模拟输入数据
output = model(input_data)

Please note that for accurate predictions, the dimensions of the input data should match the input dimensions of the model. Depending on your specific model and task, you may need to perform appropriate data preprocessing.

I hope this helps you!