vocalsourceseparation-convtasnetwtransformer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "7e4aaaa2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:01.813920Z",
     "iopub.status.busy": "2023-05-02T14:36:01.813351Z",
     "iopub.status.idle": "2023-05-02T14:36:12.316431Z",
     "shell.execute_reply": "2023-05-02T14:36:12.315142Z"
    },
    "papermill": {
     "duration": 10.512635,
     "end_time": "2023-05-02T14:36:12.319249",
     "exception": false,
     "start_time": "2023-05-02T14:36:01.806614",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting musdb\r\n",
      "  Downloading musdb-0.4.0-py2.py3-none-any.whl (29 kB)\r\n",
      "Collecting stempeg>=0.2.3\r\n",
      "  Downloading stempeg-0.2.3-py3-none-any.whl (963 kB)\r\n",
      "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m963.5/963.5 kB\u001b[0m \u001b[31m23.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\r\n",
      "\u001b[?25hRequirement already satisfied: pyaml in /opt/conda/lib/python3.7/site-packages (from musdb) (21.10.1)\r\n",
      "Requirement already satisfied: tqdm in /opt/conda/lib/python3.7/site-packages (from musdb) (4.64.1)\r\n",
      "Requirement already satisfied: numpy>=1.7 in /opt/conda/lib/python3.7/site-packages (from musdb) (1.21.6)\r\n",
      "Collecting ffmpeg-python>=0.2.0\r\n",
      "  Downloading ffmpeg_python-0.2.0-py3-none-any.whl (25 kB)\r\n",
      "Requirement already satisfied: PyYAML in /opt/conda/lib/python3.7/site-packages (from pyaml->musdb) (6.0)\r\n",
      "Requirement already satisfied: future in /opt/conda/lib/python3.7/site-packages (from ffmpeg-python>=0.2.0->stempeg>=0.2.3->musdb) (0.18.3)\r\n",
      "Installing collected packages: ffmpeg-python, stempeg, musdb\r\n",
      "Successfully installed ffmpeg-python-0.2.0 musdb-0.4.0 stempeg-0.2.3\r\n",
      "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\r\n",
      "\u001b[0m"
     ]
    }
   ],
   "source": [
    "!pip install musdb\n",
    "# !pip install librosa\n",
    "# !pip install museval"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "81efd5c0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:12.329839Z",
     "iopub.status.busy": "2023-05-02T14:36:12.329485Z",
     "iopub.status.idle": "2023-05-02T14:36:14.859386Z",
     "shell.execute_reply": "2023-05-02T14:36:14.858146Z"
    },
    "papermill": {
     "duration": 2.538417,
     "end_time": "2023-05-02T14:36:14.862262",
     "exception": false,
     "start_time": "2023-05-02T14:36:12.323845",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import os\n",
    "import random\n",
    "import numpy as np\n",
    "import torch\n",
    "import torch.nn as nn\n",
    "from torch.utils.data import Dataset, DataLoader\n",
    "import musdb\n",
    "import math\n",
    "import librosa\n",
    "from tqdm.auto import tqdm\n",
    "import torchaudio\n",
    "from torchaudio.pipelines import CONVTASNET_BASE_LIBRI2MIX"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "418d66e7",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:14.872845Z",
     "iopub.status.busy": "2023-05-02T14:36:14.872143Z",
     "iopub.status.idle": "2023-05-02T14:36:14.884976Z",
     "shell.execute_reply": "2023-05-02T14:36:14.883946Z"
    },
    "papermill": {
     "duration": 0.020658,
     "end_time": "2023-05-02T14:36:14.887197",
     "exception": false,
     "start_time": "2023-05-02T14:36:14.866539",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class MUSDB18Dataset(Dataset):\n",
    "    def __init__(self, musdb18_root, subset=\"train\", split = \"train\", sr=44100, duration=2, seed = 42):\n",
    "        self.sr = sr\n",
    "        self.duration = duration\n",
    "        self.seed = seed\n",
    "#         self.transformer = torchaudio.transforms.Spectrogram(n_fft = 600)\n",
    "        if(subset == 'test'):\n",
    "            self.musdb18 = musdb.DB(root = musdb18_root, subsets=subset)\n",
    "            print(f\"Number of Testing Samples: {len(self.musdb18)}\")\n",
    "        else:\n",
    "            self.musdb18 = musdb.DB(root = musdb18_root, subsets = subset, split = split)\n",
    "            if split == \"train\":\n",
    "                print(f\"Number of Training Samples: {len(self.musdb18)}\")\n",
    "            else:\n",
    "                print(f\"Number of Validation Samples: {len(self.musdb18)}\")\n",
    "        \n",
    "    def __getitem__(self, index):\n",
    "        random.seed(self.seed)\n",
    "        track = self.musdb18.tracks[index]\n",
    "        track.chunk_duration = self.duration\n",
    "        track.chunk_start = random.uniform(0, track.duration - track.chunk_duration)\n",
    "        \n",
    "        # Load the mixture waveform\n",
    "        audio = track.audio.T\n",
    "        audio = audio.mean(axis = 0, keepdims = True)\n",
    "        audio_tensor = torch.from_numpy(audio).float()\n",
    "#         audio_tensor = self.transformer(audio_tensor)\n",
    "        \n",
    "        # Load the target waveform (vocals)\n",
    "        vocals = track.targets[\"vocals\"].audio.T\n",
    "        vocals = vocals.mean(axis = 0, keepdims = True)\n",
    "        \n",
    "        \n",
    "        others = track.targets[\"accompaniment\"].audio.T\n",
    "        others = others.mean(axis = 0, keepdims = True)\n",
    "        \n",
    "        vocals_tensor = torch.from_numpy(np.concatenate((vocals, others), axis = 0)).float()\n",
    "        \n",
    "#       vocals_tensor = self.transformer(vocals_tensor)\n",
    "\n",
    "        return audio_tensor, vocals_tensor\n",
    "\n",
    "    def __len__(self):\n",
    "        return len(self.musdb18.tracks)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "5b79e9ae",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:14.896601Z",
     "iopub.status.busy": "2023-05-02T14:36:14.896313Z",
     "iopub.status.idle": "2023-05-02T14:36:14.902322Z",
     "shell.execute_reply": "2023-05-02T14:36:14.901303Z"
    },
    "papermill": {
     "duration": 0.013154,
     "end_time": "2023-05-02T14:36:14.904458",
     "exception": false,
     "start_time": "2023-05-02T14:36:14.891304",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def get_musdb18_dataloaders(root, batch_size=8, num_workers=0, seed = 42):\n",
    "    train_set = MUSDB18Dataset(root, subset=\"train\")\n",
    "    val_set = MUSDB18Dataset(root, subset=\"train\", split = 'valid')\n",
    "    test_set = MUSDB18Dataset(root, subset=\"test\")\n",
    "\n",
    "    train_loader = DataLoader(train_set, batch_size=batch_size, shuffle=True, num_workers=num_workers)\n",
    "    val_loader = DataLoader(val_set, batch_size=batch_size, shuffle=False, num_workers=num_workers)\n",
    "    test_loader = DataLoader(test_set, batch_size=batch_size, shuffle=False, num_workers=num_workers)\n",
    "\n",
