new Benchmark notebook

notebooks/Benchmark.ipynb

@@ -20,9 +20,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "TTS_PATH = \"/home/erogol/projects/\"\n",
@@ -33,7 +31,6 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "scrolled": true
    },
    "outputs": [],
@@ -45,6 +42,7 @@
     "import io\n",
     "import torch \n",
     "import time\n",
+    "import json\n",
     "import numpy as np\n",
     "from collections import OrderedDict\n",
     "from matplotlib import pylab as plt\n",
@@ -72,23 +70,23 @@
     "from IPython.display import Audio\n",
     "\n",
     "import os\n",
-    "os.environ['CUDA_VISIBLE_DEVICES']='1'\n",
-    "os.environ['OMP_NUM_THREADS']='1'\n"
+    "os.environ['CUDA_VISIBLE_DEVICES']='1'"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "def tts(model, text, CONFIG, use_cuda, ap, use_gl, speaker_id=None, figures=True):\n",
+    "def tts(model, text, CONFIG, use_cuda, ap, use_gl, figures=True):\n",
     "    t_1 = time.time()\n",
-    "    waveform, alignment, mel_spec, mel_postnet_spec, stop_tokens = synthesis(model, text, CONFIG, use_cuda, ap, truncated=False, speaker_id=speaker_id, enable_eos_bos_chars=CONFIG.enable_eos_bos_chars)\n",
+    "    waveform, alignment, mel_spec, mel_postnet_spec, stop_tokens = synthesis(model, text, CONFIG, use_cuda, ap, speaker_id, False, CONFIG.enable_eos_bos_chars)\n",
     "    if CONFIG.model == \"Tacotron\" and not use_gl:\n",
+    "        # coorect the normalization differences b/w TTS and the Vocoder.\n",
     "        mel_postnet_spec = ap.out_linear_to_mel(mel_postnet_spec.T).T\n",
+    "        mel_postnet_spec = ap._denormalize(mel_postnet_spec)\n",
+    "        mel_postnet_spec = ap_vocoder._normalize(mel_postnet_spec)\n",
     "    if not use_gl:\n",
     "        waveform = wavernn.generate(torch.FloatTensor(mel_postnet_spec.T).unsqueeze(0).cuda(), batched=batched_wavernn, target=11000, overlap=550)\n",
     "\n",
@@ -106,19 +104,17 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# Set constants\n",
-    "ROOT_PATH = '/media/erogol/data_ssd/Data/models/mozilla_models/4845/'\n",
-    "MODEL_PATH = ROOT_PATH + 'best_model.pth.tar'\n",
+    "ROOT_PATH = '/media/erogol/data_ssd/Models/libri_tts/5049/'\n",
+    "MODEL_PATH = ROOT_PATH + '/best_model.pth.tar'\n",
     "CONFIG_PATH = ROOT_PATH + '/config.json'\n",
-    "OUT_FOLDER = \"/home/erogol/Dropbox/AudioSamples/benchmark_samples/\"\n",
+    "OUT_FOLDER = '/home/erogol/Dropbox/AudioSamples/benchmark_samples/'\n",
     "CONFIG = load_config(CONFIG_PATH)\n",
-    "VOCODER_MODEL_PATH = \"/media/erogol/data_ssd/Data/models/wavernn/mozilla/mozilla-May24-4763/model_checkpoints/best_model.pth.tar\"\n",
-    "VOCODER_CONFIG_PATH = \"/media/erogol/data_ssd/Data/models/wavernn/mozilla/mozilla-May24-4763/config.json\"\n",
+    "VOCODER_MODEL_PATH = \"/media/erogol/data_ssd/Models/wavernn/universal/4910/best_model_16K.pth.tar\"\n",
+    "VOCODER_CONFIG_PATH = \"/media/erogol/data_ssd/Models/wavernn/universal/4910/config_16K.json\"\n",
     "VOCODER_CONFIG = load_config(VOCODER_CONFIG_PATH)\n",
     "use_cuda = False\n",
     "\n",
@@ -126,6 +122,8 @@
     "# CONFIG.windowing = False\n",
     "# CONFIG.prenet_dropout = False\n",
     "# CONFIG.separate_stopnet = True\n",
+    "# CONFIG.use_forward_attn = True\n",
+    "# CONFIG.forward_attn_mask = True\n",
     "# CONFIG.stopnet = True\n",
     "\n",
     "# Set the vocoder\n",
@@ -136,17 +134,23 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# LOAD TTS MODEL\n",
     "from utils.text.symbols import symbols, phonemes\n",
     "\n",
+    "# multi speaker \n",
+    "if CONFIG.use_speaker_embedding:\n",
+    "    speakers = json.load(open(f\"{ROOT_PATH}/speakers.json\", 'r'))\n",
+    "    speakers_idx_to_id = {v: k for k, v in speakers.items()}\n",
+    "else:\n",
+    "    speakers = []\n",
+    "    speaker_id = None\n",
+    "\n",
     "# load the model\n",
     "num_chars = len(phonemes) if CONFIG.use_phonemes else len(symbols)\n",
-    "model = setup_model(num_chars, CONFIG)\n",
+    "model = setup_model(num_chars, len(speakers), CONFIG)\n",
     "\n",
     "# load the audio processor\n",
     "ap = AudioProcessor(**CONFIG.audio)         \n",
@@ -163,39 +167,45 @@
     "if use_cuda:\n",
     "    model.cuda()\n",
     "model.eval()\n",
-    "print(cp['step'])"
