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            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m23.7/23.7 MB\u001b[0m \u001b[31m77.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m823.6/823.6 kB\u001b[0m \u001b[31m65.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m14.1/14.1 MB\u001b[0m \u001b[31m60.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m731.7/731.7 MB\u001b[0m \u001b[31m2.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m410.6/410.6 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[32m121.6/121.6 MB\u001b[0m \u001b[31m8.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m56.5/56.5 MB\u001b[0m \u001b[31m16.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m124.2/124.2 MB\u001b[0m \u001b[31m8.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m196.0/196.0 MB\u001b[0m \u001b[31m6.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m209.8/209.8 MB\u001b[0m \u001b[31m5.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m99.1/99.1 kB\u001b[0m \u001b[31m14.3 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m89.2/89.2 MB\u001b[0m \u001b[31m8.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m20.2/20.2 MB\u001b[0m \u001b[31m37.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\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",
            "fastai 2.7.12 requires torch<2.1,>=1.7, but you have torch 2.1.0 which is incompatible.\n",
            "torchdata 0.6.1 requires torch==2.0.1, but you have torch 2.1.0 which is incompatible.\n",
            "torchtext 0.15.2 requires torch==2.0.1, but you have torch 2.1.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0m  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m302.0/302.0 kB\u001b[0m \u001b[31m4.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.8/3.8 MB\u001b[0m \u001b[31m17.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m23.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m295.0/295.0 kB\u001b[0m \u001b[31m28.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m258.1/258.1 kB\u001b[0m \u001b[31m4.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m301.0/301.0 kB\u001b[0m \u001b[31m9.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m92.6/92.6 MB\u001b[0m \u001b[31m9.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m46.0/46.0 kB\u001b[0m \u001b[31m6.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m519.6/519.6 kB\u001b[0m \u001b[31m52.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.3/1.3 MB\u001b[0m \u001b[31m56.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m86.8/86.8 kB\u001b[0m \u001b[31m11.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m115.3/115.3 kB\u001b[0m \u001b[31m15.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m22.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m18.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Building wheel for optimum (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.6/1.6 MB\u001b[0m \u001b[31m3.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip install -q --upgrade torch torchvision torchaudio\n",
        "!pip install -q git+https://github.com/huggingface/transformers\n",
        "!pip install -q accelerate optimum\n",
        "!pip install -q ipython-autotime"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%load_ext autotime"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GoWs8boSf6CC",
        "outputId": "e21bd57e-8e58-49ed-f2af-6c8d65837a17"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 299 µs (started: 2023-10-14 16:00:04 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from transformers import pipeline"
      ],
      "metadata": {
        "id": "U2oi9R0xX1aX",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "56a84591-572b-4b48-9fd2-3a70eb2fbaf3"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 17.7 s (started: 2023-10-13 17:02:56 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Download a test file!\n",
        "\n",
        "The only fitting test audio to use for our benchmark would be [Lex interviewing Sam Altman](https://www.youtube.com/watch?v=L_Guz73e6fw&t=8s). We'll use the audio file corresponding to his podcast. I uploaded it on a wee dataset on the hub [here](https://huggingface.co/datasets/reach-vb/random-audios/blob/main/sam_altman_lex_podcast_367.flac)."