    "    return train_loader, val_loader, test_loader"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "3247bb44",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:14.913848Z",
     "iopub.status.busy": "2023-05-02T14:36:14.913576Z",
     "iopub.status.idle": "2023-05-02T14:36:14.923537Z",
     "shell.execute_reply": "2023-05-02T14:36:14.922415Z"
    },
    "papermill": {
     "duration": 0.017613,
     "end_time": "2023-05-02T14:36:14.926088",
     "exception": false,
     "start_time": "2023-05-02T14:36:14.908475",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "class ConvTasNetWithTransformer(nn.Module):\n",
    "    def __init__(self, num_sources = 2, hidden_size=128, num_heads=1, num_layers=1):\n",
    "        super(ConvTasNetWithTransformer, self).__init__()\n",
    "        \n",
    "        self.num_sources = num_sources\n",
    "        \n",
    "        conv_tasnet = CONVTASNET_BASE_LIBRI2MIX.get_model()\n",
    "        self.conv_tasnet_encoder = conv_tasnet.encoder\n",
    "        self.conv_tasnet_maskGenerator = conv_tasnet.mask_generator\n",
    "        self.conv_tasnet_decoder = conv_tasnet.decoder\n",
    "        \n",
    "        self.input_embed = nn.Linear(512, hidden_size)\n",
    "        self.transformer = nn.TransformerEncoderLayer(hidden_size, num_heads, hidden_size, dropout=0.1)\n",
    "        self.encoder = nn.TransformerEncoder(self.transformer, num_layers=num_layers)\n",
    "        \n",
    "        self.output_embed = nn.Linear(hidden_size, 512)\n",
    "        \n",
    "        for param in self.conv_tasnet_encoder.parameters():\n",
    "            param.requires_grad = False\n",
    "            \n",
    "        for param in self.conv_tasnet_maskGenerator.parameters():\n",
    "            param.requires_grad = False\n",
    "        \n",
    "    def forward(self, mixture):\n",
    "        # shape of mixture: [batch_size, num_channels, num_samples]\n",
    "        \n",
    "#         print(mixture.shape)\n",
    "        \n",
    "        # apply ConvTasNet for feature extraction and encoding\n",
    "        encoded = self.conv_tasnet_encoder(mixture)\n",
    "#         print(encoded.shape)\n",
    "        \n",
    "        encoded = self.conv_tasnet_maskGenerator(encoded)\n",
    "#         print(encoded.shape)\n",
    "        \n",
    "        # permute dimensions for transformer input\n",
    "        encoded = encoded.permute(3, 0, 1, 2)\n",
    "        encoded = encoded.reshape(encoded.size(0), -1, encoded.size(-1))\n",
    "#         print(encoded.shape)\n",
    "        \n",
    "        encoded = self.input_embed(encoded)\n",
    "        \n",
    "        # apply transformer\n",
    "        encoded = self.encoder(encoded)\n",
    "        \n",
    "        decoded = self.output_embed(encoded)\n",
    "#         print(decoded.shape)\n",
    "        \n",
    "        decoded = decoded.permute(1, 2, 0)\n",
    "        decoded = self.conv_tasnet_decoder(decoded)\n",
    "        \n",
    "        separated = decoded.view(-1, self.num_sources, decoded.size(-1)) \n",
    "        \n",
    "#         print(separated.shape)\n",
    "        \n",
    "        # shape of separated: [batch_size, num_sources, num_samples]\n",
    "        return separated"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7f6323ce",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:14.935971Z",
     "iopub.status.busy": "2023-05-02T14:36:14.935243Z",
     "iopub.status.idle": "2023-05-02T14:36:14.942169Z",
     "shell.execute_reply": "2023-05-02T14:36:14.941295Z"
    },
    "papermill": {
     "duration": 0.014223,
     "end_time": "2023-05-02T14:36:14.944256",
     "exception": false,
     "start_time": "2023-05-02T14:36:14.930033",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def train(model, dataloader, optimizer, loss_fn):\n",
    "    model.train()\n",
    "    total_loss = 0\n",
    "\n",
    "    for i, (audio, vocals) in enumerate(dataloader):\n",
    "        # move data to GPU if available\n",
    "        if torch.cuda.is_available():\n",
    "            audio = audio.cuda()\n",
    "            vocals = vocals.cuda()\n",
    "\n",
    "        # forward pass\n",
    "        prediction = model(audio)\n",
    "        loss = loss_fn(prediction, vocals)\n",
    "\n",
    "        # backward pass and optimization\n",
    "        optimizer.zero_grad()\n",
    "        loss.backward()\n",
    "        optimizer.step()\n",
    "\n",
    "        # update total loss\n",
    "        total_loss += loss.item()\n",
    "\n",
    "    # compute average loss\n",
    "    avg_loss = total_loss / len(dataloader)\n",
    "\n",
    "    return avg_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "976fb6b6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:14.954567Z",
     "iopub.status.busy": "2023-05-02T14:36:14.953630Z",
     "iopub.status.idle": "2023-05-02T14:36:14.960502Z",
     "shell.execute_reply": "2023-05-02T14:36:14.959546Z"
    },
    "papermill": {
     "duration": 0.014283,
     "end_time": "2023-05-02T14:36:14.962672",
     "exception": false,
     "start_time": "2023-05-02T14:36:14.948389",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def validate(model, dataloader, loss_fn):\n",
    "    model.eval()\n",
    "    total_loss = 0\n",
    "\n",
    "    with torch.no_grad():\n",
    "        for i, (audio, vocals) in enumerate(dataloader):\n",
    "            # move data to GPU if available\n",
    "            if torch.cuda.is_available():\n",
    "                audio = audio.cuda()\n",
    "                vocals = vocals.cuda()\n",
    "\n",
    "            # forward pass\n",
    "            prediction = model(audio)\n",
    "            loss = loss_fn(prediction, vocals)\n",
    "\n",
    "            # update total loss\n",
    "            total_loss += loss.item()\n",
    "\n",
    "    # compute average loss\n",
    "    avg_loss = total_loss / len(dataloader)\n",
    "\n",
    "    return avg_loss"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "27b72c5a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:14.972040Z",
     "iopub.status.busy": "2023-05-02T14:36:14.971715Z",
     "iopub.status.idle": "2023-05-02T14:36:14.977369Z",
     "shell.execute_reply": "2023-05-02T14:36:14.976359Z"
    },
    "papermill": {
     "duration": 0.012655,
     "end_time": "2023-05-02T14:36:14.979421",
     "exception": false,
     "start_time": "2023-05-02T14:36:14.966766",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def fit(model, optimizer, loss_fn, num_epochs, train_dataloader, val_dataloader):\n",
    "    for epoch in tqdm(range(num_epochs)):\n",
    "        # train model for one epoch\n",
    "        train_loss = train(model, train_dataloader, optimizer, loss_fn)\n",
    "        print(f'Epoch {epoch + 1} - Train loss: {train_loss:.4f}')\n",
    "\n",
    "        # evaluate model on validation data\n",
