{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "02ruu54h4yLc"
      },
      "source": [
        "# V-JEPA 2"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ol0IGYCd4hg4"
      },
      "source": [
        "V-JEPA 2 is a new open 1.2B video embedding model by Meta, which attempts to capture the physical world modelling through video ⏯️\n",
        "\n",
        "The model can be used for various tasks for video: fine-tuning for downstream tasks like video classification, or any task involving embeddings (similarity, retrieval and more!).\n",
        "\n",
        "You can check all V-JEPA 2 checkpoints and the datasets that come with this release [in this collection](collection_link). You can also read about the release [here](blog_link).\n",
        "\n",
        "In this notebook we will go through:\n",
        "1. Using V-JEPA 2 as feature extractor,\n",
        "2. Using V-JEPA 2 for video classification\n",
        "3. fine-tuning V-JEPA 2, on [UCF-101 action recognition dataset](https://huggingface.co/datasets/sayakpaul/ucf101-subset) using transformers.\n",
        "\n",
        "Let's go!"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kIIBxYOA41Ga"
      },
      "source": [
        "We need to install accelerate, datasets and transformers' main branch."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jDnyNeongiTP"
      },
      "outputs": [],
      "source": [
        "!pip install -U https://github.com/huggingface/transformers"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cDzUdYIHXLbP"
      },
      "source": [
        "torchcodec 0.2.1 supports Colab, which is supported by different torch and torchvision versions, so let's update them too."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qqoeMBmxrY-X",
        "outputId": "f9162900-d083-43f0-8c60-1db57a508f17"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m363.4/363.4 MB\u001b[0m \u001b[31m3.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.8/13.8 MB\u001b[0m \u001b[31m124.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m24.6/24.6 MB\u001b[0m \u001b[31m100.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m883.7/883.7 kB\u001b[0m \u001b[31m63.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m664.8/664.8 MB\u001b[0m \u001b[31m2.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m211.5/211.5 MB\u001b[0m \u001b[31m11.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.3/56.3 MB\u001b[0m \u001b[31m43.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m127.9/127.9 MB\u001b[0m \u001b[31m8.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.5/207.5 MB\u001b[0m \u001b[31m12.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.1/21.1 MB\u001b[0m \u001b[31m115.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K   \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m766.4/766.4 kB\u001b[0m \u001b[31m21.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hTorch: 2.6.0+cu124\n"
          ]
        }
      ],
      "source": [
        "!pip install -q torch==2.6.0 torchvision==0.21.0\n",
        "!pip install -q torchcodec==0.2.1\n",
        "\n",
        "import torch\n",
        "print(\"Torch:\", torch.__version__)\n",
        "from torchcodec.decoders import VideoDecoder # validate it works\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lE7_UmAfXr_X"
      },
      "source": [
        "## Simple Inference\n",
        "\n",
        "**Inference with Embeddings**\n",
        "\n",
        "You can initialize the V-JEPA 2 with ViT Giant checkpoint as follows. Feel free to replace the ID with the one you want to use. Here's [the model collection](https://huggingface.co/collections/facebook/v-jepa-2-6841bad8413014e185b497a6)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RHx7cQQvYMVW",
        "outputId": "e1e48780-38dc-4c49-d530-6adb42f0342b"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.11/dist-packages/huggingface_hub/utils/_auth.py:94: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "from transformers import AutoVideoProcessor, AutoModel\n",
        "\n",
        "model = AutoModel.from_pretrained(\"facebook/vjepa2-vitg-fpc64-384\").to(\"cuda\")\n",
        "processor = AutoVideoProcessor.from_pretrained(\"facebook/vjepa2-vitg-fpc64-384\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QS0TNSY3YWrv"
      },
      "source": [
        "Simply infer to get the embeddings."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xPXRC9nWXrRd",
        "outputId": "374f9ee2-6497-41cf-ce32-49955e726ec5"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "torch.Size([1, 9216, 1408])\n"
          ]
        }
      ],
      "source": [
        "import torch\n",
        "from torchcodec.decoders import VideoDecoder\n",
        "import numpy as np\n",
        "\n",
        "video_url = \"https://huggingface.co/datasets/merve/vlm_test_images/resolve/main/holding_phone.mp4\"\n",
        "vr = VideoDecoder(video_url)\n",
        "frame_idx = np.arange(0, 32) # choosing some frames. here, you can define more complex sampling strategy\n",
        "video_frames = vr.get_frames_at(indices=frame_idx).data  # T x C x H x W\n",
        "video = processor(video_frames, return_tensors=\"pt\").to(model.device)\n",
        "with torch.no_grad():\n",
        "    video_embeddings = model.get_vision_features(**video)\n",
        "\n",
        "print(video_embeddings.shape)\n",
        "del model\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cwnHTJoVXwHs"
      },
      "source": [
        "**Inference for Video Classification**\n",
        "\n",
        "Meta also provides a model trained on SomethingSomething-v2, a dataset of human-object interactions with 174 classes."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ul6MlUpJXy2k"
      },
      "outputs": [],
      "source": [
        "from transformers import VJEPA2ForVideoClassification, VJEPA2VideoProcessor\n",
        "\n",
        "model = VJEPA2ForVideoClassification.from_pretrained(\"facebook/vjepa2-vitl-fpc16-256-ssv2\").to(\"cuda\")\n",
        "processor = VJEPA2VideoProcessor.from_pretrained(\"facebook/vjepa2-vitl-fpc16-256-ssv2\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "guYY0V0Ob7li"
      },
      "source": [
        "We can pass the same frames to the new processor."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CsKds6fmYmrv",
        "outputId": "d0214cb6-bed5-415e-f657-dea5e6db779d"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Touching (without moving) [part] of [something]\n"
          ]
        }
      ],
      "source": [
        "inputs = processor(video_frames, return_tensors=\"pt\").to(model.device)\n",
        "\n",
        "with torch.no_grad():\n",
        "    outputs = model(**inputs)\n",
        "    logits = outputs.logits\n",
        "\n",
        "predicted_label = logits.argmax(-1).item()\n",
        "print(model.config.id2label[predicted_label])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sJNQs3VeckNG"
      },
      "source": [
        "## Data Preprocessing for Fine-tuning"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_GF3Q4-66Csr"
      },
      "source": [
        "Let's load the dataset first. UCF-101 consists of 101 different actions covering from blowing candles to playing violin. We will use [a smaller subset of UCF-101](https://huggingface.co/datasets/sayakpaul/ucf101-subset)."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "fuDD5FLs7pAw"
      },
      "outputs": [],
      "source": [
        "from huggingface_hub import hf_hub_download\n",
        "import tarfile\n",
        "import pathlib\n",
        "\n",
        "fpath = hf_hub_download(repo_id=\"sayakpaul/ucf101-subset\", filename=\"UCF101_subset.tar.gz\", repo_type=\"dataset\")\n",
        "\n",
        "with tarfile.open(fpath) as t:\n",
        "    t.extractall(\".\")\n",
        "\n",
        "dataset_root_path = pathlib.Path(\"UCF101_subset\")\n",
        "all_video_file_paths = list(dataset_root_path.glob(\"**/*.avi\"))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Hiyyi4ai89D7"
      },
      "source": [
        "We gather different splits as lists to later create the `DataLoader` for training."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6kkNNuR88qjM",
        "outputId": "e1e48214-b445-409e-ea2e-9e42f8810593"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Total videos: 405\n"
          ]
        }
      ],
      "source": [
        "train_video_file_paths = []\n",
        "val_video_file_paths = []\n",
        "test_video_file_paths = []\n",
        "\n",
        "for video_file_path in all_video_file_paths:\n",
