models/predict_guitar_light.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "import csv   \n",
    "import math\n",
    "import matplotlib.pyplot as plt\n",
    "import datetime\n",
    "\n",
    "import librosa as lr\n",
    "import librosa.display as lrd\n",
    "%matplotlib inline\n",
    "%load_ext rpy2.ipython"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "RESULTS-guitar_light-2018-01-08_22:37.csv\n"
     ]
    }
   ],
   "source": [
    "SPLIT_TRAIN_TEST = .8\n",
    "TARGET_FILE = '../data/guitar_light/guitar_light.csv'\n",
    "SAMPLES_FOLDER = '../data/guitar_light/guitar_light_samples/'\n",
    "FOLDER_PREFIX = 'guitar_light'\n",
    "\n",
    "D = str(datetime.datetime.now())\n",
    "RESULTS_FILE = 'RESULTS-' + FOLDER_PREFIX + '-' + D[:16].replace(' ','_') + '.csv'\n",
    "print RESULTS_FILE\n",
    "\n",
    "HOP_LENGTH = 512\n",
    "N_MFCC = 20\n",
    "\n",
    "N_EPOCHS = 1000\n",
    "BATCH_SIZE = 43\n",
    "VERBOSE = 1\n",
    "VALIDATION = .2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prepares datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "  filter_on_off disto_on_off reverb_on_off flanger_on_off delay_on_off    file\n",
      "0           off          off           off            off          off  s0.wav\n",
      "1           off          off            on            off          off  s1.wav\n",
      "2           off          off           off             on          off  s2.wav\n",
      "3           off          off            on             on          off  s3.wav\n",
      "4            on          off           off            off          off  s4.wav\n",
      "25 6\n",
      "\n",
      "Training data: (25, 6)\n",
      "Test data: (7, 6)\n",
      "\n",
      "0    s0.wav\n",
      "1    s1.wav\n",
      "2    s2.wav\n",
      "3    s3.wav\n",
      "4    s4.wav\n",
      "Name: file, dtype: object\n",
      "25    s25.wav\n",
      "26    s26.wav\n",
      "27    s27.wav\n",
      "28    s28.wav\n",
      "29    s29.wav\n",
      "Name: file, dtype: object\n"
     ]
    }
   ],
   "source": [
    "# Prepares labels\n",
    "Y = pd.read_csv(TARGET_FILE)\n",
    "print Y.head()\n",
    "\n",
    "len_train = int(Y.shape[0]*.8)\n",
    "len_test = int(Y.shape[0]*.2)\n",
    "print len_train, len_test\n",
    "\n",
    "Y_train = Y.iloc[:len_train,:]\n",
    "Y_test = Y.iloc[len_train:,:]\n",
    "print \n",
    "print 'Training data:', Y_train.shape\n",
    "print 'Test data:', Y_test.shape\n",
    "\n",
    "Y_train, files_train =  Y_train.drop('file', axis=1), Y_train['file']\n",
    "Y_test, files_test = Y_test.drop('file', axis=1), Y_test['file']\n",
    "print\n",
    "print files_train[:5]\n",
    "print files_test[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Sampling rate: 22050\n",
      "Loaded testing waveform #0\n",
      "(7, 18522)\n",
      "Loaded training waveform #0\n",
      "(25, 18522)\n"
     ]
    }
   ],
   "source": [
    "# Loads waveforms\n",
    "sampling_rate = lr.load(SAMPLES_FOLDER + files_train[0])[1]\n",
    "print 'Sampling rate:', sampling_rate\n",
    "\n",
    "waveforms_test = []\n",
    "for i, file_name in enumerate(files_test):\n",
    "    if i % 100 == 0:\n",
    "        print 'Loaded testing waveform #' + str(i)\n",
    "    f = SAMPLES_FOLDER + file_name\n",
    "    waveforms_test.append(lr.load(f)[0])\n",
    "X_test = np.stack(waveforms_test)\n",
    "print X_test.shape\n",
    "\n",
    "\n",
    "waveforms_train = []\n",
    "for i, file_name in enumerate(files_train):\n",
    "    if i % 100 == 0:\n",
    "        print 'Loaded training waveform #' + str(i)\n",
    "    f = SAMPLES_FOLDER + file_name\n",
    "    waveforms_train.append(lr.load(f)[0])\n",
    "X_train = np.stack(waveforms_train)\n",
    "print X_train.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Independent models"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Prepares the features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7, 20, 37)\n",
      "(25, 20, 37)\n"
     ]
    }
   ],
   "source": [
    "L_test_mfcc = []\n",
    "for i in range(X_test.shape[0]):\n",
    "    S = X_test[i,:]\n",
    "    mfcc = lr.feature.mfcc(y=S, sr=sampling_rate, hop_length=HOP_LENGTH, n_mfcc=N_MFCC)\n",
    "    L_test_mfcc.append(mfcc)\n",
    "X_test_mfcc = np.stack(L_test_mfcc)\n",
    "print X_test_mfcc.shape\n",
    "\n",
    "L_train_mfcc = []\n",
    "for i in range(X_train.shape[0]):\n",
    "    S = X_train[i,:]\n",
    "    mfcc = lr.feature.mfcc(y=S, sr=sampling_rate, hop_length=HOP_LENGTH, n_mfcc=N_MFCC)\n",
    "    L_train_mfcc.append(mfcc)\n",
    "X_train_mfcc = np.stack(L_train_mfcc)\n",
    "print X_train_mfcc.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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CUj+mMnr6k5I+eYLXrpN03XGm75G0Z5z50GkEAADoyDwlwtBpBAAA6AidRgAAANSwIug0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\n0WkEAABALTqNAAAAqEWnEQAAALX+HzhxjhuLmVHuAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x112ae3310>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(10, 4))\n",
    "lr.display.specshow(X_test_mfcc[0,...], x_axis='time')\n",
    "plt.colorbar()\n",
    "plt.title('MFCC')\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(7, 740)\n",
      "(25, 740)\n"
     ]
    }
   ],
   "source": [
    "X_test_mfcc = np.reshape(X_test_mfcc, (X_test_mfcc.shape[0],-1))\n",
    "X_train_mfcc = np.reshape(X_train_mfcc, (X_train_mfcc.shape[0],-1))\n",
    "print X_test_mfcc.shape\n",
    "print X_train_mfcc.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Predictions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "from sklearn.model_selection import cross_val_score\n",
    "from sklearn.metrics import accuracy_score,mean_absolute_error\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "\n",
    "headers=['algo', 'type', 'algo_instance_reg','algo_instance_class',\n",
    "         'target','metric', 'train_score', 'test_score']\n",
    "with open(RESULTS_FILE, 'w') as f:\n",
    "    writer = csv.writer(f)\n",
    "    writer.writerow(headers)\n",
    "\n",
    "def evaluate_algo(algo_label, grid_reg, grid_class):\n",
    "    results = []\n",
    "    for t_i, t_name in enumerate(list(Y_train)):\n",
    "        print 'predicting feature', t_name\n",
    "        y_train = Y_train[[t_name]].values.flatten()\n",
    "        y_test = Y_test[[t_name]].values.flatten()\n",
    "        print y_train.dtype\n",
    "        \n",
    "        best_params_C = None\n",
    "        best_params_R = None\n",
    "        \n",
    "        try:\n",
    "            # Case 1: classification\n",
    "            if y_train.dtype == 'object':\n",
    "\n",
    "                metric = 'class'\n",
    "\n",
    "                # Cross-Validation Score\n",
    "                grid_class.fit(X_train_mfcc, y_train)\n",
    "                cross_val_scores = grid_class.best_score_\n",
    "                best_params_C = grid_class.best_params_\n",
    "                print cross_val_scores\n",
    "\n",
    "                # Test Score\n",
    "                test_pred = grid_class.predict(X_test_mfcc)\n",
    "                test_score = accuracy_score(test_pred, y_test)\n",
    "                print test_score\n",
    "\n",
    "\n",
    "            # Case 2: regression\n",
    "            elif y_train.dtype == 'float64':\n",
    "\n",
    "                metric = 'reg'\n",
    "\n",
    "                # Cross-Validation Score\n",
    "                grid_reg.fit(X_train_mfcc, y_train)\n",
    "                cross_val_scores = grid_reg.best_score_ * -1\n",
    "                best_params_R = grid_reg.best_params_\n",
    "                print cross_val_scores\n",
    "\n",
    "                # Test Score\n",
    "                test_pred = grid_reg.predict(X_test_mfcc)\n",
    "                test_score = mean_absolute_error(test_pred, y_test)\n",
    "                print test_score\n",
    "\n",
    "            else:\n",
    "                raise ValueError('Wrong Column Type')\n",
    "\n",
    "            out = (algo_label, 'per_output', best_params_R, best_params_C,\n",
    "                   t_name, metric, cross_val_scores, test_score)\n",
    "            print out\n",
    "            with open(RESULTS_FILE, 'a') as f:\n",
    "                writer = csv.writer(f,quoting=csv.QUOTE_NONNUMERIC)\n",
    "                writer.writerow(out)\n",
    "\n",
    "        except:\n",
    "            print \"Unexpected error:\", sys.exc_info()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predicting feature filter_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 4 candidates, totalling 12 fits\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "0.88\n",
      "0.571428571429\n",
      "('kNN', 'per_output', None, {'n_neighbors': 8}, 'filter_on_off', 'class', 0.88, 0.5714285714285714)\n",
      "predicting feature disto_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 4 candidates, totalling 12 fits\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "0.68\n",
      "0.571428571429\n",
      "('kNN', 'per_output', None, {'n_neighbors': 3}, 'disto_on_off', 'class', 0.68000000000000005, 0.5714285714285714)\n",
      "predicting feature reverb_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 4 candidates, totalling 12 fits\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "0.84\n",
      "0.857142857143\n",
      "('kNN', 'per_output', None, {'n_neighbors': 3}, 'reverb_on_off', 'class', 0.83999999999999997, 0.8571428571428571)\n",
      "predicting feature flanger_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 4 candidates, totalling 12 fits\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done  12 out of  12 | elapsed:    0.1s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done  12 out of  12 | elapsed:    0.1s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done  12 out of  12 | elapsed:    0.0s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "0.68\n",
      "0.428571428571\n",
      "('kNN', 'per_output', None, {'n_neighbors': 5}, 'flanger_on_off', 'class', 0.68000000000000005, 0.42857142857142855)\n",
      "predicting feature delay_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 4 candidates, totalling 12 fits\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=3 ...................................................\n",
      "[CV] .................................... n_neighbors=3, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=5 ...................................................\n",
      "[CV] .................................... n_neighbors=5, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=8 ...................................................\n",
      "[CV] .................................... n_neighbors=8, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "[CV] n_neighbors=16 ..................................................\n",
      "[CV] ................................... n_neighbors=16, total=   0.0s\n",
      "0.84\n",
      "0.428571428571\n",
      "('kNN', 'per_output', None, {'n_neighbors': 3}, 'delay_on_off', 'class', 0.83999999999999997, 0.42857142857142855)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done  12 out of  12 | elapsed:    0.1s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done  12 out of  12 | elapsed:    0.1s finished\n"
     ]
    }
   ],
   "source": [
    "from sklearn import neighbors\n",
    "\n",
    "algo_C =neighbors.KNeighborsClassifier()\n",
    "grid_C = GridSearchCV(algo_C, {\"n_neighbors\":[3,5,8,16]}, scoring='accuracy', verbose=2)\n",
    "\n",
    "algo_R =neighbors.KNeighborsRegressor()\n",
    "grid_R = GridSearchCV(algo_R, {\"n_neighbors\":[3,5,8,16]}, scoring='neg_mean_absolute_error', verbose=2)\n",
    "\n",
    "evaluate_algo('kNN', grid_R, grid_C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predicting feature filter_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 7 candidates, totalling 21 fits\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done  21 out of  21 | elapsed:    0.1s finished\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "0.96\n",
      "0.857142857143\n",
      "('Decision Tree', 'per_output', None, {'max_depth': 8}, 'filter_on_off', 'class', 0.95999999999999996, 0.8571428571428571)\n",
      "predicting feature disto_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 7 candidates, totalling 21 fits\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "0.92\n",
      "0.857142857143\n",
      "('Decision Tree', 'per_output', None, {'max_depth': 8}, 'disto_on_off', 'class', 0.92000000000000004, 0.8571428571428571)\n",
      "predicting feature reverb_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 7 candidates, totalling 21 fits\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "0.88\n",
      "0.857142857143\n",
      "('Decision Tree', 'per_output', None, {'max_depth': 4}, 'reverb_on_off', 'class', 0.88, 0.8571428571428571)\n",
      "predicting feature flanger_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 7 candidates, totalling 21 fits\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done  21 out of  21 | elapsed:    0.1s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done  21 out of  21 | elapsed:    0.1s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "0.92\n",
      "0.714285714286\n",
      "('Decision Tree', 'per_output', None, {'max_depth': 2}, 'flanger_on_off', 'class', 0.92000000000000004, 0.7142857142857143)\n",
      "predicting feature delay_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 7 candidates, totalling 21 fits\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=2 .....................................................\n",
      "[CV] ...................................... max_depth=2, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=4 .....................................................\n",
      "[CV] ...................................... max_depth=4, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=8 .....................................................\n",
      "[CV] ...................................... max_depth=8, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=16 ....................................................\n",
      "[CV] ..................................... max_depth=16, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=32 ....................................................\n",
      "[CV] ..................................... max_depth=32, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=64 ....................................................\n",
      "[CV] ..................................... max_depth=64, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "[CV] max_depth=128 ...................................................\n",
      "[CV] .................................... max_depth=128, total=   0.0s\n",
      "0.84\n",
      "0.571428571429\n",
      "('Decision Tree', 'per_output', None, {'max_depth': 4}, 'delay_on_off', 'class', 0.83999999999999997, 0.5714285714285714)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done  21 out of  21 | elapsed:    0.1s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done  21 out of  21 | elapsed:    0.1s finished\n"
     ]
    }
   ],
   "source": [
    "from sklearn import tree\n",
    "\n",
    "algo_C = tree.DecisionTreeClassifier()\n",
    "grid_C = GridSearchCV(algo_C, {\"max_depth\":[2,4,8,16,32,64,128]}, scoring='accuracy', verbose=2)\n",
    "\n",
    "algo_R = tree.DecisionTreeRegressor()\n",
    "grid_R = GridSearchCV(algo_R, {\"max_depth\":[2,4,8,16,32,64,128]}, scoring='neg_mean_absolute_error', verbose=2)\n",
    "\n",
    "evaluate_algo('Decision Tree', grid_R, grid_C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "predicting feature filter_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
      "[CV] strategy=most_frequent ..........................................\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.0s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.0s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.0s finished\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "0.52\n",
      "0.428571428571\n",
      "('Naive', 'per_output', None, {'strategy': 'most_frequent'}, 'filter_on_off', 'class', 0.52000000000000002, 0.42857142857142855)\n",
