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Added random_seed parameter to make LsiModel reproducible #3194

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merged 6 commits into from
Oct 24, 2021
Merged

Added random_seed parameter to make LsiModel reproducible #3194

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e5c7f55
added random_seed parameter to stochastic_svd, Projections and LsiModel
parashardhapola Jul 19, 2021
06ab30b
fixed code style. Hanging indents in functions and methods along with…
parashardhapola Jul 19, 2021
deaef70
fixed code style. added hanging indents and trailing commas to more f…
parashardhapola Jul 19, 2021
6eb61cb
Update CHANGELOG.md
mpenkov Aug 12, 2021
8a8fb89
Merge remote-tracking branch 'upstream/develop' into lsimodel_randoms…
mpenkov Aug 12, 2021
8f6ec23
Merge branch 'develop' into lsimodel_randomstate
mpenkov Sep 28, 2021
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fixed code style. Hanging indents in functions and methods along with… 
… trailing commas
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@parashardhapola
parashardhapola committed Jul 19, 2021
commit 06ab30bcb7236b30f12da1e9f3b59651fe15c3cf
21 changes: 13 additions & 8 deletions gensim/models/lsimodel.py
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Expand Up @@ -23,7 +23,7 @@
* distributed computing for very large corpora, making use of a cluster of
machines

Wall-clock `performance on the English Wikipedia <http://radimrehurek.com/gensim/wiki.html>`_
Wall-clock `performance on the English Wikipedia <https://radimrehurek.com/gensim/wiki.html>`_
(2G corpus positions, 3.2M documents, 100K features, 0.5G non-zero entries in the final TF-IDF matrix),
requesting the top 400 LSI factors:

Expand Down Expand Up @@ -162,8 +162,11 @@ class Projection(utils.SaveLoad):
via :meth:`~gensim.models.lsimodel.Projection.merge`. This is how incremental training actually happens.

"""
def __init__(self, m, k, docs=None, use_svdlibc=False, power_iters=P2_EXTRA_ITERS,
extra_dims=P2_EXTRA_DIMS, dtype=np.float64, random_seed=None):

def __init__(
self, m, k, docs=None, use_svdlibc=False, power_iters=P2_EXTRA_ITERS,
extra_dims=P2_EXTRA_DIMS, dtype=np.float64, random_seed=None,
):
"""Construct the (U, S) projection from a corpus.

Parameters
Expand Down Expand Up @@ -359,9 +362,9 @@ class LsiModel(interfaces.TransformationABC, basemodel.BaseTopicModel):

def __init__(
self, corpus=None, num_topics=200, id2word=None, chunksize=20000,
decay=1.0, distributed=False, onepass=True,
power_iters=P2_EXTRA_ITERS, extra_samples=P2_EXTRA_DIMS, dtype=np.float64, random_seed=None,
):
decay=1.0, distributed=False, onepass=True, power_iters=P2_EXTRA_ITERS,
extra_samples=P2_EXTRA_DIMS, dtype=np.float64, random_seed=None,
):
"""Build an LSI model.

Parameters
Expand Down Expand Up @@ -876,8 +879,10 @@ def print_debug(id2token, u, s, topics, num_words=10, num_neg=None):
logger.info('topic #%s(%.3f): %s, ..., %s', topic, s[topic], ', '.join(pos), ', '.join(neg))


def stochastic_svd(corpus, rank, num_terms, chunksize=20000, extra_dims=None,
power_iters=0, dtype=np.float64, eps=1e-6, random_seed=None):
def stochastic_svd(
corpus, rank, num_terms, chunksize=20000, extra_dims=None,
power_iters=0, dtype=np.float64, eps=1e-6, random_seed=None,
):
"""Run truncated Singular Value Decomposition (SVD) on a sparse input.

Parameters
Expand Down