        "    video_parts = video_file_path.parts\n",
        "    if \"train\" in video_parts:\n",
        "        train_video_file_paths.append(video_file_path)\n",
        "    elif \"val\" in video_parts:\n",
        "        val_video_file_paths.append(video_file_path)\n",
        "    elif \"test\" in video_parts:\n",
        "        test_video_file_paths.append(video_file_path)\n",
        "    else:\n",
        "        raise ValueError(f\"Unknown video part: {video_parts}\")\n",
        "\n",
        "video_count_train = len(train_video_file_paths)\n",
        "video_count_val = len(val_video_file_paths)\n",
        "video_count_test = len(test_video_file_paths)\n",
        "\n",
        "video_total = video_count_train + video_count_val + video_count_test\n",
        "print(f\"Total videos: {video_total}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "PAz1842v9ib9"
      },
      "source": [
        "We need to keep a class label to human-readable label mapping and number of classes to later initialize our model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "CRkkxqMO9dHG"
      },
      "outputs": [],
      "source": [
        "class_labels = {path.parts[2] for path in all_video_file_paths}\n",
        "label2id = {label: i for i, label in enumerate(class_labels)}\n",
        "id2label = {i: label for label, i in label2id.items()}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "N9kLrfnC9pWb"
      },
      "source": [
        "We will create a `CustomVideoDataset` class and initialize our train/test/validation sets for DataLoader."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wszx85M98vwl"
      },
      "outputs": [],
      "source": [
        "from torch.utils.data import Dataset, DataLoader\n",
        "from torchcodec.decoders import VideoDecoder\n",
        "\n",
        "class CustomVideoDataset(Dataset):\n",
        "    def __init__(self, video_file_paths, label2id):\n",
        "        self.video_file_paths = video_file_paths\n",
        "        self.label2id = label2id\n",
        "\n",
        "    def __len__(self):\n",
        "        return len(self.video_file_paths)\n",
        "\n",
        "    def __getitem__(self, idx):\n",
        "        video_path = self.video_file_paths[idx]\n",
        "        label = video_path.parts[2]\n",
        "        decoder = VideoDecoder(video_path)\n",
        "        return decoder, self.label2id[label]\n",
        "\n",
        "train_ds = CustomVideoDataset(train_video_file_paths, label2id)\n",
        "val_ds = CustomVideoDataset(val_video_file_paths, label2id)\n",
        "test_ds = CustomVideoDataset(test_video_file_paths, label2id)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zrsTuN7TYxwW"
      },
      "source": [
        "V-JEPA 2 is an embedding model. To fine-tune it, we need to load the weights with a randomly initialized task-specific head put on top of them. For this, we can use `VJEPA2ForVideoClassification` class. During the initialization, we should pass in the mapping between the class labels and human readable labels, so the classification head has the same number of classes, and directly outputs human-readable labels with the confidence scores.\n",
        "\n",
        "On a separate note, if you want to only use embeddings, you can use `AutoModel` to do so. This can be used for e.g. video-to-video retrieval or calculating similarity between videos.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7tVsJ3WWBONu"
      },
      "source": [
        "We can now define augmentations and create the data collator. This notebook is made for tutorial purposes, so we keep the augmentations minimal. We can finally initialize the DataLoader afterwards."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "I9biPx184MxY"
      },
      "outputs": [],
      "source": [
        "from torchcodec.samplers import clips_at_random_indices\n",
        "from torchvision.transforms import v2\n",
        "\n",
        "\n",
        "def collate_fn(\n",
        "    samples, frames_per_clip, transforms\n",
        "):\n",
        "    \"\"\"Sample clips and apply transforms to a batch.\"\"\"\n",
        "    clips, labels = [], []\n",
        "    for decoder, lbl in samples:\n",
        "        clip = clips_at_random_indices(\n",
        "            decoder,\n",
        "            num_clips=1,\n",
        "            num_frames_per_clip=frames_per_clip,\n",
        "            num_indices_between_frames=3,\n",
        "        ).data\n",
        "        clips.append(clip)\n",
        "        labels.append(lbl)\n",
        "\n",
        "    videos = torch.cat(clips, dim=0)\n",
        "    videos = transforms(videos)\n",
        "    return videos, torch.tensor(labels)\n",
        "\n",
        "\n",
        "\n",
        "train_transforms = v2.Compose([\n",
        "        v2.RandomResizedCrop((processor.crop_size[\"height\"], processor.crop_size[\"width\"])),\n",
        "        v2.RandomHorizontalFlip(),\n",
        "    ])\n",
        "eval_transforms = v2.Compose([\n",
        "        v2.CenterCrop((processor.crop_size[\"height\"], processor.crop_size[\"width\"]))\n",
        "    ])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Op3hPQCkW16F"
      },
      "outputs": [],
      "source": [
        "from functools import partial\n",
        "\n",
        "batch_size = 1\n",
        "num_workers = 8\n",
        "\n",
        "# DataLoaders\n",
        "train_loader = DataLoader(\n",
        "    train_ds,\n",
        "    batch_size=batch_size,\n",
        "    shuffle=True,\n",
        "    collate_fn=partial(collate_fn, frames_per_clip=model.config.frames_per_clip, transforms=train_transforms),\n",
        "    num_workers=num_workers,\n",
        "    pin_memory=True,\n",
        ")\n",
        "val_loader = DataLoader(\n",
        "    val_ds,\n",
        "    batch_size=batch_size,\n",
        "    shuffle=False,\n",
        "    collate_fn=partial(collate_fn, frames_per_clip=model.config.frames_per_clip, transforms=eval_transforms),\n",
        "    num_workers=num_workers,\n",
        "    pin_memory=True,\n",
        ")\n",
        "test_loader = DataLoader(\n",
        "    test_ds,\n",
        "    batch_size=batch_size,\n",
        "    shuffle=False,\n",
        "    collate_fn=partial(collate_fn, frames_per_clip=model.config.frames_per_clip, transforms=eval_transforms),\n",
        "    num_workers=num_workers,\n",
        "    pin_memory=True,\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Model Training"
      ],
      "metadata": {
        "id": "EFmvjlMc28Yl"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zDl_a2VU5Tjc"
      },
      "source": [
        "Before training, we will login to HF Hub (to later push the model) and setup tensorboard."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 17,
          "referenced_widgets": [
            "a303072eb4d64cfc9993053056e4ee3a",
            "324e6eed4d694c7699f0350fc09aa464",
            "a5450cd991cd4a7483cb3a2ccec107ae",
            "f6768e8c3b654024a62c9eb14c961962",
            "a79aaa66ef30468584123226e62c851f",
            "f41e7dfdb83647e3997f0fbdc5208de2",
            "61cc34a0c9604e798e196ffe3d44a132",
            "6d86b57066044c5eae89f773dfbf94d8",
            "17e05a2f86b24f1a97139cf7827a62cf",
            "bde755fab399457f92bec0551d717821",
            "d293ab19173a410789fa08ac175be10d",
            "faf4387a0f9b4ccf9ad43ca3593b4dd5",
            "81adb65a7c544469bb4cdd3b2d7eb132",
            "e1b8bd360bf74c96988d90eb87757017",
            "cc8c509b8ffe4557aaa2ae4af4c25008",
            "50da253981f14f42b47b409ddca9caea",
            "6cbe308d343443328502261eaea02496",
            "c26df21cb5354d93a008c541fb96ac70",
            "dd2a4abfd46c4574a668ff4ff5d9de25",
            "e36ae300929743f997e60c852c41b966"
          ]
        },
        "id": "8-jbn-7W5fye",
        "outputId": "128d3a69-1624-471c-82f3-05b0e082fb24"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a303072eb4d64cfc9993053056e4ee3a"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "from huggingface_hub import login\n",
        "login()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Ny83xOQk5oZ4"
      },
      "outputs": [],
      "source": [
        "from torch.utils.tensorboard import SummaryWriter\n",
        "writer = SummaryWriter(\"runs/vjepa2_finetune\")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here's a small evaluation function we use so we evaluate the model training and log the number to tensorboard."
