llavanextCaption_Compression.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H1ruJihybKtN"
      },
      "source": [
        "# Extract Captions using Llava"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vZbzsfDvY5QU",
        "outputId": "1e815acf-fbe5-461f-fa81-d4eeec859df3"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
            "  from .autonotebook import tqdm as notebook_tqdm\n"
          ]
        }
      ],
      "source": [
        "import torch\n",
        "from transformers import AutoTokenizer, AutoProcessor, LlavaForConditionalGeneration, LlavaNextForConditionalGeneration, LlavaNextProcessor\n",
        "import array\n",
        "import os\n",
        "import pandas as pd\n",
        "from PIL import Image"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {},
      "outputs": [],
      "source": [
        "from transformers import LlamaTokenizer, LlamaTokenizerFast"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {},
      "outputs": [],
      "source": [
        "config = {'dataset': 'kodak'}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Loading checkpoint shards: 100%|██████████| 3/3 [00:03<00:00,  1.29s/it]\n",
            "Some parameters are on the meta device device because they were offloaded to the cpu.\n"
          ]
        }
      ],
      "source": [
        "path = \"llava-hf/llava-v1.6-vicuna-7b-hf\"\n",
        "model = LlavaNextForConditionalGeneration.from_pretrained(path, device_map = \"auto\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [],
      "source": [
        "tokenizer = LlamaTokenizerFast.from_pretrained(path, device_map = \"auto\")\n",
        "processor = LlavaNextProcessor.from_pretrained(path, device_map = \"auto\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "wa_54YfQZQn8"
      },
      "outputs": [],
      "source": [
        "path = \"/path/to/your/dataset/\"\n",
        "Image_names = os.listdir(path)\n",
        "Images = [Image.open(os.path.join(path, image_name)) for image_name in Image_names]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "nw93vYRwZ-XP"
      },
      "outputs": [],
      "source": [
        "prompts = [\n",
        "          \"USER: <image> \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n \\\n",
        "           ASSISTANT: \"\n",
        "          ]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "cwUkSudVaANK"
      },
      "outputs": [],
      "source": [
        "columns = [\"image_name\", \"item1\", \"item2\", \"item3\", \"item1_description\", \"item2_description\", \"item3_description\", \"overall_description\", \"d1_len\", \"d2_len\", \"d3_len\", \"dall_len\"]\n",
        "df = pd.DataFrame(columns = columns)\n",
        "df.loc[:, \"image_name\"] = Image_names\n",
        "df = df.set_index(\"image_name\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {},
      "outputs": [],
      "source": [
        "import re"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {},
      "outputs": [],
      "source": [
        "def extract_assistant_text(text):\n",
        "    match = re.search(r'ASSISTANT: (.*)', text)\n",
        "    if match:\n",
        "        return match.group(1)\n",
        "    return None"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [],
      "source": [
        "def extract_only_all(prompts, Image_names, Images, model, processor):\n",
        "  cnt = 0\n",
        "  for image_name, image in zip(Image_names, Images):\n",
        "    answers = []\n",
        "    for prompt in prompts:\n",
        "        inputs = processor(text=prompt, images=image, return_tensors=\"pt\").to(model.device)\n",
        "        # Generate\n",
        "        generate_ids = model.generate(**inputs, max_new_tokens=150, temperature = 0)\n",
        "        ans = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)\n",
        "        print(ans)\n",
        "    try:\n",
        "      text = extract_assistant_text(ans[0].replace('\\n', ''))\n",
        "      if(text is None):\n",
        "        print(f\"Error: text = {text}\")\n",
        "        continue\n",
        "      df.loc[image_name, \"overall_description\"] = text\n",
        "    except Exception:\n",
        "      print(f\"Error: items = {items}\")\n",
        "      continue\n",
        "    print(f\"Processed image {image_name}, overall_description = {text}\")\n",
        "    cnt+=1\n",
        "    if cnt % 50 == 0: #save\n",
        "      df.to_csv(f\"output_llavanext_{config['dataset']}.csv\")\n",
        "      \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "id": "HFjB_EYPaNUu"
      },
      "outputs": [],
      "source": [
        "def extract_description(prompts, Image_names, Images, model, processor):\n",
        "  for image_name, image in zip(Image_names, Images):\n",
        "    answers = []\n",
        "    for prompt in prompts:\n",
        "      try:\n",
        "        inputs = processor(text=prompt, images=image, return_tensors=\"pt\")\n",
        "        # Generate\n",
        "        generate_ids = model.generate(**inputs, max_new_tokens=150)\n",
        "        ans = processor.batch_decode(generate_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)\n",
        "        print(ans)\n",
        "      except Exception:\n",
        "        print(\"API Error\", Exception)\n",
        "        continue\n",
        "      answers.append(ans)\n",
        "    ans_text = [a for a in answers]\n",
        "    items = ans_text[0].split(\"$\")\n",
        "    if len(items) != 3:\n",
        "      print(f\"Error: items = {items}\")\n",
        "      continue\n",
        "    try:\n",
        "      item1, item1_desc = items[0].split(\"@\")\n",
        "      item2, item2_desc = items[1].split(\"@\")\n",
        "      item3, item3_desc = items[2].split(\"@\")\n",
        "      df.loc[image_name, \"item1\"] = item1\n",
        "      df.loc[image_name, \"item2\"] = item2\n",
        "      df.loc[image_name, \"item3\"] = item3\n",
        "      df.loc[image_name, \"item1_description\"] = item1_desc\n",
        "      df.loc[image_name, \"item2_description\"] = item2_desc\n",
        "      df.loc[image_name, \"item3_description\"] = item3_desc\n",
        "      df.loc[image_name, \"overall_description\"] = ans_text[1]\n",
        "    except Exception:\n",
        "      print(f\"Error: items = {items}\")\n",
        "      continue\n",
        "    print(f\"Processed image {image_name}, {item1}:{item1_desc},{item2}:{item2_desc},{item3}:{item3_desc}\")\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 312
        },
        "id": "xFtfbiU0bXLA",
        "outputId": "51318ac5-0e79-4dba-e2ad-b887e6e4e23a"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n",
            "We detected that you are passing `past_key_values` as a tuple and this is deprecated and will be removed in v4.43. Please use an appropriate `Cache` class (https://huggingface.co/docs/transformers/v4.41.3/en/internal/generation_utils#transformers.Cache)\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['USER:  \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n            ASSISTANT: \\n\\nThe image presents a modern and stylish bar setting. The bar counter, crafted from white marble, is adorned with a variety of decorative elements. A wooden shelf, filled with an assortment of bottles, adds a touch of rustic charm. Above the counter, a black metal shelf holds a collection of vases, each housing a different plant, contributing to the lively atmosphere. The bar stools, upholstered in white, are arranged neatly along the counter, ready for patrons. The overall ambiance is one of sophistication and comfort, inviting patrons to relax and enjoy their time.']\n",
            "Processed image c42476f8f2747cf77b4eaac719943677.png, overall_description = The image presents a modern and stylish bar setting. The bar counter, crafted from white marble, is adorned with a variety of decorative elements. A wooden shelf, filled with an assortment of bottles, adds a touch of rustic charm. Above the counter, a black metal shelf holds a collection of vases, each housing a different plant, contributing to the lively atmosphere. The bar stools, upholstered in white, are arranged neatly along the counter, ready for patrons. The overall ambiance is one of sophistication and comfort, inviting patrons to relax and enjoy their time.\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "['USER:  \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n            ASSISTANT: \\n\\nIn the image, a person is seen walking on a sidewalk, pulling a black suitcase behind them. The individual is dressed in a green shirt and blue jeans, and they appear to be in motion, possibly heading towards or returning from a journey. The suitcase is large and seems to be well-suited for travel. The setting is an urban environment, with a clear sky overhead and a building visible in the background. The overall scene suggests a sense of movement and travel.']\n",
            "Processed image 85e6554aedd269c6a08c24ee4cd1f74b.png, overall_description = In the image, a person is seen walking on a sidewalk, pulling a black suitcase behind them. The individual is dressed in a green shirt and blue jeans, and they appear to be in motion, possibly heading towards or returning from a journey. The suitcase is large and seems to be well-suited for travel. The setting is an urban environment, with a clear sky overhead and a building visible in the background. The overall scene suggests a sense of movement and travel.\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[\"USER:  \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n            ASSISTANT: \\n\\nIn the image, a man is seen riding a black motorcycle on a road under a bridge. He is wearing a black jacket, black pants, and a black helmet. The motorcycle has a blue gas tank and is equipped with a black seat. The man appears to be in motion, as suggested by the blurred background and the slight tilt of the motorcycle. The bridge in the background adds an urban touch to the scene. The man's attire and the motorcycle's design suggest a preference for a classic and timeless style.\"]\n",
            "Processed image 0f6cd456ade0adf0c1a0d4e522954d00.png, overall_description = In the image, a man is seen riding a black motorcycle on a road under a bridge. He is wearing a black jacket, black pants, and a black helmet. The motorcycle has a blue gas tank and is equipped with a black seat. The man appears to be in motion, as suggested by the blurred background and the slight tilt of the motorcycle. The bridge in the background adds an urban touch to the scene. The man's attire and the motorcycle's design suggest a preference for a classic and timeless style.\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[\"USER:  \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n            ASSISTANT: \\n\\nIn the heart of the action, a Formula 1 race car, painted in vibrant hues of orange and black, is captured in motion. The car, adorned with the number 25, is leaning into a turn on a track, demonstrating the driver's skill and the car's agility. The background reveals a blurred cityscape, adding a sense of speed and urgency to the scene. The image encapsulates the thrill and excitement of a Formula 1 race, where every second counts.\"]\n",