      "predicting feature disto_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "0.64\n",
      "0.0\n",
      "('Naive', 'per_output', None, {'strategy': 'most_frequent'}, 'disto_on_off', 'class', 0.64000000000000001, 0.0)\n",
      "predicting feature reverb_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "0.52\n",
      "0.428571428571\n",
      "('Naive', 'per_output', None, {'strategy': 'most_frequent'}, 'reverb_on_off', 'class', 0.52000000000000002, 0.42857142857142855)\n",
      "predicting feature flanger_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "0.52\n",
      "0.428571428571\n",
      "('Naive', 'per_output', None, {'strategy': 'most_frequent'}, 'flanger_on_off', 'class', 0.52000000000000002, 0.42857142857142855)\n",
      "predicting feature delay_on_off\n",
      "object\n",
      "Fitting 3 folds for each of 1 candidates, totalling 3 fits\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "[CV] strategy=most_frequent ..........................................\n",
      "[CV] ........................... strategy=most_frequent, total=   0.0s\n",
      "0.64\n",
      "0.0\n",
      "('Naive', 'per_output', None, {'strategy': 'most_frequent'}, 'delay_on_off', 'class', 0.64000000000000001, 0.0)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.0s finished\n",
      "[Parallel(n_jobs=1)]: Done   1 out of   1 | elapsed:    0.0s remaining:    0.0s\n",
      "[Parallel(n_jobs=1)]: Done   3 out of   3 | elapsed:    0.0s finished\n"
     ]
    }
   ],
   "source": [
    "from sklearn import dummy\n",
    "\n",
    "algo_C = dummy.DummyClassifier()\n",
    "grid_C = GridSearchCV(algo_C, {\"strategy\":[\"most_frequent\"]}, scoring='accuracy', verbose=2)\n",
    "\n",
    "algo_R = dummy.DummyRegressor()\n",
    "grid_R = GridSearchCV(algo_R, {\"strategy\":[\"mean\"]}, scoring='neg_mean_absolute_error', verbose=2)\n",
    "\n",
    "evaluate_algo('Naive', grid_R, grid_C)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# from sklearn import svm\n",
    "\n",
    "# algo_R = svm.SVR(kernel='linear')\n",
    "# grid_R = GridSearchCV(algo_R, {'C':[.01, .1, 1.]},\n",
    "#                       scoring='neg_mean_absolute_error', verbose=2,\n",
    "#                      n_jobs =4)\n",
    "\n",
    "# algo_C = svm.SVC(kernel='linear')\n",
    "# grid_C = GridSearchCV(algo_C, {'C':[.01, .1, 1.]},\n",
    "#                       scoring='accuracy', verbose=2,\n",
    "#                       n_jobs =4)\n",
    "\n",
    "\n",
    "# evaluate_algo('SVM_lin', grid_R, grid_C)\n",
    "\n",
    "# algo_R = svm.SVR(kernel='RBF')\n",
    "# grid_R = GridSearchCV(algo_C, {'C':[.01, .1, 1]},\n",
    "#                       scoring='neg_mean_absolute_error', verbose=2)\n",
    "\n",
    "# algo_C = svm.SVC(kernel='RBF')\n",
    "# grid_C = GridSearchCV(algo_C, {'C':[.01, .1, 1]},\n",
    "#                       scoring='accuracy', verbose=2)\n",
    "\n",
    "\n",
    "# evaluate_algo('SVM_RBF', grid_R, grid_C)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Joint modelling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "filter_on_off\n",
      "disto_on_off\n",
      "reverb_on_off\n",
      "flanger_on_off\n",
      "delay_on_off\n",
      "{'filter_on_off': {'char2int': {'on': 1, 'off': 0}, 'int2char': {0: 'off', 1: 'on'}, 'type': dtype('O')}, 'delay_on_off': {'char2int': {'on': 1, 'off': 0}, 'int2char': {0: 'off', 1: 'on'}, 'type': dtype('O')}, 'disto_on_off': {'char2int': {'on': 1, 'off': 0}, 'int2char': {0: 'off', 1: 'on'}, 'type': dtype('O')}, 'flanger_on_off': {'char2int': {'on': 1, 'off': 0}, 'int2char': {0: 'off', 1: 'on'}, 'type': dtype('O')}, 'reverb_on_off': {'char2int': {'on': 1, 'off': 0}, 'int2char': {0: 'off', 1: 'on'}, 'type': dtype('O')}}\n",
      "\n",
      "(25, 37, 20)\n",
      "(7, 37, 20)\n"
     ]
    }
   ],
   "source": [
    "\n",
    "def target_info(df_y):\n",
    "    infos = {}\n",
    "    \n",
    "    for i,name in enumerate(list(df_y)):\n",
    "        print name\n",
    "        \n",
    "        y = df_y[[name]].values.flatten()\n",
    "        infos[name] = {'type':y.dtype}\n",
    "        \n",
    "        if y.dtype=='object':\n",
    "            u_vals = sorted(np.unique(y))\n",
    "            infos[name]['int2char'] = {i:v for i,v in enumerate(u_vals)}\n",
    "            infos[name]['char2int'] = {v:i for i,v in enumerate(u_vals)}\n",
    "            \n",
    "        elif y.dtype=='float64':\n",
    "            infos[name]['mean'] = np.mean(y)\n",
    "            infos[name]['sd'] = np.std(y)\n",
    "        \n",
    "    return infos\n",
    "\n",
    "# Gets target info\n",
    "Y_info = target_info(Y_train)\n",
    "print Y_info\n",
    "\n",
    "# Preps input data\n",
    "X_train_mfcc = X_train_mfcc.reshape([X_train_mfcc.shape[0],N_MFCC,-1]).transpose(0,2,1)\n",
    "X_test_mfcc = X_test_mfcc.reshape([X_test_mfcc.shape[0],N_MFCC,-1]).transpose(0,2,1)\n",
    "\n",
    "\n",
    "print ''\n",
    "print X_train_mfcc.shape\n",
    "print X_test_mfcc.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "def format_output(Y):\n",
    "    out = {}\n",
    "    for name,infos in Y_info.iteritems():\n",
    "        if infos['type'] == 'float64':\n",
    "            y = (Y[name] - infos['mean']) / infos['sd']\n",
    "            \n",
    "        elif infos['type'] == 'object':\n",
    "            char2int = infos['char2int']\n",
    "            y = np.zeros((len(Y[name]), len(char2int)))\n",
    "            for i,yval in enumerate(Y[name]):\n",
    "                y[i, char2int[yval]] = 1\n",
    "                \n",
    "        else:\n",
    "            raise ValueError\n",
    "        \n",
    "        print name, y.shape\n",
    "        out[name] = y\n",
    "    \n",
    "    return out\n",
    "\n",
    "        \n",
    "def test_model(label, params1, params2, model):\n",
    "    \n",
    "    # Prepares input and output data\n",
    "    X_mean = np.mean(X_train_mfcc, axis=(0))\n",
    "    X_sd = np.std(X_train_mfcc, axis=(0))\n",
    "    \n",
    "    X_train = (X_train_mfcc - X_mean) / X_sd\n",
    "    X_test  = (X_test_mfcc - X_mean) / X_sd\n",
    "    \n",
    "    Y_dict_train = format_output(Y_train)\n",
    "    Y_dict_test  = format_output(Y_test)\n",
    "    \n",
    "    # Trains the model\n",
    "    hist = model.fit(X_train, Y_dict_train, \n",
    "              epochs=N_EPOCHS, batch_size=BATCH_SIZE, verbose=VERBOSE,\n",
    "             validation_split = VALIDATION)\n",
    "    \n",
    "    # Makes predictions\n",
    "    pred = model.predict(X_test, batch_size=BATCH_SIZE, verbose=VERBOSE)\n",
    "    \n",
    "    # Gets validation and test scores (for each metric)\n",
    "    Y = {}\n",
    "    for j, Y_pred in enumerate(pred):\n",
    "        t_name = Y_info.keys()[j]\n",
    "        t_infos = Y_info[t_name]\n",
    "        \n",
    "        print t_name\n",
    "        print Y_pred.shape\n",
    "\n",
    "        if t_infos['type'] == 'float64':\n",
    "            test_metric = 'reg'\n",
    "            Y_pred = Y_pred.flatten()\n",
    "            y_pred = Y_pred * t_infos['sd'] + t_infos['mean']\n",
    "            y_pred = y_pred.tolist()\n",
    "            test_score = mean_absolute_error(y_pred, Y_test[t_name])\n",
    "        \n",
    "        elif t_infos['type'] == 'object':\n",
    "            test_metric = 'class'\n",
    "            y_i = np.argmax(Y_pred, axis=1)\n",
    "            y_pred = [t_infos['int2char'][y] for y in y_i]\n",
    "            test_score = accuracy_score(y_pred, Y_test[t_name])\n",
    "\n",
    "        else:\n",
    "            raise ValueError\n",
    "        \n",
    "        #train_scores = hist.history[t_name + '_loss'][-1]\n",
    "        train_scores = -1 * hist.history['loss'][-1]\n",
    "        out = (label, 'joint', params1, params2,\n",
    "               t_name, test_metric, train_scores, test_score)\n",
    "        print out\n",
    "        with open(RESULTS_FILE, 'a') as f:\n",
    "            writer = csv.writer(f,quoting=csv.QUOTE_NONNUMERIC)\n",
    "            writer.writerow(out)\n",
    "\n",
    "        Y[t_name] = y_pred\n",
    "    \n",
    "    Y = pd.DataFrame(Y)\n",
    "    return Y"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_2 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_2 (Flatten)             (None, 740)          0           input_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 8)            5928        flatten_2[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            18          dense_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            18          dense_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            18          dense_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            18          dense_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            18          dense_2[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 6,018\n",
      "Trainable params: 6,018\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 1s 59ms/step - loss: 4.8828 - filter_on_off_loss: 1.7348 - delay_on_off_loss: 0.9725 - disto_on_off_loss: 0.6510 - flanger_on_off_loss: 0.9194 - reverb_on_off_loss: 0.6051 - val_loss: 3.7908 - val_filter_on_off_loss: 0.8688 - val_delay_on_off_loss: 1.0548 - val_disto_on_off_loss: 0.7239 - val_flanger_on_off_loss: 0.6241 - val_reverb_on_off_loss: 0.5192\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 249us/step - loss: 4.1999 - filter_on_off_loss: 1.3780 - delay_on_off_loss: 0.8237 - disto_on_off_loss: 0.5970 - flanger_on_off_loss: 0.8177 - reverb_on_off_loss: 0.5834 - val_loss: 3.7036 - val_filter_on_off_loss: 0.7361 - val_delay_on_off_loss: 1.0249 - val_disto_on_off_loss: 0.7720 - val_flanger_on_off_loss: 0.6269 - val_reverb_on_off_loss: 0.5437\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 225us/step - loss: 3.5020 - filter_on_off_loss: 0.9877 - delay_on_off_loss: 0.6706 - disto_on_off_loss: 0.5397 - flanger_on_off_loss: 0.7248 - reverb_on_off_loss: 0.5792 - val_loss: 3.6529 - val_filter_on_off_loss: 0.6308 - val_delay_on_off_loss: 0.9905 - val_disto_on_off_loss: 0.8172 - val_flanger_on_off_loss: 0.6572 - val_reverb_on_off_loss: 0.5572\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 266us/step - loss: 3.0059 - filter_on_off_loss: 0.6931 - delay_on_off_loss: 0.5701 - disto_on_off_loss: 0.5009 - flanger_on_off_loss: 0.6579 - reverb_on_off_loss: 0.5839 - val_loss: 3.3854 - val_filter_on_off_loss: 0.4948 - val_delay_on_off_loss: 0.8456 - val_disto_on_off_loss: 0.8779 - val_flanger_on_off_loss: 0.5741 - val_reverb_on_off_loss: 0.5930\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 243us/step - loss: 2.6560 - filter_on_off_loss: 0.4934 - delay_on_off_loss: 0.4958 - disto_on_off_loss: 0.4699 - flanger_on_off_loss: 0.6129 - reverb_on_off_loss: 0.5840 - val_loss: 3.1435 - val_filter_on_off_loss: 0.4058 - val_delay_on_off_loss: 0.6932 - val_disto_on_off_loss: 0.9137 - val_flanger_on_off_loss: 0.5042 - val_reverb_on_off_loss: 0.6265\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 250us/step - loss: 2.4507 - filter_on_off_loss: 0.3947 - delay_on_off_loss: 0.4434 - disto_on_off_loss: 0.4497 - flanger_on_off_loss: 0.5884 - reverb_on_off_loss: 0.5745 - val_loss: 2.9095 - val_filter_on_off_loss: 0.3479 - val_delay_on_off_loss: 0.5150 - val_disto_on_off_loss: 0.9390 - val_flanger_on_off_loss: 0.4538 - val_reverb_on_off_loss: 0.6538\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 227us/step - loss: 2.2712 - filter_on_off_loss: 0.3268 - delay_on_off_loss: 0.3948 - disto_on_off_loss: 0.4329 - flanger_on_off_loss: 0.5686 - reverb_on_off_loss: 0.5480 - val_loss: 2.7233 - val_filter_on_off_loss: 0.3119 - val_delay_on_off_loss: 0.3657 - val_disto_on_off_loss: 0.9540 - val_flanger_on_off_loss: 0.4185 - val_reverb_on_off_loss: 0.6733\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 283us/step - loss: 2.1077 - filter_on_off_loss: 0.2806 - delay_on_off_loss: 0.3534 - disto_on_off_loss: 0.4195 - flanger_on_off_loss: 0.5451 - reverb_on_off_loss: 0.5090 - val_loss: 2.5871 - val_filter_on_off_loss: 0.2840 - val_delay_on_off_loss: 0.2637 - val_disto_on_off_loss: 0.9602 - val_flanger_on_off_loss: 0.3946 - val_reverb_on_off_loss: 0.6845\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 276us/step - loss: 1.9596 - filter_on_off_loss: 0.2442 - delay_on_off_loss: 0.3211 - disto_on_off_loss: 0.4100 - flanger_on_off_loss: 0.5172 - reverb_on_off_loss: 0.4670 - val_loss: 2.4141 - val_filter_on_off_loss: 0.2251 - val_delay_on_off_loss: 0.1928 - val_disto_on_off_loss: 0.9360 - val_flanger_on_off_loss: 0.3779 - val_reverb_on_off_loss: 0.6823\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 336us/step - loss: 1.8365 - filter_on_off_loss: 0.2172 - delay_on_off_loss: 0.2951 - disto_on_off_loss: 0.4052 - flanger_on_off_loss: 0.4894 - reverb_on_off_loss: 0.4295 - val_loss: 2.2825 - val_filter_on_off_loss: 0.1906 - val_delay_on_off_loss: 0.1495 - val_disto_on_off_loss: 0.9017 - val_flanger_on_off_loss: 0.3583 - val_reverb_on_off_loss: 0.6825\n",
      "7/7 [==============================] - 0s 10ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 1, 'filter_on_off', 'class', -1.8364888429641724, 0.8571428571428571)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 1, 'delay_on_off', 'class', -1.8364888429641724, 0.7142857142857143)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 1, 'disto_on_off', 'class', -1.8364888429641724, 0.14285714285714285)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 1, 'flanger_on_off', 'class', -1.8364888429641724, 0.8571428571428571)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 1, 'reverb_on_off', 'class', -1.8364888429641724, 1.0)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_3 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_3 (Flatten)             (None, 740)          0           input_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_3 (Dense)                 (None, 16)           11856       flatten_3[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            34          dense_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            34          dense_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            34          dense_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            34          dense_3[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            34          dense_3[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 12,026\n",