    "        val_loss = validate(model, val_dataloader, loss_fn)\n",
    "        print(f'Epoch {epoch + 1} - Val loss: {val_loss:.4f}')\n",
    "        print(\"---------------------------------------------\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "ecbd71c1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:14.989170Z",
     "iopub.status.busy": "2023-05-02T14:36:14.988368Z",
     "iopub.status.idle": "2023-05-02T14:36:14.996056Z",
     "shell.execute_reply": "2023-05-02T14:36:14.995174Z"
    },
    "papermill": {
     "duration": 0.01466,
     "end_time": "2023-05-02T14:36:14.998083",
     "exception": false,
     "start_time": "2023-05-02T14:36:14.983423",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def calculate_sdr(predicted_output, ground_truth):\n",
    "    \"\"\"\n",
    "    Calculates the Signal-to-Distortion Ratio (SDR) metric between a predicted output and its corresponding ground truth.\n",
    "\n",
    "    Args:\n",
    "    predicted_output: A numpy array of shape (number of channels, number of frames, number of bins).\n",
    "    ground_truth: A numpy array of shape (number of channels, number of frames, number of bins).\n",
    "\n",
    "    Returns:\n",
    "    sdr: A scalar representing the SDR value between predicted_output and ground_truth.\n",
    "    \"\"\"\n",
    "    eps = np.finfo(np.float32).eps  # To avoid division by zero errors\n",
    "    num_channels = predicted_output.shape[0]\n",
    "    sdr_sum = 0\n",
    "    \n",
    "#     print(predicted_output.shape, ground_truth.shape)\n",
    "    \n",
    "    for c in range(num_channels):\n",
    "        # Compute the power of the true source signal\n",
    "        true_source_power = np.sum(ground_truth[c]**2)\n",
    "\n",
    "        # Compute the scalar product between true source signal and predicted signal\n",
    "        true_pred_scalar = np.sum(ground_truth[c] * predicted_output[c])\n",
    "\n",
    "        # Compute the SDR for this channel\n",
    "        sdr = 10 * np.log10(true_source_power / (np.sum(ground_truth[c]**2) - true_pred_scalar + eps) + eps)\n",
    "        if(not math.isnan(sdr)):\n",
    "            sdr_sum += sdr\n",
    "\n",
    "    # Compute the average SDR across all channels\n",
    "    sdr = sdr_sum / num_channels\n",
    "\n",
    "    return -sdr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "66769368",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:15.007733Z",
     "iopub.status.busy": "2023-05-02T14:36:15.006868Z",
     "iopub.status.idle": "2023-05-02T14:36:15.014575Z",
     "shell.execute_reply": "2023-05-02T14:36:15.013724Z"
    },
    "papermill": {
     "duration": 0.01458,
     "end_time": "2023-05-02T14:36:15.016615",
     "exception": false,
     "start_time": "2023-05-02T14:36:15.002035",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "def test(model, dataloader):\n",
    "    model.eval()\n",
    "    all_targets = []\n",
    "    all_predictions = []\n",
    "    sdr = 0\n",
    "    count = 0\n",
    "    with torch.no_grad():\n",
    "        for i, (audio, vocals) in tqdm(enumerate(dataloader)):\n",
    "            # move data to GPU if available\n",
    "            if torch.cuda.is_available():\n",
    "                audio = audio.cuda()\n",
    "                vocals = vocals.cuda()\n",
    "\n",
    "            # forward pass\n",
    "            prediction = model(audio)\n",
    "            \n",
    "            # convert predictions and ground truth to numpy arrays\n",
    "            prediction = prediction.cpu().numpy()\n",
    "            vocals = vocals.cpu().numpy()\n",
    "            \n",
    "            for i in range(prediction.shape[0]):\n",
    "                pred = prediction[i,:,:]\n",
    "                targ = vocals[i,:,:]\n",
    "                sdr += calculate_sdr(pred, targ)\n",
    "                count += 1\n",
    "    mean_sdr = sdr/count\n",
    "    return mean_sdr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f77fcac3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:15.026106Z",
     "iopub.status.busy": "2023-05-02T14:36:15.025317Z",
     "iopub.status.idle": "2023-05-02T14:36:30.780029Z",
     "shell.execute_reply": "2023-05-02T14:36:30.778378Z"
    },
    "papermill": {
     "duration": 15.761982,
     "end_time": "2023-05-02T14:36:30.782520",
     "exception": false,
     "start_time": "2023-05-02T14:36:15.020538",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of Training Samples: 87\n",
      "Number of Validation Samples: 13\n",
      "Number of Testing Samples: 50\n"
     ]
    }
   ],
   "source": [
    "root = \"/kaggle/input/musdb18/musdb18\"\n",
    "train_loader, val_loader, test_loader = get_musdb18_dataloaders(root, batch_size = 2)\n",
    "# for x, y in val_loader:\n",
    "#     print(x.shape, y.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "c0ff5048",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-02T14:36:30.793816Z",
     "iopub.status.busy": "2023-05-02T14:36:30.792812Z",
     "iopub.status.idle": "2023-05-03T00:12:58.321307Z",
     "shell.execute_reply": "2023-05-03T00:12:58.320026Z"
    },
    "papermill": {
     "duration": 34587.557791,
     "end_time": "2023-05-03T00:12:58.344850",
     "exception": false,
     "start_time": "2023-05-02T14:36:30.787059",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "ee9e8172d6bd4c9c97a090152d6154c9",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0.00/19.1M [00:00<?, ?B/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2c6b9e23768648cdbdaddd78e52fb4d1",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/150 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1 - Train loss: 111.2471\n",
      "Epoch 1 - Val loss: 32.6345\n",
      "---------------------------------------------\n",
      "Epoch 2 - Train loss: 30.2429\n",
      "Epoch 2 - Val loss: 14.3192\n",
      "---------------------------------------------\n",
      "Epoch 3 - Train loss: 19.4998\n",
      "Epoch 3 - Val loss: 9.4439\n",
      "---------------------------------------------\n",
      "Epoch 4 - Train loss: 14.6934\n",
      "Epoch 4 - Val loss: 6.9453\n",
      "---------------------------------------------\n",
      "Epoch 5 - Train loss: 11.8330\n",
      "Epoch 5 - Val loss: 5.7341\n",
      "---------------------------------------------\n",
      "Epoch 6 - Train loss: 9.8390\n",
      "Epoch 6 - Val loss: 4.7713\n",
      "---------------------------------------------\n",
      "Epoch 7 - Train loss: 8.4771\n",
      "Epoch 7 - Val loss: 4.0259\n",
      "---------------------------------------------\n",
      "Epoch 8 - Train loss: 7.1362\n",
      "Epoch 8 - Val loss: 3.3932\n",
      "---------------------------------------------\n",
      "Epoch 9 - Train loss: 6.1843\n",
      "Epoch 9 - Val loss: 3.2421\n",
      "---------------------------------------------\n",
      "Epoch 10 - Train loss: 5.5622\n",
