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⨍ Functions 68 ◇ Types & classes 18

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↓ 4 filesDonut

Class for constructing Donut model. This class provides :meth:`get_training_loss` for deriving the training loss …

donut/model.py

↓ 3 filesBatchSlidingWindow

Class for obtaining mini-batch iterators of sliding windows. Each mini-batch will have `batch_size` windows. If the final batch …

donut/utils.py

↓ 3 filesDataAugmentation

Base class for data augmentation in training. Args: mean (float): Mean of the training data. std (float): Standard deviation of …

donut/augmentation.py

↓ 2 filesMissingDataInjection

Data augmentation by injecting missing points into training data. Args: mean (float): Mean of the training data. std (float): …

donut/augmentation.py

↓ 2 filesiterative_masked_reconstruct

Iteratively reconstruct `x` with `mask` for `iter_count` times. This method will call :func:`masked_reconstruct` for `iter_count` …

donut/reconstruction.py

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Method 60

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Function 8

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tests/test_model.py11 symbols

tests/test_utils.py10 symbols

donut/model.py10 symbols

donut/augmentation.py10 symbols

tests/test_preprocessing.py7 symbols

tests/test_training.py6 symbols

tests/test_augmentation.py6 symbols

donut/prediction.py6 symbols

tests/test_reconstruction.py5 symbols

donut/utils.py4 symbols

donut/training.py4 symbols

tests/test_prediction.py2 symbols

For agents

$ claude mcp add donut \
  -- python -m otcore.mcp_server <graph>

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github.com/NetManAIOps/donut @main

Core symbols most depended-on inside this repo

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