      "Trainable params: 12,026\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 1s 67ms/step - loss: 5.0977 - filter_on_off_loss: 0.8153 - delay_on_off_loss: 0.7793 - disto_on_off_loss: 1.3403 - flanger_on_off_loss: 1.0487 - reverb_on_off_loss: 1.1141 - val_loss: 5.5148 - val_filter_on_off_loss: 0.6189 - val_delay_on_off_loss: 1.9382 - val_disto_on_off_loss: 1.4836 - val_flanger_on_off_loss: 0.2621 - val_reverb_on_off_loss: 1.2120\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 473us/step - loss: 4.0641 - filter_on_off_loss: 0.5150 - delay_on_off_loss: 0.5993 - disto_on_off_loss: 1.1656 - flanger_on_off_loss: 0.8535 - reverb_on_off_loss: 0.9307 - val_loss: 5.1275 - val_filter_on_off_loss: 0.3548 - val_delay_on_off_loss: 1.7650 - val_disto_on_off_loss: 1.4816 - val_flanger_on_off_loss: 0.2604 - val_reverb_on_off_loss: 1.2657\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 318us/step - loss: 3.2693 - filter_on_off_loss: 0.3431 - delay_on_off_loss: 0.4397 - disto_on_off_loss: 1.0219 - flanger_on_off_loss: 0.6925 - reverb_on_off_loss: 0.7721 - val_loss: 4.8630 - val_filter_on_off_loss: 0.1978 - val_delay_on_off_loss: 1.6079 - val_disto_on_off_loss: 1.4671 - val_flanger_on_off_loss: 0.2851 - val_reverb_on_off_loss: 1.3051\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 286us/step - loss: 2.6564 - filter_on_off_loss: 0.2441 - delay_on_off_loss: 0.3215 - disto_on_off_loss: 0.9123 - flanger_on_off_loss: 0.5419 - reverb_on_off_loss: 0.6365 - val_loss: 4.6579 - val_filter_on_off_loss: 0.1215 - val_delay_on_off_loss: 1.4508 - val_disto_on_off_loss: 1.4106 - val_flanger_on_off_loss: 0.3399 - val_reverb_on_off_loss: 1.3352\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 256us/step - loss: 2.2086 - filter_on_off_loss: 0.1968 - delay_on_off_loss: 0.2390 - disto_on_off_loss: 0.8138 - flanger_on_off_loss: 0.4342 - reverb_on_off_loss: 0.5249 - val_loss: 4.5269 - val_filter_on_off_loss: 0.0808 - val_delay_on_off_loss: 1.3180 - val_disto_on_off_loss: 1.3377 - val_flanger_on_off_loss: 0.4307 - val_reverb_on_off_loss: 1.3597\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 319us/step - loss: 1.9020 - filter_on_off_loss: 0.1689 - delay_on_off_loss: 0.1859 - disto_on_off_loss: 0.7345 - flanger_on_off_loss: 0.3737 - reverb_on_off_loss: 0.4390 - val_loss: 4.4884 - val_filter_on_off_loss: 0.0559 - val_delay_on_off_loss: 1.2224 - val_disto_on_off_loss: 1.2840 - val_flanger_on_off_loss: 0.5513 - val_reverb_on_off_loss: 1.3749\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 303us/step - loss: 1.6937 - filter_on_off_loss: 0.1543 - delay_on_off_loss: 0.1514 - disto_on_off_loss: 0.6776 - flanger_on_off_loss: 0.3291 - reverb_on_off_loss: 0.3813 - val_loss: 4.5141 - val_filter_on_off_loss: 0.0450 - val_delay_on_off_loss: 1.1182 - val_disto_on_off_loss: 1.2638 - val_flanger_on_off_loss: 0.6600 - val_reverb_on_off_loss: 1.4271\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 291us/step - loss: 1.5189 - filter_on_off_loss: 0.1460 - delay_on_off_loss: 0.1294 - disto_on_off_loss: 0.6199 - flanger_on_off_loss: 0.2912 - reverb_on_off_loss: 0.3323 - val_loss: 4.5403 - val_filter_on_off_loss: 0.0382 - val_delay_on_off_loss: 1.0165 - val_disto_on_off_loss: 1.2579 - val_flanger_on_off_loss: 0.7654 - val_reverb_on_off_loss: 1.4623\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 288us/step - loss: 1.3537 - filter_on_off_loss: 0.1404 - delay_on_off_loss: 0.1119 - disto_on_off_loss: 0.5535 - flanger_on_off_loss: 0.2604 - reverb_on_off_loss: 0.2875 - val_loss: 4.5595 - val_filter_on_off_loss: 0.0336 - val_delay_on_off_loss: 0.9256 - val_disto_on_off_loss: 1.2530 - val_flanger_on_off_loss: 0.8708 - val_reverb_on_off_loss: 1.4765\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 306us/step - loss: 1.2086 - filter_on_off_loss: 0.1286 - delay_on_off_loss: 0.0986 - disto_on_off_loss: 0.4953 - flanger_on_off_loss: 0.2346 - reverb_on_off_loss: 0.2516 - val_loss: 4.5592 - val_filter_on_off_loss: 0.0293 - val_delay_on_off_loss: 0.8460 - val_disto_on_off_loss: 1.2524 - val_flanger_on_off_loss: 0.9543 - val_reverb_on_off_loss: 1.4773\n",
      "7/7 [==============================] - 0s 13ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 1, 'filter_on_off', 'class', -1.2085983753204346, 0.8571428571428571)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 1, 'delay_on_off', 'class', -1.2085983753204346, 0.2857142857142857)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 1, 'disto_on_off', 'class', -1.2085983753204346, 1.0)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 1, 'flanger_on_off', 'class', -1.2085983753204346, 0.7142857142857143)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 1, 'reverb_on_off', 'class', -1.2085983753204346, 0.8571428571428571)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_4 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_4 (Flatten)             (None, 740)          0           input_4[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_4 (Dense)                 (None, 32)           23712       flatten_4[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            66          dense_4[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            66          dense_4[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            66          dense_4[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            66          dense_4[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            66          dense_4[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 24,042\n",
      "Trainable params: 24,042\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 1s 58ms/step - loss: 4.7282 - filter_on_off_loss: 0.7585 - delay_on_off_loss: 0.7943 - disto_on_off_loss: 0.8901 - flanger_on_off_loss: 1.1986 - reverb_on_off_loss: 1.0867 - val_loss: 2.7262 - val_filter_on_off_loss: 0.6257 - val_delay_on_off_loss: 0.2679 - val_disto_on_off_loss: 1.0995 - val_flanger_on_off_loss: 0.4845 - val_reverb_on_off_loss: 0.2486\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 262us/step - loss: 3.3981 - filter_on_off_loss: 0.4675 - delay_on_off_loss: 0.6498 - disto_on_off_loss: 0.6641 - flanger_on_off_loss: 0.8731 - reverb_on_off_loss: 0.7436 - val_loss: 2.5397 - val_filter_on_off_loss: 0.4159 - val_delay_on_off_loss: 0.2465 - val_disto_on_off_loss: 1.2928 - val_flanger_on_off_loss: 0.4201 - val_reverb_on_off_loss: 0.1645\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 233us/step - loss: 2.5040 - filter_on_off_loss: 0.3344 - delay_on_off_loss: 0.5380 - disto_on_off_loss: 0.4906 - flanger_on_off_loss: 0.6338 - reverb_on_off_loss: 0.5072 - val_loss: 2.4420 - val_filter_on_off_loss: 0.2682 - val_delay_on_off_loss: 0.2320 - val_disto_on_off_loss: 1.4433 - val_flanger_on_off_loss: 0.3780 - val_reverb_on_off_loss: 0.1205\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 228us/step - loss: 1.8800 - filter_on_off_loss: 0.2603 - delay_on_off_loss: 0.4269 - disto_on_off_loss: 0.3622 - flanger_on_off_loss: 0.4558 - reverb_on_off_loss: 0.3748 - val_loss: 2.4009 - val_filter_on_off_loss: 0.1697 - val_delay_on_off_loss: 0.2276 - val_disto_on_off_loss: 1.5632 - val_flanger_on_off_loss: 0.3383 - val_reverb_on_off_loss: 0.1021\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 249us/step - loss: 1.4663 - filter_on_off_loss: 0.2152 - delay_on_off_loss: 0.3397 - disto_on_off_loss: 0.2752 - flanger_on_off_loss: 0.3356 - reverb_on_off_loss: 0.3007 - val_loss: 2.3897 - val_filter_on_off_loss: 0.1062 - val_delay_on_off_loss: 0.2297 - val_disto_on_off_loss: 1.6662 - val_flanger_on_off_loss: 0.2896 - val_reverb_on_off_loss: 0.0979\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 224us/step - loss: 1.1884 - filter_on_off_loss: 0.1885 - delay_on_off_loss: 0.2727 - disto_on_off_loss: 0.2203 - flanger_on_off_loss: 0.2572 - reverb_on_off_loss: 0.2499 - val_loss: 2.4853 - val_filter_on_off_loss: 0.0681 - val_delay_on_off_loss: 0.2365 - val_disto_on_off_loss: 1.8172 - val_flanger_on_off_loss: 0.2551 - val_reverb_on_off_loss: 0.1084\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 244us/step - loss: 0.9940 - filter_on_off_loss: 0.1677 - delay_on_off_loss: 0.2242 - disto_on_off_loss: 0.1868 - flanger_on_off_loss: 0.2022 - reverb_on_off_loss: 0.2130 - val_loss: 2.6405 - val_filter_on_off_loss: 0.0462 - val_delay_on_off_loss: 0.2466 - val_disto_on_off_loss: 1.9873 - val_flanger_on_off_loss: 0.2334 - val_reverb_on_off_loss: 0.1271\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 313us/step - loss: 0.8545 - filter_on_off_loss: 0.1509 - delay_on_off_loss: 0.1883 - disto_on_off_loss: 0.1640 - flanger_on_off_loss: 0.1622 - reverb_on_off_loss: 0.1892 - val_loss: 2.7806 - val_filter_on_off_loss: 0.0330 - val_delay_on_off_loss: 0.2552 - val_disto_on_off_loss: 2.1223 - val_flanger_on_off_loss: 0.2200 - val_reverb_on_off_loss: 0.1501\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 241us/step - loss: 0.7485 - filter_on_off_loss: 0.1350 - delay_on_off_loss: 0.1623 - disto_on_off_loss: 0.1465 - flanger_on_off_loss: 0.1342 - reverb_on_off_loss: 0.1706 - val_loss: 2.8808 - val_filter_on_off_loss: 0.0255 - val_delay_on_off_loss: 0.2657 - val_disto_on_off_loss: 2.2106 - val_flanger_on_off_loss: 0.2097 - val_reverb_on_off_loss: 0.1693\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 234us/step - loss: 0.6592 - filter_on_off_loss: 0.1209 - delay_on_off_loss: 0.1408 - disto_on_off_loss: 0.1298 - flanger_on_off_loss: 0.1132 - reverb_on_off_loss: 0.1544 - val_loss: 2.9509 - val_filter_on_off_loss: 0.0214 - val_delay_on_off_loss: 0.2766 - val_disto_on_off_loss: 2.2711 - val_flanger_on_off_loss: 0.2018 - val_reverb_on_off_loss: 0.1800\n",
      "7/7 [==============================] - 0s 16ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 1, 'filter_on_off', 'class', -0.659210205078125, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 1, 'delay_on_off', 'class', -0.659210205078125, 0.0)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 1, 'disto_on_off', 'class', -0.659210205078125, 1.0)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 1, 'flanger_on_off', 'class', -0.659210205078125, 1.0)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 1, 'reverb_on_off', 'class', -0.659210205078125, 0.8571428571428571)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_5 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_5 (Flatten)             (None, 740)          0           input_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_5 (Dense)                 (None, 64)           47424       flatten_5[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            130         dense_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            130         dense_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            130         dense_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            130         dense_5[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            130         dense_5[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 48,074\n",
      "Trainable params: 48,074\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 1s 68ms/step - loss: 4.5987 - filter_on_off_loss: 0.6886 - delay_on_off_loss: 1.0677 - disto_on_off_loss: 0.9406 - flanger_on_off_loss: 1.0395 - reverb_on_off_loss: 0.8623 - val_loss: 5.1037 - val_filter_on_off_loss: 0.7668 - val_delay_on_off_loss: 2.0601 - val_disto_on_off_loss: 0.9163 - val_flanger_on_off_loss: 0.1792 - val_reverb_on_off_loss: 1.1813\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 279us/step - loss: 2.9838 - filter_on_off_loss: 0.4232 - delay_on_off_loss: 0.6715 - disto_on_off_loss: 0.6075 - flanger_on_off_loss: 0.7920 - reverb_on_off_loss: 0.4896 - val_loss: 4.3278 - val_filter_on_off_loss: 0.5267 - val_delay_on_off_loss: 1.6108 - val_disto_on_off_loss: 0.8811 - val_flanger_on_off_loss: 0.1778 - val_reverb_on_off_loss: 1.1314\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 272us/step - loss: 2.0655 - filter_on_off_loss: 0.2826 - delay_on_off_loss: 0.4304 - disto_on_off_loss: 0.4329 - flanger_on_off_loss: 0.6042 - reverb_on_off_loss: 0.3154 - val_loss: 3.6842 - val_filter_on_off_loss: 0.3240 - val_delay_on_off_loss: 1.1819 - val_disto_on_off_loss: 0.8894 - val_flanger_on_off_loss: 0.1866 - val_reverb_on_off_loss: 1.1022\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 324us/step - loss: 1.3602 - filter_on_off_loss: 0.1792 - delay_on_off_loss: 0.2582 - disto_on_off_loss: 0.2826 - flanger_on_off_loss: 0.4295 - reverb_on_off_loss: 0.2108 - val_loss: 3.2879 - val_filter_on_off_loss: 0.2046 - val_delay_on_off_loss: 0.8703 - val_disto_on_off_loss: 0.9297 - val_flanger_on_off_loss: 0.2015 - val_reverb_on_off_loss: 1.0817\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 312us/step - loss: 0.9220 - filter_on_off_loss: 0.1107 - delay_on_off_loss: 0.1648 - disto_on_off_loss: 0.1820 - flanger_on_off_loss: 0.3089 - reverb_on_off_loss: 0.1556 - val_loss: 3.0745 - val_filter_on_off_loss: 0.1330 - val_delay_on_off_loss: 0.6678 - val_disto_on_off_loss: 0.9978 - val_flanger_on_off_loss: 0.2167 - val_reverb_on_off_loss: 1.0592\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 321us/step - loss: 0.6489 - filter_on_off_loss: 0.0676 - delay_on_off_loss: 0.1130 - disto_on_off_loss: 0.1187 - flanger_on_off_loss: 0.2255 - reverb_on_off_loss: 0.1242 - val_loss: 2.9535 - val_filter_on_off_loss: 0.0928 - val_delay_on_off_loss: 0.5501 - val_disto_on_off_loss: 1.0563 - val_flanger_on_off_loss: 0.2287 - val_reverb_on_off_loss: 1.0257\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 311us/step - loss: 0.4823 - filter_on_off_loss: 0.0426 - delay_on_off_loss: 0.0852 - disto_on_off_loss: 0.0842 - flanger_on_off_loss: 0.1667 - reverb_on_off_loss: 0.1036 - val_loss: 2.8861 - val_filter_on_off_loss: 0.0674 - val_delay_on_off_loss: 0.4803 - val_disto_on_off_loss: 1.1057 - val_flanger_on_off_loss: 0.2365 - val_reverb_on_off_loss: 0.9961\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 280us/step - loss: 0.3714 - filter_on_off_loss: 0.0275 - delay_on_off_loss: 0.0672 - disto_on_off_loss: 0.0653 - flanger_on_off_loss: 0.1244 - reverb_on_off_loss: 0.0871 - val_loss: 2.8509 - val_filter_on_off_loss: 0.0509 - val_delay_on_off_loss: 0.4454 - val_disto_on_off_loss: 1.1321 - val_flanger_on_off_loss: 0.2427 - val_reverb_on_off_loss: 0.9798\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 305us/step - loss: 0.2921 - filter_on_off_loss: 0.0186 - delay_on_off_loss: 0.0542 - disto_on_off_loss: 0.0523 - flanger_on_off_loss: 0.0939 - reverb_on_off_loss: 0.0730 - val_loss: 2.8093 - val_filter_on_off_loss: 0.0392 - val_delay_on_off_loss: 0.4267 - val_disto_on_off_loss: 1.1335 - val_flanger_on_off_loss: 0.2492 - val_reverb_on_off_loss: 0.9608\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 272us/step - loss: 0.2327 - filter_on_off_loss: 0.0133 - delay_on_off_loss: 0.0438 - disto_on_off_loss: 0.0427 - flanger_on_off_loss: 0.0721 - reverb_on_off_loss: 0.0608 - val_loss: 2.7687 - val_filter_on_off_loss: 0.0306 - val_delay_on_off_loss: 0.4159 - val_disto_on_off_loss: 1.1233 - val_flanger_on_off_loss: 0.2562 - val_reverb_on_off_loss: 0.9428\n",
      "7/7 [==============================] - 0s 31ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 1, 'filter_on_off', 'class', -0.2327289879322052, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 1, 'delay_on_off', 'class', -0.2327289879322052, 0.2857142857142857)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 1, 'disto_on_off', 'class', -0.2327289879322052, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 1, 'flanger_on_off', 'class', -0.2327289879322052, 1.0)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 1, 'reverb_on_off', 'class', -0.2327289879322052, 1.0)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_6 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_6 (Flatten)             (None, 740)          0           input_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_6 (Dense)                 (None, 8)            5928        flatten_6[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_7 (Dense)                 (None, 8)            72          dense_6[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            18          dense_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            18          dense_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            18          dense_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            18          dense_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            18          dense_7[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 6,090\n",
