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  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/catastropiyush/TransformerAsOn/blob/master/Phase_transitions_LLMs.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aZ6hCqjAv7H_",
        "outputId": "2dcb88ef-87f5-4e6f-85cd-64cbc9122572"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Writing requirements.txt\n"
          ]
        }
      ],
      "source": [
        "%%writefile requirements.txt\n",
        "scipy\n",
        "matplotlib\n",
        "datasets\n",
        "vllm\n",
        "accelerate>=0.26.0"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install -r requirements.txt"
      ],
      "metadata": {
        "collapsed": true,
        "id": "0qmV6Q6iw5g9"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install huggingface_hub"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "v-aG-tUpyCcw",
        "outputId": "074deee6-1320-48bd-ebb0-591c1f9e7e34"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: huggingface_hub in /usr/local/lib/python3.11/dist-packages (0.28.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (3.17.0)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (2024.9.0)\n",
            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (24.2)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (6.0.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (2.32.3)\n",
            "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (4.67.1)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.11/dist-packages (from huggingface_hub) (4.12.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (3.4.1)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (3.10)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (2.3.0)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.11/dist-packages (from requests->huggingface_hub) (2025.1.31)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from huggingface_hub import notebook_login\n",
        "\n",
        "notebook_login()"
      ],
      "metadata": {
        "id": "BTjQ8T3g3rXN"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import json\n",
        "import numpy as np\n",
        "from huggingface_hub import snapshot_download\n",
        "os.environ[\"VLLM_LOGGING_LEVEL\"] = \"ERROR\"\n",
        "\n",
        "import torch\n",
        "import torch.distributed as dist\n",
        "from datasets import load_dataset\n",
        "from vllm import LLM, SamplingParams\n",
        "\n",
        "!mkdir -p \"/content/models\"\n",
        "!mkdir -p \"/content/outputs\"\n",
        "\n",
        "def download_model(model_name):\n",
        "    print(f\"Downloading {model_name}...\")\n",
        "    local_path = f\"/content/models/{model_name.split('/')[-1]}\"\n",
        "\n",
        "    if not os.path.exists(local_path):\n",
        "        snapshot_download(\n",
        "            repo_id=model_name,\n",
        "            local_dir=local_path,\n",
        "            ignore_patterns=[\"*.md\", \"*.pt\", \"*.bin\", \"*.txt\"],\n",
        "        )\n",
        "    return local_path\n",
        "\n",
        "# Set and download model\n",
        "model_name = \"Qwen/Qwen2.5-0.5B\"\n",
        "#model_name = \"meta-llama/Llama-3.2-1B\"\n",
        "local_model_path = download_model(model_name)\n",
        "print(f\"Model downloaded to {local_model_path}\")\n",
        "\n",
        "# Load the dataset\n",
        "ds = load_dataset(\"sentence-transformers/simple-wiki\")\n",
        "\n",
        "# Initialize LLM\n",
        "llm = LLM(\n",
        "    model=local_model_path,\n",
        "    trust_remote_code=True,\n",
        "    max_model_len=2048,\n",
        "    tensor_parallel_size=1,\n",
        "    dtype=\"float16\"\n",
        ")\n",
        "\n",
        "def gen_with_T(T, max_tokens=1024):\n",
        "    T = float(\"%.4f\"%(T))\n",
        "    params = SamplingParams(\n",
        "        n=1,\n",
        "        temperature=T,\n",
        "        max_tokens=max_tokens,\n",
        "        min_tokens=max_tokens-1,\n",
        "        seed=42,\n",
        "        skip_special_tokens=True\n",
        "    )\n",
        "\n",
        "    model_family = model_name.split(\"/\")[-2]\n",
        "    file_perfix = model_name.split(\"/\")[-1]\n",
        "\n",
        "    # Store outputs locally in Colab\n",
        "    output_dir = f\"/content/outputs/{model_family}\"\n",
        "    os.makedirs(output_dir, exist_ok=True)\n",