      "Epoch 10 - Val loss: 2.6208\n",
      "---------------------------------------------\n",
      "Epoch 11 - Train loss: 4.8751\n",
      "Epoch 11 - Val loss: 2.2771\n",
      "---------------------------------------------\n",
      "Epoch 12 - Train loss: 4.3220\n",
      "Epoch 12 - Val loss: 2.0424\n",
      "---------------------------------------------\n",
      "Epoch 13 - Train loss: 3.8862\n",
      "Epoch 13 - Val loss: 1.8344\n",
      "---------------------------------------------\n",
      "Epoch 14 - Train loss: 3.5285\n",
      "Epoch 14 - Val loss: 1.6536\n",
      "---------------------------------------------\n",
      "Epoch 15 - Train loss: 3.1870\n",
      "Epoch 15 - Val loss: 1.4907\n",
      "---------------------------------------------\n",
      "Epoch 16 - Train loss: 2.9275\n",
      "Epoch 16 - Val loss: 1.4045\n",
      "---------------------------------------------\n",
      "Epoch 17 - Train loss: 2.6878\n",
      "Epoch 17 - Val loss: 1.2773\n",
      "---------------------------------------------\n",
      "Epoch 18 - Train loss: 2.4770\n",
      "Epoch 18 - Val loss: 1.1963\n",
      "---------------------------------------------\n",
      "Epoch 19 - Train loss: 2.3101\n",
      "Epoch 19 - Val loss: 1.0963\n",
      "---------------------------------------------\n",
      "Epoch 20 - Train loss: 2.1354\n",
      "Epoch 20 - Val loss: 1.0325\n",
      "---------------------------------------------\n",
      "Epoch 21 - Train loss: 1.9546\n",
      "Epoch 21 - Val loss: 0.9462\n",
      "---------------------------------------------\n",
      "Epoch 22 - Train loss: 1.8385\n",
      "Epoch 22 - Val loss: 0.9107\n",
      "---------------------------------------------\n",
      "Epoch 23 - Train loss: 1.7306\n",
      "Epoch 23 - Val loss: 0.8584\n",
      "---------------------------------------------\n",
      "Epoch 24 - Train loss: 1.6003\n",
      "Epoch 24 - Val loss: 0.7828\n",
      "---------------------------------------------\n",
      "Epoch 25 - Train loss: 1.5124\n",
      "Epoch 25 - Val loss: 0.7604\n",
      "---------------------------------------------\n",
      "Epoch 26 - Train loss: 1.4614\n",
      "Epoch 26 - Val loss: 0.6808\n",
      "---------------------------------------------\n",
      "Epoch 27 - Train loss: 1.3258\n",
      "Epoch 27 - Val loss: 0.6421\n",
      "---------------------------------------------\n",
      "Epoch 28 - Train loss: 1.2577\n",
      "Epoch 28 - Val loss: 0.6419\n",
      "---------------------------------------------\n",
      "Epoch 29 - Train loss: 1.1886\n",
      "Epoch 29 - Val loss: 0.5865\n",
      "---------------------------------------------\n",
      "Epoch 30 - Train loss: 1.1193\n",
      "Epoch 30 - Val loss: 0.5368\n",
      "---------------------------------------------\n",
      "Epoch 31 - Train loss: 1.0575\n",
      "Epoch 31 - Val loss: 0.5157\n",
      "---------------------------------------------\n",
      "Epoch 32 - Train loss: 1.0082\n",
      "Epoch 32 - Val loss: 0.4841\n",
      "---------------------------------------------\n",
      "Epoch 33 - Train loss: 0.9698\n",
      "Epoch 33 - Val loss: 0.4615\n",
      "---------------------------------------------\n",
      "Epoch 34 - Train loss: 0.9234\n",
      "Epoch 34 - Val loss: 0.4456\n",
      "---------------------------------------------\n",
      "Epoch 35 - Train loss: 0.8750\n",
      "Epoch 35 - Val loss: 0.4271\n",
      "---------------------------------------------\n",
      "Epoch 36 - Train loss: 0.8343\n",
      "Epoch 36 - Val loss: 0.4867\n",
      "---------------------------------------------\n",
      "Epoch 37 - Train loss: 0.8048\n",
      "Epoch 37 - Val loss: 0.3968\n",
      "---------------------------------------------\n",
      "Epoch 38 - Train loss: 0.7542\n",
      "Epoch 38 - Val loss: 0.3674\n",
      "---------------------------------------------\n",
      "Epoch 39 - Train loss: 0.7279\n",
      "Epoch 39 - Val loss: 0.3642\n",
      "---------------------------------------------\n",
      "Epoch 40 - Train loss: 0.7096\n",
      "Epoch 40 - Val loss: 0.3525\n",
      "---------------------------------------------\n",
      "Epoch 41 - Train loss: 0.6720\n",
      "Epoch 41 - Val loss: 0.3396\n",
      "---------------------------------------------\n",
      "Epoch 42 - Train loss: 0.6442\n",
      "Epoch 42 - Val loss: 0.3232\n",
      "---------------------------------------------\n",
      "Epoch 43 - Train loss: 0.6159\n",
      "Epoch 43 - Val loss: 0.2928\n",
      "---------------------------------------------\n",
      "Epoch 44 - Train loss: 0.5782\n",
      "Epoch 44 - Val loss: 0.2737\n",
      "---------------------------------------------\n",
      "Epoch 45 - Train loss: 0.5567\n",
      "Epoch 45 - Val loss: 0.2752\n",
      "---------------------------------------------\n",
      "Epoch 46 - Train loss: 0.5552\n",
      "Epoch 46 - Val loss: 0.2856\n",
      "---------------------------------------------\n",
      "Epoch 47 - Train loss: 0.5172\n",
      "Epoch 47 - Val loss: 0.2545\n",
      "---------------------------------------------\n",
      "Epoch 48 - Train loss: 0.4891\n",
      "Epoch 48 - Val loss: 0.2330\n",
      "---------------------------------------------\n",
      "Epoch 49 - Train loss: 0.4737\n",
      "Epoch 49 - Val loss: 0.2327\n",
      "---------------------------------------------\n",
      "Epoch 50 - Train loss: 0.4592\n",
      "Epoch 50 - Val loss: 0.2217\n",
      "---------------------------------------------\n",
      "Epoch 51 - Train loss: 0.4345\n",
      "Epoch 51 - Val loss: 0.2270\n",
      "---------------------------------------------\n",
      "Epoch 52 - Train loss: 0.4261\n",
      "Epoch 52 - Val loss: 0.2079\n",
      "---------------------------------------------\n",
      "Epoch 53 - Train loss: 0.4058\n",
      "Epoch 53 - Val loss: 0.2079\n",
      "---------------------------------------------\n",
      "Epoch 54 - Train loss: 0.3921\n",
      "Epoch 54 - Val loss: 0.2498\n",
      "---------------------------------------------\n",
      "Epoch 55 - Train loss: 0.3812\n",
      "Epoch 55 - Val loss: 0.1912\n",
      "---------------------------------------------\n",
      "Epoch 56 - Train loss: 0.3651\n",
      "Epoch 56 - Val loss: 0.1791\n",
      "---------------------------------------------\n",
      "Epoch 57 - Train loss: 0.3673\n",
      "Epoch 57 - Val loss: 0.2398\n",
      "---------------------------------------------\n",
      "Epoch 58 - Train loss: 0.3465\n",
      "Epoch 58 - Val loss: 0.1695\n",
      "---------------------------------------------\n",
      "Epoch 59 - Train loss: 0.3262\n",
      "Epoch 59 - Val loss: 0.1665\n",
      "---------------------------------------------\n",
      "Epoch 60 - Train loss: 0.3276\n",
      "Epoch 60 - Val loss: 0.1718\n",