      ],
      "metadata": {
        "id": "QA3O1VG-2ey1"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4297lEr45ikc"
      },
      "outputs": [],
      "source": [
        "def evaluate(\n",
        "    loader: DataLoader,\n",
        "    model: VJEPA2ForVideoClassification,\n",
        "    processor: VJEPA2VideoProcessor,\n",
        "    device: torch.device,\n",
        ") -> float:\n",
        "    \"\"\"Compute accuracy over a dataset.\"\"\"\n",
        "    model.eval()\n",
        "    correct, total = 0, 0\n",
        "    with torch.no_grad():\n",
        "        for vids, labels in loader:\n",
        "            inputs = processor(vids, return_tensors=\"pt\").to(device)\n",
        "            labels = labels.to(device)\n",
        "            logits = model(**inputs).logits\n",
        "            preds = logits.argmax(-1)\n",
        "            correct += (preds == labels).sum().item()\n",
        "            total += labels.size(0)\n",
        "    return correct / total if total > 0 else 0.0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BD5IwFt_BqKx"
      },
      "source": [
        "Finally, write the training loop!\n",
        "- On A100 we can fit in single example, so for better performance we will use gradient accumulation to simulate larger batch sizes.\n",
        "- We will freeze the backbone completely and only train the head.\n",
        "- We will use Adam optimizer.\n",
        "- We need to initialize the model head with the new labels."
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "del model\n",
        "model_name = \"qubvel-hf/vjepa2-vitl-fpc16-256-ssv2\"\n",
        "processor = VJEPA2VideoProcessor.from_pretrained(model_name)\n",
        "model = VJEPA2ForVideoClassification.from_pretrained(\n",
        "    model_name,\n",
        "    torch_dtype=torch.float32,\n",
        "    label2id=label2id,\n",
        "    id2label=id2label,\n",
        "    ignore_mismatched_sizes=True,\n",
        ").to(\"cuda\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CAodWCig5YkR",
        "outputId": "b08294b7-7495-4baa-f836-4bb1c8077167"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some weights of VJEPA2ForVideoClassification were not initialized from the model checkpoint at qubvel-hf/vjepa2-vitl-fpc16-256-ssv2 and are newly initialized because the shapes did not match:\n",
            "- classifier.bias: found shape torch.Size([174]) in the checkpoint and torch.Size([10]) in the model instantiated\n",
            "- classifier.weight: found shape torch.Size([174, 1024]) in the checkpoint and torch.Size([10, 1024]) in the model instantiated\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "O2Q4i8BlBnOP"
      },
      "outputs": [],
      "source": [
        "gradient_accumulation_steps = 4\n",
        "\n",
        "for param in model.vjepa2.parameters():\n",
        "        param.requires_grad = False\n",
        "\n",
        "# Optimizer and loss\n",
        "trainable = [p for p in model.parameters() if p.requires_grad]\n",
        "optimizer = torch.optim.Adam(trainable, lr=1e-5)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WuPOuH1k5ESI",
        "outputId": "4a302957-be9a-4e9b-e400-5c122479b62c"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1 Step 4: Accumulated Loss = 2.4374\n",
            "Epoch 1 Step 8: Accumulated Loss = 2.4301\n",
            "Epoch 1 Step 12: Accumulated Loss = 2.6364\n",
            "Epoch 1 Step 16: Accumulated Loss = 2.4991\n",
            "Epoch 1 Step 20: Accumulated Loss = 2.5215\n",
            "Epoch 1 Step 24: Accumulated Loss = 2.4089\n",
            "Epoch 1 Step 28: Accumulated Loss = 2.3870\n",
            "Epoch 1 Step 32: Accumulated Loss = 2.2417\n",
            "Epoch 1 Step 36: Accumulated Loss = 2.6394\n",
            "Epoch 1 Step 40: Accumulated Loss = 2.4861\n",
            "Epoch 1 Step 44: Accumulated Loss = 2.6568\n",
            "Epoch 1 Step 48: Accumulated Loss = 2.2627\n",
            "Epoch 1 Step 52: Accumulated Loss = 2.5263\n",
            "Epoch 1 Step 56: Accumulated Loss = 2.2626\n",
            "Epoch 1 Step 60: Accumulated Loss = 2.1493\n",
            "Epoch 1 Step 64: Accumulated Loss = 2.3545\n",
            "Epoch 1 Step 68: Accumulated Loss = 2.2872\n",
            "Epoch 1 Step 72: Accumulated Loss = 2.0267\n",
            "Epoch 1 Step 76: Accumulated Loss = 2.4484\n",
            "Epoch 1 Step 80: Accumulated Loss = 2.1420\n",
            "Epoch 1 Step 84: Accumulated Loss = 2.4607\n",
            "Epoch 1 Step 88: Accumulated Loss = 2.5552\n",
            "Epoch 1 Step 92: Accumulated Loss = 2.3860\n",
            "Epoch 1 Step 96: Accumulated Loss = 2.1629\n",
            "Epoch 1 Step 100: Accumulated Loss = 2.4949\n",
            "Epoch 1 Step 104: Accumulated Loss = 2.2526\n",
            "Epoch 1 Step 108: Accumulated Loss = 2.1343\n",
            "Epoch 1 Step 112: Accumulated Loss = 2.2793\n",
            "Epoch 1 Step 116: Accumulated Loss = 1.9160\n",
            "Epoch 1 Step 120: Accumulated Loss = 2.2710\n",
            "Epoch 1 Step 124: Accumulated Loss = 2.6402\n",
            "Epoch 1 Step 128: Accumulated Loss = 2.3268\n",
            "Epoch 1 Step 132: Accumulated Loss = 2.2637\n",
            "Epoch 1 Step 136: Accumulated Loss = 2.3056\n",
            "Epoch 1 Step 140: Accumulated Loss = 1.9433\n",
            "Epoch 1 Step 144: Accumulated Loss = 2.5684\n",
            "Epoch 1 Step 148: Accumulated Loss = 2.0994\n",
            "Epoch 1 Step 152: Accumulated Loss = 2.3325\n",
            "Epoch 1 Step 156: Accumulated Loss = 2.2036\n",