        "    fname = f\"{output_dir}/{file_perfix}-T{T}.json\"\n",
        "\n",
        "    if os.path.exists(fname):\n",
        "        print(f\"{fname} already exists, skipping\")\n",
        "        return\n",
        "\n",
        "    try:\n",
        "        # Take a smaller subset for Colab\n",
        "        sample_texts = [i for i in ds['train']['text']][::2000]\n",
        "        outputs = llm.generate(sample_texts, params)\n",
        "\n",
        "        data = []\n",
        "        for output in outputs:\n",
        "            prompt = output.prompt\n",
        "            generated = output.outputs[0]\n",
        "            data.append({\n",
        "                \"prompt\": prompt,\n",
        "                \"generated\": generated.text\n",
        "            })\n",
        "\n",
        "        with open(fname, \"w\") as f:\n",
        "            json.dump(data, f, indent=4, ensure_ascii=False)\n",
        "        print(f\"saved to {fname}\")\n",
        "\n",
        "    finally:\n",
        "        if dist.is_initialized():\n",
        "            dist.destroy_process_group()\n",
        "\n",
        "if __name__==\"__main__\":\n",
        "    for T in np.linspace(0, 10, 6):\n",
        "        gen_with_T(T)\n",
        "\n",
        "    for T in np.linspace(0, 2, 11):\n",
        "        gen_with_T(T)\n",
        "\n",
        "print(\"\\nGenerated files:\")\n",
        "!ls -R /content/outputs"
      ],
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          "height": 1000,
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        },
        "id": "wxkx7Ph9xCM6",
        "outputId": "06156f68-6514-41f7-b8c7-22fc01ff2e03"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading Qwen/Qwen2.5-0.5B...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Fetching 8 files:   0%|          | 0/8 [00:00<?, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a4b0b426a73f4d359039443d91d60e0a"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/988M [00:00<?, ?B/s]"
            ],
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          "metadata": {}
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            ],
            "application/vnd.jupyter.widget-view+json": {
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              "model_id": "39d773b39ae74fadb18207ddbfbc3d84"
            }
          },
          "metadata": {}
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            "application/vnd.jupyter.widget-view+json": {
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              "model_id": "2e6186c4b5df4d00b302fb1008a68c06"
            }
          },
          "metadata": {}
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "c1601e4e7df14637a3ef1d40495104d1"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "e2ab0b9a764341b4b5622aeca412bb98"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model downloaded to /content/models/Qwen2.5-0.5B\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "fb3de1be7c1645fcbd0f1c064696e7dc"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Loading safetensors checkpoint shards:   0% Completed | 0/1 [00:00<?, ?it/s]\n"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "4224c2b864814154add16a0414076088"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Capturing CUDA graph shapes: 100%|██████████| 35/35 [00:36<00:00,  1.05s/it]\n",
            "Processed prompts: 100%|██████████| 52/52 [00:16<00:00,  3.12it/s, est. speed input: 101.25 toks/s, output: 3190.19 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T0.0.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  3.05it/s, est. speed input: 99.05 toks/s, output: 3120.98 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T2.0.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:18<00:00,  2.85it/s, est. speed input: 92.67 toks/s, output: 2919.73 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T4.0.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.98it/s, est. speed input: 96.87 toks/s, output: 3052.20 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T6.0.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.94it/s, est. speed input: 95.54 toks/s, output: 3010.29 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T8.0.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:18<00:00,  2.87it/s, est. speed input: 93.28 toks/s, output: 2939.10 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T10.0.json\n",
