Real Dataset Paths #
Generated tutorial artifacts live in NN.Examples.Data.SamplePaths.
This module names the default paths used by examples that train on datasets prepared by
scripts/datasets/download_example_data.py. The examples use small checked artifacts by default;
larger public datasets live under data/real after the user runs the preparation script.
Default root for user-downloaded real datasets.
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Parse an optional --data-dir PATH flag for real-data examples.
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Directory containing prepared CIFAR-10 .npy arrays.
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Prepared CIFAR-10 training images, shape (N, 3, 32, 32), float32 in [0, 1].
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Prepared CIFAR-10 training labels, shape (N,), float32 integer labels 0..9.
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Prepared CIFAR-10 test images, shape (N, 3, 32, 32), float32 in [0, 1].
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Prepared CIFAR-10 test labels, shape (N,), float32 integer labels 0..9.
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Directory containing a user-prepared ImageNet-style 64x64 subset.
ImageNet-style runs start from a local image-folder dataset. Users point
scripts/datasets/torchlean_data_convert.py image-folder at an ImageNet/ILSVRC,
ImageNet-compatible, or Tiny-ImageNet-style directory tree and write the converted arrays here.
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Prepared ImageNet-style training images, shape (N, 3, 64, 64), float32 in [0, 1].
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Prepared ImageNet-style training labels, shape (N,), float32 integer class ids.
The converter assigns ids by sorted subdirectory name when --labels-from-dirs is used.
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Directory containing prepared UCI household-power forecasting windows.
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Prepared UCI household-power inputs, shape (N, 24, 1), float32 normalized to [0, 1].
Each row is a 24-hour window of hourly mean Global_active_power.
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Prepared UCI household-power targets, shape (N, 24, 1), float32 normalized to [0, 1].
Each target row is the corresponding input window shifted by one hour.
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Directory containing the prepared UCI Auto MPG tabular regression CSV.
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Prepared UCI Auto MPG CSV with normalized columns x1..x7,y.
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Directory containing downloaded text corpora.
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Karpathy tiny-shakespeare corpus.
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TinyStories validation split, useful for small local language-model training checks.