            "Epoch 1 Step 160: Accumulated Loss = 2.2418\n",
            "Epoch 1 Step 164: Accumulated Loss = 2.4737\n",
            "Epoch 1 Step 168: Accumulated Loss = 2.1102\n",
            "Epoch 1 Step 172: Accumulated Loss = 2.2295\n",
            "Epoch 1 Step 176: Accumulated Loss = 2.1759\n",
            "Epoch 1 Step 180: Accumulated Loss = 2.1245\n",
            "Epoch 1 Step 184: Accumulated Loss = 2.2936\n",
            "Epoch 1 Step 188: Accumulated Loss = 2.2201\n",
            "Epoch 1 Step 192: Accumulated Loss = 2.1238\n",
            "Epoch 1 Step 196: Accumulated Loss = 2.1434\n",
            "Epoch 1 Step 200: Accumulated Loss = 2.2267\n",
            "Epoch 1 Step 204: Accumulated Loss = 2.0451\n",
            "Epoch 1 Step 208: Accumulated Loss = 2.1340\n",
            "Epoch 1 Step 212: Accumulated Loss = 2.0615\n",
            "Epoch 1 Step 216: Accumulated Loss = 2.1408\n",
            "Epoch 1 Step 220: Accumulated Loss = 1.8669\n",
            "Epoch 1 Step 224: Accumulated Loss = 2.0821\n",
            "Epoch 1 Step 228: Accumulated Loss = 2.0060\n",
            "Epoch 1 Step 232: Accumulated Loss = 2.0880\n",
            "Epoch 1 Step 236: Accumulated Loss = 2.2563\n",
            "Epoch 1 Step 240: Accumulated Loss = 2.2102\n",
            "Epoch 1 Step 244: Accumulated Loss = 1.8373\n",
            "Epoch 1 Step 248: Accumulated Loss = 1.9634\n",
            "Epoch 1 Step 252: Accumulated Loss = 2.3135\n",
            "Epoch 1 Step 256: Accumulated Loss = 1.8222\n",
            "Epoch 1 Step 260: Accumulated Loss = 2.2721\n",
            "Epoch 1 Step 264: Accumulated Loss = 2.0542\n",
            "Epoch 1 Step 268: Accumulated Loss = 2.2561\n",
            "Epoch 1 Step 272: Accumulated Loss = 2.2086\n",
            "Epoch 1 Step 276: Accumulated Loss = 1.7952\n",
            "Epoch 1 Step 280: Accumulated Loss = 2.0611\n",
            "Epoch 1 Step 284: Accumulated Loss = 2.0211\n",
            "Epoch 1 Step 288: Accumulated Loss = 1.9916\n",
            "Epoch 1 Step 292: Accumulated Loss = 1.8564\n",
            "Epoch 1 Step 296: Accumulated Loss = 2.1187\n",
            "Epoch 1 Step 300: Accumulated Loss = 1.8814\n",
            "Epoch 1 Validation Accuracy: 0.3333\n",
            "Epoch 2 Step 4: Accumulated Loss = 1.6526\n",
            "Epoch 2 Step 8: Accumulated Loss = 1.9335\n",
            "Epoch 2 Step 12: Accumulated Loss = 2.2624\n",
            "Epoch 2 Step 16: Accumulated Loss = 2.0382\n",
            "Epoch 2 Step 20: Accumulated Loss = 1.9667\n",
            "Epoch 2 Step 24: Accumulated Loss = 1.9171\n",
            "Epoch 2 Step 28: Accumulated Loss = 2.0657\n",
            "Epoch 2 Step 32: Accumulated Loss = 1.9189\n",
            "Epoch 2 Step 36: Accumulated Loss = 2.0267\n",
            "Epoch 2 Step 40: Accumulated Loss = 2.2903\n",
            "Epoch 2 Step 44: Accumulated Loss = 2.0132\n",
            "Epoch 2 Step 48: Accumulated Loss = 2.1886\n",
            "Epoch 2 Step 52: Accumulated Loss = 1.7217\n",
            "Epoch 2 Step 56: Accumulated Loss = 1.5484\n",
            "Epoch 2 Step 60: Accumulated Loss = 1.8083\n",
            "Epoch 2 Step 64: Accumulated Loss = 1.8589\n",
            "Epoch 2 Step 68: Accumulated Loss = 1.7979\n",
            "Epoch 2 Step 72: Accumulated Loss = 1.8580\n",
            "Epoch 2 Step 76: Accumulated Loss = 2.2323\n",
            "Epoch 2 Step 80: Accumulated Loss = 1.7978\n",
            "Epoch 2 Step 84: Accumulated Loss = 1.9081\n",
            "Epoch 2 Step 88: Accumulated Loss = 1.9152\n",
            "Epoch 2 Step 92: Accumulated Loss = 1.9260\n",
            "Epoch 2 Step 96: Accumulated Loss = 1.9428\n",
            "Epoch 2 Step 100: Accumulated Loss = 1.9791\n",
            "Epoch 2 Step 104: Accumulated Loss = 1.7323\n",
            "Epoch 2 Step 108: Accumulated Loss = 1.8499\n",
            "Epoch 2 Step 112: Accumulated Loss = 1.8400\n",
            "Epoch 2 Step 116: Accumulated Loss = 1.2740\n",
            "Epoch 2 Step 120: Accumulated Loss = 1.5789\n",
            "Epoch 2 Step 124: Accumulated Loss = 1.4851\n",
            "Epoch 2 Step 128: Accumulated Loss = 1.8552\n",
            "Epoch 2 Step 132: Accumulated Loss = 1.8511\n",
            "Epoch 2 Step 136: Accumulated Loss = 1.2891\n",
            "Epoch 2 Step 140: Accumulated Loss = 1.5249\n",
            "Epoch 2 Step 144: Accumulated Loss = 1.2709\n",
            "Epoch 2 Step 148: Accumulated Loss = 1.7184\n",
            "Epoch 2 Step 152: Accumulated Loss = 1.8027\n",
            "Epoch 2 Step 156: Accumulated Loss = 1.7201\n",
            "Epoch 2 Step 160: Accumulated Loss = 1.6851\n",
            "Epoch 2 Step 164: Accumulated Loss = 1.7284\n",
            "Epoch 2 Step 168: Accumulated Loss = 1.4749\n",
            "Epoch 2 Step 172: Accumulated Loss = 1.6625\n",
            "Epoch 2 Step 176: Accumulated Loss = 1.7333\n",
            "Epoch 2 Step 180: Accumulated Loss = 1.6522\n",
            "Epoch 2 Step 184: Accumulated Loss = 1.7042\n",
            "Epoch 2 Step 188: Accumulated Loss = 1.7060\n",
            "Epoch 2 Step 192: Accumulated Loss = 1.6794\n",
            "Epoch 2 Step 196: Accumulated Loss = 1.6663\n",
            "Epoch 2 Step 200: Accumulated Loss = 1.6590\n",
            "Epoch 2 Step 204: Accumulated Loss = 1.6877\n",
            "Epoch 2 Step 208: Accumulated Loss = 1.3103\n",
            "Epoch 2 Step 212: Accumulated Loss = 1.7822\n",
            "Epoch 2 Step 216: Accumulated Loss = 1.3645\n",
            "Epoch 2 Step 220: Accumulated Loss = 1.6981\n",
            "Epoch 2 Step 224: Accumulated Loss = 1.1688\n",
