Spaces:
Runtime error
Runtime error
update configs
Browse files
configs/remodiffuse/remodiffuse_kit.py
CHANGED
@@ -31,37 +31,6 @@ text_latent_dim = 256
|
|
31 |
ff_size = 1024
|
32 |
num_heads = 8
|
33 |
dropout = 0
|
34 |
-
|
35 |
-
def scale_func(timestep):
|
36 |
-
import random
|
37 |
-
w = (1 - (1000 - timestep) / 1000) * 4.0 + 1
|
38 |
-
if timestep > 100:
|
39 |
-
if random.randint(0, 1) == 0:
|
40 |
-
output = {
|
41 |
-
'both_coef': w,
|
42 |
-
'text_coef': 0,
|
43 |
-
'retr_coef': 1 - w,
|
44 |
-
'none_coef': 0
|
45 |
-
}
|
46 |
-
else:
|
47 |
-
output = {
|
48 |
-
'both_coef': 0,
|
49 |
-
'text_coef': w,
|
50 |
-
'retr_coef': 0,
|
51 |
-
'none_coef': 1 - w
|
52 |
-
}
|
53 |
-
else:
|
54 |
-
both_coef = 0.78123
|
55 |
-
text_coef = 0.39284
|
56 |
-
retr_coef = -0.12475
|
57 |
-
none_coef = 1 - both_coef - text_coef - retr_coef
|
58 |
-
output = {
|
59 |
-
'both_coef': both_coef,
|
60 |
-
'text_coef': text_coef,
|
61 |
-
'retr_coef': retr_coef,
|
62 |
-
'none_coef': none_coef
|
63 |
-
}
|
64 |
-
return output
|
65 |
|
66 |
# model settings
|
67 |
model = dict(
|
@@ -121,7 +90,12 @@ model = dict(
|
|
121 |
dropout=dropout
|
122 |
),
|
123 |
),
|
124 |
-
|
|
|
|
|
|
|
|
|
|
|
125 |
),
|
126 |
loss_recon=dict(type='MSELoss', loss_weight=1, reduction='none'),
|
127 |
diffusion_train=dict(
|
|
|
31 |
ff_size = 1024
|
32 |
num_heads = 8
|
33 |
dropout = 0
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
34 |
|
35 |
# model settings
|
36 |
model = dict(
|
|
|
90 |
dropout=dropout
|
91 |
),
|
92 |
),
|
93 |
+
scale_func_cfg=dict(
|
94 |
+
coarse_scale=4.0,
|
95 |
+
both_coef=0.78123,
|
96 |
+
text_coef=0.39284,
|
97 |
+
retr_coef=-0.12475
|
98 |
+
)
|
99 |
),
|
100 |
loss_recon=dict(type='MSELoss', loss_weight=1, reduction='none'),
|
101 |
diffusion_train=dict(
|
configs/remodiffuse/remodiffuse_t2m.py
CHANGED
@@ -32,37 +32,6 @@ ff_size = 1024
|
|
32 |
num_heads = 8
|
33 |
dropout = 0
|
34 |
|
35 |
-
def scale_func(timestep):
|
36 |
-
import random
|
37 |
-
w = (1 - (1000 - timestep) / 1000) * 6.5 + 1
|
38 |
-
if timestep > 100:
|
39 |
-
if random.randint(0, 1) == 0:
|
40 |
-
output = {
|
41 |
-
'both_coef': w,
|
42 |
-
'text_coef': 0,
|
43 |
-
'retr_coef': 1 - w,
|
44 |
-
'none_coef': 0
|
45 |
-
}
|
46 |
-
else:
|
47 |
-
output = {
|
48 |
-
'both_coef': 0,
|
49 |
-
'text_coef': w,
|
50 |
-
'retr_coef': 0,
|
51 |
-
'none_coef': 1 - w
|
52 |
-
}
|
53 |
-
else:
|
54 |
-
both_coef = 0.52351
|
55 |
-
text_coef = -0.28419
|
56 |
-
retr_coef = 2.39872
|
57 |
-
none_coef = 1 - both_coef - text_coef - retr_coef
|
58 |
-
output = {
|
59 |
-
'both_coef': both_coef,
|
60 |
-
'text_coef': text_coef,
|
61 |
-
'retr_coef': retr_coef,
|
62 |
-
'none_coef': none_coef
|
63 |
-
}
|
64 |
-
return output
|
65 |
-
|
66 |
# model settings
|
67 |
model = dict(
|
68 |
type='MotionDiffusion',
|
@@ -121,7 +90,12 @@ model = dict(
|
|
121 |
dropout=dropout
|
122 |
),
|
123 |
),
|
124 |
-
|
|
|
|
|
|
|
|
|
|
|
125 |
),
|
126 |
loss_recon=dict(type='MSELoss', loss_weight=1, reduction='none'),
|
127 |
diffusion_train=dict(
|
|
|
32 |
num_heads = 8
|
33 |
dropout = 0
|
34 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
35 |
# model settings
|
36 |
model = dict(
|
37 |
type='MotionDiffusion',
|
|
|
90 |
dropout=dropout
|
91 |
),
|
92 |
),
|
93 |
+
scale_func_cfg=dict(
|
94 |
+
coarse_scale=6.5,
|
95 |
+
both_coef=0.52351,
|
96 |
+
text_coef=-0.28419,
|
97 |
+
retr_coef=2.39872
|
98 |
+
)
|
99 |
),
|
100 |
loss_recon=dict(type='MSELoss', loss_weight=1, reduction='none'),
|
101 |
diffusion_train=dict(
|