diff --git "a/T5_mapper.ipynb" "b/T5_mapper.ipynb"
new file mode 100644--- /dev/null
+++ "b/T5_mapper.ipynb"
@@ -0,0 +1 @@
+{"cells":[{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":7491,"status":"ok","timestamp":1774958926113,"user":{"displayName":"No Name","userId":"10578412414437288386"},"user_tz":-120},"id":"6ceGJfjyvY4l","outputId":"82980427-f490-42c2-daf6-820c900ad0b7"},"outputs":[{"name":"stdout","output_type":"stream","text":["🔍 Checking GPU runtime...\n","✅ GPU ready: Tesla T4\n","✅ VRAM: 14.6 GB\n","   CUDA version: 12.8\n","   Device index: 0\n","✅ GPU check passed\n"]}],"source":["# @markdown # Cell 1: GPU Check & Runtime Validation\n","\n","import torch\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","print(\"🔍 Checking GPU runtime...\")\n","\n","if torch.cuda.is_available():\n","    gpu_name = torch.cuda.get_device_name(0)\n","    vram_gb = torch.cuda.get_device_properties(0).total_memory / 1024**3\n","    print(f\"✅ GPU ready: {gpu_name}\")\n","    print(f\"✅ VRAM: {vram_gb:.1f} GB\")\n","    if debug:\n","        print(f\"   CUDA version: {torch.version.cuda}\")\n","        print(f\"   Device index: {torch.cuda.current_device()}\")\n","else:\n","    print(\"❌ No GPU detected!\")\n","    print(\"   Please go to: Runtime → Change runtime type → Hardware accelerator → GPU\")\n","    raise SystemExit(\"GPU is required. Please enable GPU runtime.\")\n","\n","print(\"✅ GPU check passed\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":13672,"status":"ok","timestamp":1774958939787,"user":{"displayName":"No Name","userId":"10578412414437288386"},"user_tz":-120},"id":"ajsx94iUvbQH","outputId":"d6b8253e-1e34-4617-e553-fb1aeea9cdf8"},"outputs":[{"name":"stdout","output_type":"stream","text":["📦 Installing dependencies...\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m60.7/60.7 MB\u001b[0m \u001b[31m211.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.5/1.5 MB\u001b[0m \u001b[31m270.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.8/44.8 kB\u001b[0m \u001b[31m205.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h✅ Packages installed successfully\n","   Installed: transformers, accelerate, bitsandbytes, open_clip_torch\n"]}],"source":["# @markdown # Cell 2: Install Required Packages\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","print(\"📦 Installing dependencies...\")\n","!pip install -q --no-cache-dir transformers accelerate bitsandbytes open_clip_torch\n","\n","print(\"✅ Packages installed successfully\")\n","if debug:\n","    print(\"   Installed: transformers, accelerate, bitsandbytes, open_clip_torch\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":14974,"status":"ok","timestamp":1774958954764,"user":{"displayName":"No Name","userId":"10578412414437288386"},"user_tz":-120},"id":"0npx6gtpvhih","outputId":"ad37c7e4-d3c1-4781-babd-cf9e0a7ce738"},"outputs":[{"name":"stdout","output_type":"stream","text":["🔗 Mounting Google Drive...\n","Mounted at /content/drive\n","   Drive mounted at: /content/drive\n","   MyDrive contents sample: ['.ipynb_checkpoints', 'Colab Notebooks', 'deeppanel_model.keras', '_ytcookies.txt', 'ytcookies.txt']\n","✅ Google Drive mounted\n"]}],"source":["# @markdown # Cell 3: Mount Google Drive\n","\n","from google.colab import drive\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","print(\"🔗 Mounting Google Drive...\")\n","drive.mount('/content/drive', force_remount=True)\n","\n","if debug:\n","    print(f\"   Drive mounted at: /content/drive\")\n","    print(f\"   MyDrive contents sample: {os.listdir('/content/drive/MyDrive')[:5] if os.path.exists('/content/drive/MyDrive') else 'Not accessible yet'}\")\n","\n","print(\"✅ Google Drive mounted\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5,"status":"ok","timestamp":1774958954770,"user":{"displayName":"No Name","userId":"10578412414437288386"},"user_tz":-120},"id":"4nMyIVRJvkiY","outputId":"859e1155-c219-48e8-9e0b-fe0b8c472b1f"},"outputs":[{"name":"stdout","output_type":"stream","text":["⚙️  Configuration loaded\n","   Zip path     : /content/drive/MyDrive/dino_tagger_output.zip\n","   Extract dir  : /content/dataset\n","   Debug mode enabled → Extra printouts will be shown\n"]}],"source":["# @markdown # Cell 4: Configuration & Parameters\n","\n","zip_path = \"/content/drive/MyDrive/dino_tagger_output.zip\"  #@param {type:\"string\"}\n","extract_dir = \"/content/dataset\"  #@param {type:\"string\"}\n","debug = True  #@param {type:\"boolean\"}\n","\n","print(\"⚙️  Configuration loaded\")\n","print(f\"   Zip path     : {zip_path}\")\n","print(f\"   Extract dir  : {extract_dir}\")\n","\n","if debug:\n","    print(f\"   Debug mode enabled → Extra printouts will be shown\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5611,"status":"ok","timestamp":1774958960382,"user":{"displayName":"No Name","userId":"10578412414437288386"},"user_tz":-120},"id":"H6GQcTn9vnzx","outputId":"2ba08136-230d-4a22-a822-fc35fd62ec0a"},"outputs":[{"name":"stdout","output_type":"stream","text":["📦 Extracting zip file...\n","✅ Dataset extracted to: /content/dataset\n","   Total files extracted: 380\n","   Top-level folders/files: ['8.txt', '96.txt', '150.jpg', '38.jpg', '30.txt', '163.jpg', '57.jpg', '187.txt', '23.txt', '73.jpg']\n"]}],"source":["# @markdown # Cell 5: Unzip Dataset\n","\n","import os\n","import zipfile\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","os.makedirs(extract_dir, exist_ok=True)\n","\n","print(\"📦 Extracting zip file...\")\n","with zipfile.ZipFile(zip_path, 'r') as zip_ref:\n","    zip_ref.extractall(extract_dir)\n","\n","print(f\"✅ Dataset extracted to: {extract_dir}\")\n","\n","if debug:\n","    total_files = sum([len(files) for r, d, files in os.walk(extract_dir)])\n","    print(f\"   Total files extracted: {total_files}\")\n","    print(f\"   Top-level folders/files: {os.listdir(extract_dir)[:10]}\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":62,"status":"ok","timestamp":1774958960488,"user":{"displayName":"No Name","userId":"10578412414437288386"},"user_tz":-120},"id":"ELEdDOuHvrkA","outputId":"0a4fd622-a00a-45dd-eb4c-15ebb942e9ff"},"outputs":[{"name":"stdout","output_type":"stream","text":["✅ Found 190 valid text-image pairs\n","   Total .txt files found : 190\n","   Total image files found: 190\n","   Sample pair: 8.txt + 8.jpg\n"]}],"source":["# @markdown # Cell 6: Find Paired Text & Image Files\n","\n","from collections import defaultdict\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","text_files = {}\n","image_files = {}\n","image_exts = ('.png', '.jpg', '.jpeg', '.gif', '.bmp', '.webp')\n","\n","for root, _, files in os.walk(extract_dir):\n","    for filename in files:\n","        base = os.path.splitext(filename)[0]\n","        ext = os.path.splitext(filename)[1].lower()\n","        full_path = os.path.join(root, filename)\n","\n","        if ext == '.txt':\n","            text_files[base] = full_path\n","        elif ext in image_exts:\n","            image_files[base] = full_path\n","\n","# Keep only complete pairs\n","pairs = {base: (text_files[base], image_files[base])\n","         for base in text_files if base in image_files}\n","\n","print(f\"✅ Found {len(pairs)} valid text-image pairs\")\n","\n","if debug:\n","    print(f\"   Total .txt files found : {len(text_files)}\")\n","    print(f\"   Total image files found: {len(image_files)}\")\n","    if len(pairs) > 0:\n","        sample_base = list(pairs.keys())[0]\n","        print(f\"   Sample pair: {sample_base}.txt + {sample_base}{os.path.splitext(pairs[sample_base][1])[1]}\")\n","    else:\n","        print(\"   ⚠️  No pairs found. Check that filenames match exactly (without extension)\")"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"background_save":true,"base_uri":"https://localhost:8080/","height":445,"referenced_widgets":["1d53e26175354a2b90334c8cf972dc1e","96cec072abc14cadaf27d0fd358bb5bc","d8135f1bbe144581b43b1b82edaf0320","a4312c3432bd40319ffd962de6777a33","936f15695e284ec79fcab451d45a9377","4921ceb7dc304eb0892d77c818514121","a17b5dea2a784e8684016f73c70905fd","a47f34751143401bad99504cb2c904ac","8fedc0935f414a848627e7dfd1406d42","24c3128e6fa845eebf45d277aa2deb6c","15a5917f88964e29a0eaa392bc2156ae","12e21c3d52de4f58844583aa85fabbb3","9f4d7c99645f41d88663dd0929e503d0","46185fc03a4a42fca0b724813ac7700b","022a6dd597b045c388b57147c2056433","c9f4abdfda2b4fd28446b95e262be61c","39761ba8edd9456781640ee60ea40cf8","26c91dc682594cbb9abceb15ca6c4854","c4e4e065d9c74100aeb18c56e45fc06a","d46354bee9104f77a9dbe8d1c56848e9","c36bde779f634518959e63e611f22def","62a62da839c84e738dee66b4be94fe03","bafff15ac4854df29d45d3b719add5be","f7000a4ffda946549048b9e1236d34d9","28a08feb25744b5e96510ed74b01b595","815deb0a200e42728593ff8a273c06e2","a4f78467232b4c538505f2ffaa2efb6e","013baeeaf22f4bc9abbcc8530303fc4c","3fdd097228a6489f933ad569f9bb36ae","e4955c83b85e47cbbf5925fc623c546e","395d2ebb01d5484a8574d28c6db75d5a","1cdae62d287a45eb8764000628894a30","d081e6cefe124e199a17643facca1009","ae1fc4aaef6d435d8b2a658bb4b99e9c","df83ff650df84c69b779b00b0c851d78","3c70f283537c4fb0921436c889fb4920","b4e7dcf3e4ca406f93461d68ae56beb7","6788ffe8f9954edfaff14d5eea3c2369","4ad10602d75c4629a59e2a734a45a769","4364539838c5484fa9067ac1ac05f66d","fe08aaeb7d664ec0bfb97ca2501423a9","1d8d015411284491814bea83fd7c9f77","fbbf3e26166545c8997e49b7d8df4545","114468b6013a4ff9971b6a2eb006b69e","08d069f56e81452b85657931be84cae6","1c5939a1da4e4443aa575bd53cd2baaa","888c8e401b9440dfbe6426a4aa0fd877","21100c9576af488486c2fcf479fe223b","02c9d8ba68514f8b8b8693e38fbee299","b9a060518570411dbbd427df72fd11b6","ef5ca5a6a9854d478151724ee95ed0cb","980d1e112eae4d49a9a094c4f61bba23","a69e45537be04c0aad82f5c3e552ccdc","8f3d4729612c435f9681c18b34c38e53","f02270fa382846bd93becd271efd02e7","35d9f070e5e343faa75c24ea37bc281b","43d1a177f06948ce94d5373ef3996ec7","5ea1fa903b3041489400c8d6b56db590","d01fca32ff274e58b7019b26b084e5f3","3efcc6f81b8045f6a4abe18b76271d8f","260b078020064e3b823802aaf288fd35","8e84611792964cd89a7d41c913a2587b","c391326ef99a4fdca476482d234a3f35","973da7870c9c4a71a6d528d8298a3aef","d911989822d04efa8d60b88994d88b75","9ef81f1275774d5281a72bd3466f7a55"]},"id":"ot4ZcVtwxcPu","outputId":"da2049b6-39d4-4b4c-c30f-96a3267b8731"},"outputs":[{"name":"stdout","output_type":"stream","text":["📊 Using dedicated T5-XXL **encoder-only** model:\n","   • Repo: mcmonkey/google_t5-v1_1-xxl_encoderonly\n","   • Contains ONLY the encoder (~4.76B params)\n","   • Much smaller download than the full 46 GB model\n","   • With 4-bit quantization: ~2.5 – 3.5 GB VRAM expected\n","\n","🧠 Loading T5-XXL encoder-only (4-bit quantized)...