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        "description": "Piecewise Linear Functions (PWLs) can be used to approximate any 1D function. \nPWLs are built with a configurable number of line segments - the more segments the more accurate the approximation.\nThis package implements PWLs in PyTorch and as such they can be fit to the data using standard gradient descent.\nFor example:\n\nimport torchpwl\n\n# Create a PWL consisting of 3 segments for 5 features - each feature will have its own PWL function.\npwl = torchpwl.PWL(num_features=5, num_breakpoints=3)\nx = torch.Tensor(11, 5).normal_()\ny = pwl(x)\n\n\nMonotonicity is also supported via `MonoPWL`. See the class documentations for more details.\n\n\n",
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