studying_studies.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 315,
   "metadata": {},
   "outputs": [],
   "source": [
    "from kaleido.scopes.plotly import PlotlyScope\n",
    "from pippi.soundbuffer import SoundBuffer\n",
    "from pippi import dsp,fx\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import sounddevice as sd\n",
    "import helpers as hp\n",
    "import param_generation as pg\n",
    "import _pickle as pickle\n",
    "from IPython.display import Audio\n",
    "import librosa\n",
    "import librosa.feature\n",
    "from feature_extraction import pytorch_models as tm\n",
    "import optuna\n",
    "import torch\n",
    "SR = 44100\n",
    "import imp\n",
    "import joblib\n",
    "from optuna.visualization import plot_edf\n",
    "from optuna.visualization import plot_optimization_history\n",
    "from optuna.visualization import plot_parallel_coordinate\n",
    "from optuna.visualization import plot_param_importances\n",
    "from optuna.visualization import plot_slice\n",
    "drum_names = ['hat', 'kick', 'shake', 'snare']\n",
    "optuna.logging.set_verbosity(0)\n",
    "\n",
    "\n",
    "icy = ['rgb(0,0,0)','rgb(50,50,140)','rgb(70,70,160)','rgb(110,110,200)','rgb(130,130,210)',\n",
    "     'rgb(150,150,230)', 'rgb(170,170,255)','rgb(190,190,255)',\n",
    "     'rgb(200,200,255)','rgb(210,210,255)','rgb(220,220,255)','rgb(240,240,255)']\n",
    "icy_r = icy.copy()\n",
    "icy_r.reverse()\n",
    "imp.reload(tm)\n",
    "# let's sample from the probability distribution\n",
    "dt = 1\n",
    "study_name = \"HyperBand_%s\"%drum_names[dt]\n",
    "study = joblib.load(\"studies/%s_study.pkl\"%study_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 316,
   "metadata": {},
   "outputs": [],
   "source": [
    "cnet_dvn = tm.Transformer_DVN(attention_dropout=0.3,d_model=120,heads=30,encoding_layers=12,pool_dim=2,)\n",
    "cnet_dvn = cnet_dvn.load_from_checkpoint(\n",
    "    \"models/transformer/DVNepoch=41-val_accuracy=0.991-val_loss=0.048.ckpt\")\n",
    "\n",
    "cnet_dvd = tm.Transformer_DVD(attention_dropout=0.3,d_model=100,heads=20,encoding_layers=12,pool_dim=1,pct_start=0.05,max_lr=1e-4,max_momentum=0.95,epochs=50)\n",
    "cnet_dvd = cnet_dvd.load_from_checkpoint(\n",
    "    \"models/transformer/DVDepoch=59-val_accuracy=0.917-val_auc=0.9779-val_loss=0.327.ckpt\")\n",
    "device = torch.device(\"cuda:1\" if torch.cuda.is_available() else \"cpu\")\n",
    "cnet_dvn.to(device)\n",
    "cnet_dvd.to(device)\n",
    "pass "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 320,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "attempt->4, invalid programs->0\n",
      "\n",
      "0.7172191143035889 8.376440048217773\n"
     ]
    },
    {
     "data": {
      "text/html": [
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type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 320,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "space = optuna.samplers.intersection_search_space(study)\n",
    "num_invalids = 0\n",
    "for i in range(100):\n",
    "    try:\n",
    "        print(i,end=\"\\r\")\n",
    "        params = study.sampler.sample_relative(study,optuna.trial._frozen.FrozenTrial,space)\n",
    "        program = pg.StackParams()\n",
    "        program.__dict__ = dict(zip(program.__dict__.keys(),params.values()))\n",
    "        out = dsp.buffer(length=1,channels=1)\n",
    "        s = pg.Synth(program)\n",
    "        out.dub(s.buff,program.getStart())\n",
    "        out = fx.norm(out,1)\n",
    "        sound = hp.memToAud(out)\n",
    "        \n",
    "        signal = torch.tensor(librosa.resample(sound.reshape(-1),SR,SR//2)).to(device)[0:SR//4].reshape(1,-1)\n",
    "        cnet_dvn.eval(),cnet_dvd.eval()\n",
    "        with torch.no_grad():\n",
    "            score_dvn = cnet_dvn(signal).item()\n",
    "            score_dvd = cnet_dvd(signal)[0][dt].item()\n",
    "        \n",
    "        if (score_dvn < -1 or score_dvd < 0):\n",
    "            pass\n",
    "        else:\n",
    "            print(\"attempt->%d, invalid programs->%d\\n\"%(i,num_invalids))\n",
    "            print(score_dvn,score_dvd)\n",
    "            break\n",
    "    except:\n",
    "        num_invalids += 1\n",
    "        pass \n",
    "Audio(sound,rate=SR, autoplay=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scope = PlotlyScope()\n",
    "fig = plot_optimization_history(study)\n",
    "fig.update_yaxes(showgrid=False,zeroline=False,)\n",
    "# with open(\"figs/optimization_%s.pdf\"%study_name, \"wb\") as f:\n",
    "#     f.write(scope.transform(fig, format=\"pdf\", width=800,height=400,))\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scope = PlotlyScope()\n",
    "fig = plot_optimization_history(study)\n",
    "fig.update_yaxes(showgrid=False,zeroline=False,)\n",
    "# with open(\"figs/optimization_%s.pdf\"%study_name, \"wb\") as f:\n",
    "#     f.write(scope.transform(fig, format=\"pdf\", width=800,height=400,))\n",
    "fig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 480,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>number</th>\n",
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       "      <th>datetime_start</th>\n",
       "      <th>datetime_complete</th>\n",
       "      <th>duration</th>\n",
       "      <th>params_A</th>\n",
       "      <th>params_Amplitude</th>\n",
       "      <th>params_BP Order</th>\n",
       "      <th>params_D</th>\n",
       "      <th>params_High Cut</th>\n",
       "      <th>...</th>\n",
       "      <th>params_Noise Cloud</th>\n",
       "      <th>params_OSC Type</th>\n",
       "      <th>params_R</th>\n",
       "      <th>params_S</th>\n",
       "      <th>params_Start</th>\n",
       "      <th>params_pitch_0</th>\n",
       "      <th>params_pitch_1</th>\n",
       "      <th>params_pitch_2</th>\n",
       "      <th>params_pitch_3</th>\n",
       "      <th>state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "    <tr>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>2021-08-02 02:37:24.161084</td>\n",
       "      <td>2021-08-02 02:37:24.175922</td>\n",
       "      <td>00:00:00.014838</td>\n",
       "      <td>2</td>\n",
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       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>81</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>9</td>\n",
       "      <td>75</td>\n",
       "      <td>85</td>\n",
       "      <td>47</td>\n",
       "      <td>9</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2021-08-02 02:37:24.162363</td>\n",
       "      <td>2021-08-02 02:37:24.231270</td>\n",
       "      <td>00:00:00.068907</td>\n",
       "      <td>3</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>20</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>9</td>\n",
       "      <td>55</td>\n",
       "      <td>1</td>\n",
       "      <td>16</td>\n",
       "      <td>90</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2021-08-02 02:37:24.177468</td>\n",
       "      <td>2021-08-02 02:37:24.246080</td>\n",
       "      <td>00:00:00.068612</td>\n",
       "      <td>1</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>70</td>\n",
       "      <td>77</td>\n",
       "      <td>9</td>\n",
       "      <td>54</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2021-08-02 02:37:24.231784</td>\n",
       "      <td>2021-08-02 02:37:24.287795</td>\n",
       "      <td>00:00:00.056011</td>\n",
       "      <td>1</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>97</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>3</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>34</td>\n",
       "      <td>92</td>\n",
       "      <td>111</td>\n",
       "      <td>6</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>4</td>\n",
       "      <td>4</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>2021-08-02 02:37:24.246859</td>\n",
       "      <td>2021-08-02 02:37:24.259288</td>\n",
       "      <td>00:00:00.012429</td>\n",
       "      <td>3</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>99</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>68</td>\n",
       "      <td>103</td>\n",
       "      <td>102</td>\n",
       "      <td>45</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>5</td>\n",
       "      <td>5</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2021-08-02 02:37:24.259827</td>\n",
       "      <td>2021-08-02 02:37:24.321232</td>\n",
       "      <td>00:00:00.061405</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>59</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>77</td>\n",
       "      <td>98</td>\n",
       "      <td>25</td>\n",
       "      <td>92</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>6</td>\n",
       "      <td>6</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>2021-08-02 02:37:24.288257</td>\n",
       "      <td>2021-08-02 02:37:24.294297</td>\n",
       "      <td>00:00:00.006040</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>113</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>107</td>\n",
       "      <td>33</td>\n",
       "      <td>22</td>\n",
       "      <td>104</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>7</td>\n",
       "      <td>7</td>\n",
       "      <td>-10.0</td>\n",
       "      <td>2021-08-02 02:37:24.294732</td>\n",
       "      <td>2021-08-02 02:37:24.301971</td>\n",
       "      <td>00:00:00.007239</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>1</td>\n",
       "      <td>3</td>\n",
       "      <td>70</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>15</td>\n",
       "      <td>14</td>\n",
       "      <td>94</td>\n",
       "      <td>3</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2021-08-02 02:37:24.302431</td>\n",
       "      <td>2021-08-02 02:37:24.341342</td>\n",
       "      <td>00:00:00.038911</td>\n",
       "      <td>1</td>\n",
       "      <td>0.8</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>28</td>\n",
       "      <td>...</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>45</td>\n",
       "      <td>45</td>\n",
       "      <td>119</td>\n",
       "      <td>68</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td>9</td>\n",
       "      <td>9</td>\n",
       "      <td>-7.0</td>\n",
       "      <td>2021-08-02 02:37:24.321769</td>\n",
       "      <td>2021-08-02 02:37:24.358564</td>\n",
       "      <td>00:00:00.036795</td>\n",
       "      <td>1</td>\n",
       "      <td>0.5</td>\n",
       "      <td>2</td>\n",
       "      <td>0</td>\n",
       "      <td>12</td>\n",
       "      <td>...</td>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>3</td>\n",
       "      <td>95</td>\n",
       "      <td>109</td>\n",
       "      <td>2</td>\n",
       "      <td>102</td>\n",
       "      <td>COMPLETE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>10 rows × 22 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   number  value             datetime_start          datetime_complete  \\\n",
       "0       0  -10.0 2021-08-02 02:37:24.161084 2021-08-02 02:37:24.175922   \n",
       "1       1   -7.0 2021-08-02 02:37:24.162363 2021-08-02 02:37:24.231270   \n",
       "2       2   -7.0 2021-08-02 02:37:24.177468 2021-08-02 02:37:24.246080   \n",
       "3       3   -7.0 2021-08-02 02:37:24.231784 2021-08-02 02:37:24.287795   \n",
       "4       4  -10.0 2021-08-02 02:37:24.246859 2021-08-02 02:37:24.259288   \n",
       "5       5   -7.0 2021-08-02 02:37:24.259827 2021-08-02 02:37:24.321232   \n",
       "6       6  -10.0 2021-08-02 02:37:24.288257 2021-08-02 02:37:24.294297   \n",
       "7       7  -10.0 2021-08-02 02:37:24.294732 2021-08-02 02:37:24.301971   \n",
       "8       8   -7.0 2021-08-02 02:37:24.302431 2021-08-02 02:37:24.341342   \n",
       "9       9   -7.0 2021-08-02 02:37:24.321769 2021-08-02 02:37:24.358564   \n",
       "\n",
       "         duration  params_A  params_Amplitude  params_BP Order  params_D  \\\n",
       "0 00:00:00.014838         2               1.0                2         1   \n",
       "1 00:00:00.068907         3               1.0                2         1   \n",
       "2 00:00:00.068612         1               0.8                1         1   \n",
       "3 00:00:00.056011         1               1.0                2         0   \n",
       "4 00:00:00.012429         3               0.5                0         0   \n",
       "5 00:00:00.061405         1               0.5                2         2   \n",
       "6 00:00:00.006040         1               0.5                0         0   \n",
       "7 00:00:00.007239         1               0.5                1         3   \n",
       "8 00:00:00.038911         1               0.8                1         0   \n",
       "9 00:00:00.036795         1               0.5                2         0   \n",
       "\n",
       "   params_High Cut  ...  params_Noise Cloud  params_OSC Type  params_R  \\\n",
       "0               81  ...                   0                0         1   \n",
       "1               20  ...                   1                0         3   \n",
       "2               45  ...                   1                0         3   \n",
       "3               97  ...                   0                0         3   \n",
       "4               99  ...                   0                1         3   \n",
       "5               59  ...                   0                1         3   \n",
       "6              113  ...                   1                2         1   \n",
       "7               70  ...                   0                2         2   \n",
       "8               28  ...                   1                1         0   \n",
       "9               12  ...                   0                2         3   \n",
       "\n",
       "   params_S  params_Start  params_pitch_0  params_pitch_1  params_pitch_2  \\\n",
       "0         1             9              75              85              47   \n",
       "1         0             9              55               1              16   \n",
       "2         1             1              70              77               9   \n",
       "3         0             1              34              92             111   \n",
       "4         1             4              68             103             102   \n",
       "5         3             3              77              98              25   \n",
       "6         1             1             107              33              22   \n",
       "7         2             1              15              14              94   \n",
       "8         1             1              45              45             119   \n",
       "9         3             3              95             109               2   \n",
       "\n",
       "   params_pitch_3     state  \n",
       "0               9  COMPLETE  \n",
       "1              90  COMPLETE  \n",
       "2              54  COMPLETE  \n",
       "3               6  COMPLETE  \n",
       "4              45  COMPLETE  \n",
       "5              92  COMPLETE  \n",
       "6             104  COMPLETE  \n",
       "7               3  COMPLETE  \n",
       "8              68  COMPLETE  \n",
       "9             102  COMPLETE  \n",
       "\n",
       "[10 rows x 22 columns]"
      ]
     },
     "execution_count": 480,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "study.trials_dataframe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "scope = PlotlyScope()\n",
    "fig = plot_slice(study)\n",
    "fig.update_yaxes(showgrid=False,zeroline=False,)\n",
    "with open(\"figs/slice_%s.pdf\"%study_name, \"wb\") as f:\n",
    "    f.write(scope.transform(fig, format=\"pdf\", width=800,height=400,))\n",
    "# figz"
   ]
  }
 ],
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