Style_Transfer_for_Flowtron.ipynb

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  "metadata": {
    "colab": {
      "name": "Style Transfer for Flowtron",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
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    "accelerator": "GPU"
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      "cell_type": "markdown",
      "metadata": {
        "id": "Ygul_8CfZWXz",
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      "source": [
        "# Style Transfer Inference Demo for Flowtron on Google COLAB¶ \n",
        "\n",
        "Original code is by:\n",
        "\n",
        "Rafael Valle, Kevin Shih, Ryan Prenger and Bryan Catanzaro | NVIDIA\n",
        "\n",
        "The Google Colaboratory style trasfer code was written by;\n",
        "\n",
        "Bence Halpern | PhD Student | University of Amsterdam, TU Delft, Netherlands Cancer Institute\n",
        "\n",
        "## Intro\n",
        "This notebook requires a GPU runtime to run. Please select the menu option \"**Runtime**\" -> \"**Change runtime type**\", select \"**Hardware Accelerator**\" -> \"**GPU**\" and click \"**SAVE**\"\n",
        "\n",
        "## Model Description\n",
        "\n",
        "The TTS used in this colab is Flowtron. The original paper is:\n",
        "\n",
        "- VALLE, Rafael, et al. Flowtron: an Autoregressive Flow-based Generative Network for Text-to-Speech Synthesis. arXiv preprint arXiv:2005.05957, 2020.\n",
        "\n",
        "The style transfer method used is the robust reference audio-based method to perform emotional style transfer. To my knowledge, this was first done in the Tacotron 2 GST by Kwon et al. We use this method with Flowtron to get emotional audio. More detail about the reference audio-based method:\n",
        "\n",
        "- KWON, Ohsung, et al. An Effective Style Token Weight Control Technique for End-to-End Emotional Speech Synthesis. IEEE Signal Processing Letters, 2019, 26.9: 1383-1387.\n",
        "\n",
        "## Dataset\n",
        "\n",
        "The happy and sad reference emotional signals are from the RAVDESS dataset. \n",
        "\n",
        "Please cite their work if you use the emotional data in your work:\n",
        "- Livingstone SR, Russo FA (2018) The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS): A dynamic, multimodal set of facial and vocal expressions in North American English. PLoS ONE 13(5): e0196391. https://doi.org/10.1371/journal.pone.0196391.\n",
        "\n",
        "\n"
      ]
    },
    {
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      "metadata": {
        "id": "BgHhAV5h_njx",
        "colab_type": "code",
        "outputId": "13ec1330-1205-4a00-8486-57811ddf6bb6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 129
        }
      },
      "source": [
        "from google.colab import drive\n",
        "\n",
        "drive.mount('/content/gdrive')"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Go to this URL in a browser: https://accounts.google.com/o/oauth2/auth?client_id=947318989803-6bn6qk8qdgf4n4g3pfee6491hc0brc4i.apps.googleusercontent.com&redirect_uri=urn%3aietf%3awg%3aoauth%3a2.0%3aoob&response_type=code&scope=email%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdocs.test%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive%20https%3a%2f%2fwww.googleapis.com%2fauth%2fdrive.photos.readonly%20https%3a%2f%2fwww.googleapis.com%2fauth%2fpeopleapi.readonly\n",
            "\n",
            "Enter your authorization code:\n",
            "··········\n",
            "Mounted at /content/gdrive\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "caV9rNth0t35",
        "colab_type": "text"
      },
      "source": [
        "## Data preparation\n",
        "\n",
        "For your custom style transfer, you need to provide your own audio files and file lists. The easiest way you can learn how to do this is by mimicking the examples below. Upload the audio files and your file lists to your Google Drive and set it to public access.\n",
        "\n",
        "Check that the printed downloaded size agrees with the original size. If not, you might have made a mistake in the download link or you forgot to make it public.\n",
        "\n",
        "Don't forget to downsample your audios. You can use the bash script for that in the happy.zip. The Flowtron uses 22050 Hz and 16-bit depth."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9kytmjZ1_kMK",
        "colab_type": "code",
        "outputId": "9f324898-e6a4-413d-b05c-125d6745017e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "import sys\n",
        "\n",