      ],
      "metadata": {
        "id": "p7iiB5HQcmOG"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!wget https://huggingface.co/datasets/reach-vb/random-audios/resolve/main/sam_altman_lex_podcast_367.flac"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-1b4AMKScNLl",
        "outputId": "31278a5c-2fbc-4f25-ff73-f3728d95530f"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "--2023-10-14 16:00:04--  https://huggingface.co/datasets/reach-vb/random-audios/resolve/main/sam_altman_lex_podcast_367.flac\n",
            "Resolving huggingface.co (huggingface.co)... 18.172.134.88, 18.172.134.24, 18.172.134.124, ...\n",
            "Connecting to huggingface.co (huggingface.co)|18.172.134.88|:443... connected.\n",
            "HTTP request sent, awaiting response... 302 Found\n",
            "Location: https://cdn-lfs.huggingface.co/repos/96/e4/96e4f69cd112b019dd764318570e47e5fe96de53d8c32a99d745e72d9086e355/b2fd593ce144a8d904cf49a4ed77ed06eb50644a053dddd280c81a3ef94fb60e?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27sam_altman_lex_podcast_367.flac%3B+filename%3D%22sam_altman_lex_podcast_367.flac%22%3B&response-content-type=audio%2Fx-flac&Expires=1697558404&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY5NzU1ODQwNH19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy5odWdnaW5nZmFjZS5jby9yZXBvcy85Ni9lNC85NmU0ZjY5Y2QxMTJiMDE5ZGQ3NjQzMTg1NzBlNDdlNWZlOTZkZTUzZDhjMzJhOTlkNzQ1ZTcyZDkwODZlMzU1L2IyZmQ1OTNjZTE0NGE4ZDkwNGNmNDlhNGVkNzdlZDA2ZWI1MDY0NGEwNTNkZGRkMjgwYzgxYTNlZjk0ZmI2MGU%7EcmVzcG9uc2UtY29udGVudC1kaXNwb3NpdGlvbj0qJnJlc3BvbnNlLWNvbnRlbnQtdHlwZT0qIn1dfQ__&Signature=mw4yQ1cr9M1lA-V%7EonLoP4of2IBizFQ-KAXi-S6PpFnDEh%7EL1KppDZtirr5y-7xDE-65pny1xXH8tR80EOJ4KMwanuocKrEV9oBjsAEOJZBFP6Fe%7Ejge4oJEBSJT5G7r5srZWJzlrVaOQE8tXscYPj4%7EvpPAKiCU%7EKAQ3zTiWkRta6S1bZ0hm1F8UobRahyvBc%7ENfSzGSOXz2LCLWhroc5mGPA9MMusAT0RyPyX19kc1%7EGkAz6UWZQ7BY09ZEm%7ERmEsHf3ZGLWELqjRIS0pP92%7EuOGd0AUkwU78svAMJYcK8kAlCy-buaCH4Mxf4cWx8fkvNN7X6-ZnwvBFcHJ5pXQ__&Key-Pair-Id=KVTP0A1DKRTAX [following]\n",
            "--2023-10-14 16:00:04--  https://cdn-lfs.huggingface.co/repos/96/e4/96e4f69cd112b019dd764318570e47e5fe96de53d8c32a99d745e72d9086e355/b2fd593ce144a8d904cf49a4ed77ed06eb50644a053dddd280c81a3ef94fb60e?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27sam_altman_lex_podcast_367.flac%3B+filename%3D%22sam_altman_lex_podcast_367.flac%22%3B&response-content-type=audio%2Fx-flac&Expires=1697558404&Policy=eyJTdGF0ZW1lbnQiOlt7IkNvbmRpdGlvbiI6eyJEYXRlTGVzc1RoYW4iOnsiQVdTOkVwb2NoVGltZSI6MTY5NzU1ODQwNH19LCJSZXNvdXJjZSI6Imh0dHBzOi8vY2RuLWxmcy5odWdnaW5nZmFjZS5jby9yZXBvcy85Ni9lNC85NmU0ZjY5Y2QxMTJiMDE5ZGQ3NjQzMTg1NzBlNDdlNWZlOTZkZTUzZDhjMzJhOTlkNzQ1ZTcyZDkwODZlMzU1L2IyZmQ1OTNjZTE0NGE4ZDkwNGNmNDlhNGVkNzdlZDA2ZWI1MDY0NGEwNTNkZGRkMjgwYzgxYTNlZjk0ZmI2MGU%7EcmVzcG9uc2UtY29udGVudC1kaXNwb3NpdGlvbj0qJnJlc3BvbnNlLWNvbnRlbnQtdHlwZT0qIn1dfQ__&Signature=mw4yQ1cr9M1lA-V%7EonLoP4of2IBizFQ-KAXi-S6PpFnDEh%7EL1KppDZtirr5y-7xDE-65pny1xXH8tR80EOJ4KMwanuocKrEV9oBjsAEOJZBFP6Fe%7Ejge4oJEBSJT5G7r5srZWJzlrVaOQE8tXscYPj4%7EvpPAKiCU%7EKAQ3zTiWkRta6S1bZ0hm1F8UobRahyvBc%7ENfSzGSOXz2LCLWhroc5mGPA9MMusAT0RyPyX19kc1%7EGkAz6UWZQ7BY09ZEm%7ERmEsHf3ZGLWELqjRIS0pP92%7EuOGd0AUkwU78svAMJYcK8kAlCy-buaCH4Mxf4cWx8fkvNN7X6-ZnwvBFcHJ5pXQ__&Key-Pair-Id=KVTP0A1DKRTAX\n",
            "Resolving cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)... 18.154.185.26, 18.154.185.94, 18.154.185.27, ...\n",
            "Connecting to cdn-lfs.huggingface.co (cdn-lfs.huggingface.co)|18.154.185.26|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: 351705020 (335M) [audio/x-flac]\n",
            "Saving to: ‘sam_altman_lex_podcast_367.flac’\n",
            "\n",
            "sam_altman_lex_podc 100%[===================>] 335.41M   212MB/s    in 1.6s    \n",
            "\n",
            "2023-10-14 16:00:06 (212 MB/s) - ‘sam_altman_lex_podcast_367.flac’ saved [351705020/351705020]\n",
            "\n",
            "time: 1.83 s (started: 2023-10-14 16:00:04 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Base case"
      ],
      "metadata": {
        "id": "vIEtHMfYD3WT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pipe = pipeline(\"automatic-speech-recognition\",\n",
        "                \"openai/whisper-large-v2\",\n",
