Upload mdeol.py

model.py

@@ -0,0 +1,39 @@
+
+import torch
+import torch.nn as nn
+from torchvision import models
+from transformers import AutoTokenizer, AutoModel
+
+class Net(nn.Module):
+    def __init__(self):
+        super(Net, self).__init__()
+        self.image_encoder = models.resnet18()
+        self.image_encoder.fc = nn.Identity()
+
+        self.image_out = nn.Sequential(
+            nn.Linear(512, 256), nn.ReLU(), nn.Linear(256, 256)
+        )
+
+        self.text_encoder = AutoModel.from_pretrained("dbmdz/distilbert-base-turkish-cased")
+        self.target_token_idx = 0
+
+
+        self.text_out = nn.Sequential(
+            nn.Linear(768, 256), nn.ReLU(), nn.Linear(256, 256)
+        )
+
+
+    def forward(self, image, text, mask):
+
+        image_vec = self.image_encoder(image)
+
+        image_vec = self.image_out(image_vec.view(-1,512))
+
+        text_out = self.text_encoder(text, mask)
+        last_hidden_states = text_out.last_hidden_state
+
+        last_hidden_states = last_hidden_states[:,self.target_token_idx,:]
+
+        text_vec = self.text_out(last_hidden_states.view(-1,768))
+
+        return image_vec, text_vec