        "# This is to make sure that the venv corresponding to the correct\n",
        "# ipython kernel is used\n",
        "!{sys.executable} -m pip install numpy==1.13.3 tensorflow==1.15 inflect==0.2.5 librosa==0.6.0 scipy==1.0.0 tensorboardX==1.1 Unidecode==1.0.22 pillow \n",
        "\n",
        "# We need to check out a certain commit here to avoid changes\n",
        "!git clone https://github.com/karkirowle/flowtron.git\n",
        "%cd flowtron\n",
        "!git submodule init\n",
        "!git submodule update\n",
        "%cd tacotron2\n",
        "!git submodule update --init\n",
        "%cd ..\n",
        "\n",
        "\n",
        "!ls\n",
        "# This is ported from https://github.com/yhgon/mellotron/blob/master/inference_colab.ipynb\n",
        "# This downloads the style transfer data and the trained Flowtron with vocoder\n",
        "!wget -N  -q https://raw.githubusercontent.com/yhgon/colab_utils/master/gfile.py\n",
        "!python gfile.py -u 'https://drive.google.com/open?id=1KhJcPawFgmfvwV7tQAOeC253rYstLrs8' -f 'flowtron_libritts.pt'\n",
        "!python gfile.py -u 'https://drive.google.com/open?id=1Cjd6dK_eFz6DE0PKXKgKxrzTUqzzUDW-' -f 'flowtron_ljs.pt'\n",
        "\n",
        "!python gfile.py -u 'https://drive.google.com/open?id=1Rm5rV5XaWWiUbIpg5385l5sh68z2bVOE' -f 'waveglow_256channels_v4.pt'\n",
        "\n",
        "\n",
        "\n",
        "!python gfile.py -u 'https://drive.google.com/open?id=1c1gPs4sGbFMoqvM_OgvDD4k4cGkfPWUQ' -f 'happy.zip'\n",
        "!python gfile.py -u 'https://drive.google.com/open?id=1LMIXuqz12PnJNBN5L2-95-jpLwoQX4_F' -f 'sad.zip'\n",
        "\n",
        "!python gfile.py -u 'https://drive.google.com/open?id=1ncaU1lYqcDIhRwJmWtxODZDHykSYsJKt' -f 'happy_reference_audios.txt'\n",
        "!python gfile.py -u 'https://drive.google.com/open?id=1JiSkb2jW8dfGELknmPhJ1-BOxlAJ6niQ' -f 'sad_reference_audios.txt'\n",
        "\n",
        "!unzip happy.zip -d data\n",
        "!unzip sad.zip -d data\n",
        "\n",
        "!mv happy_reference_audios.txt filelists/happy_reference_audios.txt\n",
        "!mv sad_reference_audios.txt filelists/sad_reference_audios.txt\n",
        "\n",
        "\n",
        "\n"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
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            "/content/flowtron\n",
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            "Submodule path 'apex': checked out '9165b27fdf240f9bc08eac98b849a9d7c6308917'\n",
            "Submodule path 'tacotron2': checked out '6f435f7f29c3e1553cf2dd7ca2daf56903b20c39'\n",
            "/content/flowtron/tacotron2\n",
            "Submodule 'waveglow' (https://github.com/NVIDIA/waveglow) registered for path 'waveglow'\n",
            "Cloning into '/content/flowtron/tacotron2/waveglow'...\n",
            "Submodule path 'waveglow': checked out '2fd4e63e2918012f55eac2c8a8e75622a39741be'\n",
            "/content/flowtron\n",
            "apex\t\t     distributed.py\t\t inference.py\t   text\n",
            "audio_processing.py  filelists\t\t\t LICENSE\t   train.py\n",
            "config.json\t     flowtron_logger.py\t\t README.md\n",
            "data\t\t     flowtron_plotting_utils.py  requirements.txt\n",
            "data.py\t\t     flowtron.py\t\t tacotron2\n",
            "It took  7.18sec to download 232.7 MB flowtron_libritts.pt \n",
            "It took  6.67sec to download 232.6 MB flowtron_ljs.pt \n",
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          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "verT7i9fAhWt",
        "colab_type": "code",
        "outputId": "c8235332-bc7b-4d41-8d19-c5d47381720b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        }
      },
      "source": [
        "#from unidecode import unidecode\n",
        "\n",
        "import sys\n",
        "print(sys.executable)\n",
        "import os\n",
        "print(os.listdir())\n",
        "import matplotlib\n",
        "matplotlib.use(\"Agg\")\n",
        "import matplotlib.pylab as plt\n",
        "\n",
        "import os\n",
        "import argparse\n",
        "import json\n",
        "import sys\n",
        "import numpy as np\n",
        "import torch\n",
        "\n",
        "# Matplotlib might need to be downgraded?\n",
        "\n",
        "import unidecode\n",
        "\n",
        "from flowtron import Flowtron\n",
        "from torch.utils.data import DataLoader\n",
        "from data import Data, load_wav_to_torch\n",
        "from train import update_params\n",
        "\n",
        "sys.path.insert(0, \"tacotron2\")\n",
        "sys.path.insert(0, \"tacotron2/waveglow\")\n",
        "from glow import WaveGlow\n",