            "/content/outputs/Qwen/Qwen2.5-0.5B-T0.0.json already exists, skipping\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:18<00:00,  2.83it/s, est. speed input: 92.10 toks/s, output: 2901.79 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T0.2.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.95it/s, est. speed input: 95.98 toks/s, output: 3024.15 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T0.4.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.92it/s, est. speed input: 94.83 toks/s, output: 2987.81 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T0.6.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:18<00:00,  2.85it/s, est. speed input: 92.74 toks/s, output: 2921.95 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T0.8.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.95it/s, est. speed input: 95.81 toks/s, output: 3018.63 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T1.0.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.96it/s, est. speed input: 96.35 toks/s, output: 3035.73 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T1.2.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.90it/s, est. speed input: 94.18 toks/s, output: 2967.32 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T1.4.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:18<00:00,  2.83it/s, est. speed input: 91.92 toks/s, output: 2896.05 toks/s]\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T1.6.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Processed prompts: 100%|██████████| 52/52 [00:17<00:00,  2.94it/s, est. speed input: 95.70 toks/s, output: 3015.28 toks/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "saved to /content/outputs/Qwen/Qwen2.5-0.5B-T1.8.json\n",
            "/content/outputs/Qwen/Qwen2.5-0.5B-T2.0.json already exists, skipping\n",
            "\n",
            "Generated files:\n",
            "/content/outputs:\n",
            "Qwen\n",
            "\n",
            "/content/outputs/Qwen:\n",
            "Qwen2.5-0.5B-T0.0.json\tQwen2.5-0.5B-T0.8.json\t Qwen2.5-0.5B-T1.4.json  Qwen2.5-0.5B-T4.0.json\n",
            "Qwen2.5-0.5B-T0.2.json\tQwen2.5-0.5B-T10.0.json  Qwen2.5-0.5B-T1.6.json  Qwen2.5-0.5B-T6.0.json\n",
            "Qwen2.5-0.5B-T0.4.json\tQwen2.5-0.5B-T1.0.json\t Qwen2.5-0.5B-T1.8.json  Qwen2.5-0.5B-T8.0.json\n",
            "Qwen2.5-0.5B-T0.6.json\tQwen2.5-0.5B-T1.2.json\t Qwen2.5-0.5B-T2.0.json\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!sudo apt-get install texlive-latex-extra texlive-fonts-recommended dvipng cm-super"
      ],
      "metadata": {
        "id": "ZYW0sbVUKMzi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "from matplotlib import rcParams\n",
        "rcParams['text.usetex'] = True\n",
        "rcParams['text.latex.preamble'] = r'\\usepackage{amsmath}'"
      ],
      "metadata": {
        "id": "WqUKkX2tKURS"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install transformers\n",
        "!pip install tqdm"
      ],
      "metadata": {
        "collapsed": true,
        "id": "WEWDxFHoNZGb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "Y1uHR3d7QxhA"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import re\n",
        "import math\n",
        "import json\n",
        "import numpy as np\n",
        "from matplotlib import pyplot as plt\n",
        "\n",
        "import torch\n",
        "from tqdm import tqdm\n",
        "from transformers import AutoTokenizer, AutoModelForCausalLM\n",
        "\n",
        "# Create output directories\n",
        "!mkdir -p \"/content/data\"\n",
        "!mkdir -p \"/content/plots\"\n",
        "\n",
        "model_name = os.getenv(\"model_name\", \"Qwen/Qwen2.5-0.5B\")  # Default model if not set\n",
        "#model_name = os.getenv(\"model_name\", \"meta-llama/Llama-3.2-1B\")  # Default model if not set\n",
        "print(\"using %s\"%(model_name))\n",
        "\n",
        "if not model_name[0].isalpha():\n",
        "    model_name = os.path.expanduser(model_name)\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(model_name)\n",
        "model = AutoModelForCausalLM.from_pretrained(\n",
        "    model_name,\n",
        "    device_map=\"auto\"\n",
        ")\n",
        "embed_tokens = model.get_input_embeddings()\n",
        "\n",
        "def get_files(dir, file_perfix):\n",
        "    text_files = []\n",
        "    for i in os.listdir(\"/content/outputs/%s\"%(dir)):  # Changed path to Colab directory\n",