            "Epoch 2 Step 228: Accumulated Loss = 1.5811\n",
            "Epoch 2 Step 232: Accumulated Loss = 1.8784\n",
            "Epoch 2 Step 236: Accumulated Loss = 1.6202\n",
            "Epoch 2 Step 240: Accumulated Loss = 1.6725\n",
            "Epoch 2 Step 244: Accumulated Loss = 1.3409\n",
            "Epoch 2 Step 248: Accumulated Loss = 1.8178\n",
            "Epoch 2 Step 252: Accumulated Loss = 1.7902\n",
            "Epoch 2 Step 256: Accumulated Loss = 1.5866\n",
            "Epoch 2 Step 260: Accumulated Loss = 1.6365\n",
            "Epoch 2 Step 264: Accumulated Loss = 1.6587\n",
            "Epoch 2 Step 268: Accumulated Loss = 1.5618\n",
            "Epoch 2 Step 272: Accumulated Loss = 1.0878\n",
            "Epoch 2 Step 276: Accumulated Loss = 1.2646\n",
            "Epoch 2 Step 280: Accumulated Loss = 1.3983\n",
            "Epoch 2 Step 284: Accumulated Loss = 1.3916\n",
            "Epoch 2 Step 288: Accumulated Loss = 2.2084\n",
            "Epoch 2 Step 292: Accumulated Loss = 1.4725\n",
            "Epoch 2 Step 296: Accumulated Loss = 1.3443\n",
            "Epoch 2 Step 300: Accumulated Loss = 1.2341\n",
            "Epoch 2 Validation Accuracy: 0.8000\n",
            "Epoch 3 Step 4: Accumulated Loss = 1.7792\n",
            "Epoch 3 Step 8: Accumulated Loss = 1.4459\n",
            "Epoch 3 Step 12: Accumulated Loss = 1.0405\n",
            "Epoch 3 Step 16: Accumulated Loss = 1.4721\n",
            "Epoch 3 Step 20: Accumulated Loss = 1.2362\n",
            "Epoch 3 Step 24: Accumulated Loss = 1.3642\n",
            "Epoch 3 Step 28: Accumulated Loss = 1.8587\n",
            "Epoch 3 Step 32: Accumulated Loss = 1.3640\n",
            "Epoch 3 Step 36: Accumulated Loss = 1.4293\n",
            "Epoch 3 Step 40: Accumulated Loss = 1.6370\n",
            "Epoch 3 Step 44: Accumulated Loss = 1.3617\n",
            "Epoch 3 Step 48: Accumulated Loss = 1.3009\n",
            "Epoch 3 Step 52: Accumulated Loss = 1.2630\n",
            "Epoch 3 Step 56: Accumulated Loss = 0.8793\n",
            "Epoch 3 Step 60: Accumulated Loss = 1.3734\n",
            "Epoch 3 Step 64: Accumulated Loss = 1.3297\n",
            "Epoch 3 Step 68: Accumulated Loss = 1.5208\n",
            "Epoch 3 Step 72: Accumulated Loss = 0.8465\n",
            "Epoch 3 Step 76: Accumulated Loss = 1.1368\n",
            "Epoch 3 Step 80: Accumulated Loss = 0.9195\n",
            "Epoch 3 Step 84: Accumulated Loss = 1.4835\n",
            "Epoch 3 Step 88: Accumulated Loss = 0.9459\n",
            "Epoch 3 Step 92: Accumulated Loss = 1.2324\n",
            "Epoch 3 Step 96: Accumulated Loss = 1.5042\n",
            "Epoch 3 Step 100: Accumulated Loss = 1.8467\n",
            "Epoch 3 Step 104: Accumulated Loss = 1.1815\n",
            "Epoch 3 Step 108: Accumulated Loss = 1.1443\n",
            "Epoch 3 Step 112: Accumulated Loss = 1.1867\n",
            "Epoch 3 Step 116: Accumulated Loss = 1.3822\n",
            "Epoch 3 Step 120: Accumulated Loss = 1.4043\n",
            "Epoch 3 Step 124: Accumulated Loss = 1.0069\n",
            "Epoch 3 Step 128: Accumulated Loss = 1.1251\n",
            "Epoch 3 Step 132: Accumulated Loss = 1.4216\n",
            "Epoch 3 Step 136: Accumulated Loss = 1.1941\n",
            "Epoch 3 Step 140: Accumulated Loss = 1.3986\n",
            "Epoch 3 Step 144: Accumulated Loss = 0.9652\n",
            "Epoch 3 Step 148: Accumulated Loss = 0.9389\n",
            "Epoch 3 Step 152: Accumulated Loss = 1.0566\n",
            "Epoch 3 Step 156: Accumulated Loss = 1.3330\n",
            "Epoch 3 Step 160: Accumulated Loss = 1.0414\n",
            "Epoch 3 Step 164: Accumulated Loss = 1.3748\n",
            "Epoch 3 Step 168: Accumulated Loss = 1.6332\n",
            "Epoch 3 Step 172: Accumulated Loss = 1.4007\n",
            "Epoch 3 Step 176: Accumulated Loss = 0.8959\n",
            "Epoch 3 Step 180: Accumulated Loss = 1.0355\n",
            "Epoch 3 Step 184: Accumulated Loss = 0.9384\n",
            "Epoch 3 Step 188: Accumulated Loss = 1.1361\n",
            "Epoch 3 Step 192: Accumulated Loss = 0.8555\n",
            "Epoch 3 Step 196: Accumulated Loss = 0.8405\n",
            "Epoch 3 Step 200: Accumulated Loss = 1.0736\n",
            "Epoch 3 Step 204: Accumulated Loss = 1.2196\n",
            "Epoch 3 Step 208: Accumulated Loss = 1.2947\n",
            "Epoch 3 Step 212: Accumulated Loss = 1.0975\n",
            "Epoch 3 Step 216: Accumulated Loss = 0.7192\n",
            "Epoch 3 Step 220: Accumulated Loss = 1.1317\n",
            "Epoch 3 Step 224: Accumulated Loss = 1.4569\n",
            "Epoch 3 Step 228: Accumulated Loss = 1.5830\n",
            "Epoch 3 Step 232: Accumulated Loss = 0.4778\n",
            "Epoch 3 Step 236: Accumulated Loss = 0.9873\n",
            "Epoch 3 Step 240: Accumulated Loss = 1.1108\n",
            "Epoch 3 Step 244: Accumulated Loss = 1.2614\n",
            "Epoch 3 Step 248: Accumulated Loss = 1.2893\n",
            "Epoch 3 Step 252: Accumulated Loss = 0.9929\n",
            "Epoch 3 Step 256: Accumulated Loss = 1.4404\n",
            "Epoch 3 Step 260: Accumulated Loss = 0.8255\n",
            "Epoch 3 Step 264: Accumulated Loss = 1.2598\n",
            "Epoch 3 Step 268: Accumulated Loss = 0.7041\n",
            "Epoch 3 Step 272: Accumulated Loss = 1.0673\n",
            "Epoch 3 Step 276: Accumulated Loss = 0.6876\n",
            "Epoch 3 Step 280: Accumulated Loss = 0.8663\n",
            "Epoch 3 Step 284: Accumulated Loss = 0.6740\n",
            "Epoch 3 Step 288: Accumulated Loss = 0.8708\n",
            "Epoch 3 Step 292: Accumulated Loss = 1.1806\n",