+    "print(cp['step'])\n",
+    "print(cp['r'])\n",
+    "\n",
+    "# set model stepsize \n",
+    "if 'r' in cp:\n",
+    "    model.decoder.set_r(cp['r'])"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# LOAD WAVERNN\n",
     "if use_gl == False:\n",
     "    from WaveRNN.models.wavernn import Model\n",
+    "    from WaveRNN.utils.audio import AudioProcessor as AudioProcessorVocoder\n",
     "    bits = 10\n",
-    "\n",
+    "    ap_vocoder = AudioProcessorVocoder(**VOCODER_CONFIG.audio)     \n",
     "    wavernn = Model(\n",
     "            rnn_dims=512,\n",
     "            fc_dims=512,\n",
-    "            mode=\"mold\",\n",
-    "            pad=2,\n",
-    "            upsample_factors=VOCODER_CONFIG.upsample_factors,  # set this depending on dataset\n",
+    "            mode=VOCODER_CONFIG.mode,\n",
+    "            mulaw=VOCODER_CONFIG.mulaw,\n",
+    "            pad=VOCODER_CONFIG.pad,\n",
+    "            upsample_factors=VOCODER_CONFIG.upsample_factors,\n",
     "            feat_dims=VOCODER_CONFIG.audio[\"num_mels\"],\n",
     "            compute_dims=128,\n",
     "            res_out_dims=128,\n",
     "            res_blocks=10,\n",
-    "            hop_length=ap.hop_length,\n",
-    "            sample_rate=ap.sample_rate,\n",
+    "            hop_length=ap_vocoder.hop_length,\n",
+    "            sample_rate=ap_vocoder.sample_rate,\n",
+    "            use_upsample_net = True,\n",
+    "            use_aux_net = True\n",
     "        ).cuda()\n",
     "\n",
-    "\n",
     "    check = torch.load(VOCODER_MODEL_PATH)\n",
-    "    wavernn.load_state_dict(check['model'])\n",
+    "    wavernn.load_state_dict(check['model'], strict=False)\n",
     "    if use_cuda:\n",
     "        wavernn.cuda()\n",
     "    wavernn.eval();\n",
@@ -209,70 +219,75 @@
     "### Comparision with https://mycroft.ai/blog/available-voices/"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model.eval()\n",
+    "model.decoder.max_decoder_steps = 2000\n",
+    "speaker_id = 500\n",
+    "sentence =  \"Bill got in the habit of asking himself “Is that thought true?” and if he wasn’t absolutely certain it was, he just let it go.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
-    "scrolled": false
+    "scrolled": true
    },
    "outputs": [],
    "source": [
     "model.eval()\n",
     "model.decoder.max_decoder_steps = 2000\n",
-    "speaker_id = 0\n",
-    "sentence =  \"Bill got in the habit of asking himself “Is that thought true?” And if he wasn’t absolutely certain it was, he just let it go.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence =  \"Seine Fuerenden Berater hatten Donald Trump seit Wochen beschworen, berichteten US-Medien: Lassen Sie das mit den Zoellen bleiben.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "sentence = \"Be a voice, not an echo.\"  # 'echo' is not in training set. \n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence =  \"Der Klimawandel bedroht die Gletscher im Himalaya.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"The human voice is the most perfect instrument of all.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence = \"Zwei Unternehmen verlieren einem Medienbericht zufolge ihre Verträge als Maut-Inkasso-Manager.\"  # 'echo' is not in training set. \n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"I'm sorry Dave. I'm afraid I can't do that.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence = \"Eine Ausländermaut nach dem Geschmack der CSU wird es nicht geben - das bedauert außerhalb der Partei fast niemand.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true,
     "scrolled": true
    },
    "outputs": [],
    "source": [
-    "sentence = \"This cake is great. It's so delicious and moist.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence = \"Angela Merkel ist als Klimakanzlerin gestartet.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