        "        r = re.search(\"%s-T([0-9\\.]+?)\\.json\"%(file_perfix), i)\n",
        "        if not r:\n",
        "            continue\n",
        "        T = float(r.group(1))\n",
        "        text_files.append({\n",
        "            \"T\": T,\n",
        "            \"path\": \"/content/outputs/%s/%s\"%(dir,i)  # Changed path to Colab directory\n",
        "        })\n",
        "    text_files.sort(key=lambda x: x[\"T\"])\n",
        "    return text_files\n",
        "\n",
        "def load_json(filename):\n",
        "    if os.path.exists(filename):\n",
        "        with open(filename, \"r\") as f:\n",
        "            data = json.load(f)\n",
        "    else:\n",
        "        data = {}\n",
        "    return data\n",
        "\n",
        "def add_log(filename, entry, data):\n",
        "    json_data = load_json(filename)\n",
        "    if entry not in json_data:\n",
        "        json_data[entry] = data\n",
        "    else:\n",
        "        json_data[entry] = {**json_data[entry], **data}\n",
        "\n",
        "    lines = []\n",
        "    for k, v in json_data.items():\n",
        "        lines.append(\"\\\"%s\\\": %s\"%(k, json.dumps(v)))\n",
        "    with open(filename, \"w\") as f:\n",
        "        f.write(\"{\\n\")\n",
        "        f.write(\",\\n\".join(lines))\n",
        "        f.write(\"\\n}\")\n",
        "\n",
        "def energy(filename):\n",
        "    with open(filename, \"r\") as f:\n",
        "        data = json.load(f)\n",
        "    with torch.no_grad():\n",
        "        energies = []\n",
        "        lengths  = []\n",
        "        for d in data:\n",
        "            model_inputs  = tokenizer(d[\"generated\"], return_tensors=\"pt\").to(model.device)\n",
        "            inputs_embeds = embed_tokens(model_inputs[\"input_ids\"]) # 1, len, 1536\n",
        "            inputs_embeds = inputs_embeds.squeeze(0)\n",
        "            inputs_embeds/= torch.linalg.vector_norm(inputs_embeds, dim = -1, keepdim = True)\n",
        "            attn = -inputs_embeds@inputs_embeds.T # attn[i,j] = ei cdot ej\n",
        "            attn.fill_diagonal_(0.0)\n",
        "            e = (attn.sum()/attn.shape[0]).item()\n",
        "            energies.append(e)\n",
        "            lengths.append(attn.shape[0])\n",
        "    print(\"avg length for %s: %.2f\"%(filename, np.mean(lengths)))\n",
        "    return np.mean(energies), np.std(energies)/math.sqrt(len(data))\n",
        "\n",
        "def susceptibility(filename):\n",
        "    with open(filename, \"r\") as f:\n",
        "        data = json.load(f)\n",
        "    N = 512\n",
        "    with torch.no_grad():\n",
        "        spins = []\n",
        "        for d in data:\n",
        "            model_inputs  = tokenizer(d[\"generated\"], return_tensors=\"pt\").to(model.device)\n",
        "            inputs_embeds = embed_tokens(model_inputs[\"input_ids\"]) # 1, len, 1536\n",
        "            inputs_embeds = inputs_embeds.squeeze(0)\n",
        "            inputs_embeds/= torch.linalg.vector_norm(inputs_embeds, dim = -1, keepdim = True)\n",
        "            spins.append(inputs_embeds[-N:,:]) # N x 896\n",
        "\n",
        "    spins = torch.stack(spins)\n",
        "    spinsbar = spins.mean(dim=0)\n",
        "    deltaspins = spins - spinsbar # 103 x 1000 x 896\n",
        "    sisj = []\n",
        "    for i in range(N):\n",
        "        for j in range(i+1,N):\n",
        "            sisj.append((deltaspins[:,i,:]*deltaspins[:,j,:]).sum(dim=-1).mean().item())\n",
        "    return np.mean(sisj)\n",
        "\n",
        "def plot_energy(plot_flag=True):\n",
        "    dir, file_perfix = model_name.split(\"/\")[-2:] # Qwen, Qwen2.5-32B\n",
        "    text_files = get_files(dir, file_perfix)\n",
        "\n",
        "    betas, energies, sigmas = [], [], []\n",
        "    for i in text_files:\n",
        "        T, path = i[\"T\"], i[\"path\"]\n",
        "        e, s = energy(path)\n",
        "        betas.append(T)\n",
        "        energies.append(e)\n",
        "        sigmas.append(s)\n",
        "\n",
        "    print(list(zip(betas, [float(\"%2.f\"%(e)) for e in energies])))\n",
        "\n",
        "    # Save energy data to local Colab directory\n",
        "    energy_file = \"/content/data/%s-energy.json\"%(dir)\n",
