Commit 47510e91 authored by Anthony Larcher's avatar Anthony Larcher
Browse files

Merge branch 'dev_al' of https://git-lium.univ-lemans.fr/Larcher/sidekit into dev_al

parents e1f5d369 0df15d91
......@@ -221,7 +221,7 @@ class FeaturesServer(object):
feat = pca_dct(feat, self.dct_pca_config[0], self.dct_pca_config[1], self.dct_pca_config[2])
elif self.sdc:
feat = shifted_delta_cepstral(feat, d=self.sdc_config[0], p=self.sdc_config[1], k=self.sdc_config[2])
# Apply a mask on the features
if self.mask is not None:
feat = self._mask(feat)
......@@ -488,6 +488,7 @@ class FeaturesServer(object):
feat, label = self.post_processing(feat, label, global_mean, global_std)
else:
feat, label = self.post_processing(feat, label)
return feat, label
def get_features_per_speaker(self, show, idmap, channel=0, input_feature_filename=None, label=None):
......
......@@ -48,14 +48,7 @@ from .preprocessor import RawPreprocessor
from .preprocessor import MfccFrontEnd
from .preprocessor import MelSpecFrontEnd
has_pyroom = True
try:
import pyroomacoustics
except ImportError:
has_pyroom = False
if has_pyroom:
from .augmentation import AddReverb
__author__ = "Anthony Larcher and Sylvain Meignier"
......
......@@ -1480,17 +1480,17 @@ def xtrain(dataset_description,
validation_non_indices,
training_opts["mixed_precision"])
test_eer = None
if training_opts["compute_test_eer"] and local_rank < 1:
test_eer = test_metrics(model, device, model_opts, dataset_opts, training_opts)
#test_eer = None
#if training_opts["compute_test_eer"] and local_rank < 1:
# test_eer = test_metrics(model, device, model_opts, dataset_opts, training_opts)
monitor.update(test_eer=test_eer,
val_eer=val_eer,
val_loss=val_loss,
val_acc=val_acc)
if local_rank < 1:
monitor.display()
#if local_rank < 1:
# monitor.display()
# Save the current model and if needed update the best one
# TODO ajouter une option qui garde les modèles à certaines époques (par exemple avant le changement de LR
......@@ -1675,6 +1675,7 @@ def extract_embeddings(idmap_name,
model_filename,
data_root_name,
device,
batch_size=1,
file_extension="wav",
transform_pipeline={},
sliding_window=False,
......@@ -1700,6 +1701,10 @@ def extract_embeddings(idmap_name,
:param mixed_precision:
:return:
"""
if sliding_window:
batch_size = 1
# Load the model
if isinstance(model_filename, str):
checkpoint = torch.load(model_filename, map_location=device)
......@@ -1729,7 +1734,7 @@ def extract_embeddings(idmap_name,
)
dataloader = DataLoader(dataset,
batch_size=1,
batch_size=batch_size,
shuffle=False,
drop_last=False,
pin_memory=True,
......
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