      "---------------------------------------------\n",
      "Epoch 61 - Train loss: 0.3111\n",
      "Epoch 61 - Val loss: 0.1555\n",
      "---------------------------------------------\n",
      "Epoch 62 - Train loss: 0.3048\n",
      "Epoch 62 - Val loss: 0.1771\n",
      "---------------------------------------------\n",
      "Epoch 63 - Train loss: 0.2974\n",
      "Epoch 63 - Val loss: 0.1708\n",
      "---------------------------------------------\n",
      "Epoch 64 - Train loss: 0.2841\n",
      "Epoch 64 - Val loss: 0.1389\n",
      "---------------------------------------------\n",
      "Epoch 65 - Train loss: 0.2708\n",
      "Epoch 65 - Val loss: 0.1635\n",
      "---------------------------------------------\n",
      "Epoch 66 - Train loss: 0.2677\n",
      "Epoch 66 - Val loss: 0.1294\n",
      "---------------------------------------------\n",
      "Epoch 67 - Train loss: 0.2638\n",
      "Epoch 67 - Val loss: 0.1355\n",
      "---------------------------------------------\n",
      "Epoch 68 - Train loss: 0.2502\n",
      "Epoch 68 - Val loss: 0.1317\n",
      "---------------------------------------------\n",
      "Epoch 69 - Train loss: 0.2370\n",
      "Epoch 69 - Val loss: 0.1209\n",
      "---------------------------------------------\n",
      "Epoch 70 - Train loss: 0.2323\n",
      "Epoch 70 - Val loss: 0.1163\n",
      "---------------------------------------------\n",
      "Epoch 71 - Train loss: 0.2225\n",
      "Epoch 71 - Val loss: 0.1229\n",
      "---------------------------------------------\n",
      "Epoch 72 - Train loss: 0.2230\n",
      "Epoch 72 - Val loss: 0.1086\n",
      "---------------------------------------------\n",
      "Epoch 73 - Train loss: 0.2092\n",
      "Epoch 73 - Val loss: 0.1129\n",
      "---------------------------------------------\n",
      "Epoch 74 - Train loss: 0.2044\n",
      "Epoch 74 - Val loss: 0.1172\n",
      "---------------------------------------------\n",
      "Epoch 75 - Train loss: 0.2034\n",
      "Epoch 75 - Val loss: 0.0980\n",
      "---------------------------------------------\n",
      "Epoch 76 - Train loss: 0.1978\n",
      "Epoch 76 - Val loss: 0.1096\n",
      "---------------------------------------------\n",
      "Epoch 77 - Train loss: 0.1938\n",
      "Epoch 77 - Val loss: 0.1149\n",
      "---------------------------------------------\n",
      "Epoch 78 - Train loss: 0.1912\n",
      "Epoch 78 - Val loss: 0.0985\n",
      "---------------------------------------------\n",
      "Epoch 79 - Train loss: 0.1788\n",
      "Epoch 79 - Val loss: 0.0924\n",
      "---------------------------------------------\n",
      "Epoch 80 - Train loss: 0.1774\n",
      "Epoch 80 - Val loss: 0.0874\n",
      "---------------------------------------------\n",
      "Epoch 81 - Train loss: 0.1692\n",
      "Epoch 81 - Val loss: 0.0903\n",
      "---------------------------------------------\n",
      "Epoch 82 - Train loss: 0.1652\n",
      "Epoch 82 - Val loss: 0.0848\n",
      "---------------------------------------------\n",
      "Epoch 83 - Train loss: 0.1594\n",
      "Epoch 83 - Val loss: 0.0874\n",
      "---------------------------------------------\n",
      "Epoch 84 - Train loss: 0.1591\n",
      "Epoch 84 - Val loss: 0.0780\n",
      "---------------------------------------------\n",
      "Epoch 85 - Train loss: 0.1521\n",
      "Epoch 85 - Val loss: 0.0878\n",
      "---------------------------------------------\n",
      "Epoch 86 - Train loss: 0.1542\n",
      "Epoch 86 - Val loss: 0.0912\n",
      "---------------------------------------------\n",
      "Epoch 87 - Train loss: 0.1506\n",
      "Epoch 87 - Val loss: 0.0755\n",
      "---------------------------------------------\n",
      "Epoch 88 - Train loss: 0.1395\n",
      "Epoch 88 - Val loss: 0.0671\n",
      "---------------------------------------------\n",
      "Epoch 89 - Train loss: 0.1395\n",
      "Epoch 89 - Val loss: 0.0835\n",
      "---------------------------------------------\n",
      "Epoch 90 - Train loss: 0.1420\n",
      "Epoch 90 - Val loss: 0.0721\n",
      "---------------------------------------------\n",
      "Epoch 91 - Train loss: 0.1324\n",
      "Epoch 91 - Val loss: 0.0645\n",
      "---------------------------------------------\n",
      "Epoch 92 - Train loss: 0.1330\n",
      "Epoch 92 - Val loss: 0.0903\n",
      "---------------------------------------------\n",
      "Epoch 93 - Train loss: 0.1540\n",
      "Epoch 93 - Val loss: 0.1011\n",
      "---------------------------------------------\n",
      "Epoch 94 - Train loss: 0.1309\n",
      "Epoch 94 - Val loss: 0.0622\n",
      "---------------------------------------------\n",
      "Epoch 95 - Train loss: 0.1194\n",
      "Epoch 95 - Val loss: 0.0922\n",
      "---------------------------------------------\n",
      "Epoch 96 - Train loss: 0.1192\n",
      "Epoch 96 - Val loss: 0.0768\n",
      "---------------------------------------------\n",
      "Epoch 97 - Train loss: 0.1236\n",
      "Epoch 97 - Val loss: 0.0598\n",
      "---------------------------------------------\n",
      "Epoch 98 - Train loss: 0.1076\n",
      "Epoch 98 - Val loss: 0.0535\n",
      "---------------------------------------------\n",
      "Epoch 99 - Train loss: 0.1056\n",
      "Epoch 99 - Val loss: 0.0644\n",
      "---------------------------------------------\n",
      "Epoch 100 - Train loss: 0.1134\n",
      "Epoch 100 - Val loss: 0.0622\n",
      "---------------------------------------------\n",
      "Epoch 101 - Train loss: 0.1062\n",
      "Epoch 101 - Val loss: 0.0538\n",
      "---------------------------------------------\n",
      "Epoch 102 - Train loss: 0.1009\n",
      "Epoch 102 - Val loss: 0.0549\n",
      "---------------------------------------------\n",
      "Epoch 103 - Train loss: 0.0974\n",
      "Epoch 103 - Val loss: 0.0519\n",
      "---------------------------------------------\n",
      "Epoch 104 - Train loss: 0.0937\n",
      "Epoch 104 - Val loss: 0.0534\n",
      "---------------------------------------------\n",
      "Epoch 105 - Train loss: 0.0948\n",
      "Epoch 105 - Val loss: 0.0470\n",
      "---------------------------------------------\n",
      "Epoch 106 - Train loss: 0.0944\n",
      "Epoch 106 - Val loss: 0.0463\n",
      "---------------------------------------------\n",
      "Epoch 107 - Train loss: 0.0935\n",
      "Epoch 107 - Val loss: 0.0450\n",
      "---------------------------------------------\n",
      "Epoch 108 - Train loss: 0.0899\n",
      "Epoch 108 - Val loss: 0.0451\n",
      "---------------------------------------------\n",
      "Epoch 109 - Train loss: 0.0861\n",
      "Epoch 109 - Val loss: 0.1321\n",
      "---------------------------------------------\n",
      "Epoch 110 - Train loss: 0.1002\n",
      "Epoch 110 - Val loss: 0.0587\n",
      "---------------------------------------------\n",