            "Processed image 586460a320d3e725cdf3f6032dd09f52.png, overall_description = In the heart of the action, a Formula 1 race car, painted in vibrant hues of orange and black, is captured in motion. The car, adorned with the number 25, is leaning into a turn on a track, demonstrating the driver's skill and the car's agility. The background reveals a blurred cityscape, adding a sense of speed and urgency to the scene. The image encapsulates the thrill and excitement of a Formula 1 race, where every second counts.\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[\"USER:  \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n            ASSISTANT: \\n            In the image, a young couple is captured in a moment of intimacy. They are seated on the floor, leaning against a wall adorned with geometric patterns. The man, dressed in a gray shirt and black pants, holds the woman's hand, creating a sense of closeness. The woman, wearing a blue jacket and white sneakers, gazes at the man with a soft expression. A black backpack rests nearby, adding a touch of everyday life to the scene. The overall atmosphere is one of warmth and connection.\"]\n",
            "Processed image 81522064f61ba1c9ec111bb349851bca.png, overall_description =             In the image, a young couple is captured in a moment of intimacy. They are seated on the floor, leaning against a wall adorned with geometric patterns. The man, dressed in a gray shirt and black pants, holds the woman's hand, creating a sense of closeness. The woman, wearing a blue jacket and white sneakers, gazes at the man with a soft expression. A black backpack rests nearby, adding a touch of everyday life to the scene. The overall atmosphere is one of warmth and connection.\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[\"USER:  \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n            ASSISTANT: \\n\\nIn the image, a solitary figure is captured in the midst of a rainy city night. The person, clad in a black jacket and holding an umbrella, is walking on a wet sidewalk, their footprints leaving a trail behind. The cityscape is bathed in the soft glow of streetlights, casting long shadows and reflecting off the wet pavement. The scene is a blend of urban life and the tranquility of a rainy night, with the person's journey illuminated by the city's ambient light.\"]\n",
            "Processed image e22eb9ac525d8d5178014d96f024bb8d.png, overall_description = In the image, a solitary figure is captured in the midst of a rainy city night. The person, clad in a black jacket and holding an umbrella, is walking on a wet sidewalk, their footprints leaving a trail behind. The cityscape is bathed in the soft glow of streetlights, casting long shadows and reflecting off the wet pavement. The scene is a blend of urban life and the tranquility of a rainy night, with the person's journey illuminated by the city's ambient light.\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "[\"USER:  \\n please give overall description of this image in 50 words. generate only an informative and natural paragraph. \\n            ASSISTANT: \\nIn the image, a young woman stands in front of a rusted metal gate, holding an open umbrella. She is dressed in a long coat and shorts, with knee-high socks and black shoes. The gate is old and weathered, with a chain-link fence behind it. The ground is covered in fallen leaves, suggesting it might be autumn. The woman's pose and the umbrella she holds add a sense of anticipation or perhaps a hint of melancholy to the scene. The overall atmosphere is one of quiet solitude, with the woman as the central figure in this urban landscape.\"]\n",
            "Processed image d542411baac09dfc9e75b9c1b0532d94.png, overall_description = In the image, a young woman stands in front of a rusted metal gate, holding an open umbrella. She is dressed in a long coat and shorts, with knee-high socks and black shoes. The gate is old and weathered, with a chain-link fence behind it. The ground is covered in fallen leaves, suggesting it might be autumn. The woman's pose and the umbrella she holds add a sense of anticipation or perhaps a hint of melancholy to the scene. The overall atmosphere is one of quiet solitude, with the woman as the central figure in this urban landscape.\n"
          ]
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/opt/conda/lib/python3.10/site-packages/transformers/generation/configuration_utils.py:540: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "ename": "KeyboardInterrupt",
          "evalue": "",
          "output_type": "error",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "Cell \u001b[0;32mIn[12], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mextract_only_all\u001b[49m\u001b[43m(\u001b[49m\u001b[43mprompts\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mImage_names\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mImages\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mprocessor\u001b[49m\u001b[43m)\u001b[49m\n",
            "Cell \u001b[0;32mIn[11], line 9\u001b[0m, in \u001b[0;36mextract_only_all\u001b[0;34m(prompts, Image_names, Images, model, processor)\u001b[0m\n\u001b[1;32m      7\u001b[0m inputs \u001b[38;5;241m=\u001b[39m processor(text\u001b[38;5;241m=\u001b[39mprompt, images\u001b[38;5;241m=\u001b[39mimage, return_tensors\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mpt\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mto(model\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m      8\u001b[0m \u001b[38;5;66;03m# Generate\u001b[39;00m\n\u001b[0;32m----> 9\u001b[0m generate_ids \u001b[38;5;241m=\u001b[39m \u001b[43mmodel\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgenerate\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmax_new_tokens\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m150\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mtemperature\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m     10\u001b[0m ans \u001b[38;5;241m=\u001b[39m processor\u001b[38;5;241m.\u001b[39mbatch_decode(generate_ids, skip_special_tokens\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, clean_up_tokenization_spaces\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[1;32m     11\u001b[0m \u001b[38;5;28mprint\u001b[39m(ans)\n",
            "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/torch/utils/_contextlib.py:115\u001b[0m, in \u001b[0;36mcontext_decorator.<locals>.decorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    112\u001b[0m \u001b[38;5;129m@functools\u001b[39m\u001b[38;5;241m.\u001b[39mwraps(func)\n\u001b[1;32m    113\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecorate_context\u001b[39m(\u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m    114\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m ctx_factory():\n\u001b[0;32m--> 115\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
            "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/transformers/generation/utils.py:1914\u001b[0m, in \u001b[0;36mGenerationMixin.generate\u001b[0;34m(self, inputs, generation_config, logits_processor, stopping_criteria, prefix_allowed_tokens_fn, synced_gpus, assistant_model, streamer, negative_prompt_ids, negative_prompt_attention_mask, **kwargs)\u001b[0m\n\u001b[1;32m   1906\u001b[0m     input_ids, model_kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_expand_inputs_for_generation(\n\u001b[1;32m   1907\u001b[0m         input_ids\u001b[38;5;241m=\u001b[39minput_ids,\n\u001b[1;32m   1908\u001b[0m         expand_size\u001b[38;5;241m=\u001b[39mgeneration_config\u001b[38;5;241m.\u001b[39mnum_return_sequences,\n\u001b[1;32m   1909\u001b[0m         is_encoder_decoder\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mconfig\u001b[38;5;241m.\u001b[39mis_encoder_decoder,\n\u001b[1;32m   1910\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mmodel_kwargs,\n\u001b[1;32m   1911\u001b[0m     )\n\u001b[1;32m   1913\u001b[0m     \u001b[38;5;66;03m# 13. run sample (it degenerates to greedy search when `generation_config.do_sample=False`)\u001b[39;00m\n\u001b[0;32m-> 1914\u001b[0m     result \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_sample\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1915\u001b[0m \u001b[43m        \u001b[49m\u001b[43minput_ids\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1916\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlogits_processor\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprepared_logits_processor\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1917\u001b[0m \u001b[43m        \u001b[49m\u001b[43mlogits_warper\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprepared_logits_warper\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1918\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstopping_criteria\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mprepared_stopping_criteria\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1919\u001b[0m \u001b[43m        \u001b[49m\u001b[43mgeneration_config\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mgeneration_config\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1920\u001b[0m \u001b[43m        \u001b[49m\u001b[43msynced_gpus\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msynced_gpus\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1921\u001b[0m \u001b[43m        \u001b[49m\u001b[43mstreamer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mstreamer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1922\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mmodel_kwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1923\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1925\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m generation_mode \u001b[38;5;129;01min\u001b[39;00m (GenerationMode\u001b[38;5;241m.\u001b[39mBEAM_SAMPLE, GenerationMode\u001b[38;5;241m.\u001b[39mBEAM_SEARCH):\n\u001b[1;32m   1926\u001b[0m     \u001b[38;5;66;03m# 11. prepare logits warper\u001b[39;00m\n\u001b[1;32m   1927\u001b[0m     prepared_logits_warper \u001b[38;5;241m=\u001b[39m (\n\u001b[1;32m   1928\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_logits_warper(generation_config, device\u001b[38;5;241m=\u001b[39minput_ids\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m   1929\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m generation_config\u001b[38;5;241m.\u001b[39mdo_sample\n\u001b[1;32m   1930\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m   1931\u001b[0m     )\n",
            "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/transformers/generation/utils.py:2646\u001b[0m, in \u001b[0;36mGenerationMixin._sample\u001b[0;34m(self, input_ids, logits_processor, stopping_criteria, generation_config, synced_gpus, streamer, logits_warper, **model_kwargs)\u001b[0m\n\u001b[1;32m   2643\u001b[0m unfinished_sequences \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mones(batch_size, dtype\u001b[38;5;241m=\u001b[39mtorch\u001b[38;5;241m.\u001b[39mlong, device\u001b[38;5;241m=\u001b[39minput_ids\u001b[38;5;241m.\u001b[39mdevice)\n\u001b[1;32m   2644\u001b[0m model_kwargs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_get_initial_cache_position(input_ids, model_kwargs)\n\u001b[0;32m-> 2646\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_has_unfinished_sequences\u001b[49m\u001b[43m(\u001b[49m\u001b[43mthis_peer_finished\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43msynced_gpus\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mdevice\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_ids\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdevice\u001b[49m\u001b[43m)\u001b[49m:\n\u001b[1;32m   2647\u001b[0m     \u001b[38;5;66;03m# prepare model inputs\u001b[39;00m\n\u001b[1;32m   2648\u001b[0m     model_inputs \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprepare_inputs_for_generation(input_ids, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mmodel_kwargs)\n\u001b[1;32m   2650\u001b[0m     \u001b[38;5;66;03m# forward pass to get next token\u001b[39;00m\n",
            "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/transformers/generation/utils.py:2085\u001b[0m, in \u001b[0;36mGenerationMixin._has_unfinished_sequences\u001b[0;34m(self, this_peer_finished, synced_gpus, device)\u001b[0m\n\u001b[1;32m   2083\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m this_peer_finished_flag\u001b[38;5;241m.\u001b[39mitem() \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0.0\u001b[39m:\n\u001b[1;32m   2084\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m-> 2085\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m this_peer_finished:\n\u001b[1;32m   2086\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[1;32m   2087\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ],