        "    add_log(energy_file, file_perfix, {\n",
        "        \"model_size\": model.num_parameters(exclude_embeddings=True),\n",
        "        \"betas\": betas,\n",
        "        \"energies\": energies,\n",
        "        \"sigmas\": sigmas\n",
        "    })\n",
        "\n",
        "    if not plot_flag:\n",
        "        return\n",
        "\n",
        "    Tmin = round(min(betas))\n",
        "    Tmax = round(max(betas))\n",
        "\n",
        "    plt.figure(figsize=(10, 6))\n",
        "    plt.errorbar(betas, energies, yerr=sigmas, capsize=2)\n",
        "    plt.minorticks_on()\n",
        "    #plt.grid(True, which=\"both\")\n",
        "    plt.xlabel(\"Temperature\")\n",
        "    plt.ylabel(\"Energy\")\n",
        "    plt.title(file_perfix)\n",
        "    plt.tight_layout()\n",
        "\n",
        "    plot_path = f\"/content/plots/energy_{file_perfix}-{Tmin}-{Tmax}.pdf\"\n",
        "    plt.savefig(plot_path)\n",
        "    print(f\"Plot saved to {plot_path}\")\n",
        "\n",
        "    plt.show()\n",
        "\n",
        "if __name__==\"__main__\":\n",
        "    plot_energy()\n",
        "\n",
        "print(\"\\nGenerated files:\")\n",
        "!ls -R /content/data\n",
        "!ls -R /content/plots"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "b7e114a7570e4d3badd6937051098490",
            "651c587b66fa47479c53b6244ae53af4",
            "50c527c53bd748d2a2a73ca783054d94",
            "b68272f7ff4e4749a077abd9ed69a33a",
            "09d1d981df5a44d5b355ea1d9e531d8e",
            "08ca5f214df84d4f9ba783440bc6c71b",
            "9b61b1b2031c4d85a04698e76c1b8a5b",
            "a5bb0c87941649d786fa8a838767f28b",
            "ca494b245271493689bb6f4b2e72a988",
            "842274e9b69b4d10af7c1efb8902c203",
            "bb16dfaa92aa41378c8d195dce21b102"
          ]
        },
        "id": "fdew7Boszp8V",
        "outputId": "8423f963-9d3e-441b-ec22-e05bd77427f9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "using Qwen/Qwen2.5-0.5B\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "generation_config.json:   0%|          | 0.00/138 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b7e114a7570e4d3badd6937051098490"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T0.0.json: 1023.92\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T0.2.json: 1023.90\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T0.4.json: 1023.79\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T0.6.json: 1023.27\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T0.8.json: 1023.50\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T1.0.json: 1022.37\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T1.2.json: 1027.69\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T1.4.json: 1031.65\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T1.6.json: 1035.88\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T1.8.json: 1040.33\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T2.0.json: 1043.12\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T4.0.json: 1057.23\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T6.0.json: 1060.25\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T8.0.json: 1063.52\n",
            "avg length for /content/outputs/Qwen/Qwen2.5-0.5B-T10.0.json: 1062.54\n",
            "[(0.0, -130.0), (0.2, -130.0), (0.4, -133.0), (0.6, -96.0), (0.8, -82.0), (1.0, -58.0), (1.2, -26.0), (1.4, -52.0), (1.6, -66.0), (1.8, -76.0), (2.0, -85.0), (4.0, -115.0), (6.0, -126.0), (8.0, -130.0), (10.0, -131.0)]\n",
            "Plot saved to /content/plots/energy_Qwen2.5-0.5B-0-10.pdf\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "Generated files:\n",
            "/content/data:\n",
            "Qwen-energy.json\n",
            "/content/plots:\n",
            "energy_Qwen2.5-0.5B-0-10.pdf\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "N1cbIwcYdQSV"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import json\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "\n",
        "# Load the energy data\n",
        "def load_energy_data(model_family=\"Qwen\"):\n",
        "    with open(f\"/content/data/{model_family}-energy.json\", \"r\") as f:\n",
        "        data = json.load(f)\n",
        "    return data\n",
        "\n",
        "def plot_phase_transition(model_family=\"Qwen\", model_size=\"Qwen2.5-0.5B\"):\n",
        "    data = load_energy_data(model_family)\n",
        "    model_data = data[model_size]\n",