      "Epoch 111 - Train loss: 0.0837\n",
      "Epoch 111 - Val loss: 0.0420\n",
      "---------------------------------------------\n",
      "Epoch 112 - Train loss: 0.0806\n",
      "Epoch 112 - Val loss: 0.0441\n",
      "---------------------------------------------\n",
      "Epoch 113 - Train loss: 0.1124\n",
      "Epoch 113 - Val loss: 0.0938\n",
      "---------------------------------------------\n",
      "Epoch 114 - Train loss: 0.0873\n",
      "Epoch 114 - Val loss: 0.0434\n",
      "---------------------------------------------\n",
      "Epoch 115 - Train loss: 0.1013\n",
      "Epoch 115 - Val loss: 0.0378\n",
      "---------------------------------------------\n",
      "Epoch 116 - Train loss: 0.0901\n",
      "Epoch 116 - Val loss: 0.0364\n",
      "---------------------------------------------\n",
      "Epoch 117 - Train loss: 0.0728\n",
      "Epoch 117 - Val loss: 0.0356\n",
      "---------------------------------------------\n",
      "Epoch 118 - Train loss: 0.0707\n",
      "Epoch 118 - Val loss: 0.0416\n",
      "---------------------------------------------\n",
      "Epoch 119 - Train loss: 0.0694\n",
      "Epoch 119 - Val loss: 0.0338\n",
      "---------------------------------------------\n",
      "Epoch 120 - Train loss: 0.0658\n",
      "Epoch 120 - Val loss: 0.0328\n",
      "---------------------------------------------\n",
      "Epoch 121 - Train loss: 0.0660\n",
      "Epoch 121 - Val loss: 0.0427\n",
      "---------------------------------------------\n",
      "Epoch 122 - Train loss: 0.0726\n",
      "Epoch 122 - Val loss: 0.0412\n",
      "---------------------------------------------\n",
      "Epoch 123 - Train loss: 0.0685\n",
      "Epoch 123 - Val loss: 0.0329\n",
      "---------------------------------------------\n",
      "Epoch 124 - Train loss: 0.0613\n",
      "Epoch 124 - Val loss: 0.0327\n",
      "---------------------------------------------\n",
      "Epoch 125 - Train loss: 0.0590\n",
      "Epoch 125 - Val loss: 0.0345\n",
      "---------------------------------------------\n",
      "Epoch 126 - Train loss: 0.0607\n",
      "Epoch 126 - Val loss: 0.0585\n",
      "---------------------------------------------\n",
      "Epoch 127 - Train loss: 0.0630\n",
      "Epoch 127 - Val loss: 0.0341\n",
      "---------------------------------------------\n",
      "Epoch 128 - Train loss: 0.0903\n",
      "Epoch 128 - Val loss: 0.0656\n",
      "---------------------------------------------\n",
      "Epoch 129 - Train loss: 0.1824\n",
      "Epoch 129 - Val loss: 0.0485\n",
      "---------------------------------------------\n",
      "Epoch 130 - Train loss: 0.1024\n",
      "Epoch 130 - Val loss: 0.1735\n",
      "---------------------------------------------\n",
      "Epoch 131 - Train loss: 0.1202\n",
      "Epoch 131 - Val loss: 0.0555\n",
      "---------------------------------------------\n",
      "Epoch 132 - Train loss: 0.0653\n",
      "Epoch 132 - Val loss: 0.0541\n",
      "---------------------------------------------\n",
      "Epoch 133 - Train loss: 0.0569\n",
      "Epoch 133 - Val loss: 0.0403\n",
      "---------------------------------------------\n",
      "Epoch 134 - Train loss: 0.0543\n",
      "Epoch 134 - Val loss: 0.0265\n",
      "---------------------------------------------\n",
      "Epoch 135 - Train loss: 0.0498\n",
      "Epoch 135 - Val loss: 0.0275\n",
      "---------------------------------------------\n",
      "Epoch 136 - Train loss: 0.0467\n",
      "Epoch 136 - Val loss: 0.0302\n",
      "---------------------------------------------\n",
      "Epoch 137 - Train loss: 0.0506\n",
      "Epoch 137 - Val loss: 0.0356\n",
      "---------------------------------------------\n",
      "Epoch 138 - Train loss: 0.0472\n",
      "Epoch 138 - Val loss: 0.0251\n",
      "---------------------------------------------\n",
      "Epoch 139 - Train loss: 0.0481\n",
      "Epoch 139 - Val loss: 0.0251\n",
      "---------------------------------------------\n",
      "Epoch 140 - Train loss: 0.0554\n",
      "Epoch 140 - Val loss: 0.0334\n",
      "---------------------------------------------\n",
      "Epoch 141 - Train loss: 0.0438\n",
      "Epoch 141 - Val loss: 0.0245\n",
      "---------------------------------------------\n",
      "Epoch 142 - Train loss: 0.0480\n",
      "Epoch 142 - Val loss: 0.0534\n",
      "---------------------------------------------\n",
      "Epoch 143 - Train loss: 0.0523\n",
      "Epoch 143 - Val loss: 0.0371\n",
      "---------------------------------------------\n",
      "Epoch 144 - Train loss: 0.0449\n",
      "Epoch 144 - Val loss: 0.0329\n",
      "---------------------------------------------\n",
      "Epoch 145 - Train loss: 0.0427\n",
      "Epoch 145 - Val loss: 0.0463\n",
      "---------------------------------------------\n",
      "Epoch 146 - Train loss: 0.0481\n",
      "Epoch 146 - Val loss: 0.0250\n",
      "---------------------------------------------\n",
      "Epoch 147 - Train loss: 0.0412\n",
      "Epoch 147 - Val loss: 0.0257\n",
      "---------------------------------------------\n",
      "Epoch 148 - Train loss: 0.0505\n",
      "Epoch 148 - Val loss: 0.0283\n",
      "---------------------------------------------\n",
      "Epoch 149 - Train loss: 0.0436\n",
      "Epoch 149 - Val loss: 0.0209\n",
      "---------------------------------------------\n",
      "Epoch 150 - Train loss: 0.0419\n",
      "Epoch 150 - Val loss: 0.0263\n",
      "---------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "# define model and optimizer\n",
    "model = ConvTasNetWithTransformer()\n",
    "# model = PretrainedTransformer(output_size=257, num_heads = 8, num_layers = 6)\n",
    "if torch.cuda.is_available():\n",
    "    model = model.cuda()\n",
    "optimizer = torch.optim.Adam(model.parameters(), lr=1e-4)\n",
    "\n",
    "# define loss function\n",
    "loss_fn = nn.MSELoss()\n",
    "\n",
    "fit(model, optimizer, loss_fn, 150, train_loader, val_loader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "72c49138",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-03T00:12:58.386523Z",
     "iopub.status.busy": "2023-05-03T00:12:58.386086Z",
     "iopub.status.idle": "2023-05-03T00:20:20.383736Z",
     "shell.execute_reply": "2023-05-03T00:20:20.381678Z"
    },
    "papermill": {
     "duration": 442.041048,
     "end_time": "2023-05-03T00:20:20.405831",
     "exception": false,
     "start_time": "2023-05-03T00:12:58.364783",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training MSE: 0.027541908520189198\n",
      "Validation MSE: 0.026301669755152295\n",
      "Testing MSE: 0.03057378761470318\n"
     ]
    }
   ],
   "source": [
    "print(f\"Training MSE: {validate(model, train_loader, loss_fn)}\")\n",
    "print(f\"Validation MSE: {validate(model, val_loader, loss_fn)}\")\n",
