enable ucb

model/matchmaker.py

@@ -79,7 +79,7 @@ def load_json_via_sftp():
 class RunningPivot(object):
     running_pivot = []
 
-not_run = [11, 12, 13, 14, 15, 16, 17, 18, 19]
+not_run = [16, 18, 19, 22]
 
 def matchmaker(num_players, k_group=4):
     trueskill_env = TrueSkill()

model/model_manager.py

@@ -70,17 +70,17 @@ class ModelManager:
 
     def generate_image_ig_parallel_anony(self, prompt, model_A, model_B, model_C, model_D):
         if model_A == "" and model_B == "" and model_C == "" and model_D == "":
-            not_run = [11, 12, 13, 14, 15, 16, 17, 18, 19]
-            filtered_models = [model for i, model in enumerate(self.model_ig_list) if i not in not_run]
-            model_names = random.sample([model for model in filtered_models], 4)
-            
-
+            # not_run = [11, 12, 13, 14, 15, 16, 17, 18, 19]
+            # filtered_models = [model for i, model in enumerate(self.model_ig_list) if i not in not_run]
+            # model_names = random.sample([model for model in filtered_models], 4)
 
-            # from .matchmaker import matchmaker
-            # model_ids = matchmaker(num_players=len(self.model_ig_list))
-            # print(model_ids)
-            # model_names = [self.model_ig_list[i] for i in model_ids]
-            # print(model_names)
+            # model_names = random.sample([model for model in self.model_ig_list], 4)
+            
+            from .matchmaker import matchmaker
+            model_ids = matchmaker(num_players=len(self.model_ig_list))
+            print(model_ids)
+            model_names = [self.model_ig_list[i] for i in model_ids]
+            print(model_names)
         else:
             model_names = [model_A, model_B, model_C, model_D]
 
@@ -96,15 +96,11 @@ class ModelManager:
         if model_A == "" and model_B == "" and model_C == "" and model_D == "":
             # model_names = random.sample([model for model in self.model_ig_list], 4)
 
-            not_run = [11, 12, 13, 14, 15, 16, 17, 18, 19]
-            filtered_models = [model for i, model in enumerate(self.model_ig_list) if i not in not_run]
-            model_names = random.sample([model for model in filtered_models], 4)
-
-            # from .matchmaker import matchmaker
-            # model_ids = matchmaker(num_players=len(self.model_ig_list))
-            # print(model_ids)
-            # model_names = [self.model_ig_list[i] for i in model_ids]
-            # print(model_names)
+            from .matchmaker import matchmaker
+            model_ids = matchmaker(num_players=len(self.model_ig_list))
+            print(model_ids)
+            model_names = [self.model_ig_list[i] for i in model_ids]
+            print(model_names)
         else:
             model_names = [model_A, model_B, model_C, model_D]
 

model/models/other_api_models.py

@@ -47,7 +47,7 @@ class OtherModel():
                     img_id = response_json["result"]
                     result_url = self.get_url + img_id
                     print(result_url)
-                    self.repeat_num = 300
+                    self.repeat_num = 800
                     while 1:
                         time.sleep(1)
                         img_response = requests.get(result_url)