      "source": [
        "extract_only_all(prompts, Image_names, Images, model, processor)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {},
      "outputs": [],
      "source": [
        "df.to_csv(f\"{config['dataset']}_overall_description.csv\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BSXVZ0B8bbEZ"
      },
      "source": [
        "# Caption Compression"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "FmBh_HDAbvuf"
      },
      "source": [
        "# LLMzip requirements"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "6_Ld21ndb0Rr"
      },
      "outputs": [],
      "source": [
        "import torch\n",
        "import array\n",
        "import zlib\n",
        "import argparse\n",
        "\n",
        "class LlamaZip:\n",
        "    def __init__(self, model, tokenizer):\n",
        "        self.CONTEXT_SIZE = 8\n",
        "        self.BATCH_SIZE = 10\n",
        "        self.model = model\n",
        "        self.tokenizer = tokenizer\n",
        "        self.device = torch.device(\"cuda:0\" if torch.cuda.is_available() else \"cpu\")\n",
        "\n",
        "\n",
        "    def text_to_tokens(self, text):\n",
        "        # ignore the warning that this gives about too many tokens\n",
        "        tokens = self.tokenizer(text, return_tensors=\"pt\", add_special_tokens=True)\n",
        "        tokens = tokens[\"input_ids\"].squeeze()\n",
        "        return tokens\n",
        "\n",
        "    def tokens_to_text(self, tokens):\n",
        "        tokens = tokens.reshape((1, -1))\n",
        "        text = self.tokenizer.batch_decode(tokens, skip_special_tokens=False, clean_up_tokenization_spaces=False)\n",
        "        return text[0]\n",
        "\n",
        "    def pad(self, tokens, padding_val):\n",
        "        pad_len = self.CONTEXT_SIZE - tokens.shape[0] % self.CONTEXT_SIZE\n",
        "        if pad_len != self.CONTEXT_SIZE:\n",
        "            padding = torch.tensor([padding_val]*pad_len)\n",
        "\n",
        "            tokens = torch.cat((tokens, padding))\n",
        "\n",
        "        else:\n",
        "            pad_len = 0\n",
        "\n",
        "\n",
        "        return tokens, pad_len\n",
        "\n",
        "    @torch.no_grad()\n",
        "    def get_logits(self, tokens, token_index, past=None):\n",
        "        my_inputs = {}\n",
        "        my_inputs['input_ids'] = tokens[:, token_index].reshape(-1, 1)\n",
        "\n",
        "        output = self.model(**my_inputs, past_key_values=past)\n",
        "        logits = output.logits\n",
        "        if len(logits.shape) > 2:\n",
        "            logits = logits.reshape((logits.shape[0], -1))\n",
        "        return logits, output.past_key_values\n",
        "\n",
        "\n",
        "    def encode_one_batch(self, tokens, token_index, past=None):\n",
        "\n",
        "        assert len(tokens.shape) == 2\n",
        "\n",
        "        logits, past = self.get_logits(tokens, token_index, past)\n",
        "        assert len(logits.shape) == 2\n",
        "        logits, sorted_tokens = torch.sort(logits, descending=True)\n",
        "\n",
        "        assert len(sorted_tokens.shape) == 2\n",
        "\n",
        "\n",
        "        next_tokens = tokens[:, token_index + 1]\n",
        "        next_tokens_expanded = next_tokens.view(-1, 1).expand_as(sorted_tokens)\n",
        "        next_tokens_expanded = next_tokens_expanded\n",
        "\n",
        "        # Find score as index of next tokens\n",
        "        scores = (sorted_tokens==next_tokens_expanded).nonzero(as_tuple=True)\n",
        "\n",
        "        scores = scores[1] # remove index column\n",
        "\n",
        "        return scores, past\n",
        "\n",
        "    def decode_one_batch(self, input_tokens, scores, score_index, past=None):\n",
        "        assert len(scores.shape) == 2\n",
        "        logits, past = self.get_logits(input_tokens, score_index, past)\n",
        "\n",
        "        logits, sorted_tokens = torch.sort(logits, descending=True)\n",
        "        assert len(sorted_tokens.shape) == 2\n",
        "        # the scores give the indexes of the decoded tokens\n",
        "        indexes = scores[:, score_index].flatten()\n",
        "        decoded_tokens = sorted_tokens[torch.arange(indexes.shape[0]), indexes]\n",
        "\n",
        "        return decoded_tokens.int(), past\n",
        "\n",
        "\n",
        "    def encode(self, text):\n",
        "        tokens = self.text_to_tokens(text)\n",
        "        print(\"tokens:\", tokens)\n",
        "        return self.encode_tokens(tokens)\n",
        "\n",
        "    def encode_tokens(self, tokens):\n",
        "\n",
        "        tokens, pad_len = self.pad(tokens, self.tokenizer.eos_token_id)\n",
        "        tokens = tokens.view(-1, self.CONTEXT_SIZE)\n",
        "\n",
        "        output_scores = torch.zeros(tokens.shape)\n",
        "\n",
        "\n",
        "        # Add eos to the start of each block (to give it somewhere to start)\n",
        "        eos = torch.tensor([self.tokenizer.eos_token_id]*tokens.shape[0]).unsqueeze(1)\n",
        "        tokens = torch.cat((eos, tokens), 1)\n",
        "\n",
        "        tokens = tokens.to(self.device)\n",
        "\n",
        "        batches = tokens.shape[0]//self.BATCH_SIZE\n",
        "        if tokens.shape[0] % self.BATCH_SIZE != 0:\n",
        "            batches += 1\n",
        "\n",
        "        # score each batch\n",
        "        print(\"Encoding\")\n",
        "        for i in range(batches):\n",
        "            cur_tokens = tokens[i*self.BATCH_SIZE:(i + 1)*self.BATCH_SIZE]\n",
        "            cur_output_scores = torch.zeros((cur_tokens.shape[0], cur_tokens.shape[1]-1))\n",
        "            past = None\n",
        "            print(i, \"out of\", batches)\n",
        "\n",
        "            for j in range(cur_tokens.shape[1]-1):\n",
        "                cur_output_scores[:, j], past = self.encode_one_batch(cur_tokens, j, past)\n",
        "                print(\"encoded: \",j, \"out of\", cur_tokens.shape[1]-1)\n",
        "            output_scores[i*self.BATCH_SIZE:(i + 1)*self.BATCH_SIZE] = cur_output_scores\n",
        "\n",
        "        output_scores = output_scores.flatten().int()\n",
        "        if pad_len > 0:\n",
        "            output_scores = output_scores[:-pad_len]\n",
        "        return output_scores\n",
        "\n",
        "    def decode(self, scores):\n",
        "        output_tokens = self.decode_tokens(scores)\n",
        "        output_tokens = output_tokens.unsqueeze(0)\n",
        "        print(\"Decoded tokens: \", output_tokens)\n",
        "        text = self.tokenizer.batch_decode(output_tokens)\n",
        "        #text = \"\".join(text)\n",
        "        #text = text.replace(\"<|endoftext|>\", \"\")\n",
        "        return text[0]\n",
        "\n",
        "    def decode_tokens(self, scores):\n",
        "\n",
        "        scores, pad_len = self.pad(scores, self.tokenizer.eos_token_id)\n",
        "\n",
        "        scores = scores.view(-1, self.CONTEXT_SIZE) # all rows, CONTEXT_SIZE\n",
        "\n",
        "        output_tokens = torch.zeros(scores.shape, dtype=int)\n",
        "\n",
        "\n",
        "        # Add eos to the start of each block (to give it somewhere to start)\n",
        "        eos = torch.tensor([self.tokenizer.eos_token_id]*output_tokens.shape[0]).unsqueeze(1)\n",
        "        output_tokens = torch.cat((eos, output_tokens), 1) # all rows, CONTEXT_SIZE + 1\n",
        "\n",
        "        output_tokens = output_tokens.to(self.device)\n",
        "\n",
        "        batches = scores.shape[0]//self.BATCH_SIZE\n",
        "        if scores.shape[0] % self.BATCH_SIZE != 0:\n",
        "            batches += 1\n",
        "\n",
        "        # score each batch\n",
        "        print(\"Decoding\")\n",
        "        for i in range(batches):\n",
        "            print(i, \"out of\", batches)\n",
        "            cur_scores = scores[i*self.BATCH_SIZE:(i + 1)*self.BATCH_SIZE] # BATCH_SIZE, CONTEXT_SIZE\n",
        "\n",
        "            cur_output_tokens = output_tokens[i*self.BATCH_SIZE:(i + 1)*self.BATCH_SIZE] # BATCH_SIZE, CONTEXT_SIZE\n",
        "            cur_output_tokens = cur_output_tokens.to(self.device)\n",
        "            past = None\n",
        "            for j in range(scores.shape[1]):\n",
        "\n",
        "                cur_output_tokens[:, j+1], past = self.decode_one_batch(cur_output_tokens, cur_scores, j, past) # BATCH_SIZE\n",
        "\n",
        "            output_tokens[i*self.BATCH_SIZE:(i + 1)*self.BATCH_SIZE] = cur_output_tokens\n",
        "\n",
        "\n",
        "\n",
        "        output_tokens = output_tokens[:, 1:].int()\n",
        "        output_tokens = output_tokens.flatten()\n",
        "\n",
        "        if pad_len != 0:\n",
        "            output_tokens = output_tokens[:-pad_len]\n",
        "\n",
        "        return output_tokens\n",
        "\n",
        "\n",
        "\n",
        "    def encode_and_zip(self, text):\n",
        "        encoded = self.encode(text)\n",
        "        encoded = array.array(\"H\", encoded)\n",
        "        return zlib.compress(encoded, level=9)\n",
        "\n",
        "\n",
        "    def unzip_and_decode(self, zipped):\n",
        "        unzipped = zlib.decompress(zipped)\n",
        "        print(\"unzipped sequence: \", unzipped)\n",
        "        unzipped = array.array(\"H\", unzipped)\n",
        "        print(\"unzipped array: \", unzipped)\n",
        "        print(\"len: \", len(unzipped))\n",
        "        decoded = self.decode(torch.tensor(unzipped))\n",
        "        print(\"decoded: \", decoded)\n",
        "        return decoded\n",
        "\n",
        "    def zip_file(self, text_file, zip_file):\n",
        "        with open(text_file, encoding=\"utf-8\") as f:\n",
        "            text = f.read()\n",
        "\n",
        "        zipped = self.encode_and_zip(text)\n",
        "\n",
        "        with open(zip_file, \"wb\") as f:\n",
        "            f.write(zipped)\n",
        "\n",
        "    def unzip_file(self, zip_file, text_file):\n",
        "        with open(zip_file, \"rb\") as f:\n",
        "            zipped = f.read()\n",
        "        text = self.unzip_and_decode(zipped)\n",
        "\n",
        "        with open(text_file, \"w\", encoding=\"utf-8\") as f:\n",
        "            f.write(text)\n",
        "\n",
        "\n",
        "\n",
        "\n",
        "\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "fyv6RM0Xb7-6"
      },
      "source": [
        "# Compression"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "IRAi-43DcU0d"
      },
      "outputs": [],
      "source": [
        "llama_zip = LlamaZip(model, tokenizer)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "gjrjotnbb-gc"
      },
      "outputs": [],
      "source": [
        "def evaluation(llama_zip, df):\n",
        "  #dfの全要素について処理する\n",
        "  for i, image_name in enumerate(df.index):\n",
        "    if(df.loc[image_name, \"dall_len\"] > 0):\n",
        "      print(\"skipping \", image_name)\n",
        "      continue\n",
        "    text = df.loc[image_name, \"overall_description\"]\n",
        "    zipped = llama_zip.encode_and_zip(text)\n",
        "    df.loc[image_name, \"dall_len\"] = len(zipped) * 8\n",