      "Trainable params: 6,090\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 2s 79ms/step - loss: 3.7707 - filter_on_off_loss: 0.8900 - delay_on_off_loss: 0.6523 - disto_on_off_loss: 0.7248 - flanger_on_off_loss: 0.7000 - reverb_on_off_loss: 0.8036 - val_loss: 3.3016 - val_filter_on_off_loss: 0.6316 - val_delay_on_off_loss: 0.6037 - val_disto_on_off_loss: 0.7341 - val_flanger_on_off_loss: 0.7000 - val_reverb_on_off_loss: 0.6321\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 261us/step - loss: 3.5407 - filter_on_off_loss: 0.7839 - delay_on_off_loss: 0.6336 - disto_on_off_loss: 0.6516 - flanger_on_off_loss: 0.6596 - reverb_on_off_loss: 0.8119 - val_loss: 3.3067 - val_filter_on_off_loss: 0.6272 - val_delay_on_off_loss: 0.6080 - val_disto_on_off_loss: 0.7252 - val_flanger_on_off_loss: 0.7035 - val_reverb_on_off_loss: 0.6428\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 230us/step - loss: 3.3834 - filter_on_off_loss: 0.7188 - delay_on_off_loss: 0.6235 - disto_on_off_loss: 0.6089 - flanger_on_off_loss: 0.6200 - reverb_on_off_loss: 0.8122 - val_loss: 3.3147 - val_filter_on_off_loss: 0.6253 - val_delay_on_off_loss: 0.6128 - val_disto_on_off_loss: 0.7141 - val_flanger_on_off_loss: 0.7145 - val_reverb_on_off_loss: 0.6480\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 257us/step - loss: 3.2608 - filter_on_off_loss: 0.6619 - delay_on_off_loss: 0.6212 - disto_on_off_loss: 0.5885 - flanger_on_off_loss: 0.5872 - reverb_on_off_loss: 0.8020 - val_loss: 3.3028 - val_filter_on_off_loss: 0.6043 - val_delay_on_off_loss: 0.6219 - val_disto_on_off_loss: 0.7080 - val_flanger_on_off_loss: 0.7188 - val_reverb_on_off_loss: 0.6498\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 238us/step - loss: 3.1586 - filter_on_off_loss: 0.6024 - delay_on_off_loss: 0.6118 - disto_on_off_loss: 0.5930 - flanger_on_off_loss: 0.5699 - reverb_on_off_loss: 0.7816 - val_loss: 3.2873 - val_filter_on_off_loss: 0.5816 - val_delay_on_off_loss: 0.6315 - val_disto_on_off_loss: 0.7054 - val_flanger_on_off_loss: 0.7197 - val_reverb_on_off_loss: 0.6490\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 239us/step - loss: 3.0696 - filter_on_off_loss: 0.5539 - delay_on_off_loss: 0.6006 - disto_on_off_loss: 0.5991 - flanger_on_off_loss: 0.5557 - reverb_on_off_loss: 0.7603 - val_loss: 3.2725 - val_filter_on_off_loss: 0.5683 - val_delay_on_off_loss: 0.6341 - val_disto_on_off_loss: 0.6900 - val_flanger_on_off_loss: 0.7327 - val_reverb_on_off_loss: 0.6473\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 259us/step - loss: 2.9999 - filter_on_off_loss: 0.5178 - delay_on_off_loss: 0.5902 - disto_on_off_loss: 0.6054 - flanger_on_off_loss: 0.5467 - reverb_on_off_loss: 0.7398 - val_loss: 3.2566 - val_filter_on_off_loss: 0.5597 - val_delay_on_off_loss: 0.6302 - val_disto_on_off_loss: 0.6610 - val_flanger_on_off_loss: 0.7588 - val_reverb_on_off_loss: 0.6469\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 229us/step - loss: 2.9362 - filter_on_off_loss: 0.4850 - delay_on_off_loss: 0.5762 - disto_on_off_loss: 0.6084 - flanger_on_off_loss: 0.5421 - reverb_on_off_loss: 0.7245 - val_loss: 3.2435 - val_filter_on_off_loss: 0.5486 - val_delay_on_off_loss: 0.6236 - val_disto_on_off_loss: 0.6195 - val_flanger_on_off_loss: 0.8009 - val_reverb_on_off_loss: 0.6508\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 279us/step - loss: 2.8735 - filter_on_off_loss: 0.4575 - delay_on_off_loss: 0.5644 - disto_on_off_loss: 0.6060 - flanger_on_off_loss: 0.5350 - reverb_on_off_loss: 0.7105 - val_loss: 3.2349 - val_filter_on_off_loss: 0.5294 - val_delay_on_off_loss: 0.6203 - val_disto_on_off_loss: 0.5743 - val_flanger_on_off_loss: 0.8525 - val_reverb_on_off_loss: 0.6583\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 254us/step - loss: 2.8132 - filter_on_off_loss: 0.4305 - delay_on_off_loss: 0.5582 - disto_on_off_loss: 0.6019 - flanger_on_off_loss: 0.5259 - reverb_on_off_loss: 0.6968 - val_loss: 3.2342 - val_filter_on_off_loss: 0.5106 - val_delay_on_off_loss: 0.6161 - val_disto_on_off_loss: 0.5264 - val_flanger_on_off_loss: 0.9138 - val_reverb_on_off_loss: 0.6673\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "7/7 [==============================] - 0s 25ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 2, 'filter_on_off', 'class', -2.8132493495941162, 0.2857142857142857)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 2, 'delay_on_off', 'class', -2.8132493495941162, 0.14285714285714285)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 2, 'disto_on_off', 'class', -2.8132493495941162, 0.2857142857142857)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 2, 'flanger_on_off', 'class', -2.8132493495941162, 1.0)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 8, 2, 'reverb_on_off', 'class', -2.8132493495941162, 0.2857142857142857)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_7 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_7 (Flatten)             (None, 740)          0           input_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_8 (Dense)                 (None, 16)           11856       flatten_7[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_9 (Dense)                 (None, 16)           272         dense_8[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            34          dense_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            34          dense_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            34          dense_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            34          dense_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            34          dense_9[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 12,298\n",
      "Trainable params: 12,298\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 2s 91ms/step - loss: 4.0922 - filter_on_off_loss: 0.6978 - delay_on_off_loss: 0.6964 - disto_on_off_loss: 1.0324 - flanger_on_off_loss: 0.8821 - reverb_on_off_loss: 0.7835 - val_loss: 3.5790 - val_filter_on_off_loss: 0.3918 - val_delay_on_off_loss: 0.5650 - val_disto_on_off_loss: 1.3170 - val_flanger_on_off_loss: 0.5095 - val_reverb_on_off_loss: 0.7957\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 380us/step - loss: 3.3077 - filter_on_off_loss: 0.5906 - delay_on_off_loss: 0.5021 - disto_on_off_loss: 0.8811 - flanger_on_off_loss: 0.7615 - reverb_on_off_loss: 0.5725 - val_loss: 3.3675 - val_filter_on_off_loss: 0.3645 - val_delay_on_off_loss: 0.4712 - val_disto_on_off_loss: 1.2232 - val_flanger_on_off_loss: 0.4559 - val_reverb_on_off_loss: 0.8528\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 331us/step - loss: 2.7580 - filter_on_off_loss: 0.5026 - delay_on_off_loss: 0.4043 - disto_on_off_loss: 0.7580 - flanger_on_off_loss: 0.6628 - reverb_on_off_loss: 0.4303 - val_loss: 3.2119 - val_filter_on_off_loss: 0.3332 - val_delay_on_off_loss: 0.3857 - val_disto_on_off_loss: 1.1221 - val_flanger_on_off_loss: 0.3971 - val_reverb_on_off_loss: 0.9738\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 363us/step - loss: 2.4166 - filter_on_off_loss: 0.4379 - delay_on_off_loss: 0.3724 - disto_on_off_loss: 0.6624 - flanger_on_off_loss: 0.6036 - reverb_on_off_loss: 0.3403 - val_loss: 3.1653 - val_filter_on_off_loss: 0.3182 - val_delay_on_off_loss: 0.3475 - val_disto_on_off_loss: 1.0406 - val_flanger_on_off_loss: 0.3637 - val_reverb_on_off_loss: 1.0953\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 298us/step - loss: 2.1694 - filter_on_off_loss: 0.3735 - delay_on_off_loss: 0.3643 - disto_on_off_loss: 0.5917 - flanger_on_off_loss: 0.5549 - reverb_on_off_loss: 0.2851 - val_loss: 3.2230 - val_filter_on_off_loss: 0.3105 - val_delay_on_off_loss: 0.3384 - val_disto_on_off_loss: 1.0027 - val_flanger_on_off_loss: 0.3713 - val_reverb_on_off_loss: 1.2001\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 418us/step - loss: 1.9747 - filter_on_off_loss: 0.3272 - delay_on_off_loss: 0.3539 - disto_on_off_loss: 0.5386 - flanger_on_off_loss: 0.5025 - reverb_on_off_loss: 0.2525 - val_loss: 3.2912 - val_filter_on_off_loss: 0.3002 - val_delay_on_off_loss: 0.3392 - val_disto_on_off_loss: 0.9778 - val_flanger_on_off_loss: 0.3923 - val_reverb_on_off_loss: 1.2815\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 283us/step - loss: 1.7994 - filter_on_off_loss: 0.2854 - delay_on_off_loss: 0.3336 - disto_on_off_loss: 0.4952 - flanger_on_off_loss: 0.4510 - reverb_on_off_loss: 0.2341 - val_loss: 3.3472 - val_filter_on_off_loss: 0.2798 - val_delay_on_off_loss: 0.3413 - val_disto_on_off_loss: 0.9755 - val_flanger_on_off_loss: 0.4258 - val_reverb_on_off_loss: 1.3247\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 356us/step - loss: 1.6521 - filter_on_off_loss: 0.2477 - delay_on_off_loss: 0.3118 - disto_on_off_loss: 0.4656 - flanger_on_off_loss: 0.4036 - reverb_on_off_loss: 0.2233 - val_loss: 3.3944 - val_filter_on_off_loss: 0.2662 - val_delay_on_off_loss: 0.3396 - val_disto_on_off_loss: 0.9707 - val_flanger_on_off_loss: 0.4657 - val_reverb_on_off_loss: 1.3521\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 358us/step - loss: 1.5223 - filter_on_off_loss: 0.2177 - delay_on_off_loss: 0.2854 - disto_on_off_loss: 0.4374 - flanger_on_off_loss: 0.3627 - reverb_on_off_loss: 0.2191 - val_loss: 3.4216 - val_filter_on_off_loss: 0.2566 - val_delay_on_off_loss: 0.3365 - val_disto_on_off_loss: 0.9599 - val_flanger_on_off_loss: 0.5040 - val_reverb_on_off_loss: 1.3646\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 286us/step - loss: 1.4027 - filter_on_off_loss: 0.1943 - delay_on_off_loss: 0.2575 - disto_on_off_loss: 0.4092 - flanger_on_off_loss: 0.3260 - reverb_on_off_loss: 0.2157 - val_loss: 3.4484 - val_filter_on_off_loss: 0.2495 - val_delay_on_off_loss: 0.3346 - val_disto_on_off_loss: 0.9496 - val_flanger_on_off_loss: 0.5368 - val_reverb_on_off_loss: 1.3778\n",
      "7/7 [==============================] - 0s 56ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 2, 'filter_on_off', 'class', -1.4027072191238403, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 2, 'delay_on_off', 'class', -1.4027072191238403, 0.42857142857142855)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 2, 'disto_on_off', 'class', -1.4027072191238403, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 2, 'flanger_on_off', 'class', -1.4027072191238403, 0.5714285714285714)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 16, 2, 'reverb_on_off', 'class', -1.4027072191238403, 1.0)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_8 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_8 (Flatten)             (None, 740)          0           input_8[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_10 (Dense)                (None, 32)           23712       flatten_8[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_11 (Dense)                (None, 32)           1056        dense_10[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            66          dense_11[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            66          dense_11[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            66          dense_11[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            66          dense_11[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            66          dense_11[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 25,098\n",
      "Trainable params: 25,098\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 2s 94ms/step - loss: 5.0408 - filter_on_off_loss: 0.8604 - delay_on_off_loss: 1.6131 - disto_on_off_loss: 0.9296 - flanger_on_off_loss: 0.9000 - reverb_on_off_loss: 0.7377 - val_loss: 2.2808 - val_filter_on_off_loss: 0.3439 - val_delay_on_off_loss: 0.1465 - val_disto_on_off_loss: 0.6230 - val_flanger_on_off_loss: 0.5628 - val_reverb_on_off_loss: 0.6047\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 737us/step - loss: 4.1098 - filter_on_off_loss: 0.6819 - delay_on_off_loss: 1.3071 - disto_on_off_loss: 0.8076 - flanger_on_off_loss: 0.6817 - reverb_on_off_loss: 0.6315 - val_loss: 2.3174 - val_filter_on_off_loss: 0.3058 - val_delay_on_off_loss: 0.1270 - val_disto_on_off_loss: 0.6525 - val_flanger_on_off_loss: 0.6073 - val_reverb_on_off_loss: 0.6247\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 902us/step - loss: 3.5093 - filter_on_off_loss: 0.5805 - delay_on_off_loss: 1.1254 - disto_on_off_loss: 0.7175 - flanger_on_off_loss: 0.5558 - reverb_on_off_loss: 0.5301 - val_loss: 2.3611 - val_filter_on_off_loss: 0.2738 - val_delay_on_off_loss: 0.1100 - val_disto_on_off_loss: 0.6835 - val_flanger_on_off_loss: 0.6694 - val_reverb_on_off_loss: 0.6246\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 424us/step - loss: 3.1144 - filter_on_off_loss: 0.5161 - delay_on_off_loss: 1.0147 - disto_on_off_loss: 0.6495 - flanger_on_off_loss: 0.4887 - reverb_on_off_loss: 0.4453 - val_loss: 2.4167 - val_filter_on_off_loss: 0.2584 - val_delay_on_off_loss: 0.0973 - val_disto_on_off_loss: 0.7349 - val_flanger_on_off_loss: 0.7210 - val_reverb_on_off_loss: 0.6050\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 547us/step - loss: 2.8626 - filter_on_off_loss: 0.4813 - delay_on_off_loss: 0.9477 - disto_on_off_loss: 0.6071 - flanger_on_off_loss: 0.4407 - reverb_on_off_loss: 0.3859 - val_loss: 2.4558 - val_filter_on_off_loss: 0.2456 - val_delay_on_off_loss: 0.0936 - val_disto_on_off_loss: 0.7826 - val_flanger_on_off_loss: 0.7497 - val_reverb_on_off_loss: 0.5844\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 549us/step - loss: 2.6656 - filter_on_off_loss: 0.4597 - delay_on_off_loss: 0.8788 - disto_on_off_loss: 0.5784 - flanger_on_off_loss: 0.3975 - reverb_on_off_loss: 0.3512 - val_loss: 2.4939 - val_filter_on_off_loss: 0.2365 - val_delay_on_off_loss: 0.0885 - val_disto_on_off_loss: 0.8392 - val_flanger_on_off_loss: 0.7574 - val_reverb_on_off_loss: 0.5722\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 373us/step - loss: 2.5023 - filter_on_off_loss: 0.4392 - delay_on_off_loss: 0.8149 - disto_on_off_loss: 0.5502 - flanger_on_off_loss: 0.3697 - reverb_on_off_loss: 0.3282 - val_loss: 2.4884 - val_filter_on_off_loss: 0.2269 - val_delay_on_off_loss: 0.0819 - val_disto_on_off_loss: 0.8897 - val_flanger_on_off_loss: 0.7547 - val_reverb_on_off_loss: 0.5352\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 407us/step - loss: 2.3571 - filter_on_off_loss: 0.4188 - delay_on_off_loss: 0.7530 - disto_on_off_loss: 0.5220 - flanger_on_off_loss: 0.3535 - reverb_on_off_loss: 0.3098 - val_loss: 2.4783 - val_filter_on_off_loss: 0.2203 - val_delay_on_off_loss: 0.0764 - val_disto_on_off_loss: 0.9272 - val_flanger_on_off_loss: 0.7518 - val_reverb_on_off_loss: 0.5026\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 354us/step - loss: 2.2148 - filter_on_off_loss: 0.3991 - delay_on_off_loss: 0.6951 - disto_on_off_loss: 0.4909 - flanger_on_off_loss: 0.3370 - reverb_on_off_loss: 0.2928 - val_loss: 2.4902 - val_filter_on_off_loss: 0.2109 - val_delay_on_off_loss: 0.0726 - val_disto_on_off_loss: 0.9560 - val_flanger_on_off_loss: 0.7781 - val_reverb_on_off_loss: 0.4726\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 286us/step - loss: 2.0907 - filter_on_off_loss: 0.3772 - delay_on_off_loss: 0.6429 - disto_on_off_loss: 0.4637 - flanger_on_off_loss: 0.3237 - reverb_on_off_loss: 0.2831 - val_loss: 2.5050 - val_filter_on_off_loss: 0.1995 - val_delay_on_off_loss: 0.0696 - val_disto_on_off_loss: 0.9815 - val_flanger_on_off_loss: 0.8120 - val_reverb_on_off_loss: 0.4425\n",
      "7/7 [==============================] - 0s 40ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 2, 'filter_on_off', 'class', -2.0906519889831543, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 2, 'delay_on_off', 'class', -2.0906519889831543, 0.8571428571428571)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 2, 'disto_on_off', 'class', -2.0906519889831543, 0.2857142857142857)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 2, 'flanger_on_off', 'class', -2.0906519889831543, 0.8571428571428571)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 32, 2, 'reverb_on_off', 'class', -2.0906519889831543, 0.8571428571428571)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_9 (InputLayer)            (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "flatten_9 (Flatten)             (None, 740)          0           input_9[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "dense_12 (Dense)                (None, 64)           47424       flatten_9[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "dense_13 (Dense)                (None, 64)           4160        dense_12[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            130         dense_13[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            130         dense_13[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            130         dense_13[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            130         dense_13[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            130         dense_13[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 52,234\n",
