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wah

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wah

a library so simple you will learn Within An Hour

  • 1.9.0
  • PyPI
  • Socket score

Maintainers
1

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Install

pip install wah

Requirements

You might want to manually install PyTorch for GPU computation.

lightning
matplotlib
numpy
pandas
pyperclip
PyYAML
selenium
tensorboard
timm
torch
torchaudio
torchmetrics
torchvision
webdriver_manager

Examples

Structure

classification

  • attacks
    • fgsm: FGSM, IFGSM
  • datasets
    • base: ClassificationDataset
    • cifar10: CIFAR10
    • cifar100: CIFAR100
    • dataloader
      • __init__: to_dataloader
      • transforms: CollateFunction
    • imagenet: ImageNet
    • stl10: STL10
    • utils: compute_mean_and_std, DeNormalize, Normalize, portion_dataset, tensor_to_dataset
  • models
    • feature_extraction: FeatureExtractor
    • load: add_preprocess, load_model, load_state_dict
    • replace:
      • __init__: Replacer
  • test
    • accuracy: AccuracyTest
    • eval: EvalTest
    • hessian_max_eigval_spectrum: HessianMaxEigValSpectrum
    • loss: LossTest
    • pred: PredTest
    • tid: TIDTest
  • train
    • plot: proj_train_path_to_2d, TrainPathPlot2D
    • train: Wrapper, load_trainer

module

_getattr, get_attrs, get_module_name, get_module_params, get_named_modules, get_valid_attr

np

path

basename, clean, dirname, exists, isdir, join, ls, mkdir, rmdir, rmfile, split, splitext

plot

  • dist: DistPlot2D
  • hist: HistPlot2D
  • image: ImShow
  • mat: MatShow2D
  • quiver: QuiverPlot2D, TrajPlot2D
  • scatter: GridPlot2D, ScatterPlot2D

riemann

  • geodesic: optimize_geodesic
  • grad: compute_jacobian, compute_hessian
  • jacobian_sigvals: JacobianSigVals

tensor

broadcasted_elementwise_mul, create_1d_traj, create_2d_grid, flatten_batch, repeat, stretch

torch

utils

  • args: ArgumentParser
  • dictionary: dict_to_df, dict_to_tensor, load_csv_to_dict, load_yaml_to_dict, save_dict_to_csv
  • download: disable_ssl_verification, download_url, md5_check
  • logs: disable_lightning_logging
  • lst: load_txt_to_list, save_list_to_txt, sort_str_list
  • random: seed, unseed
  • time: time
  • zip: extract

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