freeze.md

Freeze a model

The trained neural network is extracted from a checkpoint and dumped into a model file. This process is called "freezing" a model. To freeze a model, typically one does

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:::{tab-item} TensorFlow {{ tensorflow_icon }}

$ dp freeze -o model.pb

in the folder where the model is trained. The output model is called model.pb. The idea and part of our code are from Morgan. :::

:::{tab-item} PyTorch {{ pytorch_icon }}

$ dp --pt freeze -o model.pth

in the folder where the model is trained. The output model is called model.pth.

In multi-task mode, you need to choose one available heads (e.g. CHOSEN_BRANCH) by --head to specify which model branch you want to freeze:

$ dp --pt freeze -o model_branch1.pth --head CHOSEN_BRANCH

The output model is called model_branch1.pth, which is the specifically frozen model with the CHOSEN_BRANCH head. :::

:::{tab-item} Paddle {{ paddle_icon }}

$ dp --pd freeze -o model

in the folder where the model is trained. The output model is called model.json and model.pdiparams.

In multi-task mode, you need to choose one available heads (e.g. CHOSEN_BRANCH) by --head to specify which model branch you want to freeze:

$ dp --pd freeze -o model_branch1 --head CHOSEN_BRANCH

The output model is called model_branch1.json, which is the specifically frozen model with the CHOSEN_BRANCH head. :::

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