预测回调

! [ -e /content ] && pip install -Uqq fastai  # 在Colab上升级fastai

from __future__ import annotations
from fastai.basics import *

from nbdev.showdoc import *
from fastai.test_utils import *

各种回调用于自定义获取预测的行为

MCDropoutCallback

在推理过程中启用 dropout，允许您多次调用 Learner.get_preds 来通过 Monte Carlo Dropout 近似模型的不确定性。

class MCDropoutCallback(Callback):
    def before_validate(self):
        for m in [m for m in flatten_model(self.model) if 'dropout' in m.__class__.__name__.lower()]:
            m.train()
    
    def after_validate(self):
        for m in [m for m in flatten_model(self.model) if 'dropout' in m.__class__.__name__.lower()]:
            m.eval()

learn = synth_learner()

# 调用 get_preds 10 次，然后将预测结果堆叠起来，生成一个形状为 [样本数, 批次大小, ...] 的张量。
dist_preds = []
for i in range(10):
    preds, targs = learn.get_preds(cbs=[MCDropoutCallback()])
    dist_preds += [preds]

torch.stack(dist_preds).shape

torch.Size([10, 32, 1])

导出 -

from nbdev import nbdev_export
nbdev_export()

Converted 00_torch_core.ipynb.
Converted 01_layers.ipynb.
Converted 02_data.load.ipynb.
Converted 03_data.core.ipynb.
Converted 04_data.external.ipynb.
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Converted 07_vision.core.ipynb.
Converted 08_vision.data.ipynb.
Converted 09_vision.augment.ipynb.
Converted 09b_vision.utils.ipynb.
Converted 09c_vision.widgets.ipynb.
Converted 10_tutorial.pets.ipynb.
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Converted 12_optimizer.ipynb.
Converted 13_callback.core.ipynb.
Converted 13a_learner.ipynb.
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Converted tutorial.ipynb.