            "Epoch 3 Step 296: Accumulated Loss = 0.6306\n",
            "Epoch 3 Step 300: Accumulated Loss = 0.5125\n",
            "Epoch 3 Validation Accuracy: 0.9333\n",
            "Epoch 4 Step 4: Accumulated Loss = 1.2487\n",
            "Epoch 4 Step 8: Accumulated Loss = 0.9501\n",
            "Epoch 4 Step 12: Accumulated Loss = 1.2593\n",
            "Epoch 4 Step 16: Accumulated Loss = 0.7914\n",
            "Epoch 4 Step 20: Accumulated Loss = 1.1403\n",
            "Epoch 4 Step 24: Accumulated Loss = 0.5162\n",
            "Epoch 4 Step 28: Accumulated Loss = 1.2825\n",
            "Epoch 4 Step 32: Accumulated Loss = 0.8180\n",
            "Epoch 4 Step 36: Accumulated Loss = 0.9460\n",
            "Epoch 4 Step 40: Accumulated Loss = 1.1084\n",
            "Epoch 4 Step 44: Accumulated Loss = 0.5445\n",
            "Epoch 4 Step 48: Accumulated Loss = 0.7064\n",
            "Epoch 4 Step 52: Accumulated Loss = 1.1141\n",
            "Epoch 4 Step 56: Accumulated Loss = 0.8156\n",
            "Epoch 4 Step 60: Accumulated Loss = 1.2378\n",
            "Epoch 4 Step 64: Accumulated Loss = 1.1159\n",
            "Epoch 4 Step 68: Accumulated Loss = 0.6981\n",
            "Epoch 4 Step 72: Accumulated Loss = 0.8476\n",
            "Epoch 4 Step 76: Accumulated Loss = 1.2047\n",
            "Epoch 4 Step 80: Accumulated Loss = 0.4300\n",
            "Epoch 4 Step 84: Accumulated Loss = 1.0843\n",
            "Epoch 4 Step 88: Accumulated Loss = 1.2620\n",
            "Epoch 4 Step 92: Accumulated Loss = 0.8930\n",
            "Epoch 4 Step 96: Accumulated Loss = 1.1604\n",
            "Epoch 4 Step 100: Accumulated Loss = 0.7082\n",
            "Epoch 4 Step 104: Accumulated Loss = 1.0360\n",
            "Epoch 4 Step 108: Accumulated Loss = 1.2594\n",
            "Epoch 4 Step 112: Accumulated Loss = 0.5446\n",
            "Epoch 4 Step 116: Accumulated Loss = 0.8314\n",
            "Epoch 4 Step 120: Accumulated Loss = 0.5678\n",
            "Epoch 4 Step 124: Accumulated Loss = 0.3157\n",
            "Epoch 4 Step 128: Accumulated Loss = 1.0529\n",
            "Epoch 4 Step 132: Accumulated Loss = 0.3604\n",
            "Epoch 4 Step 136: Accumulated Loss = 0.8248\n",
            "Epoch 4 Step 140: Accumulated Loss = 1.0236\n",
            "Epoch 4 Step 144: Accumulated Loss = 1.4206\n",
            "Epoch 4 Step 148: Accumulated Loss = 1.2134\n",
            "Epoch 4 Step 152: Accumulated Loss = 0.7005\n",
            "Epoch 4 Step 156: Accumulated Loss = 1.0403\n",
            "Epoch 4 Step 160: Accumulated Loss = 1.0285\n",
            "Epoch 4 Step 164: Accumulated Loss = 0.7162\n",
            "Epoch 4 Step 168: Accumulated Loss = 0.4477\n",
            "Epoch 4 Step 172: Accumulated Loss = 0.6524\n",
            "Epoch 4 Step 176: Accumulated Loss = 0.7357\n",
            "Epoch 4 Step 180: Accumulated Loss = 1.0750\n",
            "Epoch 4 Step 184: Accumulated Loss = 0.7942\n",
            "Epoch 4 Step 188: Accumulated Loss = 0.9292\n",
            "Epoch 4 Step 192: Accumulated Loss = 0.6608\n",
            "Epoch 4 Step 196: Accumulated Loss = 1.0487\n",
            "Epoch 4 Step 200: Accumulated Loss = 0.4057\n",
            "Epoch 4 Step 204: Accumulated Loss = 0.9824\n",
            "Epoch 4 Step 208: Accumulated Loss = 0.3539\n",
            "Epoch 4 Step 212: Accumulated Loss = 0.5370\n",
            "Epoch 4 Step 216: Accumulated Loss = 0.5966\n",
            "Epoch 4 Step 220: Accumulated Loss = 0.6836\n",
            "Epoch 4 Step 224: Accumulated Loss = 0.8325\n",
            "Epoch 4 Step 228: Accumulated Loss = 0.4702\n",
            "Epoch 4 Step 232: Accumulated Loss = 1.3814\n",
            "Epoch 4 Step 236: Accumulated Loss = 1.0648\n",
            "Epoch 4 Step 240: Accumulated Loss = 0.7933\n",
            "Epoch 4 Step 244: Accumulated Loss = 0.8002\n",
            "Epoch 4 Step 248: Accumulated Loss = 0.8704\n",
            "Epoch 4 Step 252: Accumulated Loss = 0.6652\n",
            "Epoch 4 Step 256: Accumulated Loss = 0.8532\n",
            "Epoch 4 Step 260: Accumulated Loss = 0.5731\n",
            "Epoch 4 Step 264: Accumulated Loss = 0.4963\n",
            "Epoch 4 Step 268: Accumulated Loss = 0.3430\n",
            "Epoch 4 Step 272: Accumulated Loss = 0.9138\n",
            "Epoch 4 Step 276: Accumulated Loss = 0.3177\n",
            "Epoch 4 Step 280: Accumulated Loss = 0.8100\n",
            "Epoch 4 Step 284: Accumulated Loss = 0.6994\n",
            "Epoch 4 Step 288: Accumulated Loss = 0.7007\n",
            "Epoch 4 Step 292: Accumulated Loss = 0.9177\n",
            "Epoch 4 Step 296: Accumulated Loss = 0.4323\n",
            "Epoch 4 Step 300: Accumulated Loss = 0.9394\n",
            "Epoch 4 Validation Accuracy: 0.9333\n",
            "Epoch 5 Step 4: Accumulated Loss = 0.3765\n",
            "Epoch 5 Step 8: Accumulated Loss = 0.2645\n",
            "Epoch 5 Step 12: Accumulated Loss = 0.3801\n",
            "Epoch 5 Step 16: Accumulated Loss = 1.0992\n",
            "Epoch 5 Step 20: Accumulated Loss = 1.4299\n",
            "Epoch 5 Step 24: Accumulated Loss = 0.4831\n",
            "Epoch 5 Step 28: Accumulated Loss = 1.3632\n",
            "Epoch 5 Step 32: Accumulated Loss = 0.7189\n",
            "Epoch 5 Step 36: Accumulated Loss = 1.1219\n",
            "Epoch 5 Step 40: Accumulated Loss = 0.3805\n",
            "Epoch 5 Step 44: Accumulated Loss = 0.7221\n",
            "Epoch 5 Step 48: Accumulated Loss = 0.7443\n",
            "Epoch 5 Step 52: Accumulated Loss = 0.5497\n",
            "Epoch 5 Step 56: Accumulated Loss = 0.4276\n",