@@ -285,61 +300,51 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"Generative adversarial network or variational auto-encoder.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence = \"Dann vernachlässigte sie das Thema.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"Scientists at the CERN laboratory say they have discovered a new particle.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence = \"Nun, kurz vor dem Ende, will sie damit noch einmal neu anfangen.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"Here’s a way to measure the acute emotional intelligence that has never gone out of style.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence = \"Nun ist der Spieltempel pleite, und manchen Dorfbewohnern fehlt das Geld zum Essen.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"President Trump met with other leaders at the Group of 20 conference.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence = \"Andrea Nahles will in der Fraktion die Vertrauensfrage stellen.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"The buses aren't the problem, they actually provide a solution.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence=\"Die Erfolge der Grünen bringen eine Reihe Unerfahrener in die Parlamente.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
@@ -352,212 +357,27 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"Generative adversarial network or variational auto-encoder.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"Basilar membrane and otolaryngology are not auto-correlations.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \" He has read the whole thing.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"He reads books.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true,
-    "scrolled": false
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"Thisss isrealy awhsome.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true,
-    "scrolled": false
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"This is your internet browser, Firefox.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"This is your internet browser Firefox.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"The quick brown fox jumps over the lazy dog.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"Does the quick brown fox jump over the lazy dog?\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"Eren, how are you?\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
    "metadata": {},
-   "source": [
-    "### Hard Sentences"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
    "outputs": [],
    "source": [
-    "sentence = \"Encouraged, he started with a minute a day.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence=\"Die Luftfahrtbranche arbeitet daran, CO2-neutral zu werden.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
-    "sentence = \"His meditation consisted of “body scanning” which involved focusing his mind and energy on each section of the body from head to toe .\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
+    "sentence=\"Michael Kretschmer versucht seit Monaten, die Bürger zu umgarnen.\"\n",
+    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, use_gl=use_gl, figures=True)"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"Recent research at Harvard has shown meditating for as little as 8 weeks can actually increase the grey matter in the parts of the brain responsible for emotional regulation and learning . \"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"If he decided to watch TV he really watched it.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true,
-    "scrolled": true
-   },
-   "outputs": [],
-   "source": [
-    "sentence = \"Often we try to bring about change through sheer effort and we put all of our energy into a new initiative .\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
-   "outputs": [],
-   "source": [
-    "# for twb dataset\n",
-    "sentence = \"In our preparation for Easter, God in his providence offers us each year the season of Lent as a sacramental sign of our conversion.\"\n",
-    "align, spec, stop_tokens, wav = tts(model, sentence, CONFIG, use_cuda, ap, speaker_id=speaker_id, use_gl=use_gl, figures=True)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "# !zip benchmark_samples/samples.zip benchmark_samples/*"
@@ -566,9 +386,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3(mztts)",
+   "display_name": "Python 3",
    "language": "python",
-   "name": "mztts"
+   "name": "python3"
   },
   "language_info": {
    "codemirror_mode": {
@@ -580,9 +400,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.8"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }