examples/python/transformers/HuggingFace in Spark NLP - ViTForImageClassification.ipynb

{
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RwO95VrJkP7c"
      },
      "source": [
        "![JohnSnowLabs](https://sparknlp.org/assets/images/logo.png)\n",
        "\n",
        "[![Open In Colab](https://colab.research.google.com/github/JohnSnowLabs/spark-nlp/blob/master/examples/python/transformers/HuggingFace%20in%20Spark%20NLP%20-%20ViTForImageClassification.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "luGCzhx4kP7t"
      },
      "source": [
        "## Import ViTForImageClassification models from HuggingFace 🤗 into Spark NLP 🚀\n",
        "\n",
        "### Let's keep in mind a few things before we start 😊\n",
        "\n",
        "- This feature is only in `Spark NLP 4.1.0` and after. So please make sure you have upgraded to the latest Spark NLP release\n",
        "- You can import Vision Transformer (ViT) models trained/fine-tuned for question answering via `ViTForImageClassification` or `TFViTForImageClassification`. These models are usually under `Image Classification` category and have `vit` in their labels\n",
        "- Reference: [TFViTForImageClassification](https://huggingface.co/docs/transformers/model_doc/vit#transformers.TFViTForImageClassification)\n",
        "- Some [example models](https://huggingface.co/models?other=vit&pipeline_tag=image-classification&sort=downloads)\n",
        "\n",
        "### How to Scale Vision Transformer (ViT) models in Spark NLP\n",
        "- [Scale Vision Transformers (ViT) Beyond Hugging Face | Part 1](https://blog.devgenius.io/scale-vision-transformers-vit-beyond-hugging-face-part-1-e09318cab588)\n",
        "- [Scale Vision Transformers (ViT) Beyond Hugging Face | Part 2](https://blog.devgenius.io/scale-vision-transformers-vit-beyond-hugging-face-part-2-b7b296d548b7)\n",
        "- [Scale Vision Transformers (ViT) Beyond Hugging Face | Part 3](https://blog.devgenius.io/scale-vision-transformers-vit-beyond-hugging-face-part-3-5b8c13ef6477)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "BicJ8qw3kP7y"
      },
      "source": [
        "## Export and Save HuggingFace model"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WaPWYpemkP71"
      },
      "source": [
        "- Let's install `HuggingFace` and `TensorFlow`. You don't need `TensorFlow` to be installed for Spark NLP, however, we need it to load and save models from HuggingFace.\n",
        "- We lock TensorFlow on `2.11.0` version and Transformers on `4..39.3`. This doesn't mean it won't work with the future releases, but we wanted you to know which versions have been tested successfully."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "fkbuMOf2kP73",
        "outputId": "8777febf-036a-4f37-a377-07528fd3d4bf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m8.8/8.8 MB\u001b[0m \u001b[31m7.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "\u001b[?25h\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "pandas-gbq 0.19.2 requires google-auth-oauthlib>=0.7.0, but you have google-auth-oauthlib 0.4.6 which is incompatible.\n",
            "tensorflow-datasets 4.9.4 requires protobuf>=3.20, but you have protobuf 3.19.6 which is incompatible.\n",
            "tensorflow-metadata 1.14.0 requires protobuf<4.21,>=3.20.3, but you have protobuf 3.19.6 which is incompatible.\n",
            "tf-keras 2.15.1 requires tensorflow<2.16,>=2.15, but you have tensorflow 2.11.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0m"
          ]
        }
      ],
      "source": [
        "! pip install -q transformers==4.39.3 tensorflow==2.11.0"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3j7_Tc11kP77"
      },
      "source": [
        "- HuggingFace comes with a native `saved_model` feature inside `save_pretrained` function for TensorFlow based models. We will use that to save it as TF `SavedModel`.\n",
        "- We'll use [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) model from HuggingFace as an example\n",
        "- In addition to `TFViTForImageClassification` we also need to save the `ViTFeatureExtractor`"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "6EuGHJAwkP79",
        "outputId": "04255a00-7e33-4c68-8367-6b56126d95f7",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 359,
          "referenced_widgets": [
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            "6040072521f044a4b3ade3d385203843",
            "cc9ffcf13d1145ca8c87e3289cfcba15"
          ]
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: 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"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "preprocessor_config.json:   0%|          | 0.00/160 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "07a73882f8d447c7b4a03211f35f6713"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/vit/feature_extraction_vit.py:28: FutureWarning: The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use ViTImageProcessor instead.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/69.7k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "562c16d0b10f40e098fa3d9ddef5bb58"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/346M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "3236e68223b44351a07539ff71117cfe"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "All PyTorch model weights were used when initializing TFViTForImageClassification.\n",
            "\n",
            "All the weights of TFViTForImageClassification were initialized from the PyTorch model.\n",
            "If your task is similar to the task the model of the checkpoint was trained on, you can already use TFViTForImageClassification for predictions without further training.\n",
            "WARNING:absl:Found untraced functions such as embeddings_layer_call_fn, embeddings_layer_call_and_return_conditional_losses, encoder_layer_call_fn, encoder_layer_call_and_return_conditional_losses, layernorm_layer_call_fn while saving (showing 5 of 421). These functions will not be directly callable after loading.\n"
          ]
        }
      ],
      "source": [
        "from transformers import TFViTForImageClassification, ViTForImageClassification, ViTFeatureExtractor\n",
        "\n",
        "MODEL_NAME = 'google/vit-base-patch16-224'\n",
        "\n",
        "feature_extractor = ViTFeatureExtractor.from_pretrained(MODEL_NAME)\n",
        "\n",
        "try:\n",
        "  model = TFViTForImageClassification.from_pretrained(MODEL_NAME)\n",
        "except:\n",
        "  model = TFViTForImageClassification.from_pretrained(MODEL_NAME, from_pt=True)\n",
        "\n",
        "model.save_pretrained(\"./{}\".format(MODEL_NAME), saved_model=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "xsrN9LGxkP8C"
      },
      "outputs": [],
      "source": [
        "import json\n",
        "\n",
        "# get label2id in JSON string\n",
        "json_data = json.dumps(model.config.label2id)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "zK2YwXlJkP8E",
        "outputId": "41bfd6ff-d8ef-4931-a364-e9d5ede009c3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['google/vit-base-patch16-224/saved_model/1/assets/preprocessor_config.json']"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "# Let's make sure the id is type int and not string\n",
        "\n",
        "new_dict = dict()\n",
        "old_dict = json.loads(json_data)\n",
        "for k in old_dict:\n",
        "  v = old_dict[k]\n",
        "  if type(v) == str:\n",
        "    v = int(v)\n",
        "  new_dict[k] = v\n",
        "json_data = new_dict\n",
        "\n",
        "# now we can save the labels.json to our assets directory\n",
        "with open(f'{MODEL_NAME}/saved_model/1/assets/labels.json', 'w') as outfile:\n",
        "      json.dump(json_data, outfile)\n",
        "      outfile.write('\\n')\n",
        "\n",
        "feature_extractor.save_pretrained(f\"{MODEL_NAME}/saved_model/1/assets/\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "rZYvOLnIkP8G"
      },
      "source": [
        "Let's have a look inside these two directories and see what we are dealing with:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "SrMHJ12-kP8H",
        "outputId": "762ef183-1288-4a80-adbd-ac928f2612e0",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 338492\n",
            "-rw-r--r-- 1 root root     69684 Apr 12 18:37 config.json\n",
            "drwxr-xr-x 3 root root      4096 Apr 12 18:37 saved_model\n",
            "-rw-r--r-- 1 root root 346537560 Apr 12 18:37 tf_model.h5\n"
          ]
        }
      ],
      "source": [
        "!ls -l {MODEL_NAME}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "LgcxUlJ9kP8I",
        "outputId": "85941555-b40e-4cbc-da07-a1f566a0c955",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 7308\n",
            "drwxr-xr-x 2 root root    4096 Apr 12 18:37 assets\n",
            "-rw-r--r-- 1 root root      53 Apr 12 18:37 fingerprint.pb\n",
            "-rw-r--r-- 1 root root  335829 Apr 12 18:37 keras_metadata.pb\n",
            "-rw-r--r-- 1 root root 7131464 Apr 12 18:37 saved_model.pb\n",
            "drwxr-xr-x 2 root root    4096 Apr 12 18:37 variables\n"
          ]
        }
      ],
      "source": [
        "!ls -l {MODEL_NAME}/saved_model/1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "bUc2CKMCkP8J",
        "outputId": "0d2246ff-5ca1-46cc-d061-fa252e042703",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 36\n",
            "-rw-r--r-- 1 root root 29552 Apr 12 18:37 labels.json\n",
            "-rw-r--r-- 1 root root   580 Apr 12 18:37 preprocessor_config.json\n"
          ]
        }
      ],
      "source": [
        "!ls -l {MODEL_NAME}/saved_model/1/assets"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kWTiIjKAkP8K"
      },
      "source": [
        "- As you can see, we need the SavedModel from `saved_model/1/` path\n",
        "- We also be needing `lables.json` and `preprocessor_config.json` in our `assets`"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f0IOam9mkP8L"
      },
      "source": [
        "## Import and Save ViTForImageClassification in Spark NLP\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "yhei05_FkP8M"
      },
      "source": [
        "- Let's install and setup Spark NLP in Google Colab\n",
        "- This part is pretty easy via our simple script"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "Nf7W5EZKkP8M",
        "outputId": "5673b083-17a9-419a-9430-08f9535c5a40",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-04-12 18:37:13--  http://setup.johnsnowlabs.com/colab.sh\n",
            "Resolving setup.johnsnowlabs.com (setup.johnsnowlabs.com)... 51.158.130.125\n",
            "Connecting to setup.johnsnowlabs.com (setup.johnsnowlabs.com)|51.158.130.125|:80... connected.\n",
            "HTTP request sent, awaiting response... 302 Moved Temporarily\n",
            "Location: https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp/master/scripts/colab_setup.sh [following]\n",
            "--2024-04-12 18:37:13--  https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp/master/scripts/colab_setup.sh\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.109.133, 185.199.111.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.109.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 1191 (1.2K) [text/plain]\n",
            "Saving to: ‘STDOUT’\n",
            "\n",
            "\r-                     0%[                    ]       0  --.-KB/s               \r-                   100%[===================>]   1.16K  --.-KB/s    in 0s      \n",
            "\n",
            "2024-04-12 18:37:13 (59.8 MB/s) - written to stdout [1191/1191]\n",
            "\n",
            "Installing PySpark 3.2.3 and Spark NLP 5.3.3\n",
            "setup Colab for PySpark 3.2.3 and Spark NLP 5.3.3\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m281.5/281.5 MB\u001b[0m \u001b[31m3.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m568.4/568.4 kB\u001b[0m \u001b[31m23.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m199.7/199.7 kB\u001b[0m \u001b[31m15.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for pyspark (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
          ]
        }
      ],
      "source": [
        "! wget http://setup.johnsnowlabs.com/colab.sh -O - | bash"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "C793Y-oLkP8N"
      },
      "source": [
        "Let's start Spark with Spark NLP included via our simple `start()` function"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "KvA3uD90kP8O",
        "outputId": "4fccb8b4-65c1-406b-d0c0-82ca9d0bfa53",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/lib/python3.10/subprocess.py:1796: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = _posixsubprocess.fork_exec(\n"
          ]
        }
      ],
      "source": [
        "import sparknlp\n",
        "# let's start Spark with Spark NLP\n",
        "spark = sparknlp.start()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a2wDHFldkP8O"
      },
      "source": [
        "- Let's use `loadSavedModel` functon in `ViTForImageClassification` which allows us to load TensorFlow model in SavedModel format\n",
        "- `loadSavedModel` accepts two params, first is the path to the TF SavedModel. The second is the SparkSession that is `spark` variable we previously started via `sparknlp.start()`\n",
        "- NOTE: `loadSavedModel` accepts local paths in addition to distributed file systems such as `HDFS`, `S3`, `DBFS`, etc. This feature was introduced in Spark NLP 4.2.2 release. Keep in mind the best and recommended way to move/share/reuse Spark NLP models is to use `write.save` so you can use `.load()` from any file systems natively.st and recommended way to move/share/reuse Spark NLP models is to use `write.save` so you can use `.load()` from any file systems natively.\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "ZKssRwwEkP8P"
      },
      "outputs": [],
      "source": [
        "from sparknlp.annotator import *\n",
        "from sparknlp.base import *\n",
        "\n",
        "imageClassifier = ViTForImageClassification.loadSavedModel(\n",
        "     '{}/saved_model/1'.format(MODEL_NAME),\n",
        "     spark\n",
        " )\\\n",
        "  .setInputCols([\"image_assembler\"])\\\n",
        "  .setOutputCol(\"class\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "eT6iwhpDkP8Q"
      },
      "source": [
        "- Let's save it on disk so it is easier to be moved around and also be used later via `.load` function"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "yDAAEiPakP8Q"
      },
      "outputs": [],
      "source": [
        "imageClassifier.write().overwrite().save(\"./{}_spark_nlp\".format(MODEL_NAME))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mpm1yIKYkP8R"
      },
      "source": [
        "Let's clean up stuff we don't need anymore"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "uuEZaDyJkP8S"
      },
      "outputs": [],
      "source": [
        "!rm -rf {MODEL_NAME}_tokenizer {MODEL_NAME}"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SaEtcMAakP8T"
      },
      "source": [
        "Awesome 😎  !\n",
        "\n",
        "This is your ViTForImageClassification model from HuggingFace 🤗  loaded and saved by Spark NLP 🚀"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "5M6zxw9ukP8U",
        "outputId": "997a88e6-f2fc-4ddf-a616-f7436d9dd108",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "total 345052\n",
            "drwxr-xr-x 4 root root      4096 Apr 12 18:40 fields\n",
            "-rw-r--r-- 1 root root 353317064 Apr 12 18:40 image_classification_tensorflow\n",
            "drwxr-xr-x 2 root root      4096 Apr 12 18:40 metadata\n"
          ]
        }
      ],
      "source": [
        "! ls -l {MODEL_NAME}_spark_nlp"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SSUdyG7JkP8U"
      },
      "source": [
        "Now let's see how we can use it on other machines, clusters, or any place you wish to use your new and shiny ViTForImageClassification model in Spark NLP 🚀 pipeline!"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "mE1LJWJDkP8V",
        "outputId": "798c3506-9042-4799-c435-57c5c25a4bcf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2024-04-12 18:40:16--  https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp/master/src/test/resources/image/hippopotamus.JPEG\n",
            "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 185.199.108.133, 185.199.109.133, 185.199.110.133, ...\n",
            "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|185.199.108.133|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 147353 (144K) [image/jpeg]\n",
            "Saving to: ‘hippopotamus.JPEG’\n",
            "\n",
            "hippopotamus.JPEG   100%[===================>] 143.90K  --.-KB/s    in 0.02s   \n",
            "\n",
            "2024-04-12 18:40:17 (6.08 MB/s) - ‘hippopotamus.JPEG’ saved [147353/147353]\n",
            "\n"
          ]
        }
      ],
      "source": [
        "!wget https://raw.githubusercontent.com/JohnSnowLabs/spark-nlp/master/src/test/resources/image/hippopotamus.JPEG"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "7G0p0USYkP8W",
        "outputId": "ef6593df-0318-4409-c643-d1178e27b5dc",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/jpeg": 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            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {}
        }
      ],
      "source": [
        "from IPython.display import Image, display\n",
        "display(Image(\"hippopotamus.JPEG\"))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "SNG0eyu8kP8X",
        "outputId": "1777c222-8ea9-4d20-8067-5c349764d3b3",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "+----------------------------------------------------------+\n",
            "|result                                                    |\n",
            "+----------------------------------------------------------+\n",
            "|[hippopotamus, hippo, river horse, Hippopotamus amphibius]|\n",
            "+----------------------------------------------------------+\n",
            "\n"
          ]
        }
      ],
      "source": [
        "document_assembler = ImageAssembler() \\\n",
        "    .setInputCol(\"image\") \\\n",
        "    .setOutputCol(\"image_assembler\")\n",
        "\n",
        "imageClassifier_loaded = ViTForImageClassification.load(\"./{}_spark_nlp\".format(MODEL_NAME))\\\n",
        "  .setInputCols([\"image_assembler\"])\\\n",
        "  .setOutputCol(\"class\")\n",
        "\n",
        "pipeline = Pipeline().setStages([\n",
        "    document_assembler,\n",
        "    imageClassifier_loaded\n",
        "])\n",
        "\n",
        "test_image = spark.read\\\n",
        "    .format(\"image\")\\\n",
        "    .option(\"dropInvalid\", value = True)\\\n",
        "    .load(\"./hippopotamus.JPEG\")\n",
        "\n",
        "result = pipeline.fit(test_image).transform(test_image)\n",
        "\n",
        "result.select(\"class.result\").show(1, False)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w9wVzNDdkP8Y"
      },
      "source": [
        "That's it! You can now go wild and use hundreds of `ViTForImageClassification` models from HuggingFace 🤗 in Spark NLP 🚀\n"
      ]
    }
  ],
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    "colab": {
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