            "Epoch 5 Step 60: Accumulated Loss = 0.9333\n",
            "Epoch 5 Step 64: Accumulated Loss = 0.6447\n",
            "Epoch 5 Step 68: Accumulated Loss = 0.5830\n",
            "Epoch 5 Step 72: Accumulated Loss = 0.2696\n",
            "Epoch 5 Step 76: Accumulated Loss = 0.5420\n",
            "Epoch 5 Step 80: Accumulated Loss = 0.6634\n",
            "Epoch 5 Step 84: Accumulated Loss = 0.7204\n",
            "Epoch 5 Step 88: Accumulated Loss = 0.5072\n",
            "Epoch 5 Step 92: Accumulated Loss = 0.8478\n",
            "Epoch 5 Step 96: Accumulated Loss = 0.3052\n",
            "Epoch 5 Step 100: Accumulated Loss = 0.4955\n",
            "Epoch 5 Step 104: Accumulated Loss = 0.6382\n",
            "Epoch 5 Step 108: Accumulated Loss = 0.5622\n",
            "Epoch 5 Step 112: Accumulated Loss = 0.4042\n",
            "Epoch 5 Step 116: Accumulated Loss = 0.8073\n",
            "Epoch 5 Step 120: Accumulated Loss = 0.4514\n",
            "Epoch 5 Step 124: Accumulated Loss = 0.6391\n",
            "Epoch 5 Step 128: Accumulated Loss = 0.6978\n",
            "Epoch 5 Step 132: Accumulated Loss = 0.4863\n",
            "Epoch 5 Step 136: Accumulated Loss = 0.4859\n",
            "Epoch 5 Step 140: Accumulated Loss = 0.9763\n",
            "Epoch 5 Step 144: Accumulated Loss = 0.2354\n",
            "Epoch 5 Step 148: Accumulated Loss = 0.4438\n",
            "Epoch 5 Step 152: Accumulated Loss = 0.2378\n",
            "Epoch 5 Step 156: Accumulated Loss = 0.8751\n",
            "Epoch 5 Step 160: Accumulated Loss = 0.4617\n",
            "Epoch 5 Step 164: Accumulated Loss = 0.4982\n",
            "Epoch 5 Step 168: Accumulated Loss = 0.3260\n",
            "Epoch 5 Step 172: Accumulated Loss = 0.7857\n",
            "Epoch 5 Step 176: Accumulated Loss = 0.7675\n",
            "Epoch 5 Step 180: Accumulated Loss = 1.1360\n",
            "Epoch 5 Step 184: Accumulated Loss = 0.5772\n",
            "Epoch 5 Step 188: Accumulated Loss = 1.1619\n",
            "Epoch 5 Step 192: Accumulated Loss = 0.6365\n",
            "Epoch 5 Step 196: Accumulated Loss = 0.4687\n",
            "Epoch 5 Step 200: Accumulated Loss = 1.8458\n",
            "Epoch 5 Step 204: Accumulated Loss = 0.7707\n",
            "Epoch 5 Step 208: Accumulated Loss = 0.5120\n",
            "Epoch 5 Step 212: Accumulated Loss = 0.2012\n",
            "Epoch 5 Step 216: Accumulated Loss = 0.3606\n",
            "Epoch 5 Step 220: Accumulated Loss = 0.1237\n",
            "Epoch 5 Step 224: Accumulated Loss = 0.2551\n",
            "Epoch 5 Step 228: Accumulated Loss = 0.3137\n",
            "Epoch 5 Step 232: Accumulated Loss = 0.3216\n",
            "Epoch 5 Step 236: Accumulated Loss = 0.1662\n",
            "Epoch 5 Step 240: Accumulated Loss = 0.3516\n",
            "Epoch 5 Step 244: Accumulated Loss = 0.7180\n",
            "Epoch 5 Step 248: Accumulated Loss = 0.6370\n",
            "Epoch 5 Step 252: Accumulated Loss = 0.6594\n",
            "Epoch 5 Step 256: Accumulated Loss = 0.9949\n",
            "Epoch 5 Step 260: Accumulated Loss = 0.8004\n",
            "Epoch 5 Step 264: Accumulated Loss = 0.4994\n",
            "Epoch 5 Step 268: Accumulated Loss = 0.5542\n",
            "Epoch 5 Step 272: Accumulated Loss = 0.5583\n",
            "Epoch 5 Step 276: Accumulated Loss = 0.2767\n",
            "Epoch 5 Step 280: Accumulated Loss = 0.7792\n",
            "Epoch 5 Step 284: Accumulated Loss = 0.7194\n",
            "Epoch 5 Step 288: Accumulated Loss = 0.4226\n",
            "Epoch 5 Step 292: Accumulated Loss = 1.0016\n",
            "Epoch 5 Step 296: Accumulated Loss = 0.1389\n",
            "Epoch 5 Step 300: Accumulated Loss = 0.6077\n",
            "Epoch 5 Validation Accuracy: 1.0000\n",
            "Final Test Accuracy: 0.9867\n"
          ]
        }
      ],
      "source": [
        "# Training loop with gradient accumulation and evaluation\n",
        "num_epochs = 5\n",
        "accumulation_steps = 4\n",
        "for epoch in range(1, num_epochs + 1):\n",
        "    model.train()\n",
        "    running_loss = 0.0\n",
        "    optimizer.zero_grad()\n",
        "    for step, (vids, labels) in enumerate(train_loader, start=1):\n",
        "        inputs = processor(vids, return_tensors=\"pt\").to(model.device)\n",
        "        labels = labels.to(model.device)\n",
        "        outputs = model(**inputs, labels=labels)\n",
        "        loss = outputs.loss / accumulation_steps\n",
        "        loss.backward()\n",
        "        running_loss += loss.item()\n",
        "\n",
        "        if step % accumulation_steps == 0:\n",
        "            optimizer.step()\n",
        "            optimizer.zero_grad()\n",
        "            print(f\"Epoch {epoch} Step {step}: Accumulated Loss = {running_loss:.4f}\")\n",
        "            running_loss = 0.0\n",
        "\n",
        "    # End of epoch evaluation\n",
        "    val_acc = evaluate(val_loader, model, processor, model.device)\n",
        "    print(f\"Epoch {epoch} Validation Accuracy: {val_acc:.4f}\")\n",
        "    writer.add_scalar(\"Val Acc\", val_acc, epoch * len(train_loader)) # Log loss\n",
        "\n",
        "\n",
        "\n",
        "# Final test evaluation\n",
        "test_acc = evaluate(test_loader, model, processor, model.device)\n",
        "print(f\"Final Test Accuracy: {test_acc:.4f}\")\n",
        "writer.add_scalar(\"Final Test Acc\", test_acc, epoch * len(train_loader) + step) # Log loss\n",
        "writer.close()\n"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Let's push the model and the tensorboard logs to Hub."