        "    if(i % 50 == 0):\n",
        "      df.to_csv(f\"/root/shared_smurai/df/{config['dataset']}_overall_description.csv\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "tHf62KFRdXjv"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "skipping  0\n",
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            "skipping  201\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,  2078,   271,   400,  5086,\n",
            "        14911,   616,  1776,   310,   263,   724,  1600, 19437, 17763,   839,\n",
            "        28655,   303,   263, 20619, 13569, 29889,   450, 19437, 29892,   263,\n",
            "          325,  4626,   424,   528,  1943,   310,  7254, 29892,   338, 22047,\n",
            "          491,   301,  1878,  7933, 10697,   393, 16116,   408,  2215,   408,\n",
            "          278, 10977,   508,  1074, 29889,   450,  4094, 29915, 29879,  7101,\n",
            "          338, 21732, 29892,  9432,   292,   278, 18830, 24400, 29889,   450,\n",
            "        13569,  5692,   304,   367,   263,  6837,   310,   378,  9633,   681,\n",
            "          322, 18937, 17269, 10697, 29892, 23941,   263, 16984,   321,  3944,\n",
            "          973, 29889,   450, 12463,  9088,   338,   697,   310, 22024,   339,\n",
            "         1793,   322,  5613, 15409, 29892,   263,  1243,  1166,   304,   278,\n",
            "          443, 16747,   287,   281,  2700,  2264, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
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            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  6114,   338, 15468,   297,\n",
            "          263,  3256,   310, 22024,   339,  1793, 29892,  4120, 18499,   343,\n",
            "        14895,   297,   263,  5400,  8693, 29889,  2296,   338, 27121,   297,\n",
            "          263,  4628, 14717,  4105,   322,   454,  1505,   886, 29892,   902,\n",
            "         3573,   772,  3368,   297,   263,  6411,  8362,   380,   749,   373,\n",
            "          263,  7254,   343, 14895,  1775, 29889,   450,  5716,  2820,   902,\n",
            "          338, 21779,  3730, 10200,   630,   411,   282, 15048, 18577,   322,\n",
            "          263, 27278,  3856,   305, 29892,  4969,   263,   724,  1600, 25005,\n",
            "        29889,   319,  2919,  3474,  6511,  5613,  3578,   304,  5685,   397,\n",
            "          278,  2913, 29892,  4486,  9735,  1218,   278,  9088,   322, 12141,\n",
            "          292,   278,  6114, 29915, 29879, 21309,  4603, 29889,   450, 12463,\n",
            "         4444, 14661,   263, 10776,  1319,   322,  9045, 29891,   301,  7004,\n",
            "         1508, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
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            "1 out of 2\n",
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            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,   767,   338,  3033,  2124,\n",
            "          287,   297,   670,  1616,  1287, 29892, 16246,   373,   278, 11904,\n",
            "          297,   263,  1067,  6463,   287,  5716, 29889,   940,   338, 22047,\n",
            "          491,  5164,  1616, 28075, 29892,  3704, 10675,   508, 29879,   322,\n",
            "         1506,  1878,   267, 29892, 23941,   263,   907,  1230,   322, 19587,\n",
            "         5177, 29889,   450,  5716,  3528,   338, 10423,   411, 10675,   886,\n",
            "        29892,   777,   310,   607,   526,   298,  9776,   373,   278, 10090,\n",
            "        29892,  1550,  4045,   526,  7180,   373,   278, 11904, 29889,   450,\n",
            "          767,  5692,   304,   367,   297,   278, 29214,   310,   263, 20413,\n",
            "        29892,   670,  8569,  9186,   373,   670,   664, 29889,   450, 12463,\n",
            "        25005,   310,   278,  5716, 14661,   263,  2913, 16955,   304,  1616,\n",
            "         4695,  4603,   322,   907, 28157, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  1510, 11436,   263,   325,   524,   482, 22901,\n",
            "         1165, 10656, 29892,   263,  5829,   310,  6731, 12122,  4955, 29889,\n",
            "          450, 10656, 29892,   411,   967,  4628,   322,  4796,  2927, 11380,\n",
            "        29892,   338,  2602,   287,   373,   263,  6592,   310, 19225, 11308,\n",
            "        29892, 26233,   263,  4259,   284,  1735, 29889,   450, 10656, 29915,\n",
            "        29879,   301,   575,   338,  2504,   262,  2705,  8833, 29892, 10320,\n",
            "        12818,   278, 14982,  1024,   376, 29925,   296,  1165, 29908,   322,\n",
            "          278,  1904,   376, 19111, 14619, 24540,  1642,   450, 10656, 29915,\n",
            "        29879,  2874,   322,   278, 11308,  1090,   484,   493,   372,   321,\n",
            "         5744,   263,  4060,   310, 20990,  9564,   423,   322,   278, 15409,\n",
            "          310,  5469, 29889,   450,  1967,  4332,  1973,   278,  3686,   663,\n",
            "          310,  6731,  5275, 29892,   988,   278, 10656,   338,   451,   925,\n",
            "          263,  5780, 29892,   541,   263, 21239,   393,  2225, 20098,  2626,\n",
            "         3842,   322, 10603, 15874, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  6114, 15028,   297,   263,\n",
            "         2919, 29892, 18408,  5716, 29892,   902,  1250,   304,   278, 10656,\n",
            "        29889,  2296,   338, 27121,   297,   263,  4628, 10714,   322,   263,\n",
            "        10489, 11105, 29892,   607, 18469,   902,  3700, 29889,   450,  5716,\n",
            "          338, 10423,   411,  7933,  7672,   262,   708, 29892,   322,   263,\n",
            "         2919,  3474,  6511,  5613,  3578,   304,  5685,   397,   297, 29889,\n",
            "          450,  6114, 29915, 29879,  2602,   297,   278,  4818,   310,   278,\n",
            "         5716, 29892,  3412,   411,   902,  1098,   533, 29892, 14661,   263,\n",
            "         9088,   310, 11158, 12137,   322, 29236, 29889,   450, 18408,  4444,\n",
            "          322,   902,  1098,   533, 13182,   472,   263, 15474,  1230,   393,\n",
            "          338,  1722,   304, 19854, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  6114,   338, 13407,   297,\n",
            "          385,  8034,  4444, 29892, 20793,   292,  2750,   263,  4796, 10090,\n",
            "        29889,  2296,   338,   591,  4362,   263,  4628,   322,  4796,  1248,\n",
            "         1335,  8329,  1999,  1709, 29892,  1766,  6150,   282,  1934, 29892,\n",
            "          322,  4628, 17394,   267, 29889,   512,   902,  1361, 29892,  1183,\n",
            "         8640,   263,  4796, 26935, 18002, 29889,   450,  8034,   338, 15252,\n",
            "         3276,   411,   263,   553, 29895,   322,   521,  7121, 29892,   322,\n",
            "          727, 29915, 29879,   263,  2919,  3474,   297,   278,  3239, 29892,\n",
            "        14372,  5613,  3578,   304,  5445,   278,  2913, 29889,   450,  6114,\n",
            "         5692,   304,   367,   297,   263, 26681,   287,  1400,   545, 29892,\n",
            "        26233,   263,  3209,   950,   470,  1871,   284, 25005,   297,   278,\n",
            "         8034, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
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            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
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            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,  3802, 29899,   786,  1776,\n",
            "          310,   263,   325,   524,   482,  1559, 29915, 29879, 18983,   289,\n",
            "          398,   546, 29892,   607,   338,   263, 29191, 10296,   310,  2654,\n",
            "          322, 13283, 29889,   450,   289,   398,   546,   338,   594,  1398,\n",
            "          287,   411,   263, 19308,  2654,  3578, 29892,  4417,   263,  1835,\n",
            "          310,  2927,   304,   278,  6467,  1539,   497,   293, 21285, 29889,\n",
            "          450,  1559, 29915, 29879, 19405, 15284, 29892,  5183,   376,  1529,\n",
            "        29934, 29968, 25593,   613,   338,  9436,  7962, 29892, 13182,   292,\n",
            "          472,   967,  3978,   470,  6060,   967, 12271, 29889,   450,  3239,\n",
            "        29892,  2466,  1999,   332,  1127, 29892, 14661,   263,  5613,  4444,\n",
            "        29892, 10075,   263,  1746,   470,   263, 13569, 29892, 13138,   263,\n",
            "        12814,   292,  1250,  8865,   304,   278,  1559, 29915, 29879,   767,\n",
            "        29899, 26350, 15409, 29889,   450, 12463, 15259,   310,   278,  1967,\n",
            "        14661,   263,  4060,   310, 20990,  9564,   423,   322,  5108,   362,\n",
            "          363, 22037,  3345,   711,  5475, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  1510, 11436,   263,  5400,  6956,  3631,  1766,\n",
            "          955, 29892,   263, 15655,  5214,   411,   263,  8359,   573,  4024,\n",
            "         1943, 29889,   450,  5214, 29915, 29879, 25591,   338, 13725,   310,\n",
            "        12727, 24841, 29899, 29890,  4708, 11408,  7243,  1379, 29892, 21050,\n",
            "          297,   263, 18178,  1541, 13076,  4766,   393, 12778,   304,   967,\n",
            "         7604, 25530, 29889,   450,  7243,  1379,   526,   451,  9090,   297,\n",
            "         2159, 29892,  4969,   263,  4060,   310, 10809,   322, 18459, 29889,\n",
            "          450,  5214, 29915, 29879,  2874,   338,  4340,  1035,   296, 29884,\n",
            "          630,   491,   278, 10122,   310,  2919,  5417, 29892,   607,   526,\n",
            "         1584,   368, 26325,   287,   322,  9432,   278, 18830,  5177, 29889,\n",
            "          450, 14744,   297,   278,  3239,   338,   263,  2821,  7254, 29892,\n",
            "        13138,   263,   724,  1600,  1250,  8865,   304,   278,  5214, 29889,\n",
            "          450, 12463, 15259,   310,   278,  1967, 12141, 29879,   278, 10311,\n",
            "         2592,  1546, 11258,   322,  5469, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,   767,   338,  3595,   297,\n",
            "          263,  3209,   950,  4444, 29892, 10075,   263,  2625, 20919,   470,\n",
            "          263, 11952, 29889,   940,   338, 27121,   297,   263,  7933, 28015,\n",
            "          300,   322,   263,   367,  2231,   528,  2728, 29892,   411,   263,\n",
            "         7684,  9228,   373,   670, 19917, 29889,  3600,  2175,  1361,   338,\n",
            "        13587,   263,  7684,  9228, 29892,  1550,   670,  1492,  1361,   338,\n",
            "        13587,   263,  4628,  6505, 29889,   450,   767,  5692,   304,   367,\n",
            "          297,   278,  7256,   310,   385,  3158, 29892, 10075, 10365,   292,\n",
            "          670,  9228,   470,  8454,   278,   931,   373,   670,  6505, 29889,\n",
            "          450,  3239,   338,  1999,   332,  1127, 29892,   541,   372,  2444,\n",
            "          304,   367,   385, 17164,  5177,   411,   263, 28645, 10090,   322,\n",
            "          263,   285,   663, 29889,   450,   767, 29915, 29879,  1098,   533,\n",
            "          322,   278,  4444,  4368,   263,  3209,   950, 29892,  1432,  3250,\n",
            "         9088, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   325,  4626,   424,  4272,\n",
            "        11952,   472,   270, 17400, 29892,   289, 14139,   297,   278, 14294,\n",
            "          330,   677,   310, 11952,  4366, 29879, 29889,   319, 21892,  7353,\n",
            "        29892, 20287,   292,   297,   278,   289,   929,   911, 29892, 12778,\n",
            "          263,  6023,   310,  4797, 24967,   304,   278,  9088, 29889,   450,\n",
            "        11952,   338,   301,  1312,   411, 13814, 29892,  1009,  4024,  3076,\n",
            "          594,  1398,   287,   411,   263, 12875,   310,  3787,  8862, 29879,\n",
            "          322, 18906, 29892, 13182,   292,   472,   278, 16984,  5381,   267,\n",
            "          393,  1246,   445,  2058,  3271, 29889,   450,  2625, 20919,   338,\n",
            "        18758,   411,  6354, 29892,   408,  8939,   342,   374,   550,   748,\n",
            "         1048,  1009, 11005, 29892,  1009, 13994,  4486,  9735,   630,   491,\n",
            "          278,  4964,  3578,   310,   278,  4444,  6575, 29889,   450,  9088,\n",
            "          338,   263, 22395,   310, 17164,  2834, 29892,   988,   278,   298,\n",
            "          504,   280,   322,   289,   504,   280,   310,   278,  2462,  2367,\n",
            "          982,   304,   278, 21732,   322, 11813,   310,   278, 11005])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967, 22981,   263,  2323, 29892,  4796, 26935, 18002,\n",
            "          411,   263, 14671, 21155,   367, 19698,  2768, 29892,  7180,   373,\n",
            "          263,  4796, 12507,  2265, 29889,   450, 18002,   338,  2602,   287,\n",
            "          373,   263,  4796,  7101, 29892,  4969,   263, 10311,   265,  2738,\n",
            "         2927,   282, 26456, 29889,   450, 14671, 21155,   367, 19698, 14661,\n",
            "          263,  3405,   371,   470,   274,   932, 29884,   617,  1789, 29892,\n",
            "          263,  5972,  7348,   363,  1784, 26935,   658,   874, 29889,   450,\n",
            "        23205,   310,   278,  9088, 29892,   411,   967, 13114,  4695,  3161,\n",
            "        29892, 12141, 29879,   278, 10618,   749,   310,   278, 26935, 18002,\n",
            "          322,   278,  2437, 11407,  5469,   310,   278,   367, 19698, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  6114,   338, 13407,   373,\n",
            "          263,  7679, 29891,   714, 24077,  3262, 29892,  5622,   263,  1583,\n",
            "          347,   411,   902,  9008, 29889,  2296,   338, 27121,   297,   263,\n",
            "        16749, 28015,   300,   322,   338,  3063,  4153,   472,   278, 10656,\n",
            "        29889,   450,  3239,  5680,   263,  8541,  2454, 24400,   411,   263,\n",
            "         4094, 11950,  3209, 29883,  9382,  1623,   263,  1886,  1022,  1067,\n",
            "         2593,  3700, 29889,   450, 14744, 18702,   338,   975,  4384, 29892,\n",
            "        23013,   263,  4964,  3578,   975,   278,  9088, 29889,   450,  6114,\n",
            "        29915, 29879,  2602,   373,   278,   714, 24077,  3262, 14661,  1183,\n",
            "          338,   472,   263, 15620,  3171,  2038,   278,  4094, 11950, 29892,\n",
            "        13138,   263,  5412, 18520,   310,   278,  5613, 15409,  2820,   902,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263, 12758,  6635,   338,  1236,\n",
            "         1416,   292,   714,   515,  5742,   263,  4796, 11915, 12417, 29889,\n",
            "          450, 12417,   338,   594,  1398,   287,   411,   263,  2654,   322,\n",
            "         4796,  1423, 14561,  4766, 29892,  4417,   263,  6023,   310,  2927,\n",
            "          304,   278,  9088, 29889,   450,  6635, 29892,   411,   967,  3261,\n",
            "          297,   528,  3076,   310, 16749,   322,  4796, 29892,   338,  3063,\n",
            "         4153,   472,   278, 10656, 29892,   967,  5076,  9432,   292,   263,\n",
            "         4060,   310, 11158, 12137, 29889,   450,  3239,   338,   263,  6501,\n",
            "         7254, 29892, 13138,   263, 18561, 12814,   304,   278,   301, 14643,\n",
            "         3161,   297,   278,   363, 18128, 29889,   450,  6635, 29915, 29879,\n",
            "         2602,  5742,   278, 12417, 10017,   263,  4060,   310, 10809,   297,\n",
            "          278,  1967, 29892, 11580,   278,  6316,   556, 29915, 29879,  8570,\n",
            "          304,   278,   285,  5570, 29915, 29879,   297,  7680,  3321, 12642,\n",
            "        29872, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  1510, 11436,   263, 22556,  1153,  3522,   411,\n",
            "          263, 29191, 13328,   322,  4628,  2927, 11380, 29889,   450,  1153,\n",
            "         3522,   338,  2602,   287,   373,   263,  2654,  1067,   388,  8973,\n",
            "        29892,   607,   338,   263,  3619,  7101,   363, 22556,  7087, 29889,\n",
            "          450,  1153,  3522, 29915, 29879,  6031,   526, 19932,   368,   851,\n",
            "          686, 29892, 23941,   372, 29915, 29879,  7960,   363,  1708, 29889,\n",
            "          450, 14982,  1024,   376, 29911,  1806,  2190, 29902,  5005,   317,\n",
            "         4897,  1525,  2303, 29908,   338,  2504,   262,  2705,  8833,   373,\n",
            "          278,  1153,  3522, 29892, 26233,   372, 29915, 29879,   263,  1880,\n",
            "        29899, 29567,  3234, 29889,   450,  1153,  3522, 29915, 29879,  4386,\n",
            "          322,   330,  6472,   526,  4628, 29892, 13138,   263,  7575, 12814,\n",
            "          304,   278, 13328,  3515, 29889,   450, 12463,  1967,  4076,   263,\n",
            "         4060,   310, 23483,   362,   363,   263,  3748,   310, 22556, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   289,   504,  1847,  9088,\n",
            "          472,   263,  1014,  1582,  5073, 29889,   450,  5073,   338,  2931,\n",
            "         1891,   491,   263,  2919, 29892,  3151,  1490,  2257,  6504,   594,\n",
            "         1398,   287,   411,   263, 29191,  4766,   310,  4796,   322, 16749,\n",
            "        10076,  5547, 29889,   450,  2257,  6504, 29915, 29879,  2874, 12778,\n",
            "          263,  5400,  6023,   304,   278,  6467, 13807,  1014,  1582,  4444,\n",
            "        29889,   450,  5073,   338,  1592, 16242,   411,  2999,   831,  1052,\n",
            "         4097, 29892,  1269,  8236,   304,  1422, 11174, 29889,   450,   831,\n",
            "         1052,  4097,   526,  5279,   297,   671, 29892,   411,  3196,  2305,\n",
            "        12066,  2548,   322,  5153,  2548, 29889,   450,  2305, 29892, 27121,\n",
            "          297,   263, 12875,   310,   714, 29888,  1169, 29892,   788,   263,\n",
            "         4060,   310,  2834,   322, 10298,   304,   278,  6467,  2294,  5177,\n",
            "        29889,  1576,  3578,   292,   297,   278,  5073,   338,  3964, 29892,\n",
            "         4969,   263, 10579,  2730,  1486, 25005, 29889, 19454,   445, 29892,\n",
            "          278,  5073,  5692,   304])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967, 22981,   263,  4333,   310, 15409,  9316, 21050,\n",
            "          373,   263,   282,   682,  3239, 29889,   450,  4452,  3160,   263,\n",
            "          260,  4003,   310, 17441,   303,   860, 29892,   263, 18046,   280,\n",
            "          310,  3287,   291, 29892,   263,   260,  4003,   310, 17441,  6411,\n",
            "        29885, 29892,   263,  5101,   310,   269,   686,   605,   267, 29892,\n",
            "          322,   263,  2319,   282,  3222, 29889,   450,  9316,   526, 28539,\n",
            "          368, 21050, 29892,   411,   278, 17441,   303,   860,   322, 17441,\n",
            "         6411, 29885,  7180,  2446,   304,  1269,   916, 29892,  1550,   278,\n",
            "         3287,   291,   322,   269,   686,   605,   267,   526,  2602,   287,\n",
            "        16949, 29889,   450,   282,   682,  3239,  8128,   263,  4964,   322,\n",
            "         2437, 11407,  1250,  8865,   363,   278,  9316, 29892, 12141,   292,\n",
            "         1009, 11955,   322,  1426,  1973, 29889,   450, 12463, 24628, 14661,\n",
            "          263,  8569,   373,  2071,  3742,   598,   322,  7333,  2562,  4452,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,  2078,   271,   400,  5086,\n",
            "         1776,   310,   263, 15007, 29899, 11911,   287, 14378, 19224, 29889,\n",
            "          450, 19224, 29892,  9654,   300,   287,   297,   263, 12003,  7546,\n",
            "          310, 15007, 29892, 15028, 10067,   342,  1711,  2750,   278,  1250,\n",
            "         8865,   310,   263,  2821, 14744, 29889,   450, 14378, 29915, 29879,\n",
            "        29833,  3192, 28439,   338,   270, 15048,   411, 29234, 10697, 29892,\n",
            "         4417,   263,  6023,   310,   281,  2700,  2264,   304,   278,  6467,\n",
            "          544,   391,   457,  4796, 24400, 29889,   450, 18520,   310,   278,\n",
            "         1967,   338,   515,   263,  5418, 29892, 14372,   363,   263, 15171,\n",
            "         6270,  1776,   310,   278, 14378, 29915, 29879,  6815,   332, 29889,\n",
            "          450, 12463,  9088,   338,   263,  1243,  1166,   304,   278, 15409,\n",
            "          322,   724,   264,   537,   310,  5469, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  2022,   338,  3595,   515,\n",
            "          263,  4482, 10696, 29892, 13407,   373,   263, 11915,   380,  1466,\n",
            "         4878, 29889,   450,  5375,   338,   591,  4362,   263,  5101,   310,\n",
            "         4628,   322,  4796,   269,   484, 21079, 29892,   322,  1009, 21152,\n",
            "          526, 21692, 29889,   450,   380,  1466,  4878,  5692,   304,   367,\n",
            "          297,   385, 18408,  4444, 29892,   411,   263, 11915,  1153,  6504,\n",
            "         7962, 29889,   450,  2022, 29915, 29879,  2602,   373,   278,   380,\n",
            "         7121,   322,  1009,  1098,   533,  4368,   896,  1795,   367,   263,\n",
            "        15645,   470,  4856,  9701,   297,   278,  6931,   310,   278, 24454,\n",
            "        29889,   450,  1967,  4332,  1973,   263,  3256,   310,  1603,  2264,\n",
            "        28655,   303,   825,  1033,   367,   263,   289,   504,  1847,  5177,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,  2078,   271,   400,  5086,\n",
            "         1776,   310,   278,  4646, 14744, 29892,  8022,   630,   491,   278,\n",
            "         3833,  3459,  5307, 15400, 29891, 29889,   450, 15400, 29891, 29892,\n",
            "          263,  6683,  6436,   310,  5469, 29892,   380,  2267,  6609,  4822,\n",
            "          278,  3515, 29892,   967,  4796,   322,  7254,   298,  1041, 12814,\n",
            "          292,  9560,   368,   411,   278,  6501,   261,  3239, 29889,   450,\n",
            "        14744,   338,   263, 10508,   310, 10819, 29892,  1009,  3252,   682,\n",
            "         1847, 26068, 20413,   263,  7623,   310,   278,  6776,  7681, 29889,\n",
            "          512,   278,   363, 18128, 29892,   278, 22024,   339,   309, 23474,\n",
            "        12778,   263,   724,  1600,  1543,   304,   278,  9088, 29892,   967,\n",
            "         7101,  9432,   292,   278,  6432,   342,   616, 26068, 29889,   450,\n",
            "         1967,   338,   263,  1243,  1166,   304,   278, 15409,   322,  6815,\n",
            "          332,   310,  1749, 19859, 29892, 15468,   297,   263,  2323, 29892,\n",
            "          380, 27389,  3515, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  2318,   310,  2305,   526,\n",
            "        13407,   297,  4565,   310,   263, 15655,  5214, 29892,   607,   338,\n",
            "         4486,  9735,   630,   491,   278,  6575,  4366, 24820,  1549,   967,\n",
            "         5417, 29889,   450, 15724,   526, 13587, 11480,   263,  1347,   310,\n",
            "        24841,  6411,   417,   787, 29892,   607,   526, 16526,   297,   278,\n",
