Deep-Learning-with-PyTorch

490
INDEX
V
val_loss tensor 138
val_neg loss 308
val_pos loss 308
val_stride parameter 275
validate function 216
validation 383, 409
validation loop 299–300
validation set 132, 433
validation_cadence 393
validation_dl 289
validation_ds 289
valMetrics_g 300
valMetrics_t 301
vanilla gradient descent 127
vanilla model 367
view function 294
volread function 76
volumetric data
data representation using
tensors 75–76
loading 76
volumetric pixel 239
voxel-address-based coordinate
system 265
voxels 239
converting between
millimeters and voxel
addresses 268–270
grouping voxels into nodule
candidates 411–412
voxel sizes 267–268
W
wait() method 452
weight decay 220
weight matrix 195
weight parameter 200
weight penalties 219–220
weight tensor 197
weighted loss 391
WeightedRandomSampler 339
weights 106
weights argument 339
whole-slice training 383
width of network 218–219
Wine Quality dataset 77
with statement 126
with torch.no_grad()
method 299, 447, 457, 471
word2index_dict 96
WordNet 17
writer.add_histogram 428
writer.add_scalar method
314, 396
X
Xavier initializations 228
_xyz suffix 268
xyz2irc function 269
Y
YOLOv3 paper 360
Z
zero_grad method 128
zeros function 50, 55, 125