如何将深度学习模型从MATLAB导入PyTorch? [英] How to import deep learning models from MATLAB to PyTorch?

问题描述

我正在尝试将经过DNN训练的模型从MATLAB导入PyTorch.

I’m trying to import a DNN trained model from MATLAB to PyTorch.

我找到了针对相反情况的解决方案(从PyTorch到MATLAB)，但是没有关于如何从MATLAB导入训练后的模型到PyTorch的提议解决方案.

I’ve found solutions for the opposite case (from PyTorch to MATLAB), but no proposed solutions on how to import a trained model from MATLAB to PyTorch.

有什么想法吗?

推荐答案

您可以首先 ONNX 加载模型；先决条件是:

You can first export your model to ONNX format, and then load it using ONNX; prerequisites are:

pip install onnx onnxruntime

然后

onnx.load('model.onnx')
# Check that the IR is well formed
onnx.checker.check_model(model)

到目前为止，您仍然没有PyTorch模型.由于它是本机不支持.

Until this point, you still don't have a PyTorch model. This can be done through various ways since it's not natively supported.

一种解决方法(仅通过加载 模型参数)

A workaround (by loading only the model parameters)

import onnx
onnx_model = onnx.load('model.onnx')

graph = onnx_model.graph
initalizers = dict()
for init in graph.initializer:
    initalizers[init.name] = numpy_helper.to_array(init)

for name, p in model.named_parameters():
    p.data = (torch.from_numpy(initalizers[name])).data

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使用 onnx2pytorch

import onnx

from onnx2pytorch import ConvertModel

onnx_model = onnx.load('model.onnx')
pytorch_model = ConvertModel(onnx_model)

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注意:消耗时间

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Note: Time Consuming

使用 onnx2keras ，然后使用 查看全文