    "print(f\"Testing MSE: {validate(model, test_loader, loss_fn)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "a57c86e6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2023-05-03T00:20:20.447809Z",
     "iopub.status.busy": "2023-05-03T00:20:20.446726Z",
     "iopub.status.idle": "2023-05-03T00:25:58.730281Z",
     "shell.execute_reply": "2023-05-03T00:25:58.729003Z"
    },
    "papermill": {
     "duration": 338.307347,
     "end_time": "2023-05-03T00:25:58.732738",
     "exception": false,
     "start_time": "2023-05-03T00:20:20.425391",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "849ac9ee0d8e4f2facc1caf15fe58c6c",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training SDR: 4.347351231621799\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "21d793e1c96c4f9386a300cfa8647489",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Validation SDR: 3.3966928381526555\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fbfce97357e342d983a09b91da909630",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "0it [00:00, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Testing SDR: 4.090461655007675\n"
     ]
    }
   ],
   "source": [
    "import warnings\n",
    "\n",
    "with warnings.catch_warnings():\n",
    "    warnings.filterwarnings(\"ignore\", category=RuntimeWarning)    \n",
    "    print(f\"Training SDR: {test(model, train_loader)}\")\n",
    "    print(f\"Validation SDR: {test(model, val_loader)}\")\n",
    "    print(f\"Testing SDR: {test(model, test_loader)}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "741cedd3",
   "metadata": {
    "papermill": {
     "duration": 0.020282,
     "end_time": "2023-05-03T00:25:58.773588",
     "exception": false,
     "start_time": "2023-05-03T00:25:58.753306",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.12"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 35408.079443,
   "end_time": "2023-05-03T00:26:00.586901",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2023-05-02T14:35:52.507458",
   "version": "2.4.0"
  },
  "widgets": {
   "application/vnd.jupyter.widget-state+json": {
    "state": {
     "029805c81fef4fdcbf02b63444f762e1": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "0690418a5d744b9f84a27d0dac34566e": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "081bb55bc610447abf7a850a1a2714b6": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_3c0e1b09c0704229975241dafa26ac29",
       "max": 1.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_977c5d21bb754f6594c49c07d8bd7678",
       "value": 1.0
      }
     },
     "1e31469ce7d64c4285ea8adba19f4403": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "1f94e9a673c74eb8865a3a0397f47691": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "2167a4020ef04b9b9efc2c770db39ee8": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "21d2b20c63e34050bbd3f5425bbaccfb": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "21d793e1c96c4f9386a300cfa8647489": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_acaf5acf8bae45b1aa54714731221a82",
        "IPY_MODEL_b104ef36ba4f4be6bf1c86032aeb373f",
        "IPY_MODEL_d26ae40b09bb4f2dabf3e1c1b1ea51de"
       ],
       "layout": "IPY_MODEL_95f34730e857408dbd180b9e1299d175"
      }
     },
     "27c294ae4a264ea09c63fbebbb39277d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "2a0623a8bf2c464f95c5ce80bb49b5d0": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_2167a4020ef04b9b9efc2c770db39ee8",
       "placeholder": "​",
       "style": "IPY_MODEL_f47db025ca6740ac8846f3ad6c298474",
       "value": " 150/150 [9:36:24&lt;00:00, 230.52s/it]"
      }
     },
     "2a0fa867c79d456e91f4ac34d7f7eece": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_94896b0140c3490bb29bae62ff74186d",
       "max": 150.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_4512f49e433543e19ead79f2f5decb0a",
       "value": 150.0
      }
     },
     "2c6b9e23768648cdbdaddd78e52fb4d1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_912d5f6de77044b79d1590fcdd4fa256",
        "IPY_MODEL_2a0fa867c79d456e91f4ac34d7f7eece",
        "IPY_MODEL_2a0623a8bf2c464f95c5ce80bb49b5d0"
       ],
       "layout": "IPY_MODEL_0690418a5d744b9f84a27d0dac34566e"
      }
     },
     "3a7d9a9c157b4354a0eff9be5fab94ff": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "3bc44490139447d58bca52149db42932": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_1e31469ce7d64c4285ea8adba19f4403",
       "placeholder": "​",
       "style": "IPY_MODEL_df2d7621bba74aa9b3026c367134b354",
       "value": " 19.1M/19.1M [00:00&lt;00:00, 64.6MB/s]"
      }
     },
     "3c0e1b09c0704229975241dafa26ac29": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": "20px"
      }
     },
     "3ddc7c25400d471db8a364dcc8d5c50a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "4512f49e433543e19ead79f2f5decb0a": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "4d08ea088b91479994bcfe4113aecffb": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "53c82f8168234a408ff04dd96b0a1c4d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "5b8d233329124415b73dfaa9d7713505": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "5e3f6a7d9d9a4cd29c43010ba2772fab": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "5f7c920b7867436080951641a341499b": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "68e908a1fc5441cb8543b860362d825f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_53c82f8168234a408ff04dd96b0a1c4d",
       "placeholder": "​",
       "style": "IPY_MODEL_a80e5bf9aa2740198dc2b0676e5acf5f",
       "value": ""
      }
     },
     "6f1e0c2e50354adb82de8d2a2497276f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_029805c81fef4fdcbf02b63444f762e1",
       "placeholder": "​",
       "style": "IPY_MODEL_5f7c920b7867436080951641a341499b",
       "value": "100%"
      }
     },
     "7bed89308de64101bfbee397b4df7257": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_b23885b250e24dda89e65f3af3e71145",
       "max": 1.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_c1f18e441a0e4b5cb80467856f5258d5",
       "value": 1.0
      }
     },
     "7e2c8d4b89f249998721781245bb6411": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "849ac9ee0d8e4f2facc1caf15fe58c6c": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_68e908a1fc5441cb8543b860362d825f",
        "IPY_MODEL_7bed89308de64101bfbee397b4df7257",
        "IPY_MODEL_f9055eae47f44473b87d756a40f77f09"
       ],
       "layout": "IPY_MODEL_5b8d233329124415b73dfaa9d7713505"
      }
     },
     "8d9d525760d844a4886acfeb798128de": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "912d5f6de77044b79d1590fcdd4fa256": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_4d08ea088b91479994bcfe4113aecffb",
       "placeholder": "​",
       "style": "IPY_MODEL_8d9d525760d844a4886acfeb798128de",
       "value": "100%"
      }
     },