            "         4799, 29889,   450,  6411,   417,   787,   526, 21351,   304,   278,\n",
            "         1347, 29892,   322,   278,  2305,  2833,   304,   367, 11418,  5414,\n",
            "          278,  3256, 29889,   450,  5214,   297,   278,  3239, 12778,   263,\n",
            "         4060,   310, 10809,   304,   278,  9088, 29892,   322,   278,  6575,\n",
            "         4366, 10017,   263, 14294,   322,  2437, 11407, 25005, 29889,   450,\n",
            "        12463,   286,  2092,   310,   278,  1967,   338, 22794,  1319,   322,\n",
            "        10894,  7606, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967, 22981,   263,   724,  1600,  1399, 16946,  4444,\n",
            "        29889,   319,  4796,   325,   559, 29892, 10423,   411,   301,  1878,\n",
            "         7933,   708, 29892,   269,  1169,   373,   263,   544,   391,   457,\n",
            "         4796,  7101, 29889,   450,   325,   559, 29892,   411,   967,  2560,\n",
            "        10618,   749, 29892, 12955,   263,  2319, 29892, 11158,  9593,  1302,\n",
            "         2496, 29899,  2780,   287, 26224, 17039,   545, 29889,   450, 17039,\n",
            "          545, 29892,   411,   967, 26224, 16716, 29892, 12778,   263,  6023,\n",
            "          310,  5400,   537,   304,   278,  6467,  5613,   322,  2894,   293,\n",
            "         9088, 29889,   450, 12463, 15259, 10017,   263, 10311,   265,  2738,\n",
            "         1999,   355,   310,  5469,   322,  1616, 29892,  3415, 17223,   263,\n",
            "         4060,   310, 22024,   339,  1793,   322,   263,   342, 29882,  7492,\n",
            "         5108,   362, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  7303,   338, 15468,   297,\n",
            "          263,   724,  1600,  4444, 29892, 16246,   373,   263, 27278,  3856,\n",
            "          305,   297,   263, 13569, 29889,   450,   767,   338, 27121,   297,\n",
            "          263,  7254, 14726, 29892,  1550,   278,  6114,   338,   594,  1398,\n",
            "          287,   297,   263,  7254, 10714, 29892,  1716, 19595,   287,   491,\n",
            "         4796,  2343, 14494,  1960, 29889,   450,   767, 29915, 29879,  1098,\n",
            "          533,   338,  8676,   411,   263,  4628,  3056, 29892,   322,   540,\n",
            "        14717,   263,  5101,   310,   269,   686,   605,   267, 29889,   450,\n",
            "         7303,   338,  2602,   287,   297,  4565,   310,   263,  2919,  5447,\n",
            "        29892,   607, 15028,   408,   263,  1243,  1166,   304,   278,  5613,\n",
            "        15409,   310,  1009,  8388,   618,   886, 29889,   450, 13569,  2820,\n",
            "          963,   338,   301,  1878,   322,  7933, 29892, 13138,   263, 22024,\n",
            "          339,   309,  1250,  8865,   304,  1009,  3256,   310,  3996,   621,\n",
            "          824,   404, 29889,   450,  1967,   429,  8192,   263,  4060,   310,\n",
            "        10776,   322, 10311,  2592, 29892,   408,   278,  7303,  2444])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,   767,   338,  3595,  3033,\n",
            "         6751,   297,   278,  1044,   310,  1560, 17223,   263, 14282, 29889,\n",
            "          940,   338, 27121,   297,   263, 16749,   298,  2092,   347,   322,\n",
            "          263,   367,  6067, 29892,  6820,  1075,   263,  3209,   950,   322,\n",
            "        26681,   287, 10097, 29889,   450, 14282,   540,   338,  1560, 17223,\n",
            "          338,  1754,   310,  2821, 12917, 29892, 14372,   502,   304,  1074,\n",
            "          278,   304, 29890, 17970,  2768, 29889,   940,   338, 13587,   278,\n",
            "        14282,   297,   670,  1492,  1361, 29892,  1550,   670,  2175,  1361,\n",
            "          338, 13587,   263,   301, 14643, 29892, 26233,   393,   540,   338,\n",
            "          297,   278,  1889,   310,  3578,   292,   278,   304, 29890, 17970,\n",
            "        29889,   450,  3239,   338,  1999,   332,  1127, 29892, 11580,  8569,\n",
            "          304,   278,   767,   322,   670,  6354, 29889,   450, 12463,  9088,\n",
            "        14661,   263,  3256,   310,   454,   275,   545,   470, 26681,   362,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  2022,   338,   409,   630,\n",
            "          472,   263,   553, 29895,   297,   263,  3964,   368, 11872,  5716,\n",
            "        29892,  3033,  2124,   287,   297,   664,   373,   263,  6601, 29889,\n",
            "          450,  5375,   338,   591,  4362,   263,  7933,   260, 29899,   845,\n",
            "         2728,   322,   263, 21573,  2117, 29892, 26233,   263,  3209,   950,\n",
            "          664,  5177, 29889,   450,   553, 29895,   338,  1592, 16242,   411,\n",
            "          263,  6601, 11819, 29892, 12247, 29892,   322,  9495, 29892, 23941,\n",
            "          263, 10257,  4444, 29889,   450,  5716,   756,   263,  3474,   411,\n",
            "         1999, 12772, 29892, 14372,   363,  5613,  3578,   304,  3896, 29889,\n",
            "          450, 12463, 25005,   310,   278,  1967,   338,   697,   310,  8569,\n",
            "          322,  3234,  2068, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  4123,   767,   338, 19911,\n",
            "         3730,   364,  4821,   263,  2071,   403,  3377,   373,   263, 20305,\n",
            "         8973, 29889,   940,   338,   297,   278, 29214,   310, 15859,   263,\n",
            "         8938, 29892,  6411, 19985,   373,   697,  3661,  1550,   278,   916,\n",
            "         3661,   338,   373,   278,  2071,   403,  3377, 29889,   450,  8973,\n",
            "          338,   427, 15603,   491,   263,  4628,   285,   663, 29892,   322,\n",
            "          263,  4796, 20305,  5089,   459, 15028,  2504,   262,  2705,   297,\n",
            "          278,  3239, 29889,   450,   767,   338, 27121,   297,  3209,   950,\n",
            "         1098,   533, 29892,   322,   670,  8569,   322,  3683,  3381,   526,\n",
            "        13602,   408,   540, 24138,   670,  8938, 29889,   450,  1967,  4332,\n",
            "         1973,   263,  3256,   310, 28563,   293,  1608,   322, 19911, 29892,\n",
            "          731,  2750,   278,  1250,  8865,   310,   385, 17164, 20305,  8973,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967, 22981,   263,  3802, 29899,   786,  1776,   310,\n",
            "          263,  1766, 26323,  1648,  8024, 29892,  1510, 29883,  5832,   967,\n",
            "          325,  4626,   424,  3708,   552,   322,  7933,   298,  1041, 29889,\n",
            "          450,  8024,   338,  6245,   873,  4870,   287,   411,  2319, 29892,\n",
            "         4513,  8619, 29879, 29892,  4221,  1230,   310,   967,   286,  1535,\n",
            "         7408, 29889,   450, 11308, 29892, 10371, 11407,   263,  6837,   310,\n",
            "         3708,   552,   322,  7933, 29892,   526, 21050,   297,   263,  6337,\n",
            "          284,  4766, 29892,   263, 17443,  4682,   310,  1766, 26323,  1648,\n",
            "        18577, 29889,   450,  3239,   338,  1999,   332,  1127, 29892, 11580,\n",
            "         8569,   304,   278,  8024, 29892,   322,   278, 12463, 15259,   310,\n",
            "          278,  1967, 14661,   263,  5613, 29892,   714, 17433,  4444, 29889,\n",
            "          450,  1967,  8128,   263, 13173,  1106,   472,   278,  8024, 29915,\n",
            "        29879,  3829,   322,  2927,   362, 29892, 27032,   263,   330, 12552,\n",
            "          344,   964,   278,  3186,   310,  1766, 26323,  1648, 18834,   362,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  1510, 11436,   263,   325,   524,   482,   318,\n",
            "          558,   523, 11914, 29892,   429,   566,   292,   385,  4799,   310,\n",
            "        20990,  9564,   423, 29889,   450, 11914, 29892,   411,   967,  6501,\n",
            "         8112,  8341, 29892,   338,   594,  1398,   287,   411,   263,  2654,\n",
            "          451, 19273,   322,   263,  4796,  9869,   310,  4696, 29892, 26233,\n",
            "          263,  9636,  6944,  4867, 29889,   319, 29205,   278, 11914, 29892,\n",
            "          263,  4796, 28692,   411,   263,  7933,  8024, 12778,   263,  6023,\n",
            "          310,  3632,   295,  3335, 29889,  1763,   278,  1492,   310,   278,\n",
            "        11914, 29892,   263,  5096,   310,  8277,   338, 28539,   368, 21050,\n",
            "        29892, 13182,   292,   472,   263, 21344,   368,   470,  1616,  4695,\n",
            "         4066, 29889,   450, 12463,  9088,  6788,  1372,   263,  7623,   310,\n",
            "          263,  1302,  1537, 29892, 10600, 29899,   262,  2913, 29892,   988,\n",
            "         4696,   322, 12845,   526, 14954,  3276, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  2318,   310,  2305,   526,\n",
            "        15468,   297,  7145, 29899,   303,  2426, 29892,  2734,  3412,   263,\n",
            "        11952,   393,   380,  2267,  6609,   714,   964,   278,  5418, 29889,\n",
            "          450,  6575,   338,  4482,   297,   278, 14744, 29892, 23013,   263,\n",
            "        14294,   330,   677,   975,   278,  9088,   322,  4969,  1472,   528,\n",
            "        23626,   373,   278,  5962, 29889,   450, 13814,   297,   278,  3239,\n",
            "          526,  4047, 10774,  1803,   287,  2750,   278, 14744, 29892,  4417,\n",
            "        10809,   304,   278,  1967, 29889,   450, 12463, 25005,   338,   697,\n",
            "          310, 10884,   322,  5864, 29892,   408,   278,  1065,  8397,  2615,\n",
            "          304,   367,   297,   278, 29214,   310,   263,  8175,   470,   263,\n",
            "         3209,   950,  1065, 29889,   450,  6575,   842, 12778,   263,   724,\n",
            "         1600,  1250,  8865,   304,   278,  7343,  3158,   310,   278,  1065,\n",
            "         8397, 29892,  4969,   263, 29191, 12814,  1546,   278,  5613,   322,\n",
            "          278,  5199,  3161,   297,   278,  9088, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  4123,   767,   411,   263,\n",
            "         8359,   573, 26414,  9307,  3277,   338,   278,  6555,  4377, 29889,\n",
            "          940,   338, 15468,   297,   263,  3802, 29899,   786, 10322, 29892,\n",
            "          670, 12642, 29872, 10624,  1283,   304,   278,  2625, 29892,  6820,\n",
            "          278, 17188,   310,  6483,  2714,   470,   640, 16305,   362, 29889,\n",
            "         3600, 19309,   338,   263,  3578, 17354,  2927, 29892,   322,   670,\n",
            "        11315,   338, 15877,   839,   297, 21005,   908, 29879, 29889,   940,\n",
            "          338,   591,  4362,   263, 13283,  9704, 18873,  1265, 29892,  4417,\n",
            "          263,  6023,   310, 10618,   749,   304,   670, 10097, 29889,   450,\n",
            "         3239,   338,   263,  8656,  4796, 29892,   607, 15223,   278,  8569,\n",
            "         9186,   373,  1075, 29889,   450, 12463, 15259,   310,   278,  1967,\n",
            "        14661,   263,  4060,   310, 25956, 27988,   322,  5375,   537, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,  2078,   271,   400,  5086,\n",
            "         1776,   310,   263,  3151,  1490, 12945, 29892, 13319,   515,   380,\n",
            "          332,  4518, 18387, 29892,   393, 17659,  3730,  3190,   267,   975,\n",
            "          263,  6483, 19599, 29889,   450, 12945, 29892,   411,   967, 16424,\n",
            "         3829, 29892, 19700,   408,   263, 27131,  3957,  1546,  1023, 19372,\n",
            "          292,  1067, 28324, 29889,   450, 18830, 24400,   338,   263,  1243,\n",