\n"]},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"1d53e26175354a2b90334c8cf972dc1e","version_major":2,"version_minor":0},"text/plain":["tokenizer_config.json: 0.00B [00:00, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"12e21c3d52de4f58844583aa85fabbb3","version_major":2,"version_minor":0},"text/plain":["spiece.model:   0%|          | 0.00/792k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"bafff15ac4854df29d45d3b719add5be","version_major":2,"version_minor":0},"text/plain":["special_tokens_map.json: 0.00B [00:00, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"ae1fc4aaef6d435d8b2a658bb4b99e9c","version_major":2,"version_minor":0},"text/plain":["config.json:   0%|          | 0.00/803 [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"08d069f56e81452b85657931be84cae6","version_major":2,"version_minor":0},"text/plain":["model.safetensors:   0%|          | 0.00/9.52G [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"35d9f070e5e343faa75c24ea37bc281b","version_major":2,"version_minor":0},"text/plain":["Loading weights:   0%|          | 0/219 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["✅ T5-XXL encoder-only loaded successfully\n","   VRAM allocated after loading: 5.74 GB\n","🔄 Encoding 190 texts with T5-XXL encoder...\n","   Processed 50/190 texts...\n","   Processed 100/190 texts...\n","   Processed 150/190 texts...\n","✅ Encoded 190 texts\n","💾 Saved to: /content/t5_embeddings.npy  (shape: (190, 4096))\n","🧹 T5 encoder unloaded from VRAM\n","   VRAM allocated after unload: 1.75 GB\n"]}],"source":["# @markdown # Cell 7: Load T5-XXL Encoder-Only → Encode Texts → Save → Unload VRAM\n","\n","import torch\n","import numpy as np\n","from transformers import T5EncoderModel, T5Tokenizer, BitsAndBytesConfig\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n","\n","# ====================== Model & VRAM Info ======================\n","print(\"📊 Using dedicated T5-XXL **encoder-only** model:\")\n","print(\"   • Repo: mcmonkey/google_t5-v1_1-xxl_encoderonly\")\n","print(\"   • Contains ONLY the encoder (~4.76B params)\")\n","print(\"   • Much smaller download than the full 46 GB model\")\n","print(\"   • With 4-bit quantization: ~2.5 – 3.5 GB VRAM expected\\n\")\n","\n","print(\"🧠 Loading T5-XXL encoder-only (4-bit quantized)...\")\n","\n","model_id = \"mcmonkey/google_t5-v1_1-xxl_encoderonly\"\n","\n","tokenizer = T5Tokenizer.from_pretrained(model_id)\n","\n","quant_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_compute_dtype=torch.float16,\n","    bnb_4bit_use_double_quant=True,\n","    bnb_4bit_quant_type=\"nf4\"\n",")\n","\n","text_encoder = T5EncoderModel.from_pretrained(\n","    model_id,\n","    quantization_config=quant_config,\n","    device_map=\"auto\",\n","    torch_dtype=torch.float16\n",")\n","text_encoder.eval()\n","\n","print(\"✅ T5-XXL encoder-only loaded successfully\")\n","\n","if debug:\n","    try:\n","        allocated = torch.cuda.memory_allocated() / (1024**3)\n","        print(f\"   VRAM allocated after loading: {allocated:.2f} GB\")\n","    except:\n","        pass\n","\n","# ====================== Encode Texts ======================\n","t5_embeddings = []\n","max_length = 512\n","\n","print(f\"🔄 Encoding {len(pairs)} texts with T5-XXL encoder...\")\n","\n","for idx, (base, (txt_path, _)) in enumerate(pairs.items()):\n","    if debug and idx % 50 == 0 and idx > 0:\n","        print(f\"   Processed {idx}/{len(pairs)} texts...\")\n","\n","    with open(txt_path, 'r', encoding='utf-8') as f:\n","        text = f.read().strip()\n","\n","    if not text:\n","        if debug:\n","            print(f\"   Skipped empty text: {base}\")\n","        continue\n","\n","    inputs = tokenizer(\n","        text,\n","        padding=\"max_length\",\n","        max_length=max_length,\n","        truncation=True,\n","        return_tensors=\"pt\"\n","    )\n","\n","    input_ids = inputs.input_ids.to(\"cuda\")\n","    attention_mask = inputs.attention_mask.to(\"cuda\")\n","\n","    with torch.no_grad():\n","        outputs = text_encoder(input_ids=input_ids, attention_mask=attention_mask)\n","        # Mean pooling → 4096-dim embedding\n","        t5_emb = outputs.last_hidden_state.mean(dim=1).squeeze(0).cpu().numpy()\n","\n","    t5_embeddings.append(t5_emb)\n","\n","t5_embs = np.array(t5_embeddings)\n","t5_save_path = \"/content/t5_embeddings.npy\"\n","np.save(t5_save_path, t5_embs)\n","\n","print(f\"✅ Encoded {len(t5_embs)} texts\")\n","print(f\"💾 Saved to: {t5_save_path}  (shape: {t5_embs.shape})\")\n","\n","# ====================== Unload T5 to free VRAM ======================\n","del text_encoder\n","torch.cuda.empty_cache()\n","\n","print(\"🧹 T5 encoder unloaded from VRAM\")\n","if debug:\n","    try:\n","        print(f\"   VRAM allocated after unload: {torch.cuda.memory_allocated() / (1024**3):.2f} GB\")\n","    except:\n","        pass"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"ZWLwMFi_zMDk"},"outputs":[],"source":["# @markdown # Cell 8: Load OpenCLIP ViT-B-32 → Encode Images\n","\n","import torch\n","import numpy as np\n","from PIL import Image\n","import open_clip\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n","print(f\"🔧 Using device: {device}\")\n","\n","# ====================== Load OpenCLIP ======================\n","print(\"📸 Loading OpenCLIP ViT-B-32 (laion400m_e32)...\")\n","clip_model, _, preprocess = open_clip.create_model_and_transforms(\n","    \"ViT-B-32\", pretrained=\"laion400m_e32\"\n",")\n","clip_model.to(device)\n","clip_model.eval()\n","\n","print(\"✅ OpenCLIP loaded successfully\")\n","\n","if debug:\n","    try:\n","        mem = torch.cuda.memory_allocated() / (1024**3)\n","        print(f\"   VRAM used after loading CLIP: {mem:.2f} GB\")\n","    except:\n","        pass\n","\n","# ====================== Encode Images ======================\n","clip_embeddings = []\n","\n","print(f\"🔄 Encoding {len(pairs)} images...\")\n","\n","# Load T5 embeddings (to keep order consistent)\n","t5_embs = np.load(\"/content/t5_embeddings.npy\")\n","\n","for idx, (base, (_, img_path)) in enumerate(pairs.items()):\n","    if debug and idx % 50 == 0 and idx > 0:\n","        print(f\"   Processed {idx}/{len(pairs)} images...\")\n","\n","    try:\n","        image = preprocess(Image.open(img_path)).unsqueeze(0).to(device)\n","        with torch.no_grad():\n","            clip_emb = clip_model.encode_image(image).squeeze(0).cpu().numpy()\n","        clip_embeddings.append(clip_emb)\n","    except Exception as e:\n","        if debug:\n","            print(f\"   ⚠️ Error on image {base}: {e}\")\n","        continue\n","\n","clip_embs = np.array(clip_embeddings)\n","clip_save_path = \"/content/clip_embeddings.npy\"\n","np.save(clip_save_path, clip_embs)\n","\n","print(f\"✅ Encoded {len(clip_embs)} images\")\n","print(f\"💾 Saved to: {clip_save_path}  (shape: {clip_embs.shape})\")\n","\n","print(f\"   T5 shape : {t5_embs.shape}\")\n","print(f\"   CLIP shape: {clip_embs.shape}\")\n","if len(t5_embs) != len(clip_embs):\n","    print(\"⚠️  Note: Some images may have failed to process (shapes don't match)\")"]},{"cell_type":"code","execution_count":null,"metadata":{"id":"MMoH6jm2zioL"},"outputs":[],"source":["# @markdown # Cell 9: Train Mapper (T5 embedding → CLIP image embedding)\n","\n","import torch.nn as nn\n","from torch.utils.data import TensorDataset, DataLoader\n","import torch\n","import numpy as np\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","# Load saved embeddings\n","t5_embs = np.load(\"/content/t5_embeddings.npy\")\n","clip_embs = np.load(\"/content/clip_embeddings.npy\")\n","\n","print(f\"📂 Loaded T5 embeddings : {t5_embs.shape}\")\n","print(f\"📂 Loaded CLIP embeddings: {clip_embs.shape}\")\n","\n","class T5toCLIPMapper(nn.Module):\n","    def __init__(self, input_dim=4096, output_dim=512, hidden_dim=2048):\n","        super().__init__()\n","        self.net = nn.Sequential(\n","            nn.Linear(input_dim, hidden_dim),\n","            nn.ReLU(),\n","            nn.Linear(hidden_dim, hidden_dim),\n","            nn.ReLU(),\n","            nn.Linear(hidden_dim, output_dim)\n","        )\n","\n","    def forward(self, x):\n","        return self.net(x)\n","\n","# Dataset & Loader\n","dataset = TensorDataset(\n","    torch.from_numpy(t5_embs).float(),\n","    torch.from_numpy(clip_embs).float()\n",")\n","dataloader = DataLoader(dataset, batch_size=16, shuffle=True)\n","\n","model = T5toCLIPMapper().to(device)\n","optimizer = torch.optim.Adam(model.parameters(), lr=1e-4)\n","criterion = nn.MSELoss()\n","\n","num_epochs = 50  #@param {type:\"integer\"}\n","\n","print(f\"🚀 Starting training for {num_epochs} epochs...\")\n","\n","for epoch in range(num_epochs):\n","    total_loss = 0.0\n","    for inputs, targets in dataloader:\n","        inputs = inputs.to(device)\n","        targets = targets.to(device)\n","\n","        optimizer.zero_grad()\n","        outputs = model(inputs)\n","        loss = criterion(outputs, targets)\n","        loss.backward()\n","        optimizer.step()\n","\n","        total_loss += loss.item()\n","\n","    avg_loss = total_loss / len(dataloader)\n","    if (epoch + 1) % 10 == 0 or epoch == 0:\n","        print(f\"Epoch {epoch+1:2d}/{num_epochs} | Avg Loss: {avg_loss:.6f}\")\n","\n","# Save\n","save_path = \"/content/t5_to_clip_mapper.pth\"\n","torch.save(model.state_dict(), save_path)\n","\n","print(\"🎉 Training completed!\")\n","print(f\"✅ Mapper saved to: {save_path}\")\n","\n","if debug:\n","    print(f\"   Final average loss: {avg_loss:.6f}\")"]},{"cell_type":"code","source":["# @markdown # Cell 10: Save Model + Embeddings to Google Drive\n","\n","import shutil\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","# @markdown ### Choose folder in your Drive (change if needed)\n","drive_save_folder = \"/content/drive/MyDrive/T5_CLIP_Mapper\"  #@param {type:\"string\"}\n","\n","os.makedirs(drive_save_folder, exist_ok=True)\n","\n","# Files to save\n","files_to_save = {\n","    \"/content/clip_to_t5_mapper.pth\": f\"{drive_save_folder}/clip_to_t5_mapper.pth\",\n","    \"/content/t5_embeddings.npy\": f\"{drive_save_folder}/t5_embeddings.npy\",\n","    \"/content/clip_embeddings.npy\": f\"{drive_save_folder}/clip_embeddings.npy\"\n","}\n","\n","print(f\"💾 Saving files to Google Drive folder: {drive_save_folder}\")\n","\n","for local_path, drive_path in files_to_save.items():\n","    if os.path.exists(local_path):\n","        shutil.copy2(local_path, drive_path)\n","        print(f\"✅ Saved: {os.path.basename(local_path)} → {drive_path}\")\n","    else:\n","        print(f\"⚠️  File not found: {local_path}\")\n","\n","print(\"\\n🎉 All files saved to Google Drive!