        "                device=\"cuda:0\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 486,
          "referenced_widgets": [
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            "c248c83525424032bd08de97aa53bf45",
            "ea623b4e7d62443892de827da9d2332a",
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            "0b00ae26880e400d991d564688bcf10f",
            "87c44bd8e800411d8e1ec790f0adfc57"
          ]
        },
        "id": "SExebSIlbRGP",
        "outputId": "da04934c-8c5a-4ae0-a936-33dcd15f3244"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/1.99k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c119a796918548ea8050793350f4e9c4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading model.safetensors:   0%|          | 0.00/6.17G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "43c6a7652e1248c39c2b0a3b5bdd42e9"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)neration_config.json:   0%|          | 0.00/4.26k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "db1052564aab4dc694239a7d3f577897"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/805 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c56c5630818d4cd387b27b882b352fe1"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/1.04M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "17406428a6b34e1d8f862fe2dbe71bff"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.48M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ebbbfd7dc3d5452090b873b59bdf4ec3"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)olve/main/merges.txt:   0%|          | 0.00/494k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "9a0d0a048ef04f5f80d965949c55cc70"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)main/normalizer.json:   0%|          | 0.00/52.7k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "643a752abc334232a88bdea4f2959815"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)in/added_tokens.json:   0%|          | 0.00/34.6k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c1696c2d4f2447828dbf6ff645ad1433"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/2.08k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d2d2f3d54b4e49f2ab157f13df47b3ea"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)rocessor_config.json:   0%|          | 0.00/185k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "1c9ce929a08443328569b21e5fd2b29c"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 1min 39s (started: 2023-10-13 14:26:56 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs = pipe(\"sam_altman_lex_podcast_367.flac\",\n",
        "               chunk_length_s=30)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CwwfPHH2emFE",
        "outputId": "5af4a050-ba09-4259-b2e8-4f0e6ecdef31"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 31min 1s (started: 2023-10-13 14:28:56 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs[\"text\"][:200]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 100
        },
        "id": "J9nozgCJeJm3",
        "outputId": "a2e218d1-810f-4cdd-ba16-6477d449716c"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "' We have been a misunderstood and badly mocked org for a long time. When we started, we announced the org at the end of 2015 and said we were going to work on AGI, people thought we were batshit insan'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 6.63 ms (started: 2023-10-13 15:00:48 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "It took about 31 minutes and 1 seconds to run inference on a 2.5 hour long snippet.\n",
        "\n",
        "Can we make this faster?\n",
        "\n",
        "## Cue.. Batching"
      ],
      "metadata": {
        "id": "xo6_FDUxiUNX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "outputs = pipe(\"sam_altman_lex_podcast_367.flac\",\n",
        "               chunk_length_s=30,\n",
        "               batch_size=8)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YlhvjyS0hEWp",
        "outputId": "5e05dd97-8edb-43a6-ccfa-0014bcbe6ad0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 13min 19s (started: 2023-10-13 15:00:58 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs[\"text\"][:200]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 100
        },
        "id": "gCxFEKkpknpz",
        "outputId": "725d6f53-3682-4857-a94a-4b49cf5a9205"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "' We have been a misunderstood and badly mocked org for a long time. When we started, we announced the org at the end of 2015 and said we were going to work on AGI, people thought we were batshit insan'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 10
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 3.02 ms (started: 2023-10-13 15:17:24 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Voila!! It only took the `pipeline` 13 minutes and 19 seconds to run inference this time. We were able to reduce the inference time by 50%. 🚀"
      ],
      "metadata": {
        "id": "kppo04wkkVmG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "But, the real question is - can we make it even faster? 💨\n",
        "\n",
        "## Half - Precision"
      ],
      "metadata": {
        "id": "BJKzg1Thk3ar"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pipe = pipeline(\"automatic-speech-recognition\",\n",
        "                \"openai/whisper-large-v2\",\n",
        "                torch_dtype=torch.float16,\n",
        "                device=\"cuda:0\")"
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      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/1.99k [00:00<?, ?B/s]"
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading model.safetensors:   0%|          | 0.00/6.17G [00:00<?, ?B/s]"
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        {
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          "data": {
            "text/plain": [
              "Downloading (…)neration_config.json:   0%|          | 0.00/4.26k [00:00<?, ?B/s]"
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          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/805 [00:00<?, ?B/s]"
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              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/1.04M [00:00<?, ?B/s]"
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          "data": {
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              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.48M [00:00<?, ?B/s]"
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              "Downloading (…)olve/main/merges.txt:   0%|          | 0.00/494k [00:00<?, ?B/s]"
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              "Downloading (…)in/added_tokens.json:   0%|          | 0.00/34.6k [00:00<?, ?B/s]"
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          "metadata": {}
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/2.08k [00:00<?, ?B/s]"
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        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)rocessor_config.json:   0%|          | 0.00/185k [00:00<?, ?B/s]"
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        {
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          "text": [
            "time: 2min 16s (started: 2023-10-13 16:47:41 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs = pipe(\"sam_altman_lex_podcast_367.flac\",\n",
        "               chunk_length_s=30,\n",
        "               batch_size=16,\n",
        "               return_timestamps=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i7KswTBilVVd",
        "outputId": "6cc44812-2c77-4a12-f63c-2830d91f74e9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 6min 13s (started: 2023-10-13 16:51:08 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs[\"text\"][:200]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 100
        },
        "id": "adqid4eJ-e3y",
        "outputId": "5525e2ca-66e8-4c0e-8594-a9d23a39653e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "' We have been a misunderstood and badly mocked org for a long time. Like when we started, we like announced the org at the end of 2015 and said we were going to work on AGI, like people thought we wer'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 8
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 3.41 ms (started: 2023-10-13 16:58:55 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "6 minutes 13 seconds to transcribe it all!"
