From cd6fb7ffe5dfa9f43e2910c6f1980900fc3d396f Mon Sep 17 00:00:00 2001 From: Micka <9810050+lowener@users.noreply.github.com> Date: Thu, 18 Nov 2021 18:34:33 +0100 Subject: [PATCH] Promote FITSNE from experimental (#4361) Closes #3805 Authors: - Micka (https://github.com/lowener) Approvers: - Corey J. Nolet (https://github.com/cjnolet) URL: https://github.com/rapidsai/cuml/pull/4361 --- python/cuml/manifold/t_sne.pyx | 11 +++-------- 1 file changed, 3 insertions(+), 8 deletions(-) diff --git a/python/cuml/manifold/t_sne.pyx b/python/cuml/manifold/t_sne.pyx index d4de67435e..d7d46b1834 100644 --- a/python/cuml/manifold/t_sne.pyx +++ b/python/cuml/manifold/t_sne.pyx @@ -172,7 +172,8 @@ class TSNE(Base, 0.8. (Barnes-Hut only.) learning_rate_method : str 'adaptive', 'none' or None (default 'adaptive') Either adaptive or None. 'adaptive' tunes the learning rate, early - exaggeration and perplexity automatically based on input size. + exaggeration, perplexity and n_neighbors automatically based on + input size. n_neighbors : int (default 90) The number of datapoints you want to use in the attractive forces. Smaller values are better for preserving @@ -482,11 +483,6 @@ class TSNE(Base, if self.method == 'barnes_hut': algo = TSNE_ALGORITHM.BARNES_HUT elif self.method == 'fft': - warnings.warn("Method 'fft' is experimental and may be " + - "unstable. If you find this implementation is not" + - " behaving as intended, please consider using one" + - " of the other methods, such as 'barnes_hut' or" + - " 'exact'") algo = TSNE_ALGORITHM.FFT elif self.method == 'exact': algo = TSNE_ALGORITHM.EXACT @@ -529,8 +525,7 @@ class TSNE(Base, free(params) self._kl_divergence_ = kl_divergence - if self.verbose: - print("[t-SNE] KL divergence: {}".format(kl_divergence)) + logger.debug("[t-SNE] KL divergence: {}".format(kl_divergence)) return self @generate_docstring(convert_dtype_cast='np.float32',