Spaces:
Sleeping
Sleeping
Commit
•
a1a9800
1
Parent(s):
29b27a4
lunchbreak add
Browse files
app.py
CHANGED
@@ -94,8 +94,8 @@ device_map='cuda')
|
|
94 |
|
95 |
|
96 |
|
97 |
-
unet = UNet2DConditionModel.from_pretrained('
|
98 |
-
text_encoder = CLIPTextModel.from_pretrained('
|
99 |
device_map='cpu').to(dtype)
|
100 |
|
101 |
adapter = MotionAdapter.from_pretrained("wangfuyun/AnimateLCM")
|
@@ -114,7 +114,7 @@ pipe.fuse_lora()
|
|
114 |
|
115 |
pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15_vit-G.bin", map_location='cpu')
|
116 |
# This IP adapter improves outputs substantially.
|
117 |
-
pipe.set_ip_adapter_scale(.
|
118 |
pipe.unet.fuse_qkv_projections()
|
119 |
#pipe.enable_free_init(method="gaussian", use_fast_sampling=True)
|
120 |
|
@@ -156,11 +156,12 @@ def generate(in_im_embs):
|
|
156 |
|
157 |
def get_user_emb(embs, ys):
|
158 |
# handle case where every instance of calibration videos is 'Neither' or 'Like' or 'Dislike'
|
159 |
-
if len(list(
|
160 |
-
|
161 |
-
embs
|
162 |
-
|
163 |
-
ys
|
|
|
164 |
|
165 |
indices = list(range(len(embs)))
|
166 |
# sample only as many negatives as there are positives
|
@@ -177,9 +178,14 @@ def get_user_emb(embs, ys):
|
|
177 |
if len(ys) > len(embs):
|
178 |
ys.pop(-1)
|
179 |
|
180 |
-
feature_embs =
|
181 |
#scaler = preprocessing.StandardScaler().fit(feature_embs)
|
182 |
#feature_embs = scaler.transform(feature_embs)
|
|
|
|
|
|
|
|
|
|
|
183 |
chosen_y = np.array([ys[i] for i in indices])
|
184 |
|
185 |
#lin_class = Ridge(fit_intercept=False).fit(feature_embs, chosen_y)
|
|
|
94 |
|
95 |
|
96 |
|
97 |
+
unet = UNet2DConditionModel.from_pretrained('rynmurdock/Sea_Claws', subfolder='unet',).to(dtype).to('cpu')
|
98 |
+
text_encoder = CLIPTextModel.from_pretrained('rynmurdock/Sea_Claws', subfolder='text_encoder',
|
99 |
device_map='cpu').to(dtype)
|
100 |
|
101 |
adapter = MotionAdapter.from_pretrained("wangfuyun/AnimateLCM")
|
|
|
114 |
|
115 |
pipe.load_ip_adapter("h94/IP-Adapter", subfolder="models", weight_name="ip-adapter_sd15_vit-G.bin", map_location='cpu')
|
116 |
# This IP adapter improves outputs substantially.
|
117 |
+
pipe.set_ip_adapter_scale(.9)
|
118 |
pipe.unet.fuse_qkv_projections()
|
119 |
#pipe.enable_free_init(method="gaussian", use_fast_sampling=True)
|
120 |
|
|
|
156 |
|
157 |
def get_user_emb(embs, ys):
|
158 |
# handle case where every instance of calibration videos is 'Neither' or 'Like' or 'Dislike'
|
159 |
+
if len(list(ys)) <= 7:
|
160 |
+
aways = [.01*torch.randn(1280) for i in range(3)]
|
161 |
+
embs += aways
|
162 |
+
awal = [0 for i in range(3)]
|
163 |
+
ys += awal
|
164 |
+
print('Fixing only one feedback class available.\n')
|
165 |
|
166 |
indices = list(range(len(embs)))
|
167 |
# sample only as many negatives as there are positives
|
|
|
178 |
if len(ys) > len(embs):
|
179 |
ys.pop(-1)
|
180 |
|
181 |
+
feature_embs = torch.stack([embs[i].squeeze().to('cpu') for i in indices]).to('cpu')
|
182 |
#scaler = preprocessing.StandardScaler().fit(feature_embs)
|
183 |
#feature_embs = scaler.transform(feature_embs)
|
184 |
+
|
185 |
+
|
186 |
+
if feature_embs.norm() != 0:
|
187 |
+
feature_embs = feature_embs / feature_embs.norm()
|
188 |
+
|
189 |
chosen_y = np.array([ys[i] for i in indices])
|
190 |
|
191 |
#lin_class = Ridge(fit_intercept=False).fit(feature_embs, chosen_y)
|