      "Trainable params: 52,234\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 2s 108ms/step - loss: 4.8155 - filter_on_off_loss: 1.1059 - delay_on_off_loss: 1.1829 - disto_on_off_loss: 0.8043 - flanger_on_off_loss: 0.8576 - reverb_on_off_loss: 0.8648 - val_loss: 2.2388 - val_filter_on_off_loss: 0.2565 - val_delay_on_off_loss: 0.2427 - val_disto_on_off_loss: 0.4009 - val_flanger_on_off_loss: 1.0364 - val_reverb_on_off_loss: 0.3024\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 287us/step - loss: 3.7655 - filter_on_off_loss: 0.8355 - delay_on_off_loss: 0.8874 - disto_on_off_loss: 0.6833 - flanger_on_off_loss: 0.7074 - reverb_on_off_loss: 0.6519 - val_loss: 2.1232 - val_filter_on_off_loss: 0.1745 - val_delay_on_off_loss: 0.2256 - val_disto_on_off_loss: 0.4091 - val_flanger_on_off_loss: 1.0189 - val_reverb_on_off_loss: 0.2951\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 287us/step - loss: 2.7903 - filter_on_off_loss: 0.5698 - delay_on_off_loss: 0.6231 - disto_on_off_loss: 0.5678 - flanger_on_off_loss: 0.5562 - reverb_on_off_loss: 0.4734 - val_loss: 2.0580 - val_filter_on_off_loss: 0.1301 - val_delay_on_off_loss: 0.2222 - val_disto_on_off_loss: 0.4222 - val_flanger_on_off_loss: 1.0068 - val_reverb_on_off_loss: 0.2767\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 266us/step - loss: 2.1657 - filter_on_off_loss: 0.4020 - delay_on_off_loss: 0.4648 - disto_on_off_loss: 0.4835 - flanger_on_off_loss: 0.4544 - reverb_on_off_loss: 0.3610 - val_loss: 2.0075 - val_filter_on_off_loss: 0.0992 - val_delay_on_off_loss: 0.2276 - val_disto_on_off_loss: 0.4171 - val_flanger_on_off_loss: 1.0053 - val_reverb_on_off_loss: 0.2583\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 301us/step - loss: 1.7320 - filter_on_off_loss: 0.2876 - delay_on_off_loss: 0.3681 - disto_on_off_loss: 0.4107 - flanger_on_off_loss: 0.3729 - reverb_on_off_loss: 0.2927 - val_loss: 1.9961 - val_filter_on_off_loss: 0.0729 - val_delay_on_off_loss: 0.2207 - val_disto_on_off_loss: 0.4263 - val_flanger_on_off_loss: 1.0189 - val_reverb_on_off_loss: 0.2572\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 302us/step - loss: 1.4095 - filter_on_off_loss: 0.2119 - delay_on_off_loss: 0.3008 - disto_on_off_loss: 0.3436 - flanger_on_off_loss: 0.3139 - reverb_on_off_loss: 0.2393 - val_loss: 2.0073 - val_filter_on_off_loss: 0.0533 - val_delay_on_off_loss: 0.2129 - val_disto_on_off_loss: 0.4518 - val_flanger_on_off_loss: 1.0377 - val_reverb_on_off_loss: 0.2515\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 281us/step - loss: 1.1427 - filter_on_off_loss: 0.1571 - delay_on_off_loss: 0.2423 - disto_on_off_loss: 0.2827 - flanger_on_off_loss: 0.2642 - reverb_on_off_loss: 0.1965 - val_loss: 2.0481 - val_filter_on_off_loss: 0.0394 - val_delay_on_off_loss: 0.2053 - val_disto_on_off_loss: 0.4873 - val_flanger_on_off_loss: 1.0713 - val_reverb_on_off_loss: 0.2447\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 296us/step - loss: 0.9206 - filter_on_off_loss: 0.1187 - delay_on_off_loss: 0.1934 - disto_on_off_loss: 0.2280 - flanger_on_off_loss: 0.2188 - reverb_on_off_loss: 0.1617 - val_loss: 2.0866 - val_filter_on_off_loss: 0.0302 - val_delay_on_off_loss: 0.2025 - val_disto_on_off_loss: 0.5118 - val_flanger_on_off_loss: 1.1058 - val_reverb_on_off_loss: 0.2363\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 296us/step - loss: 0.7460 - filter_on_off_loss: 0.0911 - delay_on_off_loss: 0.1544 - disto_on_off_loss: 0.1836 - flanger_on_off_loss: 0.1824 - reverb_on_off_loss: 0.1345 - val_loss: 2.1278 - val_filter_on_off_loss: 0.0236 - val_delay_on_off_loss: 0.2057 - val_disto_on_off_loss: 0.5273 - val_flanger_on_off_loss: 1.1463 - val_reverb_on_off_loss: 0.2250\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 267us/step - loss: 0.6062 - filter_on_off_loss: 0.0702 - delay_on_off_loss: 0.1232 - disto_on_off_loss: 0.1472 - flanger_on_off_loss: 0.1531 - reverb_on_off_loss: 0.1125 - val_loss: 2.1929 - val_filter_on_off_loss: 0.0190 - val_delay_on_off_loss: 0.2131 - val_disto_on_off_loss: 0.5385 - val_flanger_on_off_loss: 1.2130 - val_reverb_on_off_loss: 0.2093\n",
      "7/7 [==============================] - 1s 74ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 2, 'filter_on_off', 'class', -0.60618072748184204, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 2, 'delay_on_off', 'class', -0.60618072748184204, 0.14285714285714285)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 2, 'disto_on_off', 'class', -0.60618072748184204, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 2, 'flanger_on_off', 'class', -0.60618072748184204, 0.5714285714285714)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('MLP', 'joint', 64, 2, 'reverb_on_off', 'class', -0.60618072748184204, 1.0)\n"
     ]
    }
   ],
   "source": [
    "# Model 1: 1 layer perceptron\n",
    "from keras.layers import Input, Dense, Flatten\n",
    "from keras.models import Model\n",
    "\n",
    "def MLP(n_hidden_units, n_layers):\n",
    "    # Input layer\n",
    "    in_shape = (X_test_mfcc.shape[1],X_test_mfcc.shape[2])\n",
    "    in_layer = Input(shape=in_shape)\n",
    "    \n",
    "    # Hidden layers\n",
    "    h_layer = Flatten()(in_layer)\n",
    "    for i in range(n_layers):\n",
    "        h_layer = Dense(n_hidden_units, activation='relu')(h_layer)\n",
    "\n",
    "    # Output layers and losses\n",
    "    out_layers = []\n",
    "    losses = {}\n",
    "    metrics = {}\n",
    "    for name,infos in Y_info.iteritems():\n",
    "        \n",
    "        if infos['type'] == 'float64':\n",
    "            out_layer = Dense(1, name=name)(h_layer)\n",
    "            losses[name] = 'mean_absolute_error'\n",
    "            metrics[name] = 'mean_absolute_error'\n",
    "            \n",
    "        elif infos['type'] == 'object':\n",
    "            out_dim = len(infos['char2int'])\n",
    "            out_layer = Dense(out_dim, activation='softmax', name=name)(h_layer)\n",
    "            losses[name] = 'categorical_crossentropy'\n",
    "            metrics[name] = 'accuracy'\n",
    "\n",
    "        else:\n",
    "            raise ValueError\n",
    "        out_layers.append(out_layer)\n",
    "\n",
    "    model = Model(inputs = in_layer, outputs = out_layers)\n",
    "    model.compile(loss=losses, optimizer='adam')\n",
    "    \n",
    "    print model.summary()\n",
    "    return model\n",
    "\n",
    "for N_LAYERS in [1,2]:\n",
    "    for N_UNITS in [8,16,32,64]:\n",
    "        model = MLP(N_UNITS, N_LAYERS)\n",
    "        out = test_model('MLP', N_UNITS, N_LAYERS, model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_10 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_1 (LSTM)                   (None, 8)            928         input_10[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            18          lstm_1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            18          lstm_1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            18          lstm_1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            18          lstm_1[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            18          lstm_1[0][0]                     \n",
      "==================================================================================================\n",
      "Total params: 1,018\n",
      "Trainable params: 1,018\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 3s 144ms/step - loss: 3.5879 - filter_on_off_loss: 0.6734 - delay_on_off_loss: 0.7377 - disto_on_off_loss: 0.6833 - flanger_on_off_loss: 0.6865 - reverb_on_off_loss: 0.8070 - val_loss: 3.7678 - val_filter_on_off_loss: 0.7441 - val_delay_on_off_loss: 0.9233 - val_disto_on_off_loss: 0.8022 - val_flanger_on_off_loss: 0.5001 - val_reverb_on_off_loss: 0.7981\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.5633 - filter_on_off_loss: 0.6679 - delay_on_off_loss: 0.7276 - disto_on_off_loss: 0.6813 - flanger_on_off_loss: 0.6840 - reverb_on_off_loss: 0.8026 - val_loss: 3.7542 - val_filter_on_off_loss: 0.7406 - val_delay_on_off_loss: 0.9176 - val_disto_on_off_loss: 0.8009 - val_flanger_on_off_loss: 0.5018 - val_reverb_on_off_loss: 0.7933\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.5390 - filter_on_off_loss: 0.6623 - delay_on_off_loss: 0.7175 - disto_on_off_loss: 0.6793 - flanger_on_off_loss: 0.6816 - reverb_on_off_loss: 0.7983 - val_loss: 3.7410 - val_filter_on_off_loss: 0.7373 - val_delay_on_off_loss: 0.9119 - val_disto_on_off_loss: 0.7996 - val_flanger_on_off_loss: 0.5036 - val_reverb_on_off_loss: 0.7886\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.5149 - filter_on_off_loss: 0.6568 - delay_on_off_loss: 0.7076 - disto_on_off_loss: 0.6773 - flanger_on_off_loss: 0.6792 - reverb_on_off_loss: 0.7940 - val_loss: 3.7279 - val_filter_on_off_loss: 0.7339 - val_delay_on_off_loss: 0.9064 - val_disto_on_off_loss: 0.7982 - val_flanger_on_off_loss: 0.5054 - val_reverb_on_off_loss: 0.7839\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.4909 - filter_on_off_loss: 0.6513 - delay_on_off_loss: 0.6978 - disto_on_off_loss: 0.6752 - flanger_on_off_loss: 0.6769 - reverb_on_off_loss: 0.7897 - val_loss: 3.7151 - val_filter_on_off_loss: 0.7306 - val_delay_on_off_loss: 0.9011 - val_disto_on_off_loss: 0.7968 - val_flanger_on_off_loss: 0.5073 - val_reverb_on_off_loss: 0.7793\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.4672 - filter_on_off_loss: 0.6458 - delay_on_off_loss: 0.6881 - disto_on_off_loss: 0.6732 - flanger_on_off_loss: 0.6746 - reverb_on_off_loss: 0.7855 - val_loss: 3.7025 - val_filter_on_off_loss: 0.7275 - val_delay_on_off_loss: 0.8958 - val_disto_on_off_loss: 0.7954 - val_flanger_on_off_loss: 0.5091 - val_reverb_on_off_loss: 0.7747\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.4437 - filter_on_off_loss: 0.6403 - delay_on_off_loss: 0.6785 - disto_on_off_loss: 0.6711 - flanger_on_off_loss: 0.6724 - reverb_on_off_loss: 0.7813 - val_loss: 3.6901 - val_filter_on_off_loss: 0.7244 - val_delay_on_off_loss: 0.8905 - val_disto_on_off_loss: 0.7940 - val_flanger_on_off_loss: 0.5110 - val_reverb_on_off_loss: 0.7702\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.4205 - filter_on_off_loss: 0.6349 - delay_on_off_loss: 0.6690 - disto_on_off_loss: 0.6690 - flanger_on_off_loss: 0.6703 - reverb_on_off_loss: 0.7772 - val_loss: 3.6780 - val_filter_on_off_loss: 0.7214 - val_delay_on_off_loss: 0.8853 - val_disto_on_off_loss: 0.7927 - val_flanger_on_off_loss: 0.5128 - val_reverb_on_off_loss: 0.7657\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.3975 - filter_on_off_loss: 0.6295 - delay_on_off_loss: 0.6597 - disto_on_off_loss: 0.6670 - flanger_on_off_loss: 0.6682 - reverb_on_off_loss: 0.7732 - val_loss: 3.6661 - val_filter_on_off_loss: 0.7186 - val_delay_on_off_loss: 0.8801 - val_disto_on_off_loss: 0.7914 - val_flanger_on_off_loss: 0.5147 - val_reverb_on_off_loss: 0.7613\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.3748 - filter_on_off_loss: 0.6241 - delay_on_off_loss: 0.6505 - disto_on_off_loss: 0.6649 - flanger_on_off_loss: 0.6661 - reverb_on_off_loss: 0.7692 - val_loss: 3.6545 - val_filter_on_off_loss: 0.7159 - val_delay_on_off_loss: 0.8750 - val_disto_on_off_loss: 0.7902 - val_flanger_on_off_loss: 0.5165 - val_reverb_on_off_loss: 0.7569\n",
      "7/7 [==============================] - 1s 75ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 1, 'filter_on_off', 'class', -3.3747553825378418, 0.42857142857142855)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 1, 'delay_on_off', 'class', -3.3747553825378418, 0.42857142857142855)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 1, 'disto_on_off', 'class', -3.3747553825378418, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 1, 'flanger_on_off', 'class', -3.3747553825378418, 0.42857142857142855)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 1, 'reverb_on_off', 'class', -3.3747553825378418, 0.42857142857142855)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_11 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_2 (LSTM)                   (None, 16)           2368        input_11[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            34          lstm_2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            34          lstm_2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            34          lstm_2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            34          lstm_2[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            34          lstm_2[0][0]                     \n",
      "==================================================================================================\n",
      "Total params: 2,538\n",
      "Trainable params: 2,538\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 2s 110ms/step - loss: 3.6807 - filter_on_off_loss: 0.6992 - delay_on_off_loss: 0.8748 - disto_on_off_loss: 0.6897 - flanger_on_off_loss: 0.6194 - reverb_on_off_loss: 0.7976 - val_loss: 3.2084 - val_filter_on_off_loss: 0.4571 - val_delay_on_off_loss: 0.7775 - val_disto_on_off_loss: 0.6147 - val_flanger_on_off_loss: 0.6248 - val_reverb_on_off_loss: 0.7344\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.6456 - filter_on_off_loss: 0.6918 - delay_on_off_loss: 0.8593 - disto_on_off_loss: 0.6851 - flanger_on_off_loss: 0.6164 - reverb_on_off_loss: 0.7930 - val_loss: 3.1913 - val_filter_on_off_loss: 0.4516 - val_delay_on_off_loss: 0.7689 - val_disto_on_off_loss: 0.6087 - val_flanger_on_off_loss: 0.6307 - val_reverb_on_off_loss: 0.7315\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.5993 - filter_on_off_loss: 0.6823 - delay_on_off_loss: 0.8390 - disto_on_off_loss: 0.6789 - flanger_on_off_loss: 0.6124 - reverb_on_off_loss: 0.7867 - val_loss: 3.1751 - val_filter_on_off_loss: 0.4462 - val_delay_on_off_loss: 0.7606 - val_disto_on_off_loss: 0.6029 - val_flanger_on_off_loss: 0.6365 - val_reverb_on_off_loss: 0.7288\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.5541 - filter_on_off_loss: 0.6735 - delay_on_off_loss: 0.8192 - disto_on_off_loss: 0.6729 - flanger_on_off_loss: 0.6082 - reverb_on_off_loss: 0.7803 - val_loss: 3.1596 - val_filter_on_off_loss: 0.4409 - val_delay_on_off_loss: 0.7526 - val_disto_on_off_loss: 0.5974 - val_flanger_on_off_loss: 0.6423 - val_reverb_on_off_loss: 0.7264\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.5101 - filter_on_off_loss: 0.6652 - delay_on_off_loss: 0.8001 - disto_on_off_loss: 0.6670 - flanger_on_off_loss: 0.6038 - reverb_on_off_loss: 0.7739 - val_loss: 3.1450 - val_filter_on_off_loss: 0.4358 - val_delay_on_off_loss: 0.7450 - val_disto_on_off_loss: 0.5921 - val_flanger_on_off_loss: 0.6478 - val_reverb_on_off_loss: 0.7244\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.4671 - filter_on_off_loss: 0.6573 - delay_on_off_loss: 0.7817 - disto_on_off_loss: 0.6612 - flanger_on_off_loss: 0.5993 - reverb_on_off_loss: 0.7675 - val_loss: 3.1312 - val_filter_on_off_loss: 0.4307 - val_delay_on_off_loss: 0.7376 - val_disto_on_off_loss: 0.5870 - val_flanger_on_off_loss: 0.6532 - val_reverb_on_off_loss: 0.7226\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.4251 - filter_on_off_loss: 0.6498 - delay_on_off_loss: 0.7639 - disto_on_off_loss: 0.6555 - flanger_on_off_loss: 0.5947 - reverb_on_off_loss: 0.7611 - val_loss: 3.1180 - val_filter_on_off_loss: 0.4257 - val_delay_on_off_loss: 0.7305 - val_disto_on_off_loss: 0.5821 - val_flanger_on_off_loss: 0.6584 - val_reverb_on_off_loss: 0.7212\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.3841 - filter_on_off_loss: 0.6427 - delay_on_off_loss: 0.7469 - disto_on_off_loss: 0.6498 - flanger_on_off_loss: 0.5901 - reverb_on_off_loss: 0.7547 - val_loss: 3.1053 - val_filter_on_off_loss: 0.4207 - val_delay_on_off_loss: 0.7236 - val_disto_on_off_loss: 0.5773 - val_flanger_on_off_loss: 0.6635 - val_reverb_on_off_loss: 0.7201\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.3442 - filter_on_off_loss: 0.6358 - delay_on_off_loss: 0.7305 - disto_on_off_loss: 0.6443 - flanger_on_off_loss: 0.5854 - reverb_on_off_loss: 0.7482 - val_loss: 3.0930 - val_filter_on_off_loss: 0.4158 - val_delay_on_off_loss: 0.7169 - val_disto_on_off_loss: 0.5726 - val_flanger_on_off_loss: 0.6685 - val_reverb_on_off_loss: 0.7192\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.3052 - filter_on_off_loss: 0.6292 - delay_on_off_loss: 0.7147 - disto_on_off_loss: 0.6388 - flanger_on_off_loss: 0.5807 - reverb_on_off_loss: 0.7418 - val_loss: 3.0811 - val_filter_on_off_loss: 0.4109 - val_delay_on_off_loss: 0.7102 - val_disto_on_off_loss: 0.5681 - val_flanger_on_off_loss: 0.6733 - val_reverb_on_off_loss: 0.7185\n",
      "7/7 [==============================] - 0s 61ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 1, 'filter_on_off', 'class', -3.3052177429199219, 0.5714285714285714)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 1, 'delay_on_off', 'class', -3.3052177429199219, 0.2857142857142857)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 1, 'disto_on_off', 'class', -3.3052177429199219, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 1, 'flanger_on_off', 'class', -3.3052177429199219, 0.5714285714285714)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 1, 'reverb_on_off', 'class', -3.3052177429199219, 0.42857142857142855)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_12 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_3 (LSTM)                   (None, 32)           6784        input_12[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            66          lstm_3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            66          lstm_3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            66          lstm_3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            66          lstm_3[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            66          lstm_3[0][0]                     \n",
