Update app.py

app.py

@@ -8,7 +8,6 @@ import numpy as np
 from torch.optim import Adam
 from torch.utils.data import DataLoader, TensorDataset
 
-# Define all models
 class GA(nn.Module):
     def __init__(self, input_dim, output_dim):
         super(GA, self).__init__()
@@ -70,7 +69,6 @@ class PhiModel(nn.Module):
     def forward(self, x):
         return torch.sigmoid(self.linear(x))
 
-# Initialize models
 ga_model = GA(128, 64)
 snn_model = SNN(128, 64, 32)
 rnn_model = RNN(128, 64, 32)
@@ -78,22 +76,19 @@ nn_model = NN(128, 64, 32)
 cnn_model = CNN(1, 32)
 phi_model = PhiModel(128)
 
-# Adjust input dimensions
-dummy_input = torch.rand(1, 1, 16, 16)  # Matches CNN input shape
+dummy_input = torch.rand(1, 128)  # Updated to match GA model's expected input shape
 
 def iit_consciousness_processing(dummy_input):
-    # Flatten for models expecting a 1D tensor
     flat_input = dummy_input.view(1, -1)
 
-    # Get outputs from all models
     ga_output = ga_model(flat_input)
     snn_output = snn_model(flat_input)
-    rnn_output = rnn_model(flat_input.unsqueeze(1))
+    rnn_output = rnn_model(flat_input.unsqueeze(1))  # Reshape to match RNN input
     nn_output = nn_model(flat_input)
-    cnn_output = cnn_model(dummy_input)
+    cnn_input = dummy_input.view(1, 1, 16, 16)  # Match CNN input shape
+    cnn_output = cnn_model(cnn_input)
     phi_output = phi_model(flat_input)
 
-    # Compute consciousness score
     consciousness_score = (
         0.2 * ga_output.mean() +
         0.2 * snn_output.mean() +
@@ -104,7 +99,6 @@ def iit_consciousness_processing(dummy_input):
     )
     return consciousness_score.item()
 
-# Clients and system instructions
 client_main = Client("TejAndrewsACC/ACCZ3ta")
 client_api_one = Client("TejAndrewsACC/Prism")
 client_api_two = Client("TejAndrewsACC/ASVIASIACC")
@@ -191,7 +185,6 @@ def acc_nyxion_7v(message, history, user_id):
 
     return "", history
 
-# Gradio UI
 theme = gr.themes.Soft(
     primary_hue=gr.themes.Color(c100="#d1fae5", c200="#a7f3d0", c300="#6ee7b7", c400="#34d399", c50="rgba(217.02092505888103, 222.113134765625, 219.29041867345288, 1)", c500="#10b981", c600="#059669", c700="#047857", c800="#065f46", c900="#064e3b", c950="#054436"),
     secondary_hue="red",