     "91c59d82228648c183939fd0b4637e49": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "94896b0140c3490bb29bae62ff74186d": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "95f34730e857408dbd180b9e1299d175": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "973e3c5ded254664b7c16db3679e03ce": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "977c5d21bb754f6594c49c07d8bd7678": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "9a095e23fdb84439b1bd1a8b9a9e9eb4": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "a347634ae33d47f79759e43293d64ba3": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": "20px"
      }
     },
     "a80e5bf9aa2740198dc2b0676e5acf5f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "acaf5acf8bae45b1aa54714731221a82": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_daaeb75c34014dad83ea21cce457303c",
       "placeholder": "​",
       "style": "IPY_MODEL_3ddc7c25400d471db8a364dcc8d5c50a",
       "value": ""
      }
     },
     "b059dfab70ed48d5a406e23047838857": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_973e3c5ded254664b7c16db3679e03ce",
       "placeholder": "​",
       "style": "IPY_MODEL_21d2b20c63e34050bbd3f5425bbaccfb",
       "value": ""
      }
     },
     "b104ef36ba4f4be6bf1c86032aeb373f": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_a347634ae33d47f79759e43293d64ba3",
       "max": 1.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_5e3f6a7d9d9a4cd29c43010ba2772fab",
       "value": 1.0
      }
     },
     "b23885b250e24dda89e65f3af3e71145": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": "20px"
      }
     },
     "b717efa4793842c1b795bf34031883d8": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "be83006ec86a4676ad96d920bdc6fc85": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "FloatProgressModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "FloatProgressModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "ProgressView",
       "bar_style": "success",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_7e2c8d4b89f249998721781245bb6411",
       "max": 20049107.0,
       "min": 0.0,
       "orientation": "horizontal",
       "style": "IPY_MODEL_3a7d9a9c157b4354a0eff9be5fab94ff",
       "value": 20049107.0
      }
     },
     "c1f18e441a0e4b5cb80467856f5258d5": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "ProgressStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "ProgressStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "bar_color": null,
       "description_width": ""
      }
     },
     "c7f1fcb90c314001a67f45ab4175afe9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "cdd6cb810ed045eb970218eca86dea1c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "d249e01b0d1749ea927d4410b699dcc1": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "d26ae40b09bb4f2dabf3e1c1b1ea51de": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_27c294ae4a264ea09c63fbebbb39277d",
       "placeholder": "​",
       "style": "IPY_MODEL_c7f1fcb90c314001a67f45ab4175afe9",
       "value": " 7/? [00:30&lt;00:00,  4.07s/it]"
      }
     },
     "daaeb75c34014dad83ea21cce457303c": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.2.0",
      "model_name": "LayoutModel",
      "state": {
       "_model_module": "@jupyter-widgets/base",
       "_model_module_version": "1.2.0",
       "_model_name": "LayoutModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "LayoutView",
       "align_content": null,
       "align_items": null,
       "align_self": null,
       "border": null,
       "bottom": null,
       "display": null,
       "flex": null,
       "flex_flow": null,
       "grid_area": null,
       "grid_auto_columns": null,
       "grid_auto_flow": null,
       "grid_auto_rows": null,
       "grid_column": null,
       "grid_gap": null,
       "grid_row": null,
       "grid_template_areas": null,
       "grid_template_columns": null,
       "grid_template_rows": null,
       "height": null,
       "justify_content": null,
       "justify_items": null,
       "left": null,
       "margin": null,
       "max_height": null,
       "max_width": null,
       "min_height": null,
       "min_width": null,
       "object_fit": null,
       "object_position": null,
       "order": null,
       "overflow": null,
       "overflow_x": null,
       "overflow_y": null,
       "padding": null,
       "right": null,
       "top": null,
       "visibility": null,
       "width": null
      }
     },
     "df2d7621bba74aa9b3026c367134b354": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "dfea627363144b59a790c540d22ca2e9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_9a095e23fdb84439b1bd1a8b9a9e9eb4",
       "placeholder": "​",
       "style": "IPY_MODEL_d249e01b0d1749ea927d4410b699dcc1",
       "value": " 25/? [01:55&lt;00:00,  4.68s/it]"
      }
     },
     "ee9e8172d6bd4c9c97a090152d6154c9": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_6f1e0c2e50354adb82de8d2a2497276f",
        "IPY_MODEL_be83006ec86a4676ad96d920bdc6fc85",
        "IPY_MODEL_3bc44490139447d58bca52149db42932"
       ],
       "layout": "IPY_MODEL_1f94e9a673c74eb8865a3a0397f47691"
      }
     },
     "f47db025ca6740ac8846f3ad6c298474": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "DescriptionStyleModel",
      "state": {
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "DescriptionStyleModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/base",
       "_view_module_version": "1.2.0",
       "_view_name": "StyleView",
       "description_width": ""
      }
     },
     "f9055eae47f44473b87d756a40f77f09": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HTMLModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HTMLModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HTMLView",
       "description": "",
       "description_tooltip": null,
       "layout": "IPY_MODEL_91c59d82228648c183939fd0b4637e49",
       "placeholder": "​",
       "style": "IPY_MODEL_b717efa4793842c1b795bf34031883d8",
       "value": " 44/? [03:12&lt;00:00,  3.80s/it]"
      }
     },
     "fbfce97357e342d983a09b91da909630": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.5.0",
      "model_name": "HBoxModel",
      "state": {
       "_dom_classes": [],
       "_model_module": "@jupyter-widgets/controls",
       "_model_module_version": "1.5.0",
       "_model_name": "HBoxModel",
       "_view_count": null,
       "_view_module": "@jupyter-widgets/controls",
       "_view_module_version": "1.5.0",
       "_view_name": "HBoxView",
       "box_style": "",
       "children": [
        "IPY_MODEL_b059dfab70ed48d5a406e23047838857",
        "IPY_MODEL_081bb55bc610447abf7a850a1a2714b6",
        "IPY_MODEL_dfea627363144b59a790c540d22ca2e9"
       ],
       "layout": "IPY_MODEL_cdd6cb810ed045eb970218eca86dea1c"
      }
     }
    },
    "version_major": 2,
    "version_minor": 0
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}