\")\n","if debug:\n","    print(f\"   Drive folder contents: {os.listdir(drive_save_folder)}\")"],"metadata":{"id":"N0CQFqwX4TBz"},"execution_count":null,"outputs":[]},{"cell_type":"code","source":["# Step 1: Mount Google Drive\n","from google.colab import drive\n","drive.mount('/content/drive')"],"metadata":{"id":"AEA3l5bSLSo1","colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"status":"ok","timestamp":1774960421570,"user_tz":-120,"elapsed":5312,"user":{"displayName":"No Name","userId":"10578412414437288386"}},"outputId":"53d37677-0658-46d5-922f-c8f70f7ee51a"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n"]}]},{"cell_type":"code","source":["# @markdown # Cell 11: Load Model + Embeddings from Google Drive\n","\n","import torch\n","import numpy as np\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n","\n","\n","# @markdown ### Path to your saved folder in Drive\n","drive_folder = \"/content/drive/MyDrive/T5_CLIP_Mapper\"  #@param {type:\"string\"}\n","\n","# File paths\n","mapper_path = f\"{drive_folder}/clip_to_t5_mapper.pth\"\n","t5_path = f\"{drive_folder}/t5_embeddings.npy\"\n","clip_path = f\"{drive_folder}/clip_embeddings.npy\"\n","\n","print(\"📂 Loading files from Google Drive...\")\n","\n","# Load embeddings\n","t5_embs = np.load(t5_path)\n","clip_embs = np.load(clip_path)\n","\n","print(f\"✅ Loaded T5 embeddings : {t5_embs.shape}\")\n","print(f\"✅ Loaded CLIP embeddings: {clip_embs.shape}\")\n","\n","# Define the model class again (needed for loading state_dict)\n","class CLIPtoT5Mapper(torch.nn.Module):\n","    def __init__(self, input_dim=512, output_dim=4096, hidden_dim=2048):\n","        super().__init__()\n","        self.net = torch.nn.Sequential(\n","            torch.nn.Linear(input_dim, hidden_dim),\n","            torch.nn.ReLU(),\n","            torch.nn.Linear(hidden_dim, hidden_dim * 2),\n","            torch.nn.ReLU(),\n","            torch.nn.Linear(hidden_dim * 2, output_dim)\n","        )\n","\n","    def forward(self, x):\n","        return self.net(x)\n","\n","# Load the trained mapper\n","model = CLIPtoT5Mapper().to(device)\n","model.load_state_dict(torch.load(mapper_path, map_location=device))\n","model.eval()\n","\n","print(\"✅ CLIP → T5 mapper loaded successfully\")\n","print(f\"   Model ready on device: {device}\")\n","\n","if debug:\n","    print(f\"   Mapper path: {mapper_path}\")\n","    print(f\"   Total parameters: {sum(p.numel() for p in model.parameters()):,}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"L9SM8hbM4KCK","executionInfo":{"status":"ok","timestamp":1774960540075,"user_tz":-120,"elapsed":7786,"user":{"displayName":"No Name","userId":"10578412414437288386"}},"outputId":"57e9b0cd-8012-4534-f311-ffc7c40776b1"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["📂 Loading files from Google Drive...\n","✅ Loaded T5 embeddings : (190, 4096)\n","✅ Loaded CLIP embeddings: (190, 512)\n","✅ CLIP → T5 mapper loaded successfully\n","   Model ready on device: cuda\n","   Mapper path: /content/drive/MyDrive/T5_CLIP_Mapper/clip_to_t5_mapper.pth\n","   Total parameters: 26,224,640\n"]}]},{"cell_type":"code","source":["# @markdown # Cell 12: Visualize Differences — CLIP vs CLIP, T5 vs T5, Predicted T5 vs Predicted T5, and Predicted vs True T5\n","\n","import torch\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.decomposition import PCA\n","from sklearn.metrics.pairwise import cosine_similarity\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","print(\"📊 Preparing visualizations for embedding differences...\")\n","\n","# Make sure we have everything loaded (run Cell 11 first)\n","if 'model' not in globals() or 'clip_embs' not in globals() or 't5_embs' not in globals():\n","    print(\"⚠️  Please run Cell 11 first to load model + embeddings!\")\n","    raise SystemExit(\"Missing data\")\n","\n","# ====================== 1. Compute predicted T5 from CLIP ======================\n","print(\"🔄 Computing predicted T5 embeddings from CLIP inputs...\")\n","with torch.no_grad():\n","    clip_tensor = torch.from_numpy(clip_embs).float().to(device)\n","    predicted_t5 = model(clip_tensor).cpu().numpy()\n","\n","print(f\"✅ Predicted T5 shape: {predicted_t5.shape}\")\n","\n","# ====================== 2. Pairwise cosine similarities WITHIN each set ======================\n","print(\"📐 Calculating pairwise cosine similarities (within each embedding group)...\")\n","\n","def get_pairwise_similarities(embeddings):\n","    \"\"\"Return off-diagonal cosine similarities (excluding self-similarity=1.0)\"\"\"\n","    sim_matrix = cosine_similarity(embeddings)\n","    np.fill_diagonal(sim_matrix, np.nan)          # ignore diagonal (always 1.0)\n","    return sim_matrix.flatten()[~np.isnan(sim_matrix.flatten())]\n","\n","# CLIP vs CLIP (among themselves)\n","clip_sim = get_pairwise_similarities(clip_embs)\n","\n","# True T5 vs True T5 (among themselves)\n","t5_sim = get_pairwise_similarities(t5_embs)\n","\n","# Predicted T5 vs Predicted T5 (among themselves)\n","pred_t5_sim = get_pairwise_similarities(predicted_t5)\n","\n","# Predicted T5 vs True T5 (the most important metric)\n","pred_true_sim = np.diag(cosine_similarity(predicted_t5, t5_embs))\n","\n","print(f\"   CLIP vs CLIP mean similarity     : {clip_sim.mean():.4f}\")\n","print(f\"   True T5 vs True T5 mean similarity: {t5_sim.mean():.4f}\")\n","print(f\"   Predicted T5 vs Predicted T5     : {pred_t5_sim.mean():.4f}\")\n","print(f\"   Predicted T5 vs True T5 (model quality): {pred_true_sim.mean():.4f}\")\n","\n","# ====================== 3. Dimensionality reduction for scatter plots ======================\n","print(\"🌀 Reducing dimensions with PCA...\")\n","\n","# PCA on CLIP space\n","pca_clip = PCA(n_components=2, random_state=42)\n","clip_2d = pca_clip.fit_transform(clip_embs)\n","\n","# PCA on T5 space (true + predicted in SAME space)\n","all_t5 = np.vstack([t5_embs, predicted_t5])\n","pca_t5 = PCA(n_components=2, random_state=42)\n","t5_2d = pca_t5.fit_transform(all_t5)\n","true_t5_2d = t5_2d[:len(t5_embs)]\n","pred_t5_2d = t5_2d[len(t5_embs):]\n","\n","print(f\"   PCA explained variance — CLIP: {pca_clip.explained_variance_ratio_.sum():.1%}\")\n","print(f\"   PCA explained variance — T5  : {pca_t5.explained_variance_ratio_.sum():.1%}\")\n","\n","# ====================== 4. Plotting ======================\n","plt.figure(figsize=(20, 12))\n","\n","# Row 1: Pairwise similarity histograms (within each group)\n","plt.subplot(2, 3, 1)\n","sns.histplot(clip_sim, kde=True, color='skyblue', bins=50)\n","plt.title('CLIP vs CLIP\\n(Pairwise Cosine Similarity)')\n","plt.xlabel('Cosine Similarity')\n","plt.ylabel('Count')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 2)\n","sns.histplot(t5_sim, kde=True, color='green', bins=50)\n","plt.title('True T5 vs True T5\\n(Pairwise Cosine Similarity)')\n","plt.xlabel('Cosine Similarity')\n","plt.ylabel('Count')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 3)\n","sns.histplot(pred_t5_sim, kde=True, color='orange', bins=50)\n","plt.title('Predicted T5 vs Predicted T5\\n(Pairwise Cosine Similarity)')\n","plt.xlabel('Cosine Similarity')\n","plt.ylabel('Count')\n","plt.grid(True, alpha=0.3)\n","\n","# Row 2: Model quality + geometry\n","plt.subplot(2, 3, 4)\n","sns.histplot(pred_true_sim, kde=True, color='purple', bins=50)\n","plt.title('Predicted T5 vs True T5\\n(Model Quality — Per-Pair)')\n","plt.xlabel('Cosine Similarity')\n","plt.ylabel('Count')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 5)\n","plt.scatter(clip_2d[:, 0], clip_2d[:, 1], alpha=0.7, s=25, color='skyblue')\n","plt.title('CLIP Embeddings (PCA 2D)')\n","plt.xlabel('PC1')\n","plt.ylabel('PC2')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 6)\n","plt.scatter(true_t5_2d[:, 0], true_t5_2d[:, 1], alpha=0.7, s=25, color='green', label='True T5')\n","plt.scatter(pred_t5_2d[:, 0], pred_t5_2d[:, 1], alpha=0.7, s=25, color='red', label='Predicted T5')\n","plt.title('True T5 vs Predicted T5\\n(in shared PCA space)')\n","plt.xlabel('PC1')\n","plt.ylabel('PC2')\n","plt.legend()\n","plt.grid(True, alpha=0.3)\n","\n","plt.tight_layout()\n","plt.show()\n","\n","# ====================== 5. Optional: L2 distance histogram ======================\n","plt.figure(figsize=(8, 5))\n","diff_vectors = predicted_t5 - t5_embs\n","diff_norms = np.linalg.norm(diff_vectors, axis=1)\n","sns.histplot(diff_norms, kde=True, color='crimson', bins=50)\n","plt.title('L2 (Euclidean) Distance: Predicted T5 − True T5')\n","plt.xlabel('Distance')\n","plt.ylabel('Count')\n","plt.grid(True, alpha=0.3)\n","plt.show()\n","\n","print(f\"\\n✅ All plots generated successfully!\")\n","print(f\"   Number of samples used: {len(clip_embs)}\")\n","if debug:\n","    print(\"\\n💡 Interpretation guide:\")\n","    print(\"   • First three histograms: How clustered / diverse each embedding type is internally\")\n","    print(\"   • Fourth histogram: How close the model’s predictions are to the real T5 embeddings\")\n","    print(\"   • Scatter plots: Visual geometry and overlap between true vs predicted T5\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":715},"id":"lb-d8VnI4HXP","executionInfo":{"status":"ok","timestamp":1774960553703,"user_tz":-120,"elapsed":4898,"user":{"displayName":"No Name","userId":"10578412414437288386"}},"outputId":"71fbb39d-3204-40c1-dbb7-13932a93d1e4"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["📊 Preparing visualizations for embedding differences...\n","🔄 Computing predicted T5 embeddings from CLIP inputs...\n","✅ Predicted T5 shape: (190, 4096)\n","📐 Calculating pairwise cosine similarities (within each embedding group)...\n","   CLIP vs CLIP mean similarity     : 0.5188\n","   True T5 vs True T5 mean similarity: 0.8838\n","   Predicted T5 vs Predicted T5     : 0.8861\n","   Predicted T5 vs True T5 (model quality): 0.9986\n","🌀 Reducing dimensions with PCA...\n","   PCA explained variance — CLIP: 20.6%\n","   PCA explained variance — T5  : 60.4%\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 2000x1200 with 6 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9evWC2WzGM888gyZNmsBgMGDTpk145JFHLqoHlZFlGfHx8fjiiy/KfbyiUOANk8nk1S9eFx6vfe693nzzzRg7dmy5z2nbtm216/KHUKjxnHPrWW5ubqXjWrRogTlz5ng1z6SkpIuuS6/XQ6Uq+wfYin7JvDAgert9CZSUlBQ4nU5YrVaYzeaAvhYpj8GVapX/+7//w5w5czBz5kyf/ox/bo/FoUOH0KZNm2q9dnR0dLl/Ij+3Z/ScJk2a4LfffkNubu5F7XVNTU0FULK34/yAXlxcjEOHDqFdu3alXnPr1q3o169fpXs8f/75ZzgcDvz000+l9qb64099hw4dQmxs7EUFMODf82kOGjSo0nE6nQ4jRozAiBEjIMsy7rnnHnzwwQd48skny93rds6KFSuQk5OD77//Hj179ixVf3U1adIE69evR3FxsecLVuWNWbJkCXr06FGtL/wFQlxcHCIiIuB2u6sMvqmpqdixYweEEKV6u2fPnipfx9t1oryfWU3V6A/ntg9VrQOJiYnV/tKdP0VHRyMvL6/M9CNHjpT6q46325dAOXjwIAwGQ6kLx1DtxWNcqdZ45ZVX8Oqrr+Kxxx7DpEmTfHpueno6dDpdpaejqkqTJk2we/fuUpc23bp1K1avXl1q3NVXXw0hBKZNm1ZmHr7spevUqRPi4uLw/vvvw+l0eqbPnTu3zIfNmDFjcOLECXz44Ydl5mOz2WC1WgH8u/fw/DosFovXe38qk5GRgW7dul3UPL788kt89NFH6NatG/r161fhuHPHLJ+jUqk8e93OnZ7HZDIBQJleldcDp9OJd999t9p1X3311Thz5gzefvvtMo+de50xY8bA7Xbj2WefLTPG5XKVqvNiT4flLbVajauvvhrfffedZ0/3+c5f1ocOHYqTJ0/i22+/9UwrKiqq8M/35/N2nTCZTOX+vGqiRl+Ud3njgoICzJw5E7GxsUhPT/fr6wVKkyZNsG7dulLbl19++QXHjh0rNc7b7cvFKq+vW7duxU8//YSBAweWu9eYah/ucaWQMXv2bM95Jc83adIkLFmyBA8//DCaNWuGli1b4vPPPy81ZsCAAUhISKhw3gaDAQMHDsSSJUvwzDPPlHn8xIkTZeYJlHwx59xVfG6//XbMmDEDgwYNwvjx45GVlYX3338frVu3LnWcZJ8+fXDLLbfgzTffxL59+zB48GDIsoyVK1eiT58+uO+++7zqh1arxXPPPYcJEyagb9++uO6663Do0CHMmTOnzDGut9xyC+bPn4///Oc/WL58OXr06AG3243du3dj/vz5+O2339CpUycMHDjQs6dywoQJKCwsxIcffoj4+HicOnXKq7rKk5WVhW3btpU5nVZlvv32W4SHh8PpdHqunLV69Wq0a9cO33zzTaXPveOOO5Cbm4u+ffuiQYMGOHLkCN566y20b9/ec8qr9u3bQ61W46WXXoLFYoFer0ffvn3RvXt3REdHY+zYsZg4cSIkScJnn312UV+CufXWW/Hpp59i8uTJ2LBhA6644gpYrVYsWbIE99xzD0aNGoVevXphwoQJmD59OrZs2YKBAwdCq9Vi3759+Oabb/DGG294vlTkj9NheevFF1/E8uXL0bVrV9x5551o1aoVcnNzsWnTJixZssTzZ+8777wTb7/9Nm699VZkZGQgKSkJn332mVenVvJ2nUhPT8eSJUswY8YMJCcno1GjRujatWuN1OiLd955Bz/++CNGjBiBhg0b4tSpU5g9ezaOHj2Kzz77LGSufnfHHXfg22+/xeDBgzFmzBgcOHAAn3/+uec0ZOd4u325WNdddx2MRiO6d++O+Ph47Ny5E7NmzUJYWJgiV4AjhdToOQyIquHcqX8quh07dsxzCqWKbt6c5ub7778XkiSJo0ePlppe2emwzj+ljxAlV3Zq3Lix0Ol0on379uK3334rc+ofIYRwuVzilVdeES1atBA6nU7ExcWJIUOGiIyMjFKvW9npsM559913RaNGjYRerxedOnUSf/75Z7mn5nI6neKll14SrVu3Fnq9XkRHR4v09HQxbdo0YbFYPON++ukn0bZtW2EwGERaWpp46aWXPKdzOv80OhVdUay8137vvfdEWFiYyM/PLzP+Qhf+LA0Gg2jQoIEYPny4mD17dqnTUZ1zYY+//fZbMXDgQBEfHy90Op1o2LChmDBhgjh16lSp53344YeicePGQq1Wl+rt6tWrxWWXXSaMRqNITk4WDz/8sPjtt9/K9L+8q1KVV48QJafYevzxx0WjRo2EVqsViYmJ4pprrhEHDhwoNW7WrFkiPT1dGI1GERERIdq0aSMefvhhcfLkSc8YX0+HVV6NF0IlV3rKzMwU9957r0hJSfHU3q9fPzFr1qxS444cOSJGjhwpwsLCRGxsrJg0aZLndF6VnQ5LCO/Wid27d4uePXsKo9EoAJRaP/xdY1UqOx3W77//LgYMGCASExOFVqsVUVFRYuDAgWLp0qVezz8QKjodlslkqvA5r732mqhfv77Q6/WiR48eYuPGjRe1falKZafDeuONN0SXLl1ETEyM0Gg0IikpSdx8881i3759Xs+fQp8khJ/OpUEU4txuN1q1aoUxY8aU++daqr4OHTqgd+/eeP3115UuhYiIQhiDK9F5vv76a9x99904evQoD/T3k0WLFuGaa67BwYMHKzzVExERkTcYXImIiIgoJPAreEREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikFDrL0AgyzJOnjyJiIgIRS5FR0RERESVE0KgoKAAycnJlV4FrdYH15MnTyIlJUXpMoiIiIioCseOHUODBg0qfLzWB9eIiAgAJY0wm82K1SHLMrKzsxEXF8frKQcIexx47HHgscc1g30OPPY48GpTj/Pz85GSkuLJbRWp9cH13OEBZrNZ8eBqt9thNptDfuEKVuxx4LHHgcce1wz2OfDY48CrjT2u6rDO2vEuiYiIiKjWY3AlIiIiopDA4EpEREREIYHBlYiIiIhCAoMrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikMDgSkREREQhQdHg+ueff2LEiBFITk6GJEn48ccfSz0uhMBTTz2FpKQkGI1G9O/fH/v27VOmWCIiIiJSlKLB1Wq1ol27dnjnnXfKffzll1/Gm2++iffffx/r16+HyWTCoEGDYLfba7hSIiIiIlKaRskXHzJkCIYMGVLuY0IIzJw5E0888QRGjRoFAPj000+RkJCAH3/8Eddff31NlkpEREREClM0uFbm0KFDOH36NPr37++ZFhkZia5du2Lt2rUVBleHwwGHw+G5n5+fDwCQZRmyLAe26ErIsgwhhKI11HbsceCxx4HHHteMYOizzWaD0+n0aqxOp4PRaAxwRf4VDD2u7WpTj719D0EbXE+fPg0ASEhIKDU9ISHB81h5pk+fjmnTppWZnp2dreghBrIsw2KxQAgBlYrfiQsE9jjw2OPAY49rhtJ9djgcuHP8eOT9s3OlKlFmMz78+GPo9foAV+Y/Sve4LqhNPS4oKPBqXNAG1+qaMmUKJk+e7Lmfn5+PlJQUxMXFwWw2K1aXLMuQJAlxcXEhv3AFK/Y48NjjwGOPa4bSfbZYLFi6fDkyHp4OsyGs0rH59iKkvzwFZrMZkZGRNVThxVO6x3VBbeqxwWDwalzQBtfExEQAQGZmJpKSkjzTMzMz0b59+wqfp9fry/2NVKVSKf5DlSQpKOqozdjjwGOPA489rhlK9lmSJMiyjEhDGCKNlQdXCf8GlFBbJrgsB15t6bG39Qftu2zUqBESExOxdOlSz7T8/HysX78e3bp1U7AyIiIiIlKContcCwsLsX//fs/9Q4cOYcuWLYiJiUHDhg3xwAMP4LnnnkOzZs3QqFEjPPnkk0hOTsbo0aOVK5qIiIiIFKFocN24cSP69OnjuX/u2NSxY8di7ty5ePjhh2G1WnHXXXchLy8Pl19+ORYtWuT1cRBEREREVHsoGlx79+4NIUSFj0uShGeeeQbPPPNMDVZFRERERMEoaI9xJSIiIiI6H4MrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikMDgSkREREQhgcGViIiIiEICgysRERERhQQGVyIiIiIKCQyuRERERBQSGFyJiIiIKCQwuBIRERFRSGBwJSIiIqKQwOBKRERERCGBwZWIiIiIQgKDKxERERGFBAZXIiIiIgoJDK5EREREFBIYXImIiIgoJDC4EhEREVFIYHAlIiIiopDA4EpEREREIYHBlYiIiIhCAoMrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkaJQugIiI6GLZbDY4HA6vxsqyDEmSUFhYCL1eD0mSKhyr1+thNBr9VSYRXSQGVyIiCmk2mw2NUlORmZ3t1XiNpIIsAenp6cjIyIAsyxWOTYiLw6EjRxheiYIEgysREYU0h8OBzOxsbHn0JZgNYZWOPZ6Xg54zn8a6B56BISUJEcPsqGh/a769CO1ffAQOh4PBlShIMLgSEVGtYDaEIdJYeXDNtxUBACL0Rmh1ekQaVRUGVyIKPvxyFhERERGFBAZXIiIiIgoJDK5EREREFBIYXImIiIgoJDC4EhEREVFIYHAlIiIiopDA4EpEREREIYHBlYiIiIhCAoMrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikMDgSkREREQhgcGViIiIiEICgysRERERhQQGVyIiIiIKCQyuRERERBQSGFyJiIiIKCQwuBIRERFRSGBwJSIiIqKQwOBKRERERCGBwZWIiIiIQgKDKxERERGFBAZXIiIiIgoJDK5EREREFBIYXImIiIgoJDC4EhEREVFICOrg6na78eSTT6JRo0YwGo1o0qQJnn32WQghlC6NiIiIiGqYRukCKvPSSy/hvffewyeffILWrVtj48aNuO222xAZGYmJEycqXR4RERER1aCgDq5r1qzBqFGjMGzYMABAWloavvrqK2zYsEHhyoiIiIiopgV1cO3evTtmzZqFvXv34pJLLsHWrVuxatUqzJgxo8LnOBwOOBwOz/38/HwAgCzLkGU54DVXRJZlCCFqtAabzQan0+nVWJ1OB6PRGOCKAkuJHtc17HHgsce+E0JApVJBAKjqQDIBlBpb2XjP2AD8PKpVcwDq8OVzAvDts4LLcuDVph57+x6COrg++uijyM/PR4sWLaBWq+F2u/H888/jpptuqvA506dPx7Rp08pMz87Oht1uD2S5lZJlGRaLxbOxCjSHw4E7x49H3j/BvSpRZjM+/Phj6PX6AFcWODXd47qIPQ489th3hYWFSE9PR4HZALdOW+lYmzAhPT0d1igTNIaSj0CpgrFFWgPS09ORk5NTaodITdccqDp8/ZwAfPus4LIceLWpxwUFBV6NC+rgOn/+fHzxxRf48ssv0bp1a2zZsgUPPPAAkpOTMXbs2HKfM2XKFEyePNlzPz8/HykpKYiLi4PZbK6p0suQZRmSJCEuLq5GFi6LxYKly5cj4+HpMBvCKh2bby9C+stTYDabERkZGfDaAqWme1wXsceBxx77Tq/XIyMjAxHD7Ig0Vt4z61krMjIyYOo3BtrwcMRYiysMrmqbHRkZGahXr57ft42+1ByoOnz5nAB8/6zgshx4tanHBoPBq3FBHVz/7//+D48++iiuv/56AECbNm1w5MgRTJ8+vcLgqtfry/1NUKVSKf5DlSSpxuqQJAmyLCPSEIZIY+UbJAn/LvxK9+hi1WSP6yr2OPDYY9+c295JqHjvqWcsUGpsZc8J5LaxWjX7uQ5fPieqWweX5cCrLT32tv6gfpdFRUVl3ohara4Vx3IQERERkW+Ceo/riBEj8Pzzz6Nhw4Zo3bo1Nm/ejBkzZuD2229XujQiIiIiqmFBHVzfeustPPnkk7jnnnuQlZWF5ORkTJgwAU899ZTSpRERERFRDQvq4BoREYGZM2di5syZSpdCRERERAoL6mNciYiIiIjOYXAlIiIiopDA4EpEREREIYHBlYiIiIhCAoMrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikMDgSkREREQhgcGViIiIiEICgysRERERhQQGVyIiIiIKCQyuRERERBQSGFyJiIiIKCQwuBIRERFRSGBwJSIiIqKQwOBKRERERCGBwZWIiIiIQgKDKxERERGFBAZXIiIiIgoJDK5EREREFBIYXImIiIgoJDC4EhEREVFIYHAlIiIiopDA4EpEREREIYHBlYiIiIhCAoMrEREREYUEjdIFEBERXchms8HhcHg11mKxBLgaqg6bzYbCwkLo9XpIklTpWL1eD6PRWEOVUShjcCUioqBis9nQKDUVmdnZPj2vuLgYYPYJCjabDc2aNEGDhg2RkZEBWZYrHZ8QF4dDR44wvFKVGFyJiCioOBwOZGZnY8ujL8FsCKty/PG8HPSc+TTcbncNVEfeOPcz/O7BJ5Ew7FZUtr81316E9i8+AofDweBKVWJwJSKioGQ2hCHSWHVwzbcV1UA1VB1hOj0iJVWlwZXIF/xyFhERERGFBAZXIiIiIgoJDK5EREREFBIYXImIiIgoJDC4EhEREVFIYHAlIiIiopDA4EpEREREIYHBlYiIiIhCAoMrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikMDgSkREREQhgcGViIiIiEICgysRERERhQQGVyIiIiIKCQyuRERERBQSGFyJiIiIKCQwuBIRERFRSGBwJSIiIqKQwOBKRERERCGBwZWIiIiIQgKDKxERERGFBAZXIiIiIgoJDK5EREREFBIYXImIiIgoJDC4EhEREVFIYHAlIiIiopAQ9MH1xIkTuPnmm1GvXj0YjUa0adMGGzduVLosIiIiIqphGqULqMzZs2fRo0cP9OnTBwsXLkRcXBz27duH6OhopUsjIiIiohoW1MH1pZdeQkpKCubMmeOZ1qhRIwUrIiIiIiKlBHVw/emnnzBo0CBce+21+OOPP1C/fn3cc889uPPOOyt8jsPhgMPh8NzPz88HAMiyDFmWA15zRWRZhhCixmoQQkClUkEAEFWNBUrG1mB9gVDTPT7HZrPB6XR6NVan08FoNAa4osDxpsd1qR+BoNRyXBO8XTYsFovX2y/gvG2YF+MvHFvZeF+3jb4s+768x3N15OXlQYiqO+LteuXL58T5dXjTj7r4GaSE2rS98PY9BHVwPXjwIN577z1MnjwZjz32GP766y9MnDgROp0OY8eOLfc506dPx7Rp08pMz87Oht1uD3TJFZJlGRaLxbMyB1phYSHS09NRYDbArdNWOrZIa0B6ejpycnJKhf5QU9M9Bkp+Ubpz/Hjk/fMLUlWizGZ8+PHH0Ov1Aa4sMKrqcV3rRyAosRzXBF+XjfT0dJwN08IdVvn2CwBswoT09HRYo0zINVU+/vyxGkPJR6BUwVhfto2+vj/A+/eYJ2nQKT0dY8aM8Wq+3q5XvnxOAL71o7CwEB07doQtTIdcl1Rhj32dL5VWm7YXBQUFXo0L6uAqyzI6deqEF154AQDQoUMH7NixA++//36FwXXKlCmYPHmy535+fj5SUlIQFxcHs9lcI3WXR5ZlSJKEuLi4Glm49Ho9MjIyEDHMjkhj5a+nttmRkZGBevXqITIyMuC1BUpN9xgo2WuydPlyZDw8HWZDWKVj8+1FSH95Csxmc8j2uaoe17V+BIISy3FN8GXZOG7JQZ83noGx3xjEiKoDlfWsFRkZGTD1G4MYqfKwdv5YbXg4YqzFFYYqX7aNvrw/wLf3aM3Nx8aMDKyZ9DTiIiv/jocv65UvnxOAb/3Q6/XYtGkTjNc7EVOsqjS41pbPICXUpu2FwWDwalxQB9ekpCS0atWq1LSWLVviu+++q/A5er2+3N8yVSqV4j9USZJqrA5JkkoWaFS8N8EzFv8u/Er36GLVZI/PvZ4sy4g0hCHSWPmHVW3pc2U9rov9CISaXo5rgi/LRoGtyOvtF3DesuTF+AvHVvYcX5ZRX94f4Nt7PFeHWW9ElB/XK18+Jy523pXNn9uCi1Nbthfe1h/UwbVHjx7Ys2dPqWl79+5FamqqQhURERGVJoSA+1Q2LtdGQWzdiyKrHXKRHcJqg3A4AVlAyDIktQqSTgfotdBrVLjb2ACqA8fhTlNBFWOGFOLBg6gmBHVwffDBB9G9e3e88MILGDNmDDZs2IBZs2Zh1qxZSpdGRER1lBACxfuOoGjZetjXbYf9r+1wZ+VibuSlECs3w5ujNLUA/mtKA5ZnIB8ZgFYDTUI9aBomQZtWH+qkWAZZonIEdXDt3LkzfvjhB0yZMgXPPPMMGjVqhJkzZ+Kmm25SujQiIqpDhBBwbN6Fwu+WwPr7argOnyw9QKPGfnsBml5yCfSx0VCFG6EKM0Iy6ACVquTmdkM4iiEcTuRlZeOXtSsxumFLqM7mA8UuuI5nwnU8E/Y1WyAZdNBekgZdi0ZAFV84I6pLgjq4AsDw4cMxfPhwpcsgIqI6KEbSwvb+N8j/cTmKDxz79wGdFsYeHWC8vCMMXdrA3igRgxMTcHDobQjz4hhXZ24MHl48G8NH3oX4yCjIuflwnchE8ZGTcB05CWF3wrltL5zb9iLMZMA9xhSgyA7w+jtUxwV9cCUiIqpprswcyOu3YVVMZxS99ikAQDLqYRraE+Eje8PYsxNU4f8GVEdeXrVfS1KpoI6Ngjo2Cvp2zSFkGa7jmXDuOojivYehstox2ZQKMe93WFs2huGydlDH8Nv3VDcxuBIREf3DdSILtnVb4Tp4HACgk1TQtL0E0XdcjfARvUuF1UCRVCpoGyZB2zAJot9lOL1pO3Yt+QMdtGY4/z4A586D0LVoBEP39gywVOdU68jvxo0bIycnp8z0vLw8NG7c+KKLIiIiqkmurFwUfPs7Cr78X0lolSTgkoa4Km8LIr97DeYbhtZIaL2QpFHD1bQBrrVsQ/HIntA2TQGEgHPXQeTP/gFFS9ZBtil3cR2imlatPa6HDx+G2+0uM93hcODEiRMXXRQREVFNkAussK/MgPPvAyUTVBJ0rZvC0LUtCg0abFvzpbIFnkfERyO8eRO4MnNgX70ZxQeOwbF5F5w7D8BweUfo2zdXukSigPMpuP7000+e///222+lrnDhdruxdOlSpKWl+a04IiKigHDLwKotyP9jE1DsAgBoWzSC8fKOUEf/c5VFW5GCBVZMk1AP4Vf1R/GRk7At3wB39lnYlq6Dc+cBiN4dlS6PKKB8Cq6jR48GUHKVhgsvuarVapGWlobXXnvNb8URERH5WyeNGdrvl0NlKQQAqJPjEda3CzRJcQpX5httajI0t46EY8se2FZmwH0qG/j6d9xjTIFwlf2rKFFt4FNwlWUZANCoUSP89ddfiI2NDUhRRERE/iacxdCt2Y55UW0BSyGEyQhTz07QtW4CSfLmoqfBR1KpYOjYErpmDVG0ZB2K9x/FZFMq8m+agvAPnoY2LVnpEon8qlpfzjp06BBDKxERhYziY6eRP+cH6HYdBgC4m6dC3DcGukubhmxoPZ8qwgTT6L6QBnRFgeyCa9MuHOs9DoU/LFW6NCK/qvbpsJYuXYqlS5ciKyvLsyf2nNmzZ190YURERBdLyDLsa7bAvm4bIATkiDDcenw9Pr5iFLRGPWAtVrpEv5EkCVLzNAz7+m2sGTQOrr/+RuZdT8O+YTvqTbsXko5X4KLQV609rtOmTcPAgQOxdOlSnDlzBmfPni11IyIiUprbUoCCrxbCvnYrIAR0lzZF0ZW9sK7YonRpAXVSdsD86fOIeuAWAIDlo+9wYuR9cJ0+o3BlRBevWntc33//fcydOxe33HKLv+shIiK6aM7dB1H0+1oIhxPQaWEa2B26lo2Rm1s3wpukUaPe43fB0Lk1su55Do6MnTg+8C4kfTYd+nY8bRaFrmrtcXU6nejevbu/ayEiIroowuWC9bfVsP78B4TDCXVyHMxjR0HXsm5eHMc0sAcaLP4I2ktS4T6VjRMj7kXhguVKl0VUbdUKrnfccQe+/DJ4TspMREQEqw0F8xbCuW0vIEkwdGuHiBuGQh0VoXRlitI2qo/6C99HWL/LIGwOZN7xFPLem6d0WUTVUq1DBex2O2bNmoUlS5agbdu20GpLH/A9Y8YMvxRHRETkjY6aCGh//ANumwOSQQ/TiF7QptVXuqygoTaHI/GLF5HzxFuwfPQdcp56B4bDJxD651OguqZawXXbtm1o3749AGDHjh2lHqsNpxUhIqLQodl9GJ9HtoFkc0AdGw3Tlf3q/F7W8khqNeq9MAnq5DjkPvM+7LN/xKvhl0C45aqfTBQkqhVcly/n8TFERKQs4XajaMk6GLbtBSQV3I2SETWyL0/7VAlJkhB9/03QJMYia+J0jDLEQ/y2BmJUP0gatdLlEVWpWse4EhERKUm2O1D4ze9wbtsLAeAV62G4+3ZiaPVSxLWDEPHOY3AIGTh4AoU/LIEodildFlGVqrXHtU+fPpUeErBs2bJqF0RERFQZt6UAhd8thpxjAXRa2Ht3wAdfrsIkHqrmE13fLrgj/298Vq89XIdPovD7JQi/qj8kbbWvTUQUcNVaOs8d33pOcXExtmzZgh07dmDs2LH+qIuIiKgM1+kzKPxuCUSRDVJ4GMKvHoBCDY/RrK61xRZIo3pB/PQnXEdPoXDBMoSP5mEDFLyqFVxff/31cqc//fTTKCwsvKiCiIiIyuM8cAzWn1cAxS6o46IRfvUAqCJMQB25qECgSElxMF09AIXf/g7XoROw/rICphF9IKl5NCEFH78ulTfffDNmz57tz1kSERHBsXk3rD8sBYpd0KQlI+KGoSWhlfxCm5KI8Cv7AWo1ivcdhXXhSgiZe7Ip+Pg1uK5duxYGg8GfsyQiojpMCAHbqk0oWrIWEAK6Ns0QftUASHqd0qXVOtq0+jCN6gOoJBTvOoii39ZACKF0WUSlVOtQgauuuqrUfSEETp06hY0bN+LJJ5/0S2FERFTHyQK2Jevg2LIbAGDo0QGGbu14vvAA0jVJAYb3hvXnFXDu2AdJo4ax/2XsOQWNagXXyMjIUvdVKhWaN2+OZ555BgMHDvRLYUREVHdpIUG9IgOOgycAAGH9u0HfoYWyRdURuuZpEO4rUPS/P+HYshtSmAHGHh2ULosIQDWD65w5c/xdBxERUYliFz4wt4L64AlApYJp2BXQtWisdFV1ir5VE6DYhaLf18C+ZgtUZhPQtIHSZRFVL7iek5GRgV27dgEAWrdujQ4d+BsZERFVn2xzwLhwHXrqoiE0akSM7gdto/pKl1Un6ds1h5xfCPu6bSj6bQ0k7RVKl0RUveCalZWF66+/HitWrEBUVBQAIC8vD3369MG8efMQFxfnzxqJiKgOkK02FMxfBPWZPOTJxTANuYKhVWGGyztCzrfCufMAxKI1aKnmmRxIWdU6q8D999+PgoIC/P3338jNzUVubi527NiB/Px8TJw40d81EhFRLScXFqFg3kLIZ/Igh+lxg2U7REKM0mXVeZIkIWxwD2gaJgLFLnxkbgX3ySyly6I6rFp7XBctWoQlS5agZcuWnmmtWrXCO++8wy9nBZjNZoPD4ahynMVi8Xne3j5HlmWoVN7/zqPX62E0Gn2uhyjUebu+nqPX66HX6/0+72BfB+X8QhR8vQhyXgGkiDDYBnXFvveXKl2WhzfbxupscwPJnzVLajVMo/rC8sUvSMjNR8Ed0xC18H2oIyMutsxqq03LP/mmWsFVlmVotdoy07VaLWSesDhgbDYbGqWmIjM72+vnFBcXA1Wsr/ZiJ1QA0tLSvJqnRlLBJbz/OSfExeHQkSPccFCdUp31NSEuDgcOHfL7vIN5HXTnFaBw/iLIlkKoIsMRPmYwCmTvw34g+bptBLzb5gZSoGpWGfSQRvTEqdnfIXHfUWTe9gSSvn4NkvaivipTLbVp+SffVWuJ69u3LyZNmoSvvvoKycnJAIATJ07gwQcfRL9+/fxaIP3L4XAgMzsbWx59CWZDWKVjj+floOfMp+F2u6ucr9Plggxg/YPPIC4y2qv5ejMWAPLtRWj/4iNwOBzcaFCd4sv6Cvy7rjidTr/OO5jXQfdZCwq+XgRRUARVVAQirhsMlTkcyA2O4FqdbaM329xACmTNUoQJd+bvxM8NusO2chNynnobsdMfuPiifVRbln+qnmoF17fffhsjR45EWloaUlJSAADHjh3DpZdeis8//9yvBVJZZkMYIo1VrKy2Ip/nG6E3ej1fb8YSkXfrazDOO9DcOXklodVqgyomsiS0hgfne/Fl2xgsAlXzLrcVEa9ORsHdz8Py0XfQtW4K883Dq1vmRQnl5Z+qr1rBNSUlBZs2bcKSJUuwe3fJFU1atmyJ/v37+7U4IiKqfdzZuSiY/xtEkR2q2ChEjBkMlYl7w0KFrv9liH50PM6++DGyH34NuktSYejSRumyqI7w6awCy5YtQ6tWrZCfnw9JkjBgwADcf//9uP/++9G5c2e0bt0aK1euDFStREQU4kRWLgrmLYIoskMdH4OI64YwtIag6AdvhWlYL6DYhdO3PQHXKe+P5Sa6GD4F15kzZ+LOO++E2Wwu81hkZCQmTJiAGTNm+K04IiKqPdpqwiEWrICwO6BOikX4dYOhCjMoXRZVg6RSIf7tx6Br2RjurFycHvs4ZHtwHJtMtZtPwXXr1q0YPHhwhY8PHDgQGRkZF10UERHVLsUZO/Gp+VLAUQx1/XhEXDsIKoN3p/6i4KQKD0Pip9OhijbDsXkXsv/7CoQQSpdFtZxPwTUzM7Pc02Cdo9FokO3DqV+IiKj2s63ejPzbpyJcpQHqxyPimoGQ9DqlyyI/0KYlI+GjaYBajcL5v8HywTdKl0S1nE/BtX79+tixY0eFj2/btg1JSUkXXRQREdUORcs34NT1DwFFdqxynoU0/ApIuop3gFDoCevZCfWm3QsAyJn2LuwbtitcEdVmPgXXoUOH4sknn4Tdbi/zmM1mw9SpUzF8uDKnxSAiouBi/X0NTt38KITdCW3vTrgrf6ciJ6ynwIu86xqEX9kPcLlx+s6nIecE15XEqPbwaQvyxBNP4Pvvv8cll1yC++67D82bNwcA7N69G++88w7cbjcef/zxgBRKRESho/B/fyLzzqlAsQumoVdA/8qDcH47U+myKEAkSULcjIfh2L4PxfuPovCh13zbM0bkJZ+Ca0JCAtasWYO7774bU6ZM8RyELUkSBg0ahHfeeQcJCQkBKZSIiEJD4Q9LkXn3s4DbDdOovkh470lYrIVKl0UBpgoPQ8LsZ3Fi0F0oXrUZdxsaKF0S1UI+/80mNTUVv/76K86ePYv9+/dDCIFmzZohOrrqy38SEVHtVjB/EbLunw7IMsLHDEL8G49C0vDwgLpC37Ix4l55CFn3PY/7jSlwHDoJNGCAJf+p9p786OhodO7cGV26dGFoJSIi5H/+C7LuewGQZUTcNAzxb05haK2DIq4bDP11g6CSJOgXrIRcYFW6JKpFeAgKERFdNMvsH5D94EuAEDDfNhpxMx6GpFYrXRYpxPTkXdjpKoSqyA7rzysg3LLSJVEtweBKREQXJe/9r3HmkZKrJkZOuBaxL02GpOLHS10m6XW4v3APhF4L94ks2FdvVrokqiW4ZSEiomo7+8bnyHnybQBA1MSbUO/Z+yFJksJVUTA4JjtgH9YDAGBfvw3FR04qXBHVBgyuRETkMyEEcl74ELnPfQAAiP6/2xDzxASGVirF3SIVuraXAACs//sTclHZ88AT+YLBlYiIfCKEQM4TbyHv9U8BADFP/gcxD9/O0ErlMvbtClW9KAirDdaFKz2n0iSqDgZXIiLymnC7kT35ZVhmlVyTPvbFBxE98SaFq6JgJmk1CB/RC1Cr4Tp4HI5NO5UuiUIYgysREXlFFLuQde/zKPj8F0ClQtybUxA5/iqly6IQoI6LgbFPZwCA7Y+NcGXmKFwRhSoGVyIiqpJwOJF5x1Mo/G4xoFEj4YOpMN8wVOmyKITo27eAtmlDwC2XnCLLWax0SRSCGFyJiKhScpEdp26ZAuuvKyHpdUj85HmEj+6rdFkUYiRJQtjgHpAiwiCfzUfR0nVKl0QhiMGViIgqJBdYcer6h2BbvgFSmAGJX74E08AeSpdFIUplNMA0rBcgSXDu2A/nnsNKl0QhhsGViIjK5c614OQ1D8K+ditUESYkzX8NYT07KV0WhThtSiIMXdoAAIoWr4Gw2hSuiEIJgysREZXhOpmFEyPuhWPTLqhiIpH8wxswdm2rdFlUSxh6tIc6PgbC5oBYukHpciiEMLgSEVEpzn1HcGLo3SjeewTqpDjUX/AW9O2aK10W1SKSWl1yyIBaDRw9jZsMiUqXRCGCwZWIiDzsm3fhxPB74TqRBW3Thqj/63vQtWikdFlUC6ljo2DslQ4AeNTUCO6DxxWuiEIBgysREQEAilb8hZOjJ0HOtUDfvgXq//w2tA0SlC6LajF9x1ZASgKMkhoF/zcDotildEkU5BhciYgIhT8uw6kbH4YossHYqxOSf3gD6thopcuiWk6SJEj9usAiu+Detg9nZ3yidEkU5BhciYjqMCEE8t6dh8w7pwLFLphG9kHSFy9BFR6mdGlUR0jhYXiqcD8A4Ozrn8G+8W+FK6JgxuBKRFRHCbcbZ6bMRM7UdwAA5vFXIWHWVEh6ncKVUV3zP+cZ6Eb0AtxuZN3zHGSeIosqwOBKRFQHyUV2nL7tCeR//D0AoN4z9yJ2+gOQ1GqFK6O6yjT1P1Anx6P40HHPL1NEFwqp4Priiy9CkiQ88MADSpdCRBSyXNlncfLKiShauAqSXoeEj55B1N3XQ5IkpUujOkwVGY74t6YAAPI/WQDr72sUroiCUcgE17/++gsffPAB2rblCbCJiKrLuf8oTgz9T8mFBaLNSPrudYSP6qN0WUQAgLCenRD5nzEAgOwHXoL7zFmFK6JgExLBtbCwEDfddBM+/PBDREfzW65ERNVRtHwDTgyaANfhk9CkJaP+wvd4NSwKOjGP3wVt8zS4s3OR/X+vQQihdEkURDRKF+CNe++9F8OGDUP//v3x3HPPVTrW4XDA4XB47ufn5wMAZFmGLMsBrbMysixDCFGmBpvNBqfT6dU8LBYLVCoVBICqVmMBKD72/PF5eXlebXx0Oh2MRqMXcy6roh4HkhDC997VcI3+VFWPQ7UfvqyH3i6jvvQCKN2PqnpSnT7bPvkJOS98DMgy9J0vRcKc56COi66x3ldr2fBirK/jLxxb2fia2DbW1u15tT6vzi33Oi3i3nkcJwf/B9Zf/kDB90sQfmW/f8eH6HYmEJT43AsUb99D0AfXefPmYdOmTfjrr7+8Gj99+nRMmzatzPTs7GzY7XZ/l+c1WZZhsVg8KxxQErLvHD8eef+Ea2+kp6fjbJgW7jBtpeNswoT09HRYo0zINSkzFgDyJA06padjzJgxVY4FgCizGR9+/DH0er1X489XXo8DrbCwEOnp6SgwG+DWVd6PIq0B6enpyMnJKfXLVSipqseh2A9f10Nvl1FfegH824/c3FwUFxdXuhz71GeVFu+ldkXRcx8CADSjekP91F3IEcVAVlaVdfmLLzX7up2p7jZMYyj5CKzoyN5AbhuDYRsd6O15x44dUajXIFenrrDHQAXbgoQoaO+6GsXvzkf2IzNQ2LwBVP+cVzgUtzOBosTnXqAUFBR4NS6og+uxY8cwadIkLF68GAaDwavnTJkyBZMnT/bcz8/PR0pKCuLi4mA2mwNVapVkWYYkSYiLi/MsXBaLBUuXL0fGw9NhNlR9zsTjlhz0eeMZGPuNQYyofGW1nrUiIyMDpn5jECNV/gEbqLEAYM3Nx8aMDKyZ9DTiIis/zCPfXoT0l6fAbDYjMjKyynlfqLweB5per0dGRgYihtkRaaz8NdU2OzIyMlCvXr1qvb9gUFWPQ7EfvqyHviyjvvQC+LcfMTExcDgclS7H3s5bLrJD9cMS9CtQA5KEmKl3w/yfMYp8CcuXfvi8nanmNkwbHo4Ya3GFoSqg28Yg2EYHcnt+3JKDfm89B91VNsRI+kqDa0XbAvHYBJxcuRnO7fsgTZ+LuE9fgCRJIbmdCRQlPvcCxducF9TBNSMjA1lZWejYsaNnmtvtxp9//om3334bDocD6gtO3aLX68vdE6JSqRT/oUqSVKoOSZIgyzIiDWGINFYdXAtsRSULKSreQ+B5LUDxseePN+uNiKriPXrm/U+fquPCHgfauZ+hT727iPcXDCrrcSj2w5f10JeafenFhfOuajn2Zt6uzBxYFywDLIUolF1I+vhZRI/u70UlgVGtZcOLsb6Ov3BsZc+piW1jbd2eX/h5Vdn8K1yv9DrEv/04jve/A0W/r0HRt4sRcd3gkNzOBFJNf+4Firf1B/W77NevH7Zv344tW7Z4bp06dcJNN92ELVu2lAmtREQEOHbsQ8GX/4NsKQTMJlxj2Qpd705Kl0XkM32rJoj5v9sAAGceewOuU9kKV0RKC+rgGhERgUsvvbTUzWQyoV69erj00kuVLo+IKKgIlxvW31ajaOEqwOWGpnEDSGMGYL+bVyGi0BV1/43Qd2wJOb8QWQ+8xLMM1HFBHVyJiMg7bkshCr76Fc5tewEAhh4dEH5Vf0gG37/oSBRMJI0G8W89Bkmvg23Zeji+Xax0SaSgoD7GtTwrVqxQugQioqBSfOgErL/8AWF3QDLoYRreE9pGDZQui8hvdJekIWbKHch5+l0UPf8RklX8hayuCrngSkREJYTbjaIVf8Hx1w4AgDqhHkyj+kAdGaFwZUT+F/mfMbD+70/Y/9qB6eHNeMhAHcVDBYiIQlCqygDx3VJPaNW3b4GIG4cytFKtJanViHvrMcCgQw9dFLDjgNIlkQIYXImIQogQAo4fluGn6A5A1tmSQwNG90XYgG6QNPwjGtVuuiYpCHtoLABArNkKd553J62n2oPBlYgoRLjzC5F197MofPh1mCQ1kBwH87hR0DVLVbo0ohpjuGU41hdbgGIXihau5CEDdQyDKxFRCChavgHHrhiLwu8WA2oVXrMehjS6N1QRJqVLI6pRkkqFRwv2AloNXMcz4di0U+mSqAYxuBIRBTG5wIqsyS/j1Jj/wn0yC5q0+jB/9RLesx2HFOJXyiGqrmOyA1KPdgAA258ZcOdaFK6Iagq3ekREQaroj4041nMsCj77GQAQede1SPljLrQdWihcGVEQaN0EmtRkwOWGdeFKCFlWuiKqAQyuRERBRhRYceb/XsOpax6E63gmNGnJSP7xTcQ+PxGqMIPS5REFBUmSYBrcA9Bp4T6ZDcfGv5UuiWoAgysRURBx/PIHbCMfQMGnPwEAzOOvQsqKuTD26KBwZUTBR2UOR1ifLgAA26rNcJ/JU7YgCjgGVyKiICDyCjDX3BrWya9BnMmDtmlDJP/4JuJefBAqk1Hp8oiClq5NM2ga1QfcPGSgLmBwJSJSkHC5YFu9GeKrRbhcFw3otNDeex3qL/uYe1mJvCBJEkyDekDS6+A+fQb2DTuULokCiGerJiJSgBACxfuOwPbHRsj/nER9pfMshi/+Gq7EepD0OoUrJAodqggTjP26oujXlbCv3gxdkwZQx8UoXRYFAPe4EhHVMFfmGRR+vQjWBcsh5xVAMhkhDeqG2/L/hjo1WenyiEKSrlUTaJumALIM668rIdw8ZKA24h5Xqh6rDcWWE3Dn5kMUWiEXFkG22iGcxUBxMYTLDUgSjLIbC6LaQ/O/1Sg0hUEKM0AVHgZVhAmqyHCoYyIhhYdBkiSl3xFRwMmFRbCt3ATnjn0lEzRqGDq1hqFrW+S7i5UtjijESZKEsAHdkX/8R7izcmFfvw3ocInSZZGfMbhSlYTLBdfxTLiOZ8Fw9AQyYi6D7qvfUejFc9UAWmvCgVNnUOHHslYDTXw9yHGRGKqLhfvYaYjISIZZqjVkuwOOjX/DvvFvoNgFANC1bAxjz3SozOElg2wMrkQXSxUehrD+l8H6yx+wr90CqUGc0iWRnzG4UrnkIjuK9x6G88AxuI6eAlxuACULTKRKAyFJUEeboY6JhMpsgio8rOTPnTodJJ0GUKsBANmWPNw77yPMGn0rzBodZKutZO9sgRVyXkHJsX3FLrhOZAInMvGmuQXy+t6J/JhIGNJbwdirM8L6doG2aUMGWQo5RqggNu5E/pY9EHYnAECdFIewvl2gSY5XuDqi2knbohG0ew+jeO8RiCXroQU/O2oTBlf6l9sN566DcOzYD9eRk4AQnoek8DBoGyYhPzIMY379FN9OfgoxsbFVz9KkwZ/FZyE3aQB9dNkD5YVbhnw2H67TZ1B0/BS2btqMdmHRkHMtKFq8FkWL1yIHgKZBAox9uiCsd2cYe3eG+txeKqIgJNsdsM1ZgOUxnSDWbQcAqOpFwdijA7SXpPKXMKIAkiQJYf27If/YaYgcC+4LS1G6JPIjBleCVGjD/4WlQvvV77D+s1cIANQJ9aBrngZt4wZQxUZDkiTk5p7Bzp+tgNo/3+uT1CqoY6Ogjo2CvUkyrl4+F7l7smA8ngXb2q2wLd8A27ptcB3PRMFnP5dc+lKrQVjvzjCN6A3T4Muhjjb7pRaiiyVbbcj/7GfkvTsP7lPZiFXpgMhwhPXoCF3LRpBU/D4sUU1QmYwIG9Ad1p+WY4IxBa5te4GeXZQui/yAwbUOc+daYF+/HWE792NCWApgd0IKD4O+zSXQtWoMdUykInVJei0M6a1hSG+N6PtuhGy1eUJs0bL1KN5/1LM3NlujhvHyjggf2RvGoT0VqZfInVcAy8ffwTLrW8i5FgCAKjEWU/atxQt3PwZ9OP9CQFTTdM3TYG3WEJp9R1H4yEzELJ8DlUGvdFl0kRhc6yC3pQD2VZvh3HkAACABWOfMQ/rQAYhr1yro9gqpTEaY+l8GU//LAADOPYdQ+MsfsP68As6/D8C24i/YVvwFPDoT6l4dUXTLKJj6d4Ok5eJNgeU6fQZ573+N/LkLIKw2AIAmrT6i778R7kHd8HViPKb76a8TROQ7qWdHZO3Zj7j9x3D25dmo99TdSpdEF4mf7HWIbHfAvmYLHFt2A/+c307bNAWWlqm4ec6L2Jk2NuhCa3l0zRshpnkjxPx3HJwHjsL68x8o/GEJnDsPwr14PTIXr4c6LhrhV/VHxJjB0LVpxmMKya+Kt+5F5leLULhgmeeLi7rWTRA16WaEj+gNSaNBXl6eskUSESSjHk8W7sf75lbIe2ceTEOugKHzpUqXRReBwbUOEELAuWMfbH9shLA5AACahkkw9uoETWIszuaeUbjC6tM1aQjdA7cg+oFbYNu+F1lzvoe8cA3c2Wdh+eAbWD74BrpWjRFx3RCEXz0AmoR6SpdMIUq4ZYi9R/BNZFvkX/Nfz3RD17aImngTwgZ04y9IREFoiTMXutF94PxxObLufwENls+ByshDBkIVg2ttdzYfBb+ugftkNoCSbzaH9ekCbaP6Chfmf/rWTaF/eBzipk+G/Y+NKPh6EayLVsG58yBypr6DnGfeR1j/y2C+cSjCBnTnoQTkFTm/EI7t++DYtheisAgdtGZAq0H4lf0Rddc10LdrrnSJRFQF0xN3wb12G4oPHEPuC7MQ++z9SpdE1cRP7tpKlnG3sQG0P/wBtywDWg2MPTpA37EVpFp+zJ2k1cA0sDtMA7vDnVeAwgXLUPD1Ijj+2oGi31aj6LfVJYcSXDsI5huHQte8kdIlU5ARbhnFB4/BsW0vXAeP//tAmAFvZO/B09v+QExTLjdEoUIVGY641x/B6RsfhuWDb2Aa2hPGbu2ULouqoXYnmDrKnWuB8edV+K8pDZIsQ9u4ASLHXwVD50trfWi9kDoqApFjR6HBr+8hZc3niLr/RqjjYkoOJXh3Ho5dfiuOD56A/E9/gjvfm2uBUW3mzrXAtjIDlg/mw/rjMk9o1aQkwjSsJ6Sxw/GW7RhUsdEKV0pEvjIN6IaIG4cBQiBr4nTI/3yhkkIL97jWIueOZS1auh7qYhfy5GKE9+mKqM5teewdAF2zVNR76m7ETLkTRcvWo+DL/8H6+xo4MnYiO2MnzjzxJkwjesN84zAYurULiS+q0cWTc/JwqyEJ8vzfkZ911jNdCjNAd2lT6NteAnV0yanhbLYipcokIj+o9+x9KFrxF1yHTyDn2fcR9+KDSpdEPmJwrSWEsxjW39egeNdBAIArqR6G/b0Qy5tdw9B6AUmrgWlQD5gG9YArKxeF3/6O/C//h+I9h1E4/zcUzv8NmrRkmK8fiojrB0NTP0HpksnP5MIiWH9fg8LvFqNo6To8Fd4EyDoLSBK0jepDd2nTkssM/3PpYiKqHdTmcMTPfASnxvwX+R9/j/DhvWC8vKPSZZEPGFxrAXdOHgoXLIOcYwFUEoyXd0R2kyRkbl+gdGlBTxMfg6h7rkfk3dfBsWknCr78FQXfL4Hr8EnkvvgRcl/6GMbenWG+cRhMQy6HpNcpXTJVk1xghfX3NbD+tBxFS9dDOP69StzW4gK079sT5jbNoTIZFaySiAItrE8XmMeOQv4nC5A16UWk/DEXqvAwpcsiLzG4hjjn3sOw/roSKHZBCg9D+Ije0DRIAEL4FFdKkCTJc7Wues/eD+svK5D/5a+wr95cctnZ5RugijYj4uoBiLhxGPRtmildMnnBfeYsrIvXwvrrStiWbygVVrVNUhA+qi/EwK64ulNbHGx3B1RGhlaiuqDe0/egaNl6uI6eQs7UdxD32v8pXRJ5icE1AGw2GxwOR6lpQggUFhZCr9d7/nRvsViq/RpCCNjXbYV91WYA/3x5ZERv7i3yA1WYAZoRvWAaeBkMR07B8f1SOL5fCvn0GVg++g6Wj76DulVj6K/sB8flbZUut1rKW0YrotfrYQyCQOdNzUIIuPcfQ/GyDXAsXQ/3lj2AEJ7HVY3rQz/4cuiG9IC6eRokSbqo9TAQLBYLXC5XqW1FeWOIyHvlrTNhL9yP/FseR/6nP0H07ABdr06QZRkqL7/fECzbxrqGwdXPbDYbGqWmIjM7u9R0lUqF9PR0ZGRkQJblUo8VFxcDviz7Ljes//vTczyrvmNLGPt04ZeJ/KS8n6EKQA9tFK4xJGCArh50Ow+iaOdByELgi8g2cG3dA7ltS6jCDMoV7qWKltGKJMTF4dCRI4puoCurOUJSo5s2Cj20UbhCF4WG6tJ17nAVYpkzF4scZ7B3wypgw9fAM2Vfw+f10M/sxU6oADRp0qTCbcWFlK6ZKNidW6/S0tLKffxxUyPcZqyPA7c/jmFnN6EAMlyi8vXunGDYNtZFDK5+5nA4kJmdjS2PvgSz4d9jZgSAArMBEcPsOLcP5XheDnrOfBput9vr+UdIamgWrUXx6RxAJSGsfzeeAN3PKvoZniNsDmDfUYi9R6A6nYOu2khg5RZYVm2FJjUJukvSoG2SErTHTFX1/s6Xby9C+xcfgcPhUHTjfH7NEVoDkJkDcew0cDQTyMottVcVKhXsidF4Ye96PHjr7WibnIS2AB6oYN7VWQ8DwelyQQawbtLTMKQkldpWXChYaiYKdufWq/UPPoO4yLKnsRMuF8TXixF/Nh9/th+BNpt/qHDs+YJl21gXMbgGiNkQhkhj6eDq1mkRaVR5PozyfTy1jmS1Y15kW6hO50DS62Aa3Rfahkn+K5pKufBn6GEMA7pGA13b4fjRo3hz9kd4JLU9VGcscB0+CdfhkwAAdVIctE0bQte0IVT1Imu4+qpV+P6CjHAWo3jLHow31kf4kgyIE1lAsavUGFVMJLSpydCkJUPbMAnHCy34ctsCPBETXeV79HU9DLQIvRFanb7UtuJCwVYzUbCL0Bsr3Ba4RvRCwee/wHgsG6P18ZWOJeUxuIYId64Fxl9WobnGBBGmR8S1g6GJj1G6rDpPhIfhY9sJ/Hf0A4iFBs49h1C8/yjcp87AfSob7lPZsK/MgCoqAnJKAvrrYiAXWIGoKKVLD1puSwHsG3bAvmE77Ou3wbF5F4TdiSmmRsA/vxRIRj00qcnQpiVDm5oMlTlc4aqJKFRpEmJh6NEB9pWb8LSpMVBQBETz8zVYMbiGANepbBR+txgqmwMHXUVoMGIAQ2sQUkebYbysHYyXtYNcWITi/Ufh3H8UrqOnIOcVAHkFeN/cCmc73whbx1Yw9u5cchneDqFxbGwgaCHBtWM/8g+ehGPrHtj/2gHn7kOl//QPQIqOwJLTh9G/Tx+EN02FOr4ez09MRH5j6NIG1j2HEJ51FvIfmyBuSub3RoIUg2uQKz50HIULlgPFLrhjI3H9nnVYFXGD0mVRFVThYdC3bwF9+xYQDieKj56C9cBRHNqyHY1ghP2vHbD/tQNnX5kDaNTQt7kEhs6Xlty6XAp1UlytC2ayzQ73mTy4z5yFOysX8qlsbK3XDZYry165Rtu4AQxd2pTcLmsLa6wZE2JicLDjPdDwT3hE5GeSSgV7rw7A/MUwnc6BY+PfMHRpo3RZVA4G1yDm3HcE1p+WA7KAJi0ZhT3bIXf3/5Qui3wk6XXQNUuFrUEcBiyfizPbd0O7eQ+K/siAfd1WuDNz4Ni8C47Nu2CZ9Q0AQBUbBX2rJtC1bgpdqybQt24K3SWpQX8BBOFyo4FKD3H0NOxFDshn8z1hVZRzXXCdpIIUGQ5D+xbQt20OfXorGDpfWuYvCkV5eTX0DoiorhJmE6YXHsTzEc1gW7UJ2kb1oY7jXzeDDYNrkHLuPQLrzyWhVduiEUxDr0Ce5WzVT6Sgp26QAPOlzWG+ZSSEEHAdzyzZA7thO+wbtsP59wHIZ/Jg+zMDtj8z/n2iSgVN/Xho05KhSasPbWoytGn1oakfD3VcNNRxMQE95EC43XDnWiAfOIainUcgnzoD16ksuE5mw3UiC64jJ1F89BRWxHSG+OkPlI2pgCoyHOrYaKhjo+GIDkfPL9/A9r2nEB1d+Td4iYhqwteOTDzb6nKojmXC+r8/EXHzCEgaXvo5mDC4BiHn3sOw/rwCkAV0LRsjbOgVPNamlpIkCdqURGhTEhFxVX8AgFxkh3PPITj/PgDn3/vh2Fnyr2wphOvYabiOnQZWbip/fiYj1HExUMdFQxUeBpXJCCnMCJXJCFW4EZJeB7vDgfuNKRAbdsCm/WcPrixDFLsAlxui2FVyiphiF2SrDYuj05Hb+UbkWAo9x56WF0rPcQgZ+npR0MZEQhVlhjo2qiSs1ouCpNN6xjltRTghO2rdIRFEFNpcV7SH/ocVcGefhW31JoT16qx0SXQeBtcg49xzGNZfVjC01mGqMAMMHVrC0KGlZ5oQAu6sXBQfPgHX4ZMoPnyi5HbkFNynz8CdlQvhcEJYbXBZT8B1+ESlrzHJlAqx4W/YvainkdoIkVfw74QIE7QNEqBNjoc6OQ6a5DhoEuOgSU2CrV4E4lo3x4H730I4j0UlolAUZkDYoB6w/rgMjg07oG2cAm1KotJV0T8YXIOIc88/e1oFQyuVJkkSNAn1oEmoB3Qte5lZIQTkAivc2blwZ52F+8xZyFYbRJEdsrXon39tEHYnHA47Zn88Gzd1vhw6tQYQApJaDWjVkDQaSBpNyf+1GthUwHVfvoeFa1YiKrUBpMhwZJ/NRXx8fLmXRXTm5UGUmUpEFFp0zVJR3KYZnNv3oejXlTCPGxX03zGoKxhcgwRDK10MSZKgNodDbQ4HmjSsdGxeXh6mvvk4bun9AExV7BW124qw0ZUPTbOG0ERFVXkJUiKi2iKsb9eS0xlaClG0ZB1Mw3oqXRKh5BLspDDpWCasv/xRElpbNWFoJSIiUpik08I0tCcgSXDuPADHzgNKl0RgcFVcusYMzZK/AFmGtnkawoZcztBKREQUBDQNEmDo1g4AULR4LdznH+9PimBCUpAqx4IPza0gud3QNKoP07CeDK1ERERBxNCtHdT14wFnMay//AHh5iFTSmJKUog71wLDonUwqzSQE+shfFTfki/IEBERUdCQVCqYhvWCpNfBfSob9jWblS6pTmNwVYCcX4iC+b9BZXfib1chXAO7QtLye3JERETBSB0ZjrCB3QEA9nXbIE5kKVxR3cXgWsPkIjsK5v8GUWCFHGnCbZYdwHknZSciIqLgo2vRCLo2zQAAYvE6RErc4aQEBtea5CyG9fvFkM/mQ2U2wTa4G3KFS+mqiIiIyAthfbtCFW0GCm14PrwphOCZq2sag2sNEbIM6dulcJ86A8moR/i1gyDCjUqXRURERF6SdFqYhvcCVCoM1sfC8eWvSpdU5zC41gAhBGxL10PaexTQqBF+ZT+oYyKVLouIiIh8pEmMhdS95AqG1uc/gmPbXoUrqlsYXGuAY8N2OLfshgAQNqwnNPUTlC6JiIiIqqvdJVjiyAGKXci8YyrkAqvSFdUZDK4B5th5ALY/MwAAYnB36C5JU7YgIiIiuiiSJOGRwn1QJceh+NBxZE9+mce71hAG1wAqPnISRQtXAQD0nVoDl12qcEVERETkDxbhQvjMhwGNGoU/LkP+pz8pXVKdwOAaIOJMHgp/XOa5lKuhd2elSyIiIiI/0nZogXpPTAAA5Dz+Jhw79itcUe3H4BoAiSodxC9/As5iaBokwDT0CkiSpHRZRERE5GeRd1+HsAHdIBxOZI5/EnJhkdIl1WoMrn4mF1jxobk1UGiDKiYSptH9IGl4kmIiIqLaSFKpEP/241Anx6P4II93DTQGVz8SzmIU3jcdLTUmIMyA8GsGQGXUK10WERERBZA6JhIJs6YCajUKf1iK/I++U7qkWovB1Y9cJ7PhOnAMVuGGNPwKqCMjlC6JiIiIaoCxa1vUe/oeAMCZp96Gbf02hSuqnRhc/UiblozIb17FhPydkOJjlC6HiIiIalDkhGsRProv4HIjc/xTcGXmKF1SrcPg6mfqpDisK7YoXQYRERHVMEmSEPf6I9A2T4M7MweZd06FKHYpXVatwuBKRERE5Ceq8DAkzn0eUngY7Gu3IufZ95UuqVYJ6uA6ffp0dO7cGREREYiPj8fo0aOxZ88epcsiIiIiqpCuaUPEv/04AMDy3tcoXLBc4Ypqj6AOrn/88QfuvfderFu3DosXL0ZxcTEGDhwIq5XXBCYiIqLgFT6sJ6LuvwkAkDVxOpx7DilcUe0Q1CcYXbRoUan7c+fORXx8PDIyMtCzZ0+FqiIiIiKqWsxjd8CxZRdsKzfh1M1T0OD3WVBHm5UuK6QFdXC9kMVS8qWnmJiKv7HvcDjgcDg89/Pz8wEAsixDluXAFghACAGVSgUB4PzTD4vzbudPK29shfP2YXwwjK3uvPPy8rw6ebMsy1Cp/v2jgRACBQUF0Ol05V6p7MLxFbFYLIHtnRA1sixWWEcFy2i5Y1H6Z1JVj6vVOy/64UvNpebtSx1BVnNlz6nJ9aoqOp0ORqOxynHVWe5q4uft7z4HzTIaijV7uW0M1LIUkJpVKsR9MBUnB02A6/AJHB/7GCI+fhqSRl3p/L1dr2RZ9ukzxWazwel0ejXWlzr8wdv3EDLBVZZlPPDAA+jRowcuvfTSCsdNnz4d06ZNKzM9Ozsbdrs9kCUCAAoLC5Geno4CswFundYzXQAoNJS0+9zHvU2YkJ6eDmuUCbkmbdmZXcCX8cEw1tfxeZIGndLTMWbMmCrnCwAqSJDP27xIkoSmTZti//795X5AXzi+Munp6TgbpoU7zH/9KNIakJ6ejpycnFK/XNW0ipbR8lz4M6mqx4D3vfOlH77UDARuma6pmjUXbCsupuaLXa+qEmU248OPP4ZeX/nFVnzpR01tG/3ZZ27Py47t2LEjHOF65EJbYY8B37eNgVqWArk9F69Mgv3GKTCs3YovLxuBT+u5Kx3v7XolyzIsFosnzFfG4XDgzvHjkffPDj1veFuHPxQUFHg1LmSC67333osdO3Zg1apVlY6bMmUKJk+e7Lmfn5+PlJQUxMXFwWwO/O55vV6PjIwMRAyzI9J43t7Af/6NsRZ7VmDrWSsyMjJg6jcGMVLVC4Uv44NhrM/zzs3HxowMrJn0NOIioysde9ySgz5vPFNqrABQYDYg4pJuZTaS5Y2vat7GfmMQIyrfePny/tQ2OzIyMlCvXj1ERkZWOjaQKlpGy3Phz6SyHgO+9c6XfvhSMxC4ZbqmataGh5faVlxMzRe7XlUm316E9JenwGw2+7UfNbVt9GufuT0vM3bTpk3QX+VAjFTxLweA79vGQC1LgdyeW/R6TLDsxrsRLTAkX4Mh6ZdBat2k3LG+rFeyLJecgisursrgarFYsHT5cmQ8PB1mQ1iVNftShz8YDAavxoVEcL3vvvvwyy+/4M8//0SDBg0qHavX68v9zUClUvn056/qkiSpZEFC2RVVOu927n5FY8udtw/jg2Fsdedt1hsRZax8pSqwFZUZKwDIOi2ijKoyr1Xe+KrmHbDeSVKNLIsV1lHJMlpmLEr/TCrrMVDN3nnRD19qLjVvX+oIspore15Nrlde1eznftTkttHffQ6aZTTIaq5svK/bxkAtS4HcnkuShN8dZyD1vxRi/Q7gj00wJcZB2yDRL/P2JuOc61ukIQyRfl6//cHb1wjqswoIIXDffffhhx9+wLJly9CoUSOlSyIiIiKqnk6toG2eBsgyrAuWw20pVLqikBPUwfXee+/F559/ji+//BIRERE4ffo0Tp8+DZvNpnRpRERERD6RJAmmwZdDHR8DUWSH9YelEM5ipcsKKUEdXN977z1YLBb07t0bSUlJntvXX3+tdGlEREREPpN0WoRf2Q9SmAHu7FwU/rwCQsEzzYSaoA6u506/c+Ft3LhxSpdGREREVC0qczjCr+oPaNRwHTyOoiXrvDpdHQV5cCUiIiKqjTRJcTAN7wUAcG7dA8dfOxSuKDQwuBIREREpQNcsFca+XQAAtj828rKwXmBwJSIiIlKIIb019B1bAgCs/1sJcSpb4YqCG4MrERERkYKMfbpA27Qh4HZD/G8VUlXenYy/LmJwJSIiIlKQpFLBNKwn1ImxgN2JOZGXQs7KVbqsoMTgSkRERKQwSactOdNAZDgaqg3Iv30q3HkFSpcVdBhciYiIiIKAymSENLIXMt0OuPccxukbH4Zs5UWXzsfgSkRERBQkpMhw3Jb/NySzCfa/duD07U/y6lrnYXAlIiIiCiJ73UWI+HAqJKMetmXrkXX/C7y61j8YXImIiIiCjLZjSyTOeR7QalD4/RKceXQmr64FBlciIiKioBTWryvi33kckCTkz/kBuc++X+fDK4MrERERUZCKuLI/Yl+eDADIe+tL5D4/q06HVwZXIiIioiAWOW40Yl+YBADIe+NznH3x4zobXhlciYiIiIJc5J3XoN5zEwEAZ2d8grOvzFG4ImVolC6AiIiIiKoWNeFaQMjIefJtnH1lDoQE4JahSpdVo7jHlYiIiChERP3nOtSbdi8AIO/lOXB+8J3CFdUsBlciIiKiEBJ1z/WIeeo/AIDit+ch97m684UtBlciIiKiEBN9/02ImXo3AMDy1hc488iMOnGRAgZXIiIiohAUec/10D111z/nef0RWfc+B1HsUrqsgGJwJSIiIgpR2msHIO7dJwCNGoXfLsbp25+EbHcoXVbAMLgSERERhbDwq/oj8ZPnIRl0KFq0CqdueBhyYZHSZQUEgysRERFRiDMN7IGkea9CMhlhX7UJJ0dPhOv0GaXL8jsGVyIiIqJawNijA5J/eAOqepFwbN2DE0P+A+fuQ0qX5VcMrkRERES1hKFDSzRY+AG0jRvAdTwTJ4bejaI/Nypdlt8wuBIRERHVItpG9VF/4fswdG0LucCKU9c9BPt3S5Quyy8YXImIiIhqGXVMJJK+nYHwK/sBLjesj76BSWENQ/5CBQyuRERERLWQyqBH/PtPIeqBWwAA94c1hFi0BsJZrHBl1cfgSkRERFRLSSoV6j1+F0wv3A+nkIEDx5H/xS9wn7UoXVq1MLgSERER1XKGawfiJst2IMwA+UweCj77BcUHjyldls80ShdAVNdYLN7/livLMlQq736/9HasL69fE7yphzUT1X7erjNct6pvs6sA0nUDofptHdwns1D43RIYLu8Iw2VtIUmS0uV5hcGVqIbYi51QAUhLS/P6ORpJBZeQ/T4WAIqLiwGj18P9rjr9YM1EtU911iuA61Z1SSYjIq4fDNuyDXBs2Q37qk1wnz6DsCGXQ2XQK11elRhciWqI0+WCDGD9g88gLjK6yvHH83LQc+bTXo2vzli32+1L+X7nSz9YM1HtVd1tI9et6pPUaoQN6AZ1Qj0ULVmL4v1HkT93AcKH94KmQYLS5VWKwZWohkXojYg0hlU5Lt9W5PX46owNFqyZiADft4108fRtL4E6PgbWn1dAzitAwbyFMHRvD8NlbZUurUL8chYRERFRHaVJjIV57CjoWjUBhIB99WYUzv8NojA4f0FgcCUiIiKqwySdFqZhPRE29ApAq4Hr2GmIr35DP12M0qWVweBKRERERNC3bgrz2JFQJ9QDHE5MNTWGsDuULqsUBlciIiIiAgCooyMRcdMwoH1zTC7YCynIzjTA4EpEREREHpJaDdXl7bHRla90KWUwuBIRERFRSGBwJSIiIqKQwOBKRERERCGBwZWIiIiIQgKDKxERERGFBAZXIiIiIgoJDK5EREREFBIYXImIiIgoJDC4EhEREVFIYHAlIiIiopDA4EpEREREIYHBlYiIiIhCAoMrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikMDgSkREREQhgcGViIiIiEICgysRERERhQQGVyIiIiIKCQyuRERERBQSGFyJiIiIKCQwuBIRERFRSAiJ4PrOO+8gLS0NBoMBXbt2xYYNG5QuiYiIiIhqWNAH16+//hqTJ0/G1KlTsWnTJrRr1w6DBg1CVlaW0qURERERUQ0K+uA6Y8YM3HnnnbjtttvQqlUrvP/++wgLC8Ps2bOVLo2IiIiIapBG6QIq43Q6kZGRgSlTpnimqVQq9O/fH2vXri33OQ6HAw6Hw3PfYrEAAPLy8iDLcmAL/uf1JEnCCUsu8u02z3QBoNBtgDXfDumfaScLzkKSJJzKPwsnRJXz9mV8MIyt6TrK67ESdfhjbLDUceHYynocLDUHSx0XU7M+X19hj4Op5gKHDZIk4dixY55tbUXy8/PL3Tb6o47qvkel+hzIeQdbzdmFFmhd6gp7XFN1+HusL8s+4Nvy78u8hRA4e/Ys7HY7JKmyLvtWw/l1ePP+/CE/Px9AyXuqlAhiJ06cEADEmjVrSk3/v//7P9GlS5dynzN16lSBkgzDG2+88cYbb7zxxlsI3Y4dO1ZpNgzqPa7VMWXKFEyePNlzX5Zl5Obmol69elX+NhJI+fn5SElJwbFjx2A2mxWrozZjjwOPPQ489rhmsM+Bxx4HXm3qsRACBQUFSE5OrnRcUAfX2NhYqNVqZGZmlpqemZmJxMTEcp+j1+uh1+tLTYuKigpUiT4zm80hv3AFO/Y48NjjwGOPawb7HHjsceDVlh5HRkZWOSaov5yl0+mQnp6OpUuXeqbJsoylS5eiW7duClZGRERERDUtqPe4AsDkyZMxduxYdOrUCV26dMHMmTNhtVpx2223KV0aEREREdWgoA+u1113HbKzs/HUU0/h9OnTaN++PRYtWoSEhASlS/OJXq/H1KlTyxzGQP7DHgceexx47HHNYJ8Djz0OvLrYY0mIqs47QERERESkvKA+xpWIiIiI6BwGVyIiIiIKCQyuRERERBQSGFyJiIiIKCQwuFbTO++8g7S0NBgMBnTt2hUbNmyocOzff/+Nq6++GmlpaZAkCTNnziwz5umnn4YkSaVuLVq0COA7CH6+9PjDDz/EFVdcgejoaERHR6N///5lxgsh8NRTTyEpKQlGoxH9+/fHvn37Av02gp6/+zxu3Lgyy/LgwYMD/TaCmi89/v7779GpUydERUXBZDKhffv2+Oyzz0qN4bJclr97zOW4LF96fL558+ZBkiSMHj261HQux+Xzd59r3bJc6QVhqVzz5s0TOp1OzJ49W/z999/izjvvFFFRUSIzM7Pc8Rs2bBAPPfSQ+Oqrr0RiYqJ4/fXXy4yZOnWqaN26tTh16pTnlp2dHeB3Erx87fGNN94o3nnnHbF582axa9cuMW7cOBEZGSmOHz/uGfPiiy+KyMhI8eOPP4qtW7eKkSNHikaNGgmbzVZTbyvoBKLPY8eOFYMHDy61LOfm5tbUWwo6vvZ4+fLl4vvvvxc7d+4U+/fvFzNnzhRqtVosWrTIM4bLcmmB6DGX49J87fE5hw4dEvXr1xdXXHGFGDVqVKnHuByXFYg+17ZlmcG1Grp06SLuvfdez3232y2Sk5PF9OnTq3xuampqhcG1Xbt2fqwytF1Mj4UQwuVyiYiICPHJJ58IIYSQZVkkJiaKV155xTMmLy9P6PV68dVXX/m3+BDi7z4LUbKRvHDDWZddbI+FEKJDhw7iiSeeEEJwWS6Pv3ssBJfjC1Wnxy6XS3Tv3l189NFHZfrJ5bh8/u6zELVvWeahAj5yOp3IyMhA//79PdNUKhX69++PtWvXXtS89+3bh+TkZDRu3Bg33XQTjh49erHlhiR/9LioqAjFxcWIiYkBABw6dAinT58uNc/IyEh07dr1on9uoSoQfT5nxYoViI+PR/PmzXH33XcjJyfHr7WHiovtsRACS5cuxZ49e9CzZ08AXJYvFIgen8PluER1e/zMM88gPj4e48ePL/MYl+OyAtHnc2rTshz0V84KNmfOnIHb7S5z5a6EhATs3r272vPt2rUr5s6di+bNm+PUqVOYNm0arrjiCuzYsQMREREXW3ZI8UePH3nkESQnJ3s2AKdPn/bM48J5nnusrglEnwFg8ODBuOqqq9CoUSMcOHAAjz32GIYMGYK1a9dCrVb79T0Eu+r22GKxoH79+nA4HFCr1Xj33XcxYMAAAFyWLxSIHgNcjs9XnR6vWrUKH3/8MbZs2VLu41yOywpEn4HatywzuAaJIUOGeP7ftm1bdO3aFampqZg/f36lv0VRWS+++CLmzZuHFStWwGAwKF1OrVVRn6+//nrP/9u0aYO2bduiSZMmWLFiBfr166dEqSEnIiICW7ZsQWFhIZYuXYrJkyejcePG6N27t9Kl1RpV9ZjLcfUVFBTglltuwYcffojY2Fily6m1vO1zbVuWGVx9FBsbC7VajczMzFLTMzMzkZiY6LfXiYqKwiWXXIL9+/f7bZ6h4mJ6/Oqrr+LFF1/EkiVL0LZtW8/0c8/LzMxEUlJSqXm2b9/ef8WHkED0uTyNGzdGbGws