      ],
      "metadata": {
        "id": "WQ7ElROf1LLq"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ogNAQTWF5JVP",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 101,
          "referenced_widgets": [
            "a2968992d54e49a2b9cc4fe4188b4966",
            "d2469efafa7c46fd99e21e0e072f3c17",
            "db421d09ce8a4176810e8c077cc09349",
            "1d49042c64f3406998d04ca269e9917b",
            "db8415fd606d46cfabb2339ae5d6cd55",
            "e84e157ffc8744a7a47c1ff6728f079f",
            "d9624aa94bc24c0a90f36b0ef0df6f46",
            "d0861171bf1e4c058467a4c3d5a92488",
            "b260a503457a4f1993152ececb7e4393",
            "12b1529d0e254ad8a9efd35b6efee321",
            "cc50db90c3e448449cecc7f1750db542"
          ]
        },
        "outputId": "53e2b1a0-2b83-4e70-fefc-46d8be2562b4"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/1.50G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a2968992d54e49a2b9cc4fe4188b4966"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "CommitInfo(commit_url='https://huggingface.co/merve/vjepa2-vitl-fpc16-256-ssv2-ucf101/commit/4da9a6ab7afa6440b18257b361b635c5cf1fa3c5', commit_message='Upload processor', commit_description='', oid='4da9a6ab7afa6440b18257b361b635c5cf1fa3c5', pr_url=None, repo_url=RepoUrl('https://huggingface.co/merve/vjepa2-vitl-fpc16-256-ssv2-ucf101', endpoint='https://huggingface.co', repo_type='model', repo_id='merve/vjepa2-vitl-fpc16-256-ssv2-ucf101'), pr_revision=None, pr_num=None)"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 20
        }
      ],
      "source": [
        "model.push_to_hub(\"merve/vjepa2-vitl-fpc16-256-ssv2-ucf101\")\n",
        "processor.push_to_hub(\"merve/vjepa2-vitl-fpc16-256-ssv2-ucf101\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from huggingface_hub import upload_folder\n",
        "upload_folder(\n",
        "    repo_id=\"merve/vjepa2-vitl-fpc16-256-ssv2-ucf101\",\n",
        "    folder_path=\"runs\",\n",
        "    path_in_repo=\"runs\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 101,
          "referenced_widgets": [
            "c35ab4407f3940e494db6a1351cba109",
            "c7b65b8da06b4a13822037698287411d",
            "b3da0c02641549d9bab4069bfbb07f80",
            "de117c8ebf0d4ea3b664a9caab6b5deb",
            "de49cdea39294e8a94b304abde65e403",
            "079f0794d23a48b190d57066047d75de",
            "1c0398695ec24603a1c002dce26e9eea",
            "ecd905cd7bf94339a8cb985d3e0b467f",
            "49973216a28549eba70a9f816d2eb9fc",
            "46d7050d9695409c819c2924a50d1ce4",
            "545cd68b6152416988327c478bcc8242"
          ]
        },
        "id": "yaCDB4A70e77",
        "outputId": "2f7521d1-393c-4a10-b5c3-53be0efad590"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "events.out.tfevents.1749828509.38da49c797ee.13694.0:   0%|          | 0.00/371 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c35ab4407f3940e494db6a1351cba109"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "CommitInfo(commit_url='https://huggingface.co/merve/vjepa2-vitl-fpc16-256-ssv2-ucf101/commit/4c0648e3194239a9bebe1dfffff04486d130e2bb', commit_message='Upload folder using huggingface_hub', commit_description='', oid='4c0648e3194239a9bebe1dfffff04486d130e2bb', pr_url=None, repo_url=RepoUrl('https://huggingface.co/merve/vjepa2-vitl-fpc16-256-ssv2-ucf101', endpoint='https://huggingface.co', repo_type='model', repo_id='merve/vjepa2-vitl-fpc16-256-ssv2-ucf101'), pr_revision=None, pr_num=None)"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Evaluation"
      ],
      "metadata": {
        "id": "Sh3c-eUY2_bK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "You can view the logs [here](https://huggingface.co/merve/vjepa2-vitl-fpc16-256-ssv2-ucf101/tensorboard).\n",
        "\n",
        "Let's put model to test with an in-the-wild video of a concert scene, although we don't exactly have this label, we have \"Band Marching\" which is the closest one."
      ],
      "metadata": {
        "id": "l3ZYg9_L0pFd"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "oK2ZOGfT9-Nk"
      },
      "outputs": [],
      "source": [
        "# Utility to plot the frames\n",
        "# (taken from: https://docs.pytorch.org/torchcodec/stable/generated_examples/basic_example.html#sphx-glr-generated-examples-basic-example-py)\n",
        "def plot(frames, title, fname):\n",
        "    try:\n",
        "        from torchvision.utils import make_grid\n",
        "        from torchvision.transforms.v2.functional import to_pil_image\n",
        "        import matplotlib.pyplot as plt\n",
        "    except ImportError:\n",
        "        print(\"Cannot plot, please run `pip install torchvision matplotlib`\")\n",
        "        return\n",
        "\n",
        "    plt.rcParams[\"savefig.bbox\"] = 'tight'\n",
        "    _, ax = plt.subplots()\n",
        "    ax.imshow(to_pil_image(make_grid(frames)))\n",
        "    ax.set(xticklabels=[], yticklabels=[], xticks=[], yticks=[])\n",
        "    if title is not None:\n",
        "        ax.set_title(title)\n",
        "    plt.tight_layout()\n",
        "    plt.savefig(fname)\n",
        "    plt.close()\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from PIL import Image\n",
        "video_url = \"https://huggingface.co/datasets/merve/vlm_test_images/resolve/main/IMG_3830.mp4\"\n",
        "vr = VideoDecoder(video_url)\n",
        "frame_idx = np.arange(0, 32)\n",
        "video_frames = vr.get_frames_at(indices=frame_idx).data\n",
        "\n",
        "video = clips_at_random_indices(\n",
        "    vr,\n",
        "    num_clips=1,\n",
        "    num_frames_per_clip=model.config.frames_per_clip,\n",
        "    num_indices_between_frames=4,\n",
        ").data\n",
        "\n",
        "plot(video[0], title=\"Concert Scene\", fname=\"test.png\")\n",
        "display(Image.open(\"test.png\"))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 330
        },
        "id": "2LrMg4wS3yok",
        "outputId": "50b59a96-55ec-45aa-d99b-fca550716b06"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<PIL.PngImagePlugin.PngImageFile image mode=RGBA size=630x313>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Closest label is BandMarching so we get this."
      ],
      "metadata": {
        "id": "7vndbNZT8_eE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "inputs = processor(video_frames, return_tensors=\"pt\").to(model.device)\n",
        "\n",
        "with torch.no_grad():\n",
        "    logits = model(**inputs).logits\n",
        "\n",
        "predicted_class_idx = logits.argmax(-1).item()\n",
        "print(\"Predicted class:\", id2label[predicted_class_idx])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "yHNn-Wxh8VfZ",
        "outputId": "d6ad6096-6db2-4ac2-9417-3a43286d5009"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Predicted class: BandMarching\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "We're looking forward to see what you'll build with V-JEPA 2!"
      ],
      "metadata": {
        "id": "KkdrD_Pq9FWw"
      }
    }
  ],
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