Upload fusion_t2i_CLIP_interrogator.ipynb

Google Colab Jupyter Notebooks/fusion_t2i_CLIP_interrogator.ipynb

@@ -3122,9 +3122,21 @@
         "references = torch.load('reference_text_and_image_encodings.pt'  , weights_only=False)\n",
         "reference = torch.add(reference, prompt_strength * C * references[index][0].dequantize())\n",
         "reference = torch.add(reference, prompt_strength * (1-C) * references[index][1].dequantize())\n",
-        "references = ''\n",
+        "references = '' # Clear up memory\n",
         "# @markdown -----------\n",
-        "# @markdown 📝➕ Enhance similarity to prompt(s)\n",
+        "# @markdown 📝➕ 1st Enhance similarity to prompt(s)\n",
+        "POS = '' # @param {type:'string' ,placeholder:'item1 , item2 , ...'}\n",
+        "log_strength = 1.06 # @param {type:\"slider\", min:-5, max:5, step:0.01}\n",
+        "pos_strength = math.pow(10 ,log_strength-1)\n",
+        "for _POS in POS.split(','):\n",
+        "  inputs = tokenizer(text = _POS.strip(), truncation = True  , padding=True, return_tensors=\"pt\")\n",
+        "  text_features_POS = model.get_text_features(**inputs)\n",
+        "  text_features_POS = text_features_POS/text_features_POS.norm(p=2, dim=-1, keepdim=True)\n",
+        "  reference = torch.add(reference, pos_strength * text_features_POS)\n",
+        "# @markdown -----------\n",
+        "\n",
+        "# @markdown -----------\n",
+        "# @markdown 📝➕ 2nd Enhance similarity to prompt(s)\n",
         "POS = '' # @param {type:'string' ,placeholder:'item1 , item2 , ...'}\n",
         "log_strength = 1.06 # @param {type:\"slider\", min:-5, max:5, step:0.01}\n",
         "pos_strength = math.pow(10 ,log_strength-1)\n",