testing deployment with HFe

requirements.txt

@@ -1,2 +1,3 @@
 concrete-ml==1.1.0
 gradio
+fastapi

seizure_detection.py

@@ -0,0 +1,39 @@
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+
+class SeizureDetectionCNN(nn.Module):
+    def __init__(self, num_classes=2):
+        super(SeizureDetectionCNN, self).__init__()
+        self.conv1= nn.Conv2d(1, 32, kernel_size=3, stride=1, padding=1) # 32, 224, 224
+
+        self.pool= nn.MaxPool2d(kernel_size=2, stride=2) # 32, 112, 112
+
+        self.conv2= nn.Conv2d(32, 64, kernel_size=3, stride=1, padding=1) # 64, 112, 112 -> 64, 56, 56
+        self.conv3= nn.Conv2d(64, 128, kernel_size=3, stride=1, padding=1) # 128, 56, 56 -> 128, 28, 28
+        self.conv4= nn.Conv2d(128, 256, kernel_size=3, stride=1, padding=1) # 256, 28, 28 -> 256, 14, 14
+
+        # Adding Batch Normalization
+        self.bn1 = nn.BatchNorm2d(32)
+        self.bn2 = nn.BatchNorm2d(64)
+        self.bn3 = nn.BatchNorm2d(128)
+        self.bn4 = nn.BatchNorm2d(256)
+
+        self.dropout = nn.Dropout(p=0.5)  # Dropout with a probability of 50%
+
+        self.fc1= nn.Linear(256*14*14, 120)
+        self.fc2= nn.Linear(120, 32)
+        self.fc3= nn.Linear(32, num_classes)
+
+    def forward(self, x):
+        x = self.pool(F.relu(self.bn1(self.conv1(x))))  # 32, 112, 112
+        x = self.pool(F.relu(self.bn2(self.conv2(x))))  # 64, 56, 56
+        x = self.pool(F.relu(self.bn3(self.conv3(x))))  # 128, 28, 28
+        x = self.pool(F.relu(self.bn4(self.conv4(x))))  # 256, 14, 14
+
+        x = torch.flatten(x, 1)
+        x = self.dropout(F.relu(self.fc1(x)))  # Apply dropout
+        x = self.dropout(F.relu(self.fc2(x)))  # Apply dropout
+        x = self.fc3(x)
+        return x

seizure_detection/deployment/client.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:8519d16d710945ce7470058a783984cffb8f2b1040283daec32e523d5c95736b
+size 7408

seizure_detection/deployment/server.zip

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7ad7802d887e387740a2c89c04eb7ba4aafaddd62b3bbaa3a907c8657236ad76
+size 1465254

server.py

@@ -9,7 +9,7 @@ from common import SERVER_TMP_PATH
 from client_server_interface import FHEServer
 
 # Load the server object for seizure detection
-FHE_SERVER = FHEServer(model_path="path/to/seizure_detection_model")
+FHE_SERVER = FHEServer(model_path="ThomasCdnns/EEG-Seizure-Detection/resolve/main/seizure_detection_model-4.pth")
 
 def get_server_file_path(name, user_id):
     """Get the correct temporary file path for the server.