Add RationalQuadraticSpline#71
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| bin_slope = bin_height / bin_width | ||
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| z = (x - x_pos_bin[0]) / bin_width | ||
| z = jnp.clip(z, 0.0, 1.0) |
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this function has some good comments in the distrax codebase, we should copy them over
| """A rational-quadratic spline bijector. | ||
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| Implements the spline bijector introduced by: | ||
| > Durkan et al., Neural Spline Flows, https://arxiv.org/abs/1906.04032, 2019. |
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we can do the special bib notation here for mkdocs (e.g. ??? cite "References")
| ): | ||
| """Initializes a RationalQuadraticSpline bijector. | ||
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| Args: |
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should match docstring style (e.g. **Arguments**)
| unnormalized_bin_heights = params[ | ||
| ..., self.num_bins : 2 * self.num_bins # noqa: E203 | ||
| ] | ||
| unnormalized_knot_slopes = params[..., 2 * self.num_bins :] # noqa: E203 |
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I thought I fixed the black/flake interaction for these, does it error if you remove the # noqa: E203 ?
| from distreqx.bijectors import RationalQuadraticSpline | ||
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| class RationalQuadraticSplineTest(TestCase): |
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There's a few more low hanging fruit from the distrax tests, e.g. https://github.com/google-deepmind/distrax/blob/main/distrax/_src/bijectors/rational_quadratic_spline_test.py#L153 that are worth porting over
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Adds the rational quadratic spline bijector, very useful for complex normalizing flows. Reference distrax code is here