      "==================================================================================================\n",
      "Total params: 7,114\n",
      "Trainable params: 7,114\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 3s 120ms/step - loss: 3.7591 - filter_on_off_loss: 0.6721 - delay_on_off_loss: 0.8245 - disto_on_off_loss: 0.7557 - flanger_on_off_loss: 0.7500 - reverb_on_off_loss: 0.7568 - val_loss: 3.7323 - val_filter_on_off_loss: 0.6679 - val_delay_on_off_loss: 1.0624 - val_disto_on_off_loss: 0.6672 - val_flanger_on_off_loss: 0.7400 - val_reverb_on_off_loss: 0.5949\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.6833 - filter_on_off_loss: 0.6579 - delay_on_off_loss: 0.7989 - disto_on_off_loss: 0.7425 - flanger_on_off_loss: 0.7421 - reverb_on_off_loss: 0.7419 - val_loss: 3.7159 - val_filter_on_off_loss: 0.6619 - val_delay_on_off_loss: 1.0481 - val_disto_on_off_loss: 0.6664 - val_flanger_on_off_loss: 0.7432 - val_reverb_on_off_loss: 0.5963\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.6095 - filter_on_off_loss: 0.6439 - delay_on_off_loss: 0.7743 - disto_on_off_loss: 0.7295 - flanger_on_off_loss: 0.7344 - reverb_on_off_loss: 0.7274 - val_loss: 3.7000 - val_filter_on_off_loss: 0.6558 - val_delay_on_off_loss: 1.0343 - val_disto_on_off_loss: 0.6656 - val_flanger_on_off_loss: 0.7464 - val_reverb_on_off_loss: 0.5978\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.5376 - filter_on_off_loss: 0.6300 - delay_on_off_loss: 0.7506 - disto_on_off_loss: 0.7169 - flanger_on_off_loss: 0.7269 - reverb_on_off_loss: 0.7133 - val_loss: 3.6845 - val_filter_on_off_loss: 0.6496 - val_delay_on_off_loss: 1.0209 - val_disto_on_off_loss: 0.6647 - val_flanger_on_off_loss: 0.7499 - val_reverb_on_off_loss: 0.5994\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.4677 - filter_on_off_loss: 0.6162 - delay_on_off_loss: 0.7278 - disto_on_off_loss: 0.7046 - flanger_on_off_loss: 0.7194 - reverb_on_off_loss: 0.6996 - val_loss: 3.6694 - val_filter_on_off_loss: 0.6434 - val_delay_on_off_loss: 1.0076 - val_disto_on_off_loss: 0.6639 - val_flanger_on_off_loss: 0.7534 - val_reverb_on_off_loss: 0.6011\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.3995 - filter_on_off_loss: 0.6026 - delay_on_off_loss: 0.7059 - disto_on_off_loss: 0.6927 - flanger_on_off_loss: 0.7120 - reverb_on_off_loss: 0.6864 - val_loss: 3.6546 - val_filter_on_off_loss: 0.6371 - val_delay_on_off_loss: 0.9946 - val_disto_on_off_loss: 0.6629 - val_flanger_on_off_loss: 0.7571 - val_reverb_on_off_loss: 0.6028\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.3333 - filter_on_off_loss: 0.5891 - delay_on_off_loss: 0.6849 - disto_on_off_loss: 0.6810 - flanger_on_off_loss: 0.7047 - reverb_on_off_loss: 0.6736 - val_loss: 3.6400 - val_filter_on_off_loss: 0.6308 - val_delay_on_off_loss: 0.9818 - val_disto_on_off_loss: 0.6619 - val_flanger_on_off_loss: 0.7610 - val_reverb_on_off_loss: 0.6046\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.2688 - filter_on_off_loss: 0.5757 - delay_on_off_loss: 0.6649 - disto_on_off_loss: 0.6696 - flanger_on_off_loss: 0.6974 - reverb_on_off_loss: 0.6611 - val_loss: 3.6257 - val_filter_on_off_loss: 0.6246 - val_delay_on_off_loss: 0.9691 - val_disto_on_off_loss: 0.6607 - val_flanger_on_off_loss: 0.7649 - val_reverb_on_off_loss: 0.6063\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.2061 - filter_on_off_loss: 0.5625 - delay_on_off_loss: 0.6458 - disto_on_off_loss: 0.6585 - flanger_on_off_loss: 0.6901 - reverb_on_off_loss: 0.6491 - val_loss: 3.6114 - val_filter_on_off_loss: 0.6184 - val_delay_on_off_loss: 0.9567 - val_disto_on_off_loss: 0.6594 - val_flanger_on_off_loss: 0.7689 - val_reverb_on_off_loss: 0.6080\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.1450 - filter_on_off_loss: 0.5495 - delay_on_off_loss: 0.6276 - disto_on_off_loss: 0.6476 - flanger_on_off_loss: 0.6829 - reverb_on_off_loss: 0.6375 - val_loss: 3.5974 - val_filter_on_off_loss: 0.6123 - val_delay_on_off_loss: 0.9446 - val_disto_on_off_loss: 0.6579 - val_flanger_on_off_loss: 0.7729 - val_reverb_on_off_loss: 0.6096\n",
      "7/7 [==============================] - 0s 68ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 1, 'filter_on_off', 'class', -3.1450347900390625, 0.7142857142857143)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 1, 'delay_on_off', 'class', -3.1450347900390625, 0.7142857142857143)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 1, 'disto_on_off', 'class', -3.1450347900390625, 0.5714285714285714)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 1, 'flanger_on_off', 'class', -3.1450347900390625, 0.42857142857142855)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 1, 'reverb_on_off', 'class', -3.1450347900390625, 0.5714285714285714)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_13 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_4 (LSTM)                   (None, 64)           21760       input_13[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            130         lstm_4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            130         lstm_4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            130         lstm_4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            130         lstm_4[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            130         lstm_4[0][0]                     \n",
      "==================================================================================================\n",
      "Total params: 22,410\n",
      "Trainable params: 22,410\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 4s 163ms/step - loss: 3.4223 - filter_on_off_loss: 0.6709 - delay_on_off_loss: 0.6885 - disto_on_off_loss: 0.6790 - flanger_on_off_loss: 0.7224 - reverb_on_off_loss: 0.6614 - val_loss: 3.3728 - val_filter_on_off_loss: 0.5249 - val_delay_on_off_loss: 0.7243 - val_disto_on_off_loss: 0.7746 - val_flanger_on_off_loss: 0.7124 - val_reverb_on_off_loss: 0.6365\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.2961 - filter_on_off_loss: 0.6402 - delay_on_off_loss: 0.6569 - disto_on_off_loss: 0.6545 - flanger_on_off_loss: 0.7113 - reverb_on_off_loss: 0.6333 - val_loss: 3.3405 - val_filter_on_off_loss: 0.5109 - val_delay_on_off_loss: 0.7102 - val_disto_on_off_loss: 0.7712 - val_flanger_on_off_loss: 0.7167 - val_reverb_on_off_loss: 0.6317\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 3.1750 - filter_on_off_loss: 0.6106 - delay_on_off_loss: 0.6264 - disto_on_off_loss: 0.6311 - flanger_on_off_loss: 0.7003 - reverb_on_off_loss: 0.6065 - val_loss: 3.3106 - val_filter_on_off_loss: 0.4973 - val_delay_on_off_loss: 0.6965 - val_disto_on_off_loss: 0.7683 - val_flanger_on_off_loss: 0.7214 - val_reverb_on_off_loss: 0.6271\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.0586 - filter_on_off_loss: 0.5821 - delay_on_off_loss: 0.5973 - disto_on_off_loss: 0.6086 - flanger_on_off_loss: 0.6895 - reverb_on_off_loss: 0.5810 - val_loss: 3.2829 - val_filter_on_off_loss: 0.4841 - val_delay_on_off_loss: 0.6832 - val_disto_on_off_loss: 0.7660 - val_flanger_on_off_loss: 0.7268 - val_reverb_on_off_loss: 0.6229\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 2.9469 - filter_on_off_loss: 0.5546 - delay_on_off_loss: 0.5695 - disto_on_off_loss: 0.5870 - flanger_on_off_loss: 0.6789 - reverb_on_off_loss: 0.5569 - val_loss: 3.2574 - val_filter_on_off_loss: 0.4713 - val_delay_on_off_loss: 0.6703 - val_disto_on_off_loss: 0.7641 - val_flanger_on_off_loss: 0.7327 - val_reverb_on_off_loss: 0.6190\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 2.8398 - filter_on_off_loss: 0.5280 - delay_on_off_loss: 0.5429 - disto_on_off_loss: 0.5662 - flanger_on_off_loss: 0.6684 - reverb_on_off_loss: 0.5342 - val_loss: 3.2341 - val_filter_on_off_loss: 0.4590 - val_delay_on_off_loss: 0.6579 - val_disto_on_off_loss: 0.7626 - val_flanger_on_off_loss: 0.7393 - val_reverb_on_off_loss: 0.6154\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 2.7368 - filter_on_off_loss: 0.5024 - delay_on_off_loss: 0.5175 - disto_on_off_loss: 0.5461 - flanger_on_off_loss: 0.6581 - reverb_on_off_loss: 0.5127 - val_loss: 3.2127 - val_filter_on_off_loss: 0.4470 - val_delay_on_off_loss: 0.6460 - val_disto_on_off_loss: 0.7613 - val_flanger_on_off_loss: 0.7463 - val_reverb_on_off_loss: 0.6120\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 2.6380 - filter_on_off_loss: 0.4776 - delay_on_off_loss: 0.4932 - disto_on_off_loss: 0.5267 - flanger_on_off_loss: 0.6479 - reverb_on_off_loss: 0.4925 - val_loss: 3.1930 - val_filter_on_off_loss: 0.4355 - val_delay_on_off_loss: 0.6343 - val_disto_on_off_loss: 0.7603 - val_flanger_on_off_loss: 0.7540 - val_reverb_on_off_loss: 0.6089\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 2.5431 - filter_on_off_loss: 0.4537 - delay_on_off_loss: 0.4700 - disto_on_off_loss: 0.5080 - flanger_on_off_loss: 0.6379 - reverb_on_off_loss: 0.4734 - val_loss: 3.1751 - val_filter_on_off_loss: 0.4243 - val_delay_on_off_loss: 0.6230 - val_disto_on_off_loss: 0.7594 - val_flanger_on_off_loss: 0.7623 - val_reverb_on_off_loss: 0.6060\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 2ms/step - loss: 2.4519 - filter_on_off_loss: 0.4307 - delay_on_off_loss: 0.4478 - disto_on_off_loss: 0.4899 - flanger_on_off_loss: 0.6280 - reverb_on_off_loss: 0.4554 - val_loss: 3.1589 - val_filter_on_off_loss: 0.4137 - val_delay_on_off_loss: 0.6119 - val_disto_on_off_loss: 0.7587 - val_flanger_on_off_loss: 0.7713 - val_reverb_on_off_loss: 0.6033\n",
      "7/7 [==============================] - 1s 80ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 1, 'filter_on_off', 'class', -2.45186448097229, 0.8571428571428571)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 1, 'delay_on_off', 'class', -2.45186448097229, 0.7142857142857143)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 1, 'disto_on_off', 'class', -2.45186448097229, 0.2857142857142857)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 1, 'flanger_on_off', 'class', -2.45186448097229, 0.7142857142857143)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 1, 'reverb_on_off', 'class', -2.45186448097229, 1.0)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_14 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_5 (LSTM)                   (None, 128)          76288       input_14[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            258         lstm_5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            258         lstm_5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            258         lstm_5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            258         lstm_5[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            258         lstm_5[0][0]                     \n",
      "==================================================================================================\n",
      "Total params: 77,578\n",
      "Trainable params: 77,578\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 4s 171ms/step - loss: 3.5283 - filter_on_off_loss: 0.6976 - delay_on_off_loss: 0.7931 - disto_on_off_loss: 0.6939 - flanger_on_off_loss: 0.6589 - reverb_on_off_loss: 0.6848 - val_loss: 3.3145 - val_filter_on_off_loss: 0.6823 - val_delay_on_off_loss: 0.6859 - val_disto_on_off_loss: 0.5069 - val_flanger_on_off_loss: 0.6722 - val_reverb_on_off_loss: 0.7674\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.2875 - filter_on_off_loss: 0.6355 - delay_on_off_loss: 0.7200 - disto_on_off_loss: 0.6532 - flanger_on_off_loss: 0.6407 - reverb_on_off_loss: 0.6381 - val_loss: 3.2229 - val_filter_on_off_loss: 0.6373 - val_delay_on_off_loss: 0.6323 - val_disto_on_off_loss: 0.5100 - val_flanger_on_off_loss: 0.6869 - val_reverb_on_off_loss: 0.7565\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.0633 - filter_on_off_loss: 0.5770 - delay_on_off_loss: 0.6536 - disto_on_off_loss: 0.6142 - flanger_on_off_loss: 0.6229 - reverb_on_off_loss: 0.5956 - val_loss: 3.1387 - val_filter_on_off_loss: 0.5944 - val_delay_on_off_loss: 0.5826 - val_disto_on_off_loss: 0.5134 - val_flanger_on_off_loss: 0.7023 - val_reverb_on_off_loss: 0.7460\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 2.8538 - filter_on_off_loss: 0.5215 - delay_on_off_loss: 0.5933 - disto_on_off_loss: 0.5764 - flanger_on_off_loss: 0.6056 - reverb_on_off_loss: 0.5570 - val_loss: 3.0618 - val_filter_on_off_loss: 0.5534 - val_delay_on_off_loss: 0.5364 - val_disto_on_off_loss: 0.5172 - val_flanger_on_off_loss: 0.7188 - val_reverb_on_off_loss: 0.7360\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 2.6573 - filter_on_off_loss: 0.4687 - delay_on_off_loss: 0.5385 - disto_on_off_loss: 0.5396 - flanger_on_off_loss: 0.5886 - reverb_on_off_loss: 0.5220 - val_loss: 2.9922 - val_filter_on_off_loss: 0.5142 - val_delay_on_off_loss: 0.4934 - val_disto_on_off_loss: 0.5215 - val_flanger_on_off_loss: 0.7366 - val_reverb_on_off_loss: 0.7266\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 2.4726 - filter_on_off_loss: 0.4183 - delay_on_off_loss: 0.4888 - disto_on_off_loss: 0.5035 - flanger_on_off_loss: 0.5720 - reverb_on_off_loss: 0.4900 - val_loss: 2.9302 - val_filter_on_off_loss: 0.4769 - val_delay_on_off_loss: 0.4533 - val_disto_on_off_loss: 0.5264 - val_flanger_on_off_loss: 0.7560 - val_reverb_on_off_loss: 0.7175\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 2.2986 - filter_on_off_loss: 0.3704 - delay_on_off_loss: 0.4436 - disto_on_off_loss: 0.4681 - flanger_on_off_loss: 0.5557 - reverb_on_off_loss: 0.4609 - val_loss: 2.8765 - val_filter_on_off_loss: 0.4419 - val_delay_on_off_loss: 0.4161 - val_disto_on_off_loss: 0.5322 - val_flanger_on_off_loss: 0.7776 - val_reverb_on_off_loss: 0.7087\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 2.1346 - filter_on_off_loss: 0.3251 - delay_on_off_loss: 0.4026 - disto_on_off_loss: 0.4331 - flanger_on_off_loss: 0.5395 - reverb_on_off_loss: 0.4342 - val_loss: 2.8319 - val_filter_on_off_loss: 0.4094 - val_delay_on_off_loss: 0.3814 - val_disto_on_off_loss: 0.5390 - val_flanger_on_off_loss: 0.8018 - val_reverb_on_off_loss: 0.7002\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 1.9801 - filter_on_off_loss: 0.2826 - delay_on_off_loss: 0.3656 - disto_on_off_loss: 0.3988 - flanger_on_off_loss: 0.5234 - reverb_on_off_loss: 0.4098 - val_loss: 2.7972 - val_filter_on_off_loss: 0.3798 - val_delay_on_off_loss: 0.3492 - val_disto_on_off_loss: 0.5468 - val_flanger_on_off_loss: 0.8293 - val_reverb_on_off_loss: 0.6921\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 1.8350 - filter_on_off_loss: 0.2434 - delay_on_off_loss: 0.3321 - disto_on_off_loss: 0.3650 - flanger_on_off_loss: 0.5071 - reverb_on_off_loss: 0.3874 - val_loss: 2.7731 - val_filter_on_off_loss: 0.3533 - val_delay_on_off_loss: 0.3192 - val_disto_on_off_loss: 0.5557 - val_flanger_on_off_loss: 0.8604 - val_reverb_on_off_loss: 0.6845\n",
      "7/7 [==============================] - 1s 113ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 1, 'filter_on_off', 'class', -1.8349549770355225, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 1, 'delay_on_off', 'class', -1.8349549770355225, 0.8571428571428571)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 1, 'disto_on_off', 'class', -1.8349549770355225, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 1, 'flanger_on_off', 'class', -1.8349549770355225, 0.7142857142857143)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 1, 'reverb_on_off', 'class', -1.8349549770355225, 0.5714285714285714)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_15 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_6 (LSTM)                   (None, 37, 8)        928         input_15[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "lstm_7 (LSTM)                   (None, 8)            544         lstm_6[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            18          lstm_7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            18          lstm_7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            18          lstm_7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            18          lstm_7[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            18          lstm_7[0][0]                     \n",