        "\n",
        "    # Extract data\n",
        "    temperatures = np.array(model_data['betas'])\n",
        "    energies = np.array(model_data['energies'])\n",
        "    errors = np.array(model_data['sigmas'])\n",
        "\n",
        "    plt.figure(figsize=(10, 6))\n",
        "    plt.errorbar(temperatures, energies, yerr=errors,\n",
        "                fmt='o-', capsize=3, markersize=8,\n",
        "                linewidth=2, label=model_size)\n",
        "\n",
        "    plt.xlabel('Temperature', fontsize=12)\n",
        "    plt.ylabel('Energy', fontsize=12)\n",
        "    plt.title(f'Phase Transition in {model_size}', fontsize=14)\n",
        "    plt.grid(True, alpha=0.3)\n",
        "    plt.legend()\n",
        "\n",
        "    # Add vertical line at potential critical temperature\n",
        "    critical_temp = temperatures[np.argmax(np.gradient(energies))]\n",
        "    plt.axvline(x=critical_temp, color='r', linestyle='--',\n",
        "                alpha=0.5, label=f'Tc ≈ {critical_temp:.2f}')\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "    print(f\"Estimated critical temperature: {critical_temp:.2f}\")\n",
        "\n",
        "\n",
        "plot_phase_transition()\n",
        "\n",
        "# models = [\"Qwen2.5-0.5B\", \"Qwen2.5-1.5B\", \"Qwen2.5-7B\"]\n",
        "# for model in models:\n",
        "#     plot_phase_transition(model_size=model)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 550
        },
        "id": "Hpp9qzzIN0Ic",
        "outputId": "650130d2-7f7a-45a3-c21a-3bbc3ff90b1b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Estimated critical temperature: 1.00\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        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)"
      ],
      "metadata": {
        "id": "t0CEjd7HQ7XL"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import json\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt\n",
        "from tqdm import tqdm\n",
        "\n",
        "def calculate_susceptibility(model_name=\"Qwen/Qwen2.5-0.5B\"):\n",
        "    dir, file_perfix = model_name.split(\"/\")[-2:]\n",
        "    text_files = []\n",
        "\n",
        "    # Get files\n",
        "    for i in os.listdir(f\"/content/outputs/{dir}\"):\n",
        "        r = re.search(f\"{file_perfix}-T([0-9\\.]+?)\\.json\", i)\n",
        "        if not r:\n",
        "            continue\n",
        "        T = float(r.group(1))\n",
        "        text_files.append({\n",
        "            \"T\": T,\n",
        "            \"path\": f\"/content/outputs/{dir}/{i}\"\n",
        "        })\n",
        "    text_files.sort(key=lambda x: x[\"T\"])\n",
        "\n",
        "    # Calculate susceptibility for each temperature\n",
        "    temperatures = []\n",
        "    susceptibilities = []\n",
        "\n",
        "    for file_info in tqdm(text_files):\n",
        "        T = file_info[\"T\"]\n",
        "        chi = susceptibility(file_info[\"path\"])  # Using the existing susceptibility function\n",
        "        temperatures.append(T)\n",
        "        susceptibilities.append(chi)\n",
        "\n",
        "    plt.figure(figsize=(10, 6))\n",
        "    plt.plot(temperatures, susceptibilities, 'o-', linewidth=2, markersize=8)\n",
        "    plt.xlabel('Temperature', fontsize=12)\n",
        "    plt.ylabel('Susceptibility', fontsize=12)\n",
        "    plt.title(f'Magnetic Susceptibility vs Temperature for {file_perfix}', fontsize=14)\n",
        "    plt.grid(True, alpha=0.3)\n",
        "\n",
        "    peak_idx = np.argmax(susceptibilities)\n",
        "    peak_temp = temperatures[peak_idx]\n",
        "    plt.axvline(x=peak_temp, color='r', linestyle='--',\n",
        "                alpha=0.5, label=f'Peak at T ≈ {peak_temp:.2f}')\n",
        "    plt.legend()\n",
        "\n",
        "    plt.tight_layout()\n",
        "    plt.show()\n",
        "\n",
        "    return temperatures, susceptibilities\n",
        "\n",
        "# Run the analysis\n",
        "temps, suscs = calculate_susceptibility()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 549
        },
        "id": "l0HWZlcqOR0q",
        "outputId": "a95a4231-7d64-415e-e8d2-f931df8b838f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 15/15 [02:37<00:00, 10.51s/it]\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1000x600 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}