-
Notifications
You must be signed in to change notification settings - Fork 0
/
config_Sh_CWGAN_GP.yaml
126 lines (91 loc) · 2.57 KB
/
config_Sh_CWGAN_GP.yaml
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
base_pth: /home/tl/CVAE-GANS/egg drilling dataset/
# Batch size for training
batch_size: 64
# Beta1 parameter, not in use for RMSProp
betas:
- 0.5
- 0.9
# Folder arrangement of the dataset with their respective classes
# Drilling angle: sm, lg, v; Drilling force: 0, 1, 2, 3
cls_pth:
sm:
- '0'
- '1'
- '2'
- '3'
# lg:
# - '0'
# - '1'
# - '2'
# - '3'
# v:
# - '0'
# - '1'
# - '2'
# - '3'
# Training epochs
epochs: 1000
# Training with mel spectrogram strips. Always 'True' for shallow CGAN
in_strips: True
num_strips: 8
# The penalty coefficient for WGAN-GP
lambda_gp: 10
# Number of critic iterations for WGAN-GP
n_critic: 5
# Dimension of latent space / distribution
latent_dim: 64
# Learning rate of the optimizer
learning_rate: 5.0e-05
# Number of categories in each class
num_class:
- 4
# Normalize the audio waveform to a magnitude between -1 and 1
max_wav_value: 32768.0
# Desired sample rate
sample_rate: 22050
# For STFT
n_fft: 1024
# For mel scaling of a magnitude spectrogram, n_fft / 2 + 1
n_stft: 513
# For STFT
win_length: 1024
# For STFT, set hop length to get desired time frame. Current melspec size: (128 x 128)
hop_length: 345
# Min frequency
f_min: 0
# Max frequency. Should at most half of the sample rate
f_max: 11025
# Number of mel filter banks for mel spectrogram
n_mels: 128
# Default hanning window for STFT computations
window_fn: hann_window
# Raise the complex spectrogram to the power of N. Defaulted at 2 for mel spectrogram computation
power: 2
# To normalize spectrogram / mel spectrogram
normalized: False
# Momentum for Griffin-Lim numerical calculations
momentum: 0.99
# Number of iterations for Griffin-Lim.
n_iter: 32
# To randomly shuffle the data during dataset and dataloader phase
shuffle: True
# To enable log range compression on the mel spectrogram
enable_compression: True
# Number of workers for dataloading
num_workers: 2
# Which n-th conv layer for feature matching in the discriminator, 0 to 2
dis_fm_idx: 2
# N-points for the EWMA filter for the feature maps, previously 25
ewma_n: 10
# Set whether to load from checkpoint
load_from_checkpoint: False
# Set whether to use GPU (CUDA) or not
cuda: True
# Set the class condition of the forces, ie: 0, 1, 2, 3. For inference/generation
force_level: 1
# Select the number of generations of fake mel spectrogram
num_gen: 1
# Select the starting index for naming the generated files (to avoid overlap)
start_index: 50
# Define filepath to save generated mel spectrogram as image, format is 'png' always
save_path_for_generated: /home/tl/CVAE-GANS/evaluations/generated_SCWGANGP/