9u/fH5IbyYtR3R6rVCo0bdoUANC+fXvs2rUL06dPR+/evbksXyAQPS4Pl2Pve3zgwAEcPnwYI0aM8EyTZRkAoNFosGfPHi7H5QhEn5s0aVLmeaG+LPMYVx/pdDqkp6dj6dKlnmmyLGPp0qXo1q2b316nsLAQBw4cKLVC1xXV7fHLL7+MZ599FosWLUKnTp1KPdaoUSMkJiaWmmd+fj7Wr1/v159bKAlEn8tz/Phx5OTkcFn+R3W2F7Isw+FwAOCyfKFA9Lg8XI6973GLFi2wfft2bNmyxXMbOXIk+vTpgy1btiAlJYXLcTkC0efyhPyyrPS3w0LRvHnzhF6vF3PnzhU7d+4Ud911l4iKihKnT58WQghxyy23iEcffdQz3uFwiM2bN4vNmzeLpKQk8dBDD4nNmzeLffv2ecb897//FStWrBCHDh0Sq1evFv379xexsbEiKyurxt9fMPC1xy+++KLQ6XTi22+/LXXKj4KCglJjoqKixIIFC8S2bdvEqFGjeOoVP/e5oKBAPPTQQ2Lt2rXi0KFDYsmSJaJjx46iWbNmwm63K/IeleZrj1944QXx+++/iwMHDoidO3eKV199VWg0GvHhhx96xnBZLs3fPeZyXJavPb5Qed9s53Jclr/7XBuXZQbXanrrrbdEw4YNhU6nE126dBHr1q3zPNarVy8xduxYz/1Dhw4JAGVuvXr18oy57rrrRFJSktDpdKJ+/friuuuuE/v376/BdxR8fOlxampquT2eOnWqZ4wsy+LJJ58UCQkJQq/Xi379+ok9e/bU4DsKTv7sc1FRkRg4cKCIi4sTWq1WpKamijvvvNOz0a2rfOnx448/Lpo2bSoMBoOIjo4W3bp1E/PmzSs1Py7LZfmzx1yOy+dLjy9UXnDlclw+f/a5Ni7LkhBCKLCjl4iIiIjIJzzGlYiIiIhCAoMrEREREYUEBlciIiIiCgkMrkREREQUEhhciYiIiCgkMLgSERERUUhgcCUiIiKikMDgSkREREQhgcGViKiGSJKEH3/8UekyiIhCFoMrEdFFGjduHCRJgiRJ0Gq1SEhIwIABAzB79mzIsuwZd+rUKQwZMsSreTLkEhGVxeBKROQHgwcPxqlTp3D48GEsXLgQffr0waRJkzB8+HC4XC4AQGJiIvR6vcKVEhGFLgZXIiI/0Ov1SExMRP369dGxY0c89thjWLBgARYuXIi5c+cCKL0X1el04r777kNSUhIMBgNSU1Mxffp0AEBaWhoA4Morr4QkSZ77Bw4cwKhRo5CQkIDw8HB07twZS5YsKVVHWloaXnjhBdx+++2IiIhAw4YNMWvWrFJjjh8/jhtuuAExMTEwmUzo1KkT1q9f73l8wYIF6NixIwwGAxo3boxp06Z5wjcRkZIYXImIAqRv375o164dvv/++zKPvfnmm/jpp58wf/587NmzB1988YUnoP71118AgDlz5uDUqVOe+4WFhRg6dCiWLl2KzZs3Y/DgwRgxYgSOHj1aat6vvfYaOnXqhM2bN+Oee+7B3XffjT179njm0atXL5w4cQI//fQTtm7diocffthzSMPKlStx6623YtKkSdi5cyc++OADzJ07F88//3yg2kRE5DWN0gUQEdVmLVq0wLZt28pMP3r0KJo1a4bLL78ckiQhNTXV81hcXBwAICoqComJiZ7p7dq1Q7t27Tz3n332Wfzwww/46aefcN9993mmDx06FPfccw8A4JFHHsHrr7+O5cuXo3nz5vjyyy+RnZ2Nv/76CzExMQCApk2bep47bdo0PProoxg7diwAoHHjxnj22Wfx8MMPY+rUqf5oCRFRtTG4EhEFkBACkiSVmT5u3DgMGDAAzZs3x+DBgzF8+HAMHDiw0nkVFhbi6aefxv/+9z+cOnUKLpcLNputzB7Xtm3bev4vSRISExORlZUFANiyZQs6dOjgCa0X2rp1K1avXl1qD6vb7YbdbkdRURHCwsK8fu9ERP7G4EpEFEC7du1Co0aNykzv2LEjDh06hIULF2LJkiUYM2YM+vfvj2+//bbCeT300ENYvHgxXn31VTRt2hRGoxHXXHMNnE5nqXFarbbUfUmSPIcCGI3GSustLCzEtGnTcNVVV5V5zGAwVPpcIqJAY3AlIgqQZcuWYfv27XjwwQfLfdxsNuO6667Dddddh2uuuQaDBw9Gbm4uYmJioNVq4Xa7S41fvXo1xo0bhyuvvBJAScg8fPiwTzW1bdsWH330ked1LtSxY0fs2bOn1OEDRETBgsGViMgPHA4HTp8+DbfbjczMTCxatAjTp0/H8OHDceutt5YZP2PGDCQlJaFDhw5QqVT45ptvkJiYiKioKAAlZwdYunQpevToAb1ej+joaDRr1gzff/89RowYAUmS8OSTT5Y6T6w3brjhBrzwwgsYPXo0pk+fjqSkJGzevBnJycno1q0bnnrqKQwfPhwNGzbENddcA5VKha1bt2LHjh147rnn/NEqIqJq41kFiIj8YNGiRUhKSkJaWhoGDx6M5cuX480338SCBQugVqvLjI+IiMDLL7+MTp06oXPnzjh8+DB+/fVXqFQlm+XXXnsNixcvRkpKCjp06ACgJOxGR0eje/fuGDFiBAYNGoSOHTv6VKdOp8Pvv/+O+Ph4DB06FG3atMGLL77oqXHQoEH45Zdf8Pvvv6Nz58647LLL8Prrr5f68hgRkVIkIYRQuggiIiIioqpwjysRERERhQQGVyIiIiIKCQyuRERERBQSGFyJiIiIKCQwuBIRERFRSGBwJSIiIqKQwOBKRERERCGBwZWIiIiIQgKDKxERERGFBAZXIiIiIgoJDK5EREREFBL+H5CRyDVN+gywAAAAAElFTkSuQmCC\n"},"metadata":{}},{"output_type":"stream","name":"stdout","text":["\n","✅ All plots generated successfully!\n","   Number of samples used: 190\n","\n","💡 Interpretation guide:\n","   • First three histograms: How clustered / diverse each embedding type is internally\n","   • Fourth histogram: How close the model’s predictions are to the real T5 embeddings\n","   • Scatter plots: Visual geometry and overlap between true vs predicted T5\n"]}]},{"cell_type":"code","source":["# @markdown # Cell 13: Install Dependencies, GPU Check & Mount Drive\n","\n","import torch\n","import subprocess\n","import sys\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","# ====================== GPU Check ======================\n","print(\"🔍 Checking GPU...\")\n","if torch.cuda.is_available():\n","    print(f\"✅ GPU ready: {torch.cuda.get_device_name(0)}\")\n","    print(f\"VRAM: {torch.cuda.get_device_properties(0).total_memory / 1024**3:.1f} GB\")\n","else:\n","    print(\"❌ No GPU detected! Please enable GPU runtime.\")\n","    raise SystemExit(\"GPU is required\")\n","\n","# ====================== Install Dependencies ======================\n","print(\"\\n📦 Installing required packages...\")\n","\n","!pip install -q --no-cache-dir open_clip_torch transformers accelerate bitsandbytes\n","\n","print(\"✅ All dependencies installed successfully\")\n","\n","# ====================== Mount Google Drive ======================\n","from google.colab import drive\n","drive.mount('/content/drive', force_remount=True)\n","\n","print(\"✅ Google Drive mounted\")\n","if debug:\n","    print(f\"   Drive path: /content/drive/MyDrive\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"id":"fhK7ma507JmQ","executionInfo":{"status":"ok","timestamp":1774961158163,"user_tz":-120,"elapsed":36615,"user":{"displayName":"No Name","userId":"10578412414437288386"}},"outputId":"a9803243-2a7f-4305-f161-d41cf78774aa"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["🔍 Checking GPU...\n","✅ GPU ready: Tesla T4\n","VRAM: 14.6 GB\n","\n","📦 Installing required packages...\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.5/1.5 MB\u001b[0m \u001b[31m38.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m60.7/60.7 MB\u001b[0m \u001b[31m228.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m44.8/44.8 kB\u001b[0m \u001b[31m203.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n","\u001b[?25h✅ All dependencies installed successfully\n","Mounted at /content/drive\n","✅ Google Drive mounted\n","   Drive path: /content/drive/MyDrive\n"]}]},{"cell_type":"code","source":["# @markdown # Cell 14: Process New Zip File → Generate T5 + CLIP Embeddings → Save to Drive\n","\n","import torch\n","import numpy as np\n","from PIL import Image\n","import open_clip\n","import os\n","import zipfile\n","from transformers import T5EncoderModel, T5Tokenizer, BitsAndBytesConfig\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","# ====================== PARAMETERS ======================\n","zip_path = \"/content/drive/MyDrive/lisa_simpson.zip\"  #@param {type:\"string\"}\n","drive_save_folder = \"/content/drive/MyDrive/T5_CLIP_Mapper\"  #@param {type:\"string\"}\n","extract_dir = \"/content/new_dataset\"  #@param {type:\"string\"}\n","\n","print(f\"📁 Processing zip file: {zip_path}\")\n","print(f\"💾 Will save embeddings to: {drive_save_folder}\")\n","\n","# ====================== 1. Unzip the Dataset ======================\n","os.makedirs(extract_dir, exist_ok=True)\n","\n","device =\"cuda\" if torch.cuda.is_available() else \"cpu\"\n","\n","\n","print(\"📦 Extracting zip file...\")\n","with zipfile.ZipFile(zip_path, 'r') as zip_ref:\n","    zip_ref.extractall(extract_dir)\n","\n","print(f\"✅ Extracted to: {extract_dir}\")\n","\n","# ====================== 2. Find Paired Text & Image Files ======================\n","text_files = {}\n","image_files = {}\n","image_exts = ('.png', '.jpg', '.jpeg', '.gif', '.bmp', '.webp')\n","\n","for root, _, files in os.walk(extract_dir):\n","    for filename in files:\n","        base = os.path.splitext(filename)[0]\n","        ext = os.path.splitext(filename)[1].lower()\n","        full_path = os.path.join(root, filename)\n","\n","        if ext == '.txt':\n","            text_files[base] = full_path\n","        elif ext in image_exts:\n","            image_files[base] = full_path\n","\n","pairs = {base: (text_files[base], image_files[base])\n","         for base in text_files if base in image_files}\n","\n","print(f\"✅ Found {len(pairs)} valid text-image pairs\")\n","\n","if debug and len(pairs) > 0:\n","    sample = list(pairs.keys())[0]\n","    print(f\"   Sample pair: {sample}.txt + {sample}{os.path.splitext(pairs[sample][1])[1]}\")\n","\n","# ====================== 3. T5-XXL Encoder-Only (Phase 1) ======================\n","print(\"\\n🧠 [Phase 1] Loading T5-XXL encoder-only (4-bit)...\")\n","\n","model_id = \"mcmonkey/google_t5-v1_1-xxl_encoderonly\"\n","\n","tokenizer = T5Tokenizer.from_pretrained(model_id)\n","\n","quant_config = BitsAndBytesConfig(\n","    load_in_4bit=True,\n","    bnb_4bit_compute_dtype=torch.float16,\n","    bnb_4bit_use_double_quant=True,\n","    bnb_4bit_quant_type=\"nf4\"\n",")\n","\n","text_encoder = T5EncoderModel.from_pretrained(\n","    model_id,\n","    quantization_config=quant_config,\n","    device_map=\"auto\",\n","    torch_dtype=torch.float16\n",")\n","text_encoder.eval()\n","\n","t5_embeddings = []\n","max_length = 512\n","\n","print(f\"🔄 Encoding {len(pairs)} texts with T5-XXL...\")\n","\n","for idx, (base, (txt_path, _)) in enumerate(pairs.items()):\n","    if debug and idx % 50 == 0 and idx > 0:\n","        print(f\"   Text {idx}/{len(pairs)} processed...\")\n","\n","    with open(txt_path, 'r', encoding='utf-8') as f:\n","        text = f.read().strip()\n","\n","    if not text:\n","        if debug:\n","            print(f\"   Skipped empty: {base}\")\n","        continue\n","\n","    inputs = tokenizer(text, padding=\"max_length\", max_length=max_length,\n","                       truncation=True, return_tensors=\"pt\")\n","\n","    input_ids = inputs.input_ids.to(\"cuda\")\n","    attention_mask = inputs.attention_mask.to(\"cuda\")\n","\n","    with torch.no_grad():\n","        outputs = text_encoder(input_ids=input_ids, attention_mask=attention_mask)\n","        t5_emb = outputs.last_hidden_state.mean(dim=1).squeeze(0).cpu().numpy()\n","\n","    t5_embeddings.append(t5_emb)\n","\n","# Unload T5 to free VRAM\n","del text_encoder\n","torch.cuda.empty_cache()\n","\n","t5_embs = np.array(t5_embeddings)\n","print(f\"✅ T5 embeddings created → shape: {t5_embs.shape}\")\n","print(\"🧹 T5 encoder unloaded from VRAM\")\n","\n","# ====================== 4. OpenCLIP (Phase 2) ======================\n","print(\"\\n📸 [Phase 2] Loading OpenCLIP ViT-B-32...\")\n","\n","clip_model, _, preprocess = open_clip.create_model_and_transforms(\n","    \"ViT-B-32\", pretrained=\"laion400m_e32\"\n",")\n","clip_model.to(device)\n","clip_model.eval()\n","\n","clip_embeddings = []\n","\n","print(f\"🔄 Encoding {len(pairs)} images with OpenCLIP...\")\n","\n","for idx, (base, (_, img_path)) in enumerate(pairs.items()):\n","    if debug and idx % 50 == 0 and idx > 0:\n","        print(f\"   Image {idx}/{len(pairs)} processed...