        "from scipy.io.wavfile import write\n",
        "from torch.nn import ReplicationPad1d, ReflectionPad1d\n",
        "from glob import glob\n",
        "from torch.distributions import Normal\n",
        "\n",
        "import IPython\n",
        "from data import DataCollate\n"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/bin/python3\n",
            "['README.md', 'data', 'text', 'requirements.txt', 'sad.zip', 'flowtron.py', 'waveglow_256channels_v4.pt', 'gfile.py', '.git', 'flowtron_libritts.pt', 'train.py', 'LICENSE', 'flowtron_ljs.pt', 'apex', 'filelists', 'distributed.py', 'audio_processing.py', 'inference.py', 'flowtron_logger.py', 'data.py', 'config.json', 'flowtron_plotting_utils.py', '.gitmodules', 'happy.zip', 'tacotron2']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LREx8RyTBS0b",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "def infer(flowtron_path, waveglow_path, text, speaker_id, n_frames, sigma,\n",
        "          seed,emotion,utterance=None):\n",
        "    torch.manual_seed(seed)\n",
        "    torch.cuda.manual_seed(seed)\n",
        "\n",
        "    # load waveglow\n",
        "    waveglow = torch.load(waveglow_path)['model'].cuda().eval()\n",
        "    waveglow.cuda().half()\n",
        "    for k in waveglow.convinv:\n",
        "        k.float()\n",
        "    waveglow.eval()\n",
        "\n",
        "    # load flowtron\n",
        "    model = Flowtron(**model_config).cuda()\n",
        "    state_dict = torch.load(flowtron_path, map_location='cpu')['state_dict']\n",
        "    model.load_state_dict(state_dict)\n",
        "    model.eval()\n",
        "    print(\"Loaded checkpoint '{}')\" .format(flowtron_path))\n",
        "\n",
        "    ignore_keys = ['training_files', 'validation_files']\n",
        "    trainset = Data(\n",
        "        data_config['training_files'],\n",
        "        **dict((k, v) for k, v in data_config.items() if k not in ignore_keys))\n",
        "    speaker_vecs = trainset.get_speaker_id(speaker_id).cuda()\n",
        "\n",
        "    styleset = Data(\"filelists/\" + str(emotion) +\"_reference_audios.txt\",\n",
        "                    **dict((k, v) for k, v in data_config.items() if k not in ignore_keys))\n",
        "\n",
        "    print(len(styleset))\n",
        " # Feeding the dataset in one batch: modify if you have larger datast\n",
        "    batch_size = len(styleset)\n",
        "\n",
        "    # Sampler is assumed none for COLAB, because n_gpu=1\n",
        "    style_loader = DataLoader(styleset, num_workers=1, shuffle=False,\n",
        "                              sampler=None, batch_size=batch_size,\n",
        "                              pin_memory=False, collate_fn=DataCollate())\n",
        "\n",
        "    speaker_vecs = trainset.get_speaker_id(speaker_id).cuda()\n",
        "\n",
        "    text = trainset.get_text(text).cuda()\n",
        "    synth_speaker_vecs = speaker_vecs[None]\n",
        "    text = text[None]\n",
        "\n",
        "\n",
        "    with torch.no_grad():\n",
        "\n",
        "\n",
        "        for batch in style_loader:\n",
        "            mel, speaker_vecs, utt_text, in_lens, out_lens, gate_target = batch\n",
        "\n",
        "            mel, speaker_vecs, utt_text = mel.cuda(), speaker_vecs.cuda(), utt_text.cuda()\n",
        "            in_lens, out_lens, gate_target = in_lens.cuda(), out_lens.cuda(), gate_target.cuda()\n",
        "\n",
        "            residual, _, _, _, _, _, _ = model.forward(mel, speaker_vecs, utt_text, in_lens, out_lens)\n",
        "            residual = residual.permute(1, 2, 0)\n",
        "\n",
        "        # At this stage the latent vectors are zero-padded which is not appropriate, because it violates the assumption\n",
        "        # of Gaussian latent space, leading to artefacts.\n",
        "\n",
        "\n",
        "\n",
        "        residual_accumulator = torch.zeros((residual.shape[0], 80, n_frames)).to(\"cuda\")\n",
        "\n",
        "        for i in range(residual.shape[0]):\n",
        "            current_len = out_lens[i].cpu().numpy()\n",
        "\n",
        "            if current_len < n_frames:\n",
        "                num_tile = int(np.ceil(n_frames/current_len))\n",
        "                residual_accumulator[i,:,:] = torch.repeat_interleave(residual[i,:,:current_len],repeats=num_tile,dim=1)[:,:n_frames]\n",
        "\n",
        "        residual_accumulator = torch.mean(residual_accumulator,dim=0)[None,:,:]\n",
        "       \n",
        "        average_over_time = False\n",
