From b1cd7bc6efa0c26b961379254e475aa008d5e024 Mon Sep 17 00:00:00 2001
From: Amir MOHAMMADI <amir.mohammadi@idiap.ch>
Date: Tue, 26 Apr 2022 20:38:50 +0200
Subject: [PATCH] small fixes
---
bob/learn/em/factor_analysis.py | 11 ++++-------
1 file changed, 4 insertions(+), 7 deletions(-)
diff --git a/bob/learn/em/factor_analysis.py b/bob/learn/em/factor_analysis.py
index 779068b..cd9a769 100644
--- a/bob/learn/em/factor_analysis.py
+++ b/bob/learn/em/factor_analysis.py
@@ -230,12 +230,13 @@ class FactorAnalysisBase(BaseEstimator):
"""
if self.ubm is None:
- logger.info("FA: Creating a new GMMMachine and training it.")
+ logger.info("Creating a new GMMMachine and training it.")
gmm_class = self.ubm_kwargs.pop("gmm_class", GMMMachine)
self.ubm: GMMMachine = gmm_class(**self.ubm_kwargs)
self.ubm.fit(X)
if self.ubm._means is None:
+ logger.info("UBM means are None, training the UBM.")
self.ubm.fit(X)
# Initializing the state matrix
@@ -1276,21 +1277,17 @@ class FactorAnalysisBase(BaseEstimator):
class_indices = y == class_id
X_new.append(X[class_indices])
y_new.append(y[class_indices])
- __import__("ipdb").set_trace()
X, y = X_new, y_new
+ del X_new, y_new
stats = [
dask.delayed(self.ubm.stats_per_sample)(xx).persist()
for xx in X
]
- # try:
- # client = dask.distributed.Client.current()
- # stats = client.scatter(stats)
- # except ValueError:
- # pass
else:
stats = self.ubm.stats_per_sample(X)
+ del X
self.fit_using_stats(stats, y)
return self
--
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