model/models/replicate_api_models.py

@@ -6,24 +6,24 @@ import os
 import base64
 
 Replicate_MODEl_NAME_MAP = {
-    "SDXL": "stability-ai/sdxl:7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc",
-    "SD-v3.0": "stability-ai/stable-diffusion-3",
-    "SD-v2.1": "stability-ai/stable-diffusion:ac732df83cea7fff18b8472768c88ad041fa750ff7682a21affe81863cbe77e4",
-    "SD-v1.5": "stability-ai/stable-diffusion:b3d14e1cd1f9470bbb0bb68cac48e5f483e5be309551992cc33dc30654a82bb7",
-    "SDXL-Lightning": "bytedance/sdxl-lightning-4step:5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f",
-    "Kandinsky-v2.0": "ai-forever/kandinsky-2:3c6374e7a9a17e01afe306a5218cc67de55b19ea536466d6ea2602cfecea40a9",
-    "Kandinsky-v2.2": "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a",
-    "Proteus-v0.2": "lucataco/proteus-v0.2:06775cd262843edbde5abab958abdbb65a0a6b58ca301c9fd78fa55c775fc019",
-    "Playground-v2.0": "playgroundai/playground-v2-1024px-aesthetic:42fe626e41cc811eaf02c94b892774839268ce1994ea778eba97103fe1ef51b8",
-    "Playground-v2.5": "playgroundai/playground-v2.5-1024px-aesthetic:a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24",
-    "Dreamshaper-xl-turbo": "lucataco/dreamshaper-xl-turbo:0a1710e0187b01a255302738ca0158ff02a22f4638679533e111082f9dd1b615",
-    "SDXL-Deepcache": "lucataco/sdxl-deepcache:eaf678fb34006669e9a3c6dd5971e2279bf20ee0adeced464d7b6d95de16dc93",
-    "Openjourney-v4": "prompthero/openjourney:ad59ca21177f9e217b9075e7300cf6e14f7e5b4505b87b9689dbd866e9768969",
-    "LCM-v1.5": "fofr/latent-consistency-model:683d19dc312f7a9f0428b04429a9ccefd28dbf7785fef083ad5cf991b65f406f",
-    "Realvisxl-v3.0": "fofr/realvisxl-v3:33279060bbbb8858700eb2146350a98d96ef334fcf817f37eb05915e1534aa1c", 
+    # "SDXL": "stability-ai/sdxl:7762fd07cf82c948538e41f63f77d685e02b063e37e496e96eefd46c929f9bdc",
+    # "SD-v3.0": "stability-ai/stable-diffusion-3",
+    # "SD-v2.1": "stability-ai/stable-diffusion:ac732df83cea7fff18b8472768c88ad041fa750ff7682a21affe81863cbe77e4",
+    # "SD-v1.5": "stability-ai/stable-diffusion:b3d14e1cd1f9470bbb0bb68cac48e5f483e5be309551992cc33dc30654a82bb7",
+    # "SDXL-Lightning": "bytedance/sdxl-lightning-4step:5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f",
+    # "Kandinsky-v2.0": "ai-forever/kandinsky-2:3c6374e7a9a17e01afe306a5218cc67de55b19ea536466d6ea2602cfecea40a9",
+    # "Kandinsky-v2.2": "ai-forever/kandinsky-2.2:ad9d7879fbffa2874e1d909d1d37d9bc682889cc65b31f7bb00d2362619f194a",
+    # "Proteus-v0.2": "lucataco/proteus-v0.2:06775cd262843edbde5abab958abdbb65a0a6b58ca301c9fd78fa55c775fc019",
+    # "Playground-v2.0": "playgroundai/playground-v2-1024px-aesthetic:42fe626e41cc811eaf02c94b892774839268ce1994ea778eba97103fe1ef51b8",
+    # "Playground-v2.5": "playgroundai/playground-v2.5-1024px-aesthetic:a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24",
+    # "Dreamshaper-xl-turbo": "lucataco/dreamshaper-xl-turbo:0a1710e0187b01a255302738ca0158ff02a22f4638679533e111082f9dd1b615",
+    # "SDXL-Deepcache": "lucataco/sdxl-deepcache:eaf678fb34006669e9a3c6dd5971e2279bf20ee0adeced464d7b6d95de16dc93",
+    # "Openjourney-v4": "prompthero/openjourney:ad59ca21177f9e217b9075e7300cf6e14f7e5b4505b87b9689dbd866e9768969",
+    # "LCM-v1.5": "fofr/latent-consistency-model:683d19dc312f7a9f0428b04429a9ccefd28dbf7785fef083ad5cf991b65f406f",
+    # "Realvisxl-v3.0": "fofr/realvisxl-v3:33279060bbbb8858700eb2146350a98d96ef334fcf817f37eb05915e1534aa1c", 
     
-    "Realvisxl-v2.0": "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08",
-    "Pixart-Sigma": "cjwbw/pixart-sigma:5a54352c99d9fef467986bc8f3a20205e8712cbd3df1cbae4975d6254c902de1",
+    # "Realvisxl-v2.0": "lucataco/realvisxl-v2.0:7d6a2f9c4754477b12c14ed2a58f89bb85128edcdd581d24ce58b6926029de08",
+    # "Pixart-Sigma": "cjwbw/pixart-sigma:5a54352c99d9fef467986bc8f3a20205e8712cbd3df1cbae4975d6254c902de1",
     "SSD-1b": "lucataco/ssd-1b:b19e3639452c59ce8295b82aba70a231404cb062f2eb580ea894b31e8ce5bbb6",
     "Open-Dalle-v1.1": "lucataco/open-dalle-v1.1:1c7d4c8dec39c7306df7794b28419078cb9d18b9213ab1c21fdc46a1deca0144",
     "Deepfloyd-IF": "andreasjansson/deepfloyd-if:fb84d659df149f4515c351e394d22222a94144aa1403870c36025c8b28846c8d",

serve/update_skill.py

@@ -82,7 +82,6 @@ def update_skill(rank, model_names, k_group=4):
 
     ratings, comparison_counts, total_comparisons = load_json_via_sftp()
 
-    '''
     # group = Model_ID.group
     group = []
     for model_name in model_names:
@@ -102,11 +101,11 @@ def update_skill(rank, model_names, k_group=4):
             
         comparison_counts[group[player1], group[player2]] += 1
         comparison_counts[group[player2], group[player1]] += 1
-    '''
+    
     total_comparisons += 1
 
     save_json_via_sftp(ratings, comparison_counts, total_comparisons)
 
-    # from model.matchmaker import RunningPivot
-    # if group[0] in RunningPivot.running_pivot:
-    #     RunningPivot.running_pivot.remove(group[0])
+    from model.matchmaker import RunningPivot
+    if group[0] in RunningPivot.running_pivot:
+        RunningPivot.running_pivot.remove(group[0])