        "        if not average_over_time:\n",
        "            dist = Normal(residual_accumulator, sigma)\n",
        "            z_style = dist.sample()\n",
        "        else:\n",
        "            print(residual_accumulator.shape)\n",
        "            residual_accumulator = residual_accumulator.mean(dim=2)\n",
        "            dist = Normal(residual_accumulator,sigma)\n",
        "            z_style = dist.sample((n_frames,)).permute(1,2,0)\n",
        "\n",
        "        mels, attentions = model.infer(z_style, synth_speaker_vecs, text)\n",
        "\n",
        "    for k in range(len(attentions)):\n",
        "        attention = torch.cat(attentions[k]).cpu().numpy()\n",
        "        fig, axes = plt.subplots(1, 2, figsize=(16, 4))\n",
        "        axes[0].imshow(mels[0].cpu().numpy(), origin='bottom', aspect='auto')\n",
        "        axes[1].imshow(attention[:, 0].transpose(), origin='bottom', aspect='auto')\n",
        "        fig.savefig('sid{}_sigma{}_attnlayer{}.png'.format(speaker_id, sigma, k))\n",
        "        plt.close(\"all\")\n",
        "\n",
        "    audio = waveglow.infer(mels.half(), sigma=0.8).float()\n",
        "    audio = audio.cpu().numpy()[0]\n",
        "    # normalize audio for now\n",
        "    audio = audio / np.abs(audio).max()\n",
        "    return audio"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lOYvZooE_b68",
        "colab_type": "code",
        "outputId": "6b9b522e-f602-4e78-a694-2f454353c75e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 512
        }
      },
      "source": [
        "# Parse configs. Globals are never nice, but we use it anyway\n",
        "with open(\"config.json\") as f:\n",
        "  data = f.read()\n",
        "\n",
        "global config\n",
        "config = json.loads(data)\n",
        "#update_params(config, args.params)\n",
        "\n",
        "data_config = config[\"data_config\"]\n",
        "global model_config\n",
        "model_config = config[\"model_config\"]\n",
        "\n",
        "torch.backends.cudnn.enabled = True\n",
        "torch.backends.cudnn.benchmark = False\n",
        "\n",
        "# Emotion parameter, happy and sad is implemented\n",
        "emotion=\"happy\"\n",
        "#emotion=\"sad\"\n",
        "\n",
        "# DEFAULT SETUP: LJS\n",
        "speaker_id=0\n",
        "\n",
        "# LIBRITTS SETUP - UNCOMMENT\n",
        "#data_config[\"training_files\"] = \"filelists/libritts_train_clean_100_audiopath_text_sid_shorterthan10s_atleast5min_train_filelist.txt\"\n",
        "#model_config[\"n_speakers\"] = 123\n",
        "#speaker_id=40 \n",
        "\n",
        "\n",
        "# There are some utterances that don't work, this one is tested, feel free to\n",
        "# experiment, but don't ask why it doesn't work! \n",
        "\n",
        "# I don't know what is going\n",
        "audio = infer('flowtron_ljs.pt','waveglow_256channels_v4.pt',\"I don't know what is going on.\", speaker_id=speaker_id,n_frames=400, sigma=0.01, seed=1,emotion=emotion)\n",
        "\n",
        "%matplotlib inline\n",
        "plt.plot(audio[:])\n",
        "\n",
        "IPython.display.Audio(audio[:],rate=22050)"
      ],
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/torch/serialization.py:657: SourceChangeWarning: source code of class 'torch.nn.modules.conv.ConvTranspose1d' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n",
            "  warnings.warn(msg, SourceChangeWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/torch/serialization.py:657: SourceChangeWarning: source code of class 'torch.nn.modules.container.ModuleList' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n",
            "  warnings.warn(msg, SourceChangeWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/torch/serialization.py:657: SourceChangeWarning: source code of class 'torch.nn.modules.conv.Conv1d' has changed. you can retrieve the original source code by accessing the object's source attribute or set `torch.nn.Module.dump_patches = True` and use the patch tool to revert the changes.\n",
            "  warnings.warn(msg, SourceChangeWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Loaded checkpoint 'flowtron_ljs.pt')\n",
            "Number of speakers : 1\n",
            "Number of speakers : 1\n",
            "24\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "                <audio controls=\"controls\" >\n",
              "                    <source 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\" type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ],
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    }
  ]
}