      "==================================================================================================\n",
      "Total params: 1,562\n",
      "Trainable params: 1,562\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 5s 213ms/step - loss: 3.7089 - filter_on_off_loss: 0.7622 - delay_on_off_loss: 0.7255 - disto_on_off_loss: 0.6995 - flanger_on_off_loss: 0.6999 - reverb_on_off_loss: 0.8219 - val_loss: 3.5272 - val_filter_on_off_loss: 0.7053 - val_delay_on_off_loss: 0.7032 - val_disto_on_off_loss: 0.6786 - val_flanger_on_off_loss: 0.6384 - val_reverb_on_off_loss: 0.8017\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.6886 - filter_on_off_loss: 0.7585 - delay_on_off_loss: 0.7224 - disto_on_off_loss: 0.6987 - flanger_on_off_loss: 0.6939 - reverb_on_off_loss: 0.8151 - val_loss: 3.5263 - val_filter_on_off_loss: 0.7031 - val_delay_on_off_loss: 0.7049 - val_disto_on_off_loss: 0.6798 - val_flanger_on_off_loss: 0.6402 - val_reverb_on_off_loss: 0.7983\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.6685 - filter_on_off_loss: 0.7550 - delay_on_off_loss: 0.7193 - disto_on_off_loss: 0.6980 - flanger_on_off_loss: 0.6878 - reverb_on_off_loss: 0.8084 - val_loss: 3.5255 - val_filter_on_off_loss: 0.7011 - val_delay_on_off_loss: 0.7066 - val_disto_on_off_loss: 0.6809 - val_flanger_on_off_loss: 0.6419 - val_reverb_on_off_loss: 0.7950\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.6486 - filter_on_off_loss: 0.7516 - delay_on_off_loss: 0.7163 - disto_on_off_loss: 0.6973 - flanger_on_off_loss: 0.6818 - reverb_on_off_loss: 0.8016 - val_loss: 3.5248 - val_filter_on_off_loss: 0.6991 - val_delay_on_off_loss: 0.7082 - val_disto_on_off_loss: 0.6821 - val_flanger_on_off_loss: 0.6437 - val_reverb_on_off_loss: 0.7916\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.6289 - filter_on_off_loss: 0.7482 - delay_on_off_loss: 0.7133 - disto_on_off_loss: 0.6967 - flanger_on_off_loss: 0.6759 - reverb_on_off_loss: 0.7948 - val_loss: 3.5242 - val_filter_on_off_loss: 0.6972 - val_delay_on_off_loss: 0.7098 - val_disto_on_off_loss: 0.6833 - val_flanger_on_off_loss: 0.6454 - val_reverb_on_off_loss: 0.7885\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.6102 - filter_on_off_loss: 0.7452 - delay_on_off_loss: 0.7105 - disto_on_off_loss: 0.6961 - flanger_on_off_loss: 0.6702 - reverb_on_off_loss: 0.7883 - val_loss: 3.5238 - val_filter_on_off_loss: 0.6953 - val_delay_on_off_loss: 0.7114 - val_disto_on_off_loss: 0.6845 - val_flanger_on_off_loss: 0.6472 - val_reverb_on_off_loss: 0.7853\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.5909 - filter_on_off_loss: 0.7420 - delay_on_off_loss: 0.7075 - disto_on_off_loss: 0.6954 - flanger_on_off_loss: 0.6643 - reverb_on_off_loss: 0.7816 - val_loss: 3.5235 - val_filter_on_off_loss: 0.6934 - val_delay_on_off_loss: 0.7130 - val_disto_on_off_loss: 0.6858 - val_flanger_on_off_loss: 0.6491 - val_reverb_on_off_loss: 0.7822\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.5718 - filter_on_off_loss: 0.7389 - delay_on_off_loss: 0.7046 - disto_on_off_loss: 0.6948 - flanger_on_off_loss: 0.6585 - reverb_on_off_loss: 0.7750 - val_loss: 3.5235 - val_filter_on_off_loss: 0.6916 - val_delay_on_off_loss: 0.7146 - val_disto_on_off_loss: 0.6871 - val_flanger_on_off_loss: 0.6510 - val_reverb_on_off_loss: 0.7792\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.5529 - filter_on_off_loss: 0.7358 - delay_on_off_loss: 0.7017 - disto_on_off_loss: 0.6941 - flanger_on_off_loss: 0.6528 - reverb_on_off_loss: 0.7685 - val_loss: 3.5236 - val_filter_on_off_loss: 0.6899 - val_delay_on_off_loss: 0.7162 - val_disto_on_off_loss: 0.6884 - val_flanger_on_off_loss: 0.6529 - val_reverb_on_off_loss: 0.7762\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.5343 - filter_on_off_loss: 0.7328 - delay_on_off_loss: 0.6988 - disto_on_off_loss: 0.6934 - flanger_on_off_loss: 0.6471 - reverb_on_off_loss: 0.7622 - val_loss: 3.5239 - val_filter_on_off_loss: 0.6882 - val_delay_on_off_loss: 0.7178 - val_disto_on_off_loss: 0.6897 - val_flanger_on_off_loss: 0.6549 - val_reverb_on_off_loss: 0.7734\n",
      "7/7 [==============================] - 1s 111ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 2, 'filter_on_off', 'class', -3.5343389511108398, 0.7142857142857143)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 2, 'delay_on_off', 'class', -3.5343389511108398, 0.42857142857142855)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 2, 'disto_on_off', 'class', -3.5343389511108398, 0.2857142857142857)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 2, 'flanger_on_off', 'class', -3.5343389511108398, 0.5714285714285714)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 8, 2, 'reverb_on_off', 'class', -3.5343389511108398, 0.42857142857142855)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_16 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_8 (LSTM)                   (None, 37, 16)       2368        input_16[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "lstm_9 (LSTM)                   (None, 16)           2112        lstm_8[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            34          lstm_9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            34          lstm_9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            34          lstm_9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            34          lstm_9[0][0]                     \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            34          lstm_9[0][0]                     \n",
      "==================================================================================================\n",
      "Total params: 4,650\n",
      "Trainable params: 4,650\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 6s 255ms/step - loss: 3.5469 - filter_on_off_loss: 0.6997 - delay_on_off_loss: 0.7891 - disto_on_off_loss: 0.6666 - flanger_on_off_loss: 0.6953 - reverb_on_off_loss: 0.6963 - val_loss: 3.6195 - val_filter_on_off_loss: 0.7199 - val_delay_on_off_loss: 0.7752 - val_disto_on_off_loss: 0.6749 - val_flanger_on_off_loss: 0.5874 - val_reverb_on_off_loss: 0.8620\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.5133 - filter_on_off_loss: 0.6949 - delay_on_off_loss: 0.7727 - disto_on_off_loss: 0.6641 - flanger_on_off_loss: 0.6917 - reverb_on_off_loss: 0.6900 - val_loss: 3.6128 - val_filter_on_off_loss: 0.7162 - val_delay_on_off_loss: 0.7755 - val_disto_on_off_loss: 0.6728 - val_flanger_on_off_loss: 0.5911 - val_reverb_on_off_loss: 0.8572\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.4808 - filter_on_off_loss: 0.6901 - delay_on_off_loss: 0.7571 - disto_on_off_loss: 0.6616 - flanger_on_off_loss: 0.6881 - reverb_on_off_loss: 0.6838 - val_loss: 3.6064 - val_filter_on_off_loss: 0.7125 - val_delay_on_off_loss: 0.7758 - val_disto_on_off_loss: 0.6707 - val_flanger_on_off_loss: 0.5949 - val_reverb_on_off_loss: 0.8524\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.4493 - filter_on_off_loss: 0.6855 - delay_on_off_loss: 0.7423 - disto_on_off_loss: 0.6593 - flanger_on_off_loss: 0.6846 - reverb_on_off_loss: 0.6777 - val_loss: 3.6001 - val_filter_on_off_loss: 0.7088 - val_delay_on_off_loss: 0.7761 - val_disto_on_off_loss: 0.6687 - val_flanger_on_off_loss: 0.5987 - val_reverb_on_off_loss: 0.8478\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.4189 - filter_on_off_loss: 0.6808 - delay_on_off_loss: 0.7282 - disto_on_off_loss: 0.6570 - flanger_on_off_loss: 0.6812 - reverb_on_off_loss: 0.6717 - val_loss: 3.5939 - val_filter_on_off_loss: 0.7052 - val_delay_on_off_loss: 0.7762 - val_disto_on_off_loss: 0.6667 - val_flanger_on_off_loss: 0.6025 - val_reverb_on_off_loss: 0.8432\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.3893 - filter_on_off_loss: 0.6762 - delay_on_off_loss: 0.7147 - disto_on_off_loss: 0.6547 - flanger_on_off_loss: 0.6779 - reverb_on_off_loss: 0.6657 - val_loss: 3.5877 - val_filter_on_off_loss: 0.7016 - val_delay_on_off_loss: 0.7764 - val_disto_on_off_loss: 0.6647 - val_flanger_on_off_loss: 0.6063 - val_reverb_on_off_loss: 0.8388\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.3606 - filter_on_off_loss: 0.6716 - delay_on_off_loss: 0.7019 - disto_on_off_loss: 0.6525 - flanger_on_off_loss: 0.6747 - reverb_on_off_loss: 0.6599 - val_loss: 3.5817 - val_filter_on_off_loss: 0.6982 - val_delay_on_off_loss: 0.7765 - val_disto_on_off_loss: 0.6627 - val_flanger_on_off_loss: 0.6099 - val_reverb_on_off_loss: 0.8343\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.3334 - filter_on_off_loss: 0.6672 - delay_on_off_loss: 0.6899 - disto_on_off_loss: 0.6503 - flanger_on_off_loss: 0.6716 - reverb_on_off_loss: 0.6543 - val_loss: 3.5757 - val_filter_on_off_loss: 0.6947 - val_delay_on_off_loss: 0.7767 - val_disto_on_off_loss: 0.6607 - val_flanger_on_off_loss: 0.6137 - val_reverb_on_off_loss: 0.8298\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.3062 - filter_on_off_loss: 0.6627 - delay_on_off_loss: 0.6782 - disto_on_off_loss: 0.6481 - flanger_on_off_loss: 0.6684 - reverb_on_off_loss: 0.6487 - val_loss: 3.5696 - val_filter_on_off_loss: 0.6912 - val_delay_on_off_loss: 0.7770 - val_disto_on_off_loss: 0.6588 - val_flanger_on_off_loss: 0.6175 - val_reverb_on_off_loss: 0.8252\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.2797 - filter_on_off_loss: 0.6583 - delay_on_off_loss: 0.6670 - disto_on_off_loss: 0.6458 - flanger_on_off_loss: 0.6654 - reverb_on_off_loss: 0.6432 - val_loss: 3.5634 - val_filter_on_off_loss: 0.6878 - val_delay_on_off_loss: 0.7772 - val_disto_on_off_loss: 0.6568 - val_flanger_on_off_loss: 0.6212 - val_reverb_on_off_loss: 0.8204\n",
      "7/7 [==============================] - 1s 123ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 2, 'filter_on_off', 'class', -3.2797374725341797, 0.8571428571428571)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 2, 'delay_on_off', 'class', -3.2797374725341797, 0.14285714285714285)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 2, 'disto_on_off', 'class', -3.2797374725341797, 0.42857142857142855)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 2, 'flanger_on_off', 'class', -3.2797374725341797, 0.42857142857142855)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 16, 2, 'reverb_on_off', 'class', -3.2797374725341797, 0.7142857142857143)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_17 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_10 (LSTM)                  (None, 37, 32)       6784        input_17[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "lstm_11 (LSTM)                  (None, 32)           8320        lstm_10[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            66          lstm_11[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            66          lstm_11[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            66          lstm_11[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            66          lstm_11[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            66          lstm_11[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 15,434\n",
      "Trainable params: 15,434\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 5s 222ms/step - loss: 3.3865 - filter_on_off_loss: 0.6199 - delay_on_off_loss: 0.6828 - disto_on_off_loss: 0.6935 - flanger_on_off_loss: 0.6773 - reverb_on_off_loss: 0.7131 - val_loss: 3.3457 - val_filter_on_off_loss: 0.5652 - val_delay_on_off_loss: 0.6474 - val_disto_on_off_loss: 0.6971 - val_flanger_on_off_loss: 0.7719 - val_reverb_on_off_loss: 0.6641\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.3144 - filter_on_off_loss: 0.5936 - delay_on_off_loss: 0.6618 - disto_on_off_loss: 0.6860 - flanger_on_off_loss: 0.6722 - reverb_on_off_loss: 0.7007 - val_loss: 3.3228 - val_filter_on_off_loss: 0.5452 - val_delay_on_off_loss: 0.6500 - val_disto_on_off_loss: 0.6955 - val_flanger_on_off_loss: 0.7793 - val_reverb_on_off_loss: 0.6528\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.2443 - filter_on_off_loss: 0.5679 - delay_on_off_loss: 0.6422 - disto_on_off_loss: 0.6785 - flanger_on_off_loss: 0.6671 - reverb_on_off_loss: 0.6886 - val_loss: 3.3013 - val_filter_on_off_loss: 0.5256 - val_delay_on_off_loss: 0.6528 - val_disto_on_off_loss: 0.6941 - val_flanger_on_off_loss: 0.7871 - val_reverb_on_off_loss: 0.6417\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.1760 - filter_on_off_loss: 0.5425 - delay_on_off_loss: 0.6238 - disto_on_off_loss: 0.6709 - flanger_on_off_loss: 0.6621 - reverb_on_off_loss: 0.6767 - val_loss: 3.2812 - val_filter_on_off_loss: 0.5064 - val_delay_on_off_loss: 0.6556 - val_disto_on_off_loss: 0.6931 - val_flanger_on_off_loss: 0.7954 - val_reverb_on_off_loss: 0.6307\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.1094 - filter_on_off_loss: 0.5176 - delay_on_off_loss: 0.6064 - disto_on_off_loss: 0.6632 - flanger_on_off_loss: 0.6571 - reverb_on_off_loss: 0.6651 - val_loss: 3.2627 - val_filter_on_off_loss: 0.4876 - val_delay_on_off_loss: 0.6586 - val_disto_on_off_loss: 0.6925 - val_flanger_on_off_loss: 0.8041 - val_reverb_on_off_loss: 0.6198\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 3.0444 - filter_on_off_loss: 0.4931 - delay_on_off_loss: 0.5898 - disto_on_off_loss: 0.6555 - flanger_on_off_loss: 0.6521 - reverb_on_off_loss: 0.6538 - val_loss: 3.2458 - val_filter_on_off_loss: 0.4693 - val_delay_on_off_loss: 0.6618 - val_disto_on_off_loss: 0.6924 - val_flanger_on_off_loss: 0.8133 - val_reverb_on_off_loss: 0.6089\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 2.9808 - filter_on_off_loss: 0.4691 - delay_on_off_loss: 0.5740 - disto_on_off_loss: 0.6476 - flanger_on_off_loss: 0.6472 - reverb_on_off_loss: 0.6429 - val_loss: 3.2306 - val_filter_on_off_loss: 0.4516 - val_delay_on_off_loss: 0.6652 - val_disto_on_off_loss: 0.6927 - val_flanger_on_off_loss: 0.8230 - val_reverb_on_off_loss: 0.5981\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 2.9187 - filter_on_off_loss: 0.4455 - delay_on_off_loss: 0.5588 - disto_on_off_loss: 0.6397 - flanger_on_off_loss: 0.6423 - reverb_on_off_loss: 0.6323 - val_loss: 3.2173 - val_filter_on_off_loss: 0.4343 - val_delay_on_off_loss: 0.6688 - val_disto_on_off_loss: 0.6935 - val_flanger_on_off_loss: 0.8333 - val_reverb_on_off_loss: 0.5874\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 2.8578 - filter_on_off_loss: 0.4225 - delay_on_off_loss: 0.5441 - disto_on_off_loss: 0.6317 - flanger_on_off_loss: 0.6374 - reverb_on_off_loss: 0.6221 - val_loss: 3.2059 - val_filter_on_off_loss: 0.4175 - val_delay_on_off_loss: 0.6725 - val_disto_on_off_loss: 0.6949 - val_flanger_on_off_loss: 0.8441 - val_reverb_on_off_loss: 0.5769\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 2.7984 - filter_on_off_loss: 0.4002 - delay_on_off_loss: 0.5298 - disto_on_off_loss: 0.6236 - flanger_on_off_loss: 0.6326 - reverb_on_off_loss: 0.6122 - val_loss: 3.1964 - val_filter_on_off_loss: 0.4014 - val_delay_on_off_loss: 0.6763 - val_disto_on_off_loss: 0.6966 - val_flanger_on_off_loss: 0.8554 - val_reverb_on_off_loss: 0.5666\n",
      "7/7 [==============================] - 1s 164ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 2, 'filter_on_off', 'class', -2.7983865737915039, 0.7142857142857143)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 2, 'delay_on_off', 'class', -2.7983865737915039, 0.5714285714285714)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 2, 'disto_on_off', 'class', -2.7983865737915039, 0.2857142857142857)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 2, 'flanger_on_off', 'class', -2.7983865737915039, 0.42857142857142855)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 32, 2, 'reverb_on_off', 'class', -2.7983865737915039, 0.8571428571428571)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_18 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_12 (LSTM)                  (None, 37, 64)       21760       input_18[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "lstm_13 (LSTM)                  (None, 64)           33024       lstm_12[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            130         lstm_13[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            130         lstm_13[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            130         lstm_13[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            130         lstm_13[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            130         lstm_13[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 55,434\n",
