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Fix/batched non sym cost #518
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Algue-Rythme
approved these changes
Apr 11, 2024
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LGTM!
@@ -199,51 +198,39 @@ def apply_lse_kernel( # noqa: D102 | |||
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def body0(carry, i: int): | |||
f, g, eps, vec = carry | |||
y = jax.lax.dynamic_slice( | |||
self.y, (i * self.batch_size, 0), (self.batch_size, self.y.shape[1]) | |||
y, g_ = self._leading_slice(self.y, i), self._leading_slice(g, i) |
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I realise it might be worth using jax.lax.dynamic_slice_in_dim
instead of jax.lax.dynamic_slice
in self._leading_slice
implem
michalk8
added a commit
that referenced
this pull request
Jun 27, 2024
* Fix transport from f_u/g_v in non-symm case * Fix `apply_kernel` and `apply_lse_kernel` * Use `self._leading_slice` * Fix `_compute_summary_online` * Use more of `self._leading_slice` * Fix `_apply_cost` * Fix transport * Add initial test * Test for online mean/max * Finish the test * Fix not using pairwise * Fix transport from pots/scalings; don't transpose
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Fixes wrong computation for non-symmetric costs. This bug was only present when
batch_size
was passed in thePointCloud
.