            "         1166,   304,   278, 29833,  3192, 15409,   310,  5469, 29892,   411,\n",
            "          278, 12868,   424,  7933,   708,   310,   278,  1067, 28324, 12814,\n",
            "          292,   411,   278,  2821,  7254, 14744, 29889,   450, 18520,   310,\n",
            "          278,  1967, 29892,  4586,   515,   263,  5418, 29892,  6511,   363,\n",
            "          263, 15171,  6270,  1776,   310,   278, 12945,   322,   967,  8388,\n",
            "          618,   886, 29892, 19310,  5281,   278, 21210,   573, 21639,  1238,\n",
            "          271, 28655,   303,   278,  5613,  6815,   332, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  1361,   338,  3595, 13587,\n",
            "          263, 12917,   310, 14671, 21155,   367, 19698, 29892, 10075,   263,\n",
            "         3405,   371,   470,   263,   274,   932, 29884,   617,  1789, 29892,\n",
            "         2750,   263,  1250,  8865,   310,  3252,   682,  1847,  4796, 26068,\n",
            "        29889,   450, 12917,   338, 10423,   304,   278,  1506,   326, 29892,\n",
            "          411,   278, 14671, 21155,   367, 19698, 21534,   304,   367,   263,\n",
            "         3578, 17354,  2927, 29889,   450,  1361,   338,  2602,   287,   297,\n",
            "         1316,   263,   982,   393,   278, 12917,   338,  4934,   701,   304,\n",
            "          278, 10656, 29892, 14372,   278,  6316,   556,   304,  1074,   278,\n",
            "          367, 19698, 29915, 29879, 18459,   322,  2927, 29889,   450,  4796,\n",
            "        26068,   297,   278,  3239,  1653,   263, 10982,   573,   322,  1302,\n",
            "         1537, 25005, 29892, 26233,   393,   278, 15373,  1795,   505,  1063,\n",
            "         4586,  2645,   263,  8753, 22394,  4259,   470,   263,  4266, 10039,\n",
            "        29889,   450, 12463, 15259,   310,   278,  1967,   378,   345,   952,\n",
            "          263,  4060,   310, 14294,   386,   322, 10894,   362, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   325,  4626,   424,  4646,\n",
            "         9088,   373,   263,   289,   504,  1847, 11952,   297,   385, 20021,\n",
            "         4272, 29889,   450, 11952,   338,   301,  1312,   411,   263, 12875,\n",
            "          310,   528,  3554,   322, 12374,  1934, 29892,  1009, 18906,   322,\n",
            "        26068,   330,   677,   292,  2750,   278,  6501, 14744, 29889,   319,\n",
            "         6114,   338,  3595, 22049,   373,   278,  2625, 20919, 29892,   902,\n",
            "         4377,  4486,  9735,   630,   491,   278, 25040,  3578, 29889,   450,\n",
            "        11952,   338, 19587,   411,  6354, 29892,   411,  2305,   322, 24413,\n",
            "         4417,   304,   278,   301,  3598, 25005, 29889,   450, 13814, 29892,\n",
            "        18906, 29892,   322,  2305,   599, 29126,   304,   263,  4060,   310,\n",
            "        17164,  2834,   322, 16375,  6894,   537, 29889,   450,  1967,   338,\n",
            "          263, 22395,   310,  1432,  3250,  2834,   297,   445,  4272, 29892,\n",
            "         1510, 29883,  5832,   278,  5864,   322,  4292,  1608,   310,   278,\n",
            "         2058, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263, 26373,   653,  4377, 15028,\n",
            "          373,   263,  7679, 29891,   714, 29883,  1336, 29892,   975, 23261,\n",
            "          263,   724,  1600, 19437, 29889,   450,  2022,   338,  1067,   328,\n",
            "          297,   263, 13328, 28015,   300, 29892, 13138,   263,   325,  4626,\n",
            "          424, 12814,   304,   278,  5613,  8388,   618,   886, 29889,   450,\n",
            "        19437, 29892,   263, 19571,   310, 22024,   339,  1793, 29892,   338,\n",
            "        17763,   839, 28655,   303,   263, 24400,   310, 10697,   322, 19223,\n",
            "        29889,   450, 14744, 18702,   338, 10423,   411, 27091, 29892, 23013,\n",
            "          263,  4964,  3578,   975,   278,  9088, 29889,   450, 12463, 25005,\n",
            "          338,   697,   310,   899,  4279,   322, 10776, 29892,   408,   278,\n",
            "         2022,  2444,   304,   367,  5714,   297,   278, 15409,   310,  5469,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   724,  1600,  1120,  1227,\n",
            "         9088, 29889,   319,   281,  4015,   270,  2728,  2224, 29892,  9654,\n",
            "          300,   287,   297, 19225, 11308, 29892,   592,   392,   414,  1549,\n",
            "          263, 20619, 13569, 29889,   450,  2224, 29892, 21534,   408,   263,\n",
            "        16835, 18130,  6718, 29892,   338, 22047,   491,   263,  1773,  4279,\n",
            "          310, 10697, 29892,  1009, 11308,   263,   325,  4626,   424,  6837,\n",
            "          310, 24841,   322, 13328, 29889,   450, 13569,   338, 20619, 29892,\n",
            "          411,   278,  2224, 25417,   292,   964,   278,  5418, 29892,  2437,\n",
            "        11407,   278,  6316,   556,   304, 14034,   278, 16342,   393, 12185,\n",
            "        14432, 29889,   450, 12463, 25005,   338,   697,   310, 22024,   339,\n",
            "         1793,   322,   278, 15409,   310,  5469, 29915, 29879,  4259,   284,\n",
            "        13852, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   724,  1600,  1120,  1227,\n",
            "         9088,   373,   263, 20201,   616, 11952, 29889,   319,  4628,   319,\n",
            "         4749,  1559,   338, 14089,   287,   373,   278,  2625,   310,   278,\n",
            "         6520, 29892,   967, 12844,  1416,  2874, 12814,   292,   411,   278,\n",
            "          325,  4626,   424, 11955,   310,   278,  4259, 29889,   450,  1559,\n",
            "          338, 22047,   491, 19225, 11308, 29892,  1009,   298,  1041,   310,\n",
            "        24841,   322, 13328,  4969,   263,  9560,  1559, 10963,   373,   278,\n",
            "          408,   561,  1997, 29889,   450, 11952,   338,   301,  1312,   411,\n",
            "        10697, 29892,  1009, 11308,   263,  6837,   310, 24841,   322, 13328,\n",
            "        29892,  4221,  1230,   310,   278,  4259, 29889,   512,   278,  3239,\n",
            "        29892,   263,  4796,  3699,   508,   367,  3595, 29892,  4417,   304,\n",
            "          278,  1014, 25006, 21192,   310,   278,  9088, 29889,   450, 12463,\n",
            "        25005,   338,   697,   310, 22024,   339,  1793,   322, 15409, 29892,\n",
            "          263, 22395,   310,  2834, 29915, 29879,  2560,  5644, 25414, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278, 22024,   339,   309,  4444,   310,   263,  4091,\n",
            "          340,  3573,   310,  4094, 29892,   263,  2323,  1652, 11500, 29877,\n",
            "        15028, 10067,   342,  1711, 29889,  8011,   325,  4626,   424,   282,\n",
            "          682,   715,   398,   482, 12814, 29879,  9560,   368,   411,   278,\n",
            "         6501,   261,   298,  1041,   310,   278,  4094, 29889,   450,  1652,\n",
            "        11500, 29877, 29892, 14870,  7113,   278,  1492,  2625,   310,   278,\n",
            "         1967, 29892,  5692,   304,   367,   297,   263,  2106,   310,  1791,\n",
            "        29892,   967,  2343, 10029,   260,  2782,   287,  1623,  2935, 29889,\n",
            "          450,  4094,  2820,   372,   338, 21732, 29892,   411,  2319,   364,\n",
            "         8377,   793,   330,  2705, 29543,   292,   278,  7101, 29889,   450,\n",
            "         1652, 11500, 29877, 29915, 29879,  2602,   297,   278,  4818,   310,\n",
            "          278,  1967,  4216, 29879,   278,  6316,   556, 29915, 29879,  8570,\n",
            "        29892,  3907,   372,   278, 12789,   284,  1298,   310,   445,   724,\n",
            "         1600,  9088, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   724,  1600,  1120,  1227,\n",
            "         9088,   297,   263, 13569, 29889,   450, 13569,   338, 10423,   411,\n",
            "        15655, 29892,  2243,  1581, 10697,   393,   505,  6077,   263,   325,\n",
            "         4626,   424, 13328, 29892, 23941,   278,  4259, 29889,   450,  6575,\n",
            "         4366, 18094,  1549,   278,   508,  2270, 29892, 23013,   263, 14294,\n",
            "          330,   677,   373,   278,  5962,  2400, 29889,   450, 13569, 11904,\n",
            "          338, 10664,   297, 19225, 11308, 29892,  4417,   304,   278,  1120,\n",
            "         1227,   284,  3181,  8837, 29889,   512,   278,   363, 18128, 29892,\n",
            "          263,  2919,   289,   483,   261,   508,   367,  3595, 29892, 13138,\n",
            "          263,  4060,   310,  6287,   322, 10809,   304,   278,  9088, 29889,\n",
            "          450, 12463, 25005,   338,   697,   310, 22024,   339,  1793,   322,\n",
            "         5613, 15409, 29892,   263,  1243,  1166,   304,   278,  6480, 20084,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  2022,   338, 13407,   373,\n",
            "          263,  7679, 29891,   714, 29883,  1336, 29892,   975, 23261,   263,\n",
            "        13426, 24400, 29889,   450,  5375,   338, 27121,   297,   263,  4628,\n",
            "        28015,   300,   322,  4628,   282,  1934, 29892,   411,   263,  4628,\n",
            "          367,  6067, 21653,  1009,  2343, 29889,  2688,   526, 13587,   263,\n",
            "        10656, 29892, 26233,   896,  1795,   367,   263, 17739,   261,  4332,\n",
            "         3864,   278,  2078,   271,   400,  5086,  1776, 29889,   450,  6575,\n",
            "          338,  4444,   297,   278,  3239, 29892, 23013,   263, 14294,   330,\n",
            "          677,   975,   278,  9088, 29889,   450, 24400,   338, 29833,  3192,\n",
            "          322,  7679, 29891, 29892,   411,   263,  6837,   310, 17455,   322,\n",
            "        14653, 23954, 29574,  4822,   278, 28439, 29889,   450,  2022, 29915,\n",
            "        29879,  2602,   373,   278,  7679, 29891,   714, 29883,  1336,  8128,\n",
            "          263,   325,  8501,  1298,   515,   607,   304, 11188,   278, 15409,\n",
            "          310,   278, 18830,  5177, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967, 22981,   263,  4333,   310, 15409,   322,  2071,\n",
            "         3742,   598,  9316, 21050,   373,   263,   282,   682,  3239, 29889,\n",
            "          450,  4452,  3160,   263, 12875,   310, 18046,   793, 29892,   263,\n",
            "         5101,   310,  7684, 29899,  2780,   287,   885,   790,   943, 29892,\n",
            "          263,   282,   682, 11315, 20102, 29892,   322,   263,   282,   682,\n",
            "        11315, 22134, 29889,   450,  9316,   526, 28539,   368, 21050, 29892,\n",
            "          411,   777,  7180,   373,   263,   282,   682,  7679,   322,  4045,\n",
            "          373,   263,   282,   682, 18187, 29889,   450, 12463,   263,   342,\n",
            "        29882,  7492, 14661,   263,  8569,   373, 15409,   322,  7333,  2562,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   724,  1600,  1120,  1227,\n",
            "         9088, 29892,  8022,   630,   491,   278,   301,  1878,  7933,   708,\n",
            "          310,   263,   282,   457,  5447, 29889,   450,  5447, 29892,   411,\n",
            "          967, 20619,   900, 29875,   482, 29892, 15028,   408,   263,  1243,\n",
            "         1166,   304,   278,   620,  2638,   663,   310,  5469, 29889,  4124,\n",
            "         1028,   414,   287,  4249,   278,  7933,   817,   793,   526, 19225,\n",
            "        11308, 29892,  1009,   325,  4626,   424,   298,  1041,   310, 24841,\n",
            "          322, 13328,  4417,   263,  8536,  1161,   310,  2927,   304,   278,\n",