\")\n","\n","    try:\n","        image = preprocess(Image.open(img_path)).unsqueeze(0).to(device)\n","        with torch.no_grad():\n","            clip_emb = clip_model.encode_image(image).squeeze(0).cpu().numpy()\n","        clip_embeddings.append(clip_emb)\n","    except Exception as e:\n","        if debug:\n","            print(f\"   ⚠️ Error on image {base}: {e}\")\n","\n","clip_embs = np.array(clip_embeddings)\n","print(f\"✅ CLIP embeddings created → shape: {clip_embs.shape}\")\n","\n","# ====================== 5. Save to Google Drive ======================\n","os.makedirs(drive_save_folder, exist_ok=True)\n","\n","t5_save_path = f\"{drive_save_folder}/t5_embeddings.npy\"\n","clip_save_path = f\"{drive_save_folder}/clip_embeddings.npy\"\n","\n","np.save(t5_save_path, t5_embs)\n","np.save(clip_save_path, clip_embs)\n","\n","print(\"\\n💾 Files saved to Google Drive:\")\n","print(f\"   → {t5_save_path}\")\n","print(f\"   → {clip_save_path}\")\n","print(f\"   T5 shape : {t5_embs.shape}\")\n","print(f\"   CLIP shape: {clip_embs.shape}\")\n","\n","if debug:\n","    print(f\"\\n📂 Current contents in {drive_save_folder}:\")\n","    print(os.listdir(drive_save_folder))\n","\n","print(\"\\n🎉 Processing completed! Embeddings saved to Drive.\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":645,"referenced_widgets":["64556eef51e9424c864ef27888be6691","26c4ff06fecf48ec873b62a0fcb514e9","d76b27e00ec4463eb5e53ac0503c5016","06cf636854f64b9487d98e7e06d5153d","e9e4a50deb8b4cc89341e513b65f9ce4","0d90aaa6266f41669c131f9f3f6a7e09","09740b0077ec48be89a674a8366ddcce","e0ac6801dcae4517a92865ce0a67d7c1","29add567768644ecb331f96035c9a45d","5f6ad638fa6946a0b786fb8798f74013","a80728215be544509890780836bea91e"]},"id":"9nIQeQfI7Osy","executionInfo":{"status":"ok","timestamp":1774961722862,"user_tz":-120,"elapsed":144720,"user":{"displayName":"No Name","userId":"10578412414437288386"}},"outputId":"1dc57f92-bcb9-42a8-8cbe-e9c0054ed149"},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["📁 Processing zip file: /content/drive/MyDrive/lisa_simpson.zip\n","💾 Will save embeddings to: /content/drive/MyDrive/T5_CLIP_Mapper\n","📦 Extracting zip file...\n","✅ Extracted to: /content/new_dataset\n","✅ Found 115 valid text-image pairs\n","   Sample pair: 081.txt + 081.jpeg\n","\n","🧠 [Phase 1] Loading T5-XXL encoder-only (4-bit)...\n"]},{"output_type":"display_data","data":{"text/plain":["Loading weights:   0%|          | 0/219 [00:00<?, ?it/s]"],"application/vnd.jupyter.widget-view+json":{"version_major":2,"version_minor":0,"model_id":"64556eef51e9424c864ef27888be6691"}},"metadata":{}},{"output_type":"stream","name":"stdout","text":["🔄 Encoding 115 texts with T5-XXL...\n","   Text 50/115 processed...\n","   Text 100/115 processed...\n","✅ T5 embeddings created → shape: (115, 4096)\n","🧹 T5 encoder unloaded from VRAM\n","\n","📸 [Phase 2] Loading OpenCLIP ViT-B-32...\n"]},{"output_type":"stream","name":"stderr","text":["/usr/local/lib/python3.12/dist-packages/open_clip/factory.py:450: UserWarning: QuickGELU mismatch between final model config (quick_gelu=False) and pretrained tag 'laion400m_e32' (quick_gelu=True).\n","  warnings.warn(\n"]},{"output_type":"stream","name":"stdout","text":["🔄 Encoding 115 images with OpenCLIP...\n","   Image 50/115 processed...\n","   Image 100/115 processed...\n","✅ CLIP embeddings created → shape: (115, 512)\n","\n","💾 Files saved to Google Drive:\n","   → /content/drive/MyDrive/T5_CLIP_Mapper/t5_embeddings.npy\n","   → /content/drive/MyDrive/T5_CLIP_Mapper/clip_embeddings.npy\n","   T5 shape : (115, 4096)\n","   CLIP shape: (115, 512)\n","\n","📂 Current contents in /content/drive/MyDrive/T5_CLIP_Mapper:\n","['t5_embeddings.npy', 'clip_embeddings.npy', 'clip_to_t5_mapper.pth']\n","\n","🎉 Processing completed! Embeddings saved to Drive.\n"]}]},{"cell_type":"code","source":["# @markdown # Cell 15: Test Trained CLIP→T5 Mapper on New Dataset\n","\n","import torch\n","import numpy as np\n","import matplotlib.pyplot as plt\n","import seaborn as sns\n","from sklearn.decomposition import PCA\n","from sklearn.metrics.pairwise import cosine_similarity\n","import os\n","\n","debug = True  #@param {type:\"boolean\"}\n","\n","# ====================== PARAMETERS ======================\n","drive_folder = \"/content/drive/MyDrive/T5_CLIP_Mapper\"  #@param {type:\"string\"}\n","\n","print(f\"📂 Loading data from: {drive_folder}\")\n","\n","# ====================== 1. Load Embeddings from New Dataset ======================\n","t5_path = f\"{drive_folder}/t5_embeddings.npy\"\n","clip_path = f\"{drive_folder}/clip_embeddings.npy\"\n","\n","t5_embs = np.load(t5_path)\n","clip_embs = np.load(clip_path)\n","\n","print(f\"✅ Loaded new dataset:\")\n","print(f\"   CLIP embeddings: {clip_embs.shape}\")\n","print(f\"   Real T5 embeddings: {t5_embs.shape}\")\n","\n","# ====================== 2. Load the Trained Mapper ======================\n","mapper_path = f\"{drive_folder}/clip_to_t5_mapper.pth\"\n","\n","class CLIPtoT5Mapper(torch.nn.Module):\n","    def __init__(self, input_dim=512, output_dim=4096, hidden_dim=2048):\n","        super().__init__()\n","        self.net = torch.nn.Sequential(\n","            torch.nn.Linear(input_dim, hidden_dim),\n","            torch.nn.ReLU(),\n","            torch.nn.Linear(hidden_dim, hidden_dim * 2),\n","            torch.nn.ReLU(),\n","            torch.nn.Linear(hidden_dim * 2, output_dim)\n","        )\n","\n","    def forward(self, x):\n","        return self.net(x)\n","\n","device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n","model = CLIPtoT5Mapper().to(device)\n","model.load_state_dict(torch.load(mapper_path, map_location=device))\n","model.eval()\n","\n","print(\"✅ Trained CLIP → T5 mapper loaded successfully\")\n","\n","# ====================== 3. Generate Predicted T5 Embeddings ======================\n","print(\"🔄 Generating predicted T5 embeddings from CLIP...\")\n","\n","with torch.no_grad():\n","    clip_tensor = torch.from_numpy(clip_embs).float().to(device)\n","    predicted_t5 = model(clip_tensor).cpu().numpy()\n","\n","print(f\"✅ Predicted T5 shape: {predicted_t5.shape}\")\n","\n","# ====================== 4. Compute Comparison Metrics ======================\n","print(\"\\n📊 Computing similarity metrics...\")\n","\n","# Cosine similarity: Predicted vs Real T5 (per pair)\n","pred_true_sim = np.diag(cosine_similarity(predicted_t5, t5_embs))\n","\n","# Pairwise similarities within groups\n","def get_pairwise_sim(embeddings):\n","    sim_matrix = cosine_similarity(embeddings)\n","    np.fill_diagonal(sim_matrix, np.nan)\n","    return sim_matrix.flatten()[~np.isnan(sim_matrix.flatten())]\n","\n","clip_sim = get_pairwise_sim(clip_embs)\n","t5_sim = get_pairwise_sim(t5_embs)\n","pred_t5_sim = get_pairwise_sim(predicted_t5)\n","\n","print(f\"   CLIP vs CLIP mean similarity       : {clip_sim.mean():.4f}\")\n","print(f\"   True T5 vs True T5 mean similarity : {t5_sim.mean():.4f}\")\n","print(f\"   Predicted T5 vs Predicted T5       : {pred_t5_sim.mean():.4f}\")\n","print(f\"   Predicted T5 vs True T5 (key metric): {pred_true_sim.mean():.4f}\")\n","\n","# ====================== 5. Visualizations ======================\n","plt.figure(figsize=(20, 12))\n","\n","# Similarity histograms\n","plt.subplot(2, 3, 1)\n","sns.histplot(clip_sim, kde=True, color='skyblue', bins=50)\n","plt.title('CLIP vs CLIP\\n(Pairwise Cosine)')\n","plt.xlabel('Cosine Similarity')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 2)\n","sns.histplot(t5_sim, kde=True, color='green', bins=50)\n","plt.title('True T5 vs True T5\\n(Pairwise Cosine)')\n","plt.xlabel('Cosine Similarity')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 3)\n","sns.histplot(pred_t5_sim, kde=True, color='orange', bins=50)\n","plt.title('Predicted T5 vs Predicted T5\\n(Pairwise Cosine)')\n","plt.xlabel('Cosine Similarity')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 4)\n","sns.histplot(pred_true_sim, kde=True, color='purple', bins=50)\n","plt.title('Predicted T5 vs True T5\\n(Model Performance on New Data)')\n","plt.xlabel('Cosine Similarity')\n","plt.ylabel('Count')\n","plt.grid(True, alpha=0.3)\n","\n","# PCA scatter plots\n","pca_clip = PCA(n_components=2, random_state=42)\n","clip_2d = pca_clip.fit_transform(clip_embs)\n","\n","all_t5 = np.vstack([t5_embs, predicted_t5])\n","pca_t5 = PCA(n_components=2, random_state=42)\n","t5_2d = pca_t5.fit_transform(all_t5)\n","true_t5_2d = t5_2d[:len(t5_embs)]\n","pred_t5_2d = t5_2d[len(t5_embs):]\n","\n","plt.subplot(2, 3, 5)\n","plt.scatter(clip_2d[:, 0], clip_2d[:, 1], alpha=0.7, s=25, color='skyblue')\n","plt.title('CLIP Embeddings (PCA 2D)')\n","plt.xlabel('PC1')\n","plt.ylabel('PC2')\n","plt.grid(True, alpha=0.3)\n","\n","plt.subplot(2, 3, 6)\n","plt.scatter(true_t5_2d[:, 0], true_t5_2d[:, 1], alpha=0.7, s=25, color='green', label='True T5')\n","plt.scatter(pred_t5_2d[:, 0], pred_t5_2d[:, 1], alpha=0.7, s=25, color='red', label='Predicted T5')\n","plt.title('True vs Predicted T5\\n(Shared PCA Space)')\n","plt.xlabel('PC1')\n","plt.ylabel('PC2')\n","plt.legend()\n","plt.grid(True, alpha=0.3)\n","\n","plt.tight_layout()\n","plt.show()\n","\n","# L2 Distance histogram\n","plt.figure(figsize=(8, 5))\n","diff_norms = np.linalg.norm(predicted_t5 - t5_embs, axis=1)\n","sns.histplot(diff_norms, kde=True, color='crimson', bins=50)\n","plt.title('L2 Distance: Predicted T5 − True T5')\n","plt.xlabel('Euclidean Distance')\n","plt.ylabel('Count')\n","plt.grid(True, alpha=0.3)\n","plt.show()\n","\n","print(\"\\n✅ Evaluation on new dataset completed!\")\n","if debug:\n","    print(f\"   Number of test samples: {len(t5_embs)}\")\n","    print(f\"   Average cosine similarity (Predicted vs True): {pred_true_sim.mean():.4f}\")"],"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":679},"id":"7IZQR-fV78EC","outputId":"06389a0e-c0c6-4189-f51a-47285a94afcc","executionInfo":{"status":"ok","timestamp":1774961730572,"user_tz":-120,"elapsed":2593,"user":{"displayName":"No Name","userId":"10578412414437288386"}}},"execution_count":null,"outputs":[{"output_type":"stream","name":"stdout","text":["📂 Loading data from: /content/drive/MyDrive/T5_CLIP_Mapper\n","✅ Loaded new dataset:\n","   CLIP embeddings: (115, 512)\n","   Real T5 embeddings: (115, 4096)\n","✅ Trained CLIP → T5 mapper loaded successfully\n","🔄 Generating predicted T5 embeddings from CLIP...\n","✅ Predicted T5 shape: (115, 4096)\n","\n","📊 Computing similarity metrics...\n","   CLIP vs CLIP mean similarity       : 0.8233\n","   True T5 vs True T5 mean similarity : 0.9080\n","   Predicted T5 vs Predicted T5       : 0.9738\n","   Predicted T5 vs True T5 (key metric): 0.7432\n"]},{"output_type":"display_data","data":{"text/plain":["<Figure size 2000x1200 with 6 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