      ],
      "metadata": {
        "id": "EpWlzw67ogmL"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "## BetterTransformer"
      ],
      "metadata": {
        "id": "xwO3In02mE7z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "pipe = pipeline(\"automatic-speech-recognition\",\n",
        "                \"openai/whisper-large-v2\",\n",
        "                torch_dtype=torch.float16,\n",
        "                device=\"cuda:0\")\n",
        "\n",
        "pipe.model = pipe.model.to_bettertransformer()"
      ],
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        "outputId": "1cad418c-304c-4008-d8a3-b028830859b7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/1.99k [00:00<?, ?B/s]"
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading model.safetensors:   0%|          | 0.00/6.17G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
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          "data": {
            "text/plain": [
              "Downloading (…)neration_config.json:   0%|          | 0.00/4.26k [00:00<?, ?B/s]"
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              "version_major": 2,
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        {
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          "data": {
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              "Downloading (…)okenizer_config.json:   0%|          | 0.00/805 [00:00<?, ?B/s]"
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        {
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          "data": {
            "text/plain": [
              "Downloading (…)olve/main/vocab.json:   0%|          | 0.00/1.04M [00:00<?, ?B/s]"
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          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)/main/tokenizer.json:   0%|          | 0.00/2.48M [00:00<?, ?B/s]"
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          "data": {
            "text/plain": [
              "Downloading (…)in/added_tokens.json:   0%|          | 0.00/34.6k [00:00<?, ?B/s]"
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          "data": {
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              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/2.08k [00:00<?, ?B/s]"
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          "metadata": {}
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        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)rocessor_config.json:   0%|          | 0.00/185k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The BetterTransformer implementation does not support padding during training, as the fused kernels do not support attention masks. Beware that passing padded batched data during training may result in unexpected outputs. Please refer to https://huggingface.co/docs/optimum/bettertransformer/overview for more details.\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 2min 17s (started: 2023-10-13 17:03:16 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs = pipe(\"sam_altman_lex_podcast_367.flac\",\n",
        "               chunk_length_s=30,\n",
        "               batch_size=16,\n",
        "               return_timestamps=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qtggr0dVQS3o",
        "outputId": "dec45c63-cc77-4a12-97da-fed20d7f8ece"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 5min 42s (started: 2023-10-13 17:05:33 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs[\"text\"][:200]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 100
        },
        "id": "9CS8DHHY-zpV",
        "outputId": "47c0f87a-0a2a-4008-a5ed-8cb860926407"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "' We have been a misunderstood and badly mocked org for a long time. Like when we started, we like announced the org at the end of 2015 and said we were going to work on AGI, like people thought we wer'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 7
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 2.31 ms (started: 2023-10-13 17:11:17 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## BetterTransformer + Higher batch size"
      ],
      "metadata": {
        "id": "YMPhuebaEAQK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "outputs = pipe(\"sam_altman_lex_podcast_367.flac\",\n",
        "               chunk_length_s=30,\n",
        "               batch_size=24,\n",
        "               return_timestamps=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ysbukpIoANGD",
        "outputId": "2ce9755d-509e-4e43-b6fe-0a358de78021"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 5min 2s (started: 2023-10-13 17:11:22 +00:00)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "outputs[\"text\"][:200]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 100
        },
        "id": "KAW4k-P8AQDF",
        "outputId": "10f4cf4f-3713-46d5-947d-a523a77b44e6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "' We have been a misunderstood and badly mocked org for a long time. Like when we started, we like announced the org at the end of 2015 and said we were going to work on AGI, like people thought we wer'"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            }
          },
          "metadata": {},
          "execution_count": 9
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "time: 3.87 ms (started: 2023-10-13 17:17:24 +00:00)\n"
          ]
        }
      ]
    }
  ]
}