            "         6467,  1601,  2878,   456,  2454,   282, 26456, 29889,   450, 11308,\n",
            "        29892, 29574,   447,   561,   834,   538,   368, 29892, 13182,   472,\n",
            "          278,  6480, 20084,   322,   278,  5447, 29915, 29879,  1303,  3335,\n",
            "          304, 28453,   967, 11308,   297, 10223,   362,   363,   278, 13851,\n",
            "         7378, 29889,   450,  1967, 29892,  4586,   515,   263,  4482, 10696,\n",
            "        29892, 26371,  2925,   278,  5447, 29915, 29879,  7275,   292, 10122,\n",
            "        29892,  3907,   372,  2615,   408,   263, 19372,   292,  2665])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  2022,   338,   409,   630,\n",
            "          472,   263,   553, 29895, 29892,  3033,  2124,   287,   297,   664,\n",
            "          373,   263, 19022, 29889,   450, 19022,  4315, 14423,   263,  1899,\n",
            "         1196,  5067, 29892, 26233,   393,   278,  1404,  1795,   367,  9701,\n",
            "          297, 14137,   470,  1788, 17517,  9595, 29889,   450,   553, 29895,\n",
            "          338,  1592, 16242,   411,  1023,  1601, 17259, 29892,   697,   310,\n",
            "          607,   338,  6077,  1283, 29892,  1550,   278,   916,   338, 16384,\n",
            "          263, 24499, 29889,   450,  2022,   338,   591,  4362,   263, 13328,\n",
            "         4105,   346,  1026, 29892,  4417,   263,  7333,  6023,   304,   278,\n",
            "        10257,  4444, 29889,   450, 12463,  9088, 14661,   263,  5400,   664,\n",
            "         3493,   988, 15483, 13582,   263,  7282,  6297,   297,   278,  5375,\n",
            "        29915, 29879, 14218,  9595, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   724,  1600, 24400,   988,\n",
            "          263,  8580, 24536,   330,  2705,  1549,   263,   301,  1878, 29892,\n",
            "          363,  2868, 19599, 29889,   450,  8580, 29892,   263,  6483,   528,\n",
            "         1943,   310,  7254, 29892,   338, 17763,   839, 28655,   303,   278,\n",
            "        12868,   424,  7933,   708,   310,   278, 18830, 10697, 29889,   319,\n",
            "        29205, 29892,   278, 14744,   338,   263, 10508,   310,   975,  4384,\n",
            "        27091, 29892, 23013,   263,  4964, 29892,  2923,  3880,  3578,   975,\n",
            "          278,  9088, 29889,   450, 18520,   310,   278,  1967,   338,   515,\n",
            "          263,  1880,   325,  8501,  1298, 29892, 27032,   263,  7243,   272,\n",
            "          314,   293,  1776,   310,   278,  8580,   322,   278, 19599, 29889,\n",
            "          450, 12463, 25005,   338,   697,   310, 22024,   339,  1793,   322,\n",
            "         5613, 15409, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   325,  4626,   424,  4272,\n",
            "         9088, 29892,  8022,   630,   491,   263,  2919,  5214,   411,   263,\n",
            "         8359,   573,  4024,  1943, 29889,   450,  5214, 29915, 29879, 25591,\n",
            "          338,   594,  1398,   287,   411,   263,  6856,   310, 12917,  7243,\n",
            "         1379, 29892,  4969,   263,  5400,   322, 12844,  1416, 10097, 29889,\n",
            "          450,  5214, 29915, 29879,  2874,   338,  4340,  1035,   296, 29884,\n",
            "          630,   491,   278, 10122,   310,  5112, 29885, 10697, 29892,  4417,\n",
            "          263,  6023,   310,  5469,   304,   278, 17164, 24400, 29889,   450,\n",
            "         5112, 29885, 10697,   526, 29574, 10106,   278,  9088, 29892,  1009,\n",
            "          301,  1878,  7933, 11308, 12814,   292,   411,   278,  5214, 29915,\n",
            "        29879, 12917,  4024,  1943, 29889,   450,  1967,   884,  7805,   263,\n",
            "         2022, 29892,  4417,   263,  5199,  1543,   304,   278,  9088, 29889,\n",
            "          450, 12463, 15259,   310,   278,  1967, 14661,   263,   289,   504,\n",
            "         1847,  4272,  5177, 29892,   988,  5469,   322, 11258,  1302, 28997,\n",
            "        29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  6114,   338,  3595, 13407,\n",
            "          297,  4565,   310,   263, 13807, 10369, 17567, 29889,  2296,   338,\n",
            "        27121,   297,   263,  4796,   413,   326,  3231, 29892,   607,   338,\n",
            "          594,  1398,   287,   411,   263, 28149,   373,   902, 11315, 29889,\n",
            "          450, 17567, 29892,  2931,  1891,   491,   967,  2654,   322, 24841,\n",
            "          298,  1041, 29892,  5680,   263,  2919, 27278, 12417,   322,   263,\n",
            "          260,  2356, 17526, 29889,   450,  6114,   338,  2602,   287,   373,\n",
            "          263, 27278, 19810, 29892,  3063,   714,  7113,   263,  4272, 29879,\n",
            "         5738,   393,   380,  2267,  6609,   714,   297,   278,  3239, 29889,\n",
            "          450, 12463,  9088,  4332,  1973,   263,  3256,   310, 22024,   339,\n",
            "         1793,   322, 16375,  5108,   362, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  4123,  6114,   338, 15468,\n",
            "          297,   263,  3256,   310,  1708,  1319,  2264, 29889,  2296,   338,\n",
            "        13407,   373,   263, 27278, 11904, 29892,   902,  3573, 20793,   292,\n",
            "         6375,   411,   263, 17819,   373,   902,  3700, 29889,  2439,  1472,\n",
            "         1999, 13469, 11315,  3209, 29883,  3076,  1623, 29892, 12814,   292,\n",
            "          411,   902,  4628,   322,  4796,  1423, 14561,   282,  1934, 29889,\n",
            "          512,   902,  6567, 29892,  1183,  8640,   263, 17354,  3056, 29892,\n",
            "         6060,   263,  3107,   363,   263,  3748,   470,   263,  5829,   310,\n",
            "          902,  2562,  9021,  8548, 29889,   450,  3239,   338,  2560,   322,\n",
            "          443,   695,  6463,   287, 29892, 14372,   278,  6316,   556,   304,\n",
            "         8569,   373,   278,  6114,   322,   902,  8820, 29889,   450, 12463,\n",
            "        25005,   310,   278,  1967,   338,  3578, 29899, 23057,   287,   322,\n",
            "        15331,  1319, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   591,   526,  2183,   263, 11199,\n",
            "        29915, 29879, 10977,  1776,   515,  2768,   263,  9121,  1081,   293,\n",
            "        19959, 29889,   450,  1081,   293, 19959,   338,  1592, 16242,   411,\n",
            "          263,  2919,  3474, 29892,  1549,   607,   591,   508,  1074,   278,\n",
            "        13426,  1518, 12350,   310,   278, 14744, 29889,   450, 14744,   338,\n",
            "        23139,   297,   298,  1041,   310, 24841,   322,  7254, 29892, 26233,\n",
            "          393,   278, 15373,   471,  4586,  2645,  6575,   842, 29889,   450,\n",
            "         1081,   293, 19959,   338,   451,  7432,   297,   278, 14744, 29936,\n",
            "          372,   338, 21302,   491,  3196,   916,  1081,   293,   459,  2153,\n",
            "        29892,   599,   310,   607,   526, 22764,   297,   278,  1021,  5305,\n",
            "        29889,   450,  1081,   293,   459,  2153,   526,  9677,   714,  4822,\n",
            "          278, 14744, 29892,  4969,   263,  4060,   310, 10809,   322,  5418,\n",
            "        29889,   450,  1967,  4332,  1973,   263,  3256,   310, 22024,   339,\n",
            "         1793,   322,   899,  4279, 29892,   408,   278,  1081,   293,   459,\n",
            "         2153, 23624,   278,  1722, 14744, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   450,  1967,  4332,  1973,   263,   724,  1600,  9088,   310,\n",
            "          263, 27278,  3699, 17763,   839, 28655,   303,  5469, 29889,   450,\n",
            "         3699, 29892,   411,   967, 17354, 25591, 29892, 15028,   714,  2750,\n",
            "          278,   301,  1878,  7933,   708,   393,  8388,  3885,   372, 29889,\n",
            "          450,  3699,   338, 22047,   491,   263,  1532, 29899, 29885,  2365,\n",
            "         7114, 16423, 29892,   734,   331,   292,   411,   263, 12875,   310,\n",
            "        18577,   322, 10697, 29889,   450, 16423,   338,   427, 15603,   491,\n",
            "          263,   380,   332,  4518, 27278,   285,   663, 29892,  4417,   304,\n",
            "          278, 21580,   293, 21192,   310,   278,  4444, 29889,   450, 14744,\n",
            "         2038,   338,   263,  2821,  7254, 29892, 26233,   263, 11785,   322,\n",
            "         6575,  1460,  2462, 29889,   450, 12463, 25005,   310,   278,  1967,\n",
            "          338, 10776,  1319,   322,  1178,  2904,   506, 29892,  3415, 17223,\n",
            "          263,  4060,   310, 22024,   339,  1793,   322, 10311,  2592,   411,\n",
            "         5469, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "tokens: tensor([    1,   512,   278,  1967, 29892,   263,  6114,   411,   263,   528,\n",
            "        10511,  2343,   322,   263, 26414,  9307,  3277,   338,   278,  6555,\n",
            "         4377, 29889,  2296,   338, 27121,   297,   263,  4796, 29892,   425,\n",
            "          346, 29899, 15450,  2168,  2246,   322,   338,  3595,   515,   278,\n",
            "         1250, 29892,   411,   902,  6567,  7180,   373,   902,  2343, 29889,\n",
            "          450,  3239,  5680,   263,  1999,   332,  1127,  4272, 29879,  5738,\n",
            "        29892, 26233,   385, 17164,  4444, 29889,   450,  6114, 29915, 29879,\n",
            "        18593,   322,   278,  4272, 29915, 29879,  1250,  8865,  1653,   263,\n",
            "        12814,  1546,   278, 13173, 29892,  1426,  2955,  1067,  6046,   322,\n",
            "          278,  4964, 29892,  1399,   391,  5562,  4272,  5177, 29889,   450,\n",
            "         1967,  4332,  1973,   263,  3256,   310, 11813, 25956, 27988, 28655,\n",
            "          303,   278,   289,   504,  1847,  4272,  2834, 29889])\n",
            "Encoding\n",
            "0 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n",
            "1 out of 2\n",
            "encoded:  0 out of 8\n",
            "encoded:  1 out of 8\n",
            "encoded:  2 out of 8\n",
            "encoded:  3 out of 8\n",
            "encoded:  4 out of 8\n",
            "encoded:  5 out of 8\n",
            "encoded:  6 out of 8\n",
            "encoded:  7 out of 8\n"
          ]
        }
      ],
      "source": [
        "evaluation(llama_zip, df)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [],
      "source": [
        "df.to_csv(f\"{config['dataset']}_llava_1.6_vicuna.csv\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {},
      "source": [
        "# Ablation Study"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "overall_description    The image presents a modern and stylish bar se...\n",
            "zlib_len                                                          598960\n",
            "dtype: object\n"
          ]
        }
      ],
      "source": [
        "import zlib\n",
        "df['zlib_len'] = df['overall_description'].apply(lambda x: len(zlib.compress(x.encode('utf-8'))) * 8)\n",
        "\n",
        "# 結果を表示\n",
        "print(df[['overall_description', 'zlib_len']].sum())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {},
      "outputs": [],
      "source": [
        "zlib_len_sum = df['zlib_len'].sum()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "598960\n"
          ]
        }
      ],
      "source": [
        "print(zlib_len_sum)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {},
      "outputs": [
        {
          "data": {
            "text/plain": [
              "56.72743252867816"
            ]
          },
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