      "Trainable params: 55,434\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 8s 348ms/step - loss: 3.4293 - filter_on_off_loss: 0.6372 - delay_on_off_loss: 0.6785 - disto_on_off_loss: 0.7485 - flanger_on_off_loss: 0.6911 - reverb_on_off_loss: 0.6740 - val_loss: 3.1949 - val_filter_on_off_loss: 0.5441 - val_delay_on_off_loss: 0.6827 - val_disto_on_off_loss: 0.6824 - val_flanger_on_off_loss: 0.7180 - val_reverb_on_off_loss: 0.5677\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.2819 - filter_on_off_loss: 0.5987 - delay_on_off_loss: 0.6393 - disto_on_off_loss: 0.7239 - flanger_on_off_loss: 0.6742 - reverb_on_off_loss: 0.6458 - val_loss: 3.1372 - val_filter_on_off_loss: 0.5206 - val_delay_on_off_loss: 0.6610 - val_disto_on_off_loss: 0.6732 - val_flanger_on_off_loss: 0.7335 - val_reverb_on_off_loss: 0.5489\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.1597 - filter_on_off_loss: 0.5662 - delay_on_off_loss: 0.6073 - disto_on_off_loss: 0.7036 - flanger_on_off_loss: 0.6597 - reverb_on_off_loss: 0.6229 - val_loss: 3.0742 - val_filter_on_off_loss: 0.4933 - val_delay_on_off_loss: 0.6366 - val_disto_on_off_loss: 0.6629 - val_flanger_on_off_loss: 0.7536 - val_reverb_on_off_loss: 0.5278\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 3ms/step - loss: 3.0214 - filter_on_off_loss: 0.5286 - delay_on_off_loss: 0.5716 - disto_on_off_loss: 0.6807 - flanger_on_off_loss: 0.6427 - reverb_on_off_loss: 0.5977 - val_loss: 3.0155 - val_filter_on_off_loss: 0.4661 - val_delay_on_off_loss: 0.6130 - val_disto_on_off_loss: 0.6532 - val_flanger_on_off_loss: 0.7756 - val_reverb_on_off_loss: 0.5077\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 2.8868 - filter_on_off_loss: 0.4911 - delay_on_off_loss: 0.5374 - disto_on_off_loss: 0.6583 - flanger_on_off_loss: 0.6257 - reverb_on_off_loss: 0.5743 - val_loss: 2.9614 - val_filter_on_off_loss: 0.4392 - val_delay_on_off_loss: 0.5900 - val_disto_on_off_loss: 0.6440 - val_flanger_on_off_loss: 0.7994 - val_reverb_on_off_loss: 0.4889\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 2.7558 - filter_on_off_loss: 0.4540 - delay_on_off_loss: 0.5044 - disto_on_off_loss: 0.6362 - flanger_on_off_loss: 0.6086 - reverb_on_off_loss: 0.5526 - val_loss: 2.9124 - val_filter_on_off_loss: 0.4129 - val_delay_on_off_loss: 0.5676 - val_disto_on_off_loss: 0.6355 - val_flanger_on_off_loss: 0.8249 - val_reverb_on_off_loss: 0.4715\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 2.6281 - filter_on_off_loss: 0.4174 - delay_on_off_loss: 0.4724 - disto_on_off_loss: 0.6142 - flanger_on_off_loss: 0.5915 - reverb_on_off_loss: 0.5326 - val_loss: 2.8689 - val_filter_on_off_loss: 0.3873 - val_delay_on_off_loss: 0.5458 - val_disto_on_off_loss: 0.6279 - val_flanger_on_off_loss: 0.8521 - val_reverb_on_off_loss: 0.4558\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 2.5038 - filter_on_off_loss: 0.3816 - delay_on_off_loss: 0.4413 - disto_on_off_loss: 0.5922 - flanger_on_off_loss: 0.5745 - reverb_on_off_loss: 0.5143 - val_loss: 2.8315 - val_filter_on_off_loss: 0.3630 - val_delay_on_off_loss: 0.5246 - val_disto_on_off_loss: 0.6212 - val_flanger_on_off_loss: 0.8809 - val_reverb_on_off_loss: 0.4419\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 2.3832 - filter_on_off_loss: 0.3470 - delay_on_off_loss: 0.4111 - disto_on_off_loss: 0.5700 - flanger_on_off_loss: 0.5575 - reverb_on_off_loss: 0.4975 - val_loss: 2.8005 - val_filter_on_off_loss: 0.3401 - val_delay_on_off_loss: 0.5038 - val_disto_on_off_loss: 0.6158 - val_flanger_on_off_loss: 0.9109 - val_reverb_on_off_loss: 0.4298\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 4ms/step - loss: 2.2662 - filter_on_off_loss: 0.3142 - delay_on_off_loss: 0.3820 - disto_on_off_loss: 0.5477 - flanger_on_off_loss: 0.5406 - reverb_on_off_loss: 0.4817 - val_loss: 2.7757 - val_filter_on_off_loss: 0.3190 - val_delay_on_off_loss: 0.4836 - val_disto_on_off_loss: 0.6118 - val_flanger_on_off_loss: 0.9418 - val_reverb_on_off_loss: 0.4195\n",
      "7/7 [==============================] - 1s 180ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 2, 'filter_on_off', 'class', -2.2662496566772461, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 2, 'delay_on_off', 'class', -2.2662496566772461, 0.2857142857142857)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 2, 'disto_on_off', 'class', -2.2662496566772461, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 2, 'flanger_on_off', 'class', -2.2662496566772461, 1.0)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 64, 2, 'reverb_on_off', 'class', -2.2662496566772461, 0.5714285714285714)\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_19 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "lstm_14 (LSTM)                  (None, 37, 128)      76288       input_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "lstm_15 (LSTM)                  (None, 128)          131584      lstm_14[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            258         lstm_15[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            258         lstm_15[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            258         lstm_15[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            258         lstm_15[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            258         lstm_15[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 209,162\n",
      "Trainable params: 209,162\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 7s 329ms/step - loss: 3.5277 - filter_on_off_loss: 0.7314 - delay_on_off_loss: 0.6833 - disto_on_off_loss: 0.7274 - flanger_on_off_loss: 0.6911 - reverb_on_off_loss: 0.6946 - val_loss: 3.4171 - val_filter_on_off_loss: 0.6715 - val_delay_on_off_loss: 0.6029 - val_disto_on_off_loss: 0.7072 - val_flanger_on_off_loss: 0.8122 - val_reverb_on_off_loss: 0.6233\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 5ms/step - loss: 3.2011 - filter_on_off_loss: 0.6249 - delay_on_off_loss: 0.6131 - disto_on_off_loss: 0.6649 - flanger_on_off_loss: 0.6508 - reverb_on_off_loss: 0.6474 - val_loss: 3.2765 - val_filter_on_off_loss: 0.6096 - val_delay_on_off_loss: 0.5583 - val_disto_on_off_loss: 0.6830 - val_flanger_on_off_loss: 0.8430 - val_reverb_on_off_loss: 0.5826\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 2.9050 - filter_on_off_loss: 0.5318 - delay_on_off_loss: 0.5493 - disto_on_off_loss: 0.6063 - flanger_on_off_loss: 0.6128 - reverb_on_off_loss: 0.6048 - val_loss: 3.1546 - val_filter_on_off_loss: 0.5571 - val_delay_on_off_loss: 0.5157 - val_disto_on_off_loss: 0.6605 - val_flanger_on_off_loss: 0.8775 - val_reverb_on_off_loss: 0.5438\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 2.6280 - filter_on_off_loss: 0.4477 - delay_on_off_loss: 0.4894 - disto_on_off_loss: 0.5494 - flanger_on_off_loss: 0.5757 - reverb_on_off_loss: 0.5659 - val_loss: 3.0528 - val_filter_on_off_loss: 0.5123 - val_delay_on_off_loss: 0.4750 - val_disto_on_off_loss: 0.6403 - val_flanger_on_off_loss: 0.9185 - val_reverb_on_off_loss: 0.5066\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 2.3644 - filter_on_off_loss: 0.3706 - delay_on_off_loss: 0.4327 - disto_on_off_loss: 0.4930 - flanger_on_off_loss: 0.5382 - reverb_on_off_loss: 0.5300 - val_loss: 2.9741 - val_filter_on_off_loss: 0.4746 - val_delay_on_off_loss: 0.4362 - val_disto_on_off_loss: 0.6230 - val_flanger_on_off_loss: 0.9692 - val_reverb_on_off_loss: 0.4712\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 2.1137 - filter_on_off_loss: 0.3009 - delay_on_off_loss: 0.3792 - disto_on_off_loss: 0.4373 - flanger_on_off_loss: 0.4996 - reverb_on_off_loss: 0.4968 - val_loss: 2.9230 - val_filter_on_off_loss: 0.4434 - val_delay_on_off_loss: 0.4000 - val_disto_on_off_loss: 0.6090 - val_flanger_on_off_loss: 1.0323 - val_reverb_on_off_loss: 0.4382\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 1.8788 - filter_on_off_loss: 0.2401 - delay_on_off_loss: 0.3298 - disto_on_off_loss: 0.3828 - flanger_on_off_loss: 0.4599 - reverb_on_off_loss: 0.4662 - val_loss: 2.9025 - val_filter_on_off_loss: 0.4179 - val_delay_on_off_loss: 0.3675 - val_disto_on_off_loss: 0.5988 - val_flanger_on_off_loss: 1.1100 - val_reverb_on_off_loss: 0.4083\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 1.6639 - filter_on_off_loss: 0.1903 - delay_on_off_loss: 0.2856 - disto_on_off_loss: 0.3311 - flanger_on_off_loss: 0.4195 - reverb_on_off_loss: 0.4374 - val_loss: 2.9121 - val_filter_on_off_loss: 0.3961 - val_delay_on_off_loss: 0.3399 - val_disto_on_off_loss: 0.5927 - val_flanger_on_off_loss: 1.2018 - val_reverb_on_off_loss: 0.3817\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 1.4720 - filter_on_off_loss: 0.1520 - delay_on_off_loss: 0.2475 - disto_on_off_loss: 0.2840 - flanger_on_off_loss: 0.3793 - reverb_on_off_loss: 0.4092 - val_loss: 2.9452 - val_filter_on_off_loss: 0.3762 - val_delay_on_off_loss: 0.3179 - val_disto_on_off_loss: 0.5903 - val_flanger_on_off_loss: 1.3030 - val_reverb_on_off_loss: 0.3577\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 6ms/step - loss: 1.3020 - filter_on_off_loss: 0.1246 - delay_on_off_loss: 0.2152 - disto_on_off_loss: 0.2427 - flanger_on_off_loss: 0.3387 - reverb_on_off_loss: 0.3807 - val_loss: 2.9880 - val_filter_on_off_loss: 0.3569 - val_delay_on_off_loss: 0.3019 - val_disto_on_off_loss: 0.5903 - val_flanger_on_off_loss: 1.4044 - val_reverb_on_off_loss: 0.3345\n",
      "7/7 [==============================] - 1s 180ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 2, 'filter_on_off', 'class', -1.3020336627960205, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 2, 'delay_on_off', 'class', -1.3020336627960205, 0.14285714285714285)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 2, 'disto_on_off', 'class', -1.3020336627960205, 0.7142857142857143)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 2, 'flanger_on_off', 'class', -1.3020336627960205, 0.8571428571428571)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('LSTM', 'joint', 128, 2, 'reverb_on_off', 'class', -1.3020336627960205, 1.0)\n"
     ]
    }
   ],
   "source": [
    "from keras.layers import LSTM\n",
    "\n",
    "def modLSTM(n_hidden_units, n_layers):\n",
    "    # Input layer\n",
    "    in_shape = (X_test_mfcc.shape[1],X_test_mfcc.shape[2])\n",
    "    in_layer = Input(shape=in_shape)\n",
    "    \n",
    "    # Hidden layers\n",
    "    h_layer = in_layer\n",
    "    for i in range(n_layers):\n",
    "        seq = i < n_layers - 1\n",
    "        h_layer = LSTM(n_hidden_units, return_sequences=seq)(h_layer)\n",
    "        \n",
    "    # Output layers and losses\n",
    "    out_layers = []\n",
    "    losses = {}\n",
    "    metrics = {}\n",
    "    for name,infos in Y_info.iteritems():\n",
    "        \n",
    "        if infos['type'] == 'float64':\n",
    "            out_layer = Dense(1, name=name)(h_layer)\n",
    "            losses[name] = 'mean_absolute_error'\n",
    "            metrics[name] = 'mean_absolute_error'\n",
    "            \n",
    "        elif infos['type'] == 'object':\n",
    "            out_dim = len(infos['char2int'])\n",
    "            out_layer = Dense(out_dim, activation='softmax', name=name)(h_layer)\n",
    "            losses[name] = 'categorical_crossentropy'\n",
    "            metrics[name] = 'accuracy'\n",
    "\n",
    "        else:\n",
    "            raise ValueError\n",
    "        out_layers.append(out_layer)\n",
    "\n",
    "    model = Model(inputs = in_layer, outputs = out_layers)\n",
    "    model.compile(loss=losses, optimizer='adam')\n",
    "    \n",
    "    print model.summary()\n",
    "    return model\n",
    "\n",
    "for N_LAYERS in [1,2]:\n",
    "    for N_UNITS in [4,8,16,32,64,128,256]:\n",
    "        model = modLSTM(N_UNITS, N_LAYERS)\n",
    "        out = test_model('LSTM', N_UNITS, N_LAYERS, model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(37, 20)\n",
      "0\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_20 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_1 (Conv1D)               (None, 34, 8)        648         input_20[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_1 (MaxPooling1D)  (None, 16, 8)        0           conv1d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling1d_1 (GlobalM (None, 8)            0           max_pooling1d_1[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dense_14 (Dense)                (None, 8)            72          global_max_pooling1d_1[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            18          dense_14[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            18          dense_14[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            18          dense_14[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            18          dense_14[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            18          dense_14[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 810\n",
      "Trainable params: 810\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 4s 178ms/step - loss: 7.6528 - filter_on_off_loss: 0.6430 - delay_on_off_loss: 0.5597 - disto_on_off_loss: 3.5271 - flanger_on_off_loss: 0.6372 - reverb_on_off_loss: 2.2859 - val_loss: 8.4099 - val_filter_on_off_loss: 0.6251 - val_delay_on_off_loss: 1.1020 - val_disto_on_off_loss: 4.6086 - val_flanger_on_off_loss: 0.3329 - val_reverb_on_off_loss: 1.7413\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 348us/step - loss: 7.4400 - filter_on_off_loss: 0.6051 - delay_on_off_loss: 0.5567 - disto_on_off_loss: 3.4310 - flanger_on_off_loss: 0.6261 - reverb_on_off_loss: 2.2211 - val_loss: 8.2589 - val_filter_on_off_loss: 0.5983 - val_delay_on_off_loss: 1.0956 - val_disto_on_off_loss: 4.5220 - val_flanger_on_off_loss: 0.3434 - val_reverb_on_off_loss: 1.6995\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 335us/step - loss: 7.2334 - filter_on_off_loss: 0.5691 - delay_on_off_loss: 0.5542 - disto_on_off_loss: 3.3370 - flanger_on_off_loss: 0.6157 - reverb_on_off_loss: 2.1574 - val_loss: 8.1069 - val_filter_on_off_loss: 0.5723 - val_delay_on_off_loss: 1.0889 - val_disto_on_off_loss: 4.4345 - val_flanger_on_off_loss: 0.3540 - val_reverb_on_off_loss: 1.6571\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 351us/step - loss: 7.0354 - filter_on_off_loss: 0.5363 - delay_on_off_loss: 0.5525 - disto_on_off_loss: 3.2458 - flanger_on_off_loss: 0.6058 - reverb_on_off_loss: 2.0950 - val_loss: 7.9540 - val_filter_on_off_loss: 0.5483 - val_delay_on_off_loss: 1.0812 - val_disto_on_off_loss: 4.3457 - val_flanger_on_off_loss: 0.3647 - val_reverb_on_off_loss: 1.6142\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 328us/step - loss: 6.8425 - filter_on_off_loss: 0.5059 - delay_on_off_loss: 0.5509 - disto_on_off_loss: 3.1562 - flanger_on_off_loss: 0.5966 - reverb_on_off_loss: 2.0329 - val_loss: 7.8027 - val_filter_on_off_loss: 0.5261 - val_delay_on_off_loss: 1.0729 - val_disto_on_off_loss: 4.2573 - val_flanger_on_off_loss: 0.3751 - val_reverb_on_off_loss: 1.5714\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 346us/step - loss: 6.6555 - filter_on_off_loss: 0.4777 - delay_on_off_loss: 0.5495 - disto_on_off_loss: 3.0686 - flanger_on_off_loss: 0.5879 - reverb_on_off_loss: 1.9719 - val_loss: 7.6552 - val_filter_on_off_loss: 0.5065 - val_delay_on_off_loss: 1.0646 - val_disto_on_off_loss: 4.1697 - val_flanger_on_off_loss: 0.3848 - val_reverb_on_off_loss: 1.5296\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 356us/step - loss: 6.4739 - filter_on_off_loss: 0.4519 - delay_on_off_loss: 0.5480 - disto_on_off_loss: 2.9823 - flanger_on_off_loss: 0.5798 - reverb_on_off_loss: 1.9119 - val_loss: 7.5103 - val_filter_on_off_loss: 0.4886 - val_delay_on_off_loss: 1.0561 - val_disto_on_off_loss: 4.0828 - val_flanger_on_off_loss: 0.3940 - val_reverb_on_off_loss: 1.4888\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 348us/step - loss: 6.2977 - filter_on_off_loss: 0.4286 - delay_on_off_loss: 0.5465 - disto_on_off_loss: 2.8971 - flanger_on_off_loss: 0.5723 - reverb_on_off_loss: 1.8531 - val_loss: 7.3681 - val_filter_on_off_loss: 0.4722 - val_delay_on_off_loss: 1.0474 - val_disto_on_off_loss: 3.9967 - val_flanger_on_off_loss: 0.4029 - val_reverb_on_off_loss: 1.4489\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 348us/step - loss: 6.1267 - filter_on_off_loss: 0.4073 - delay_on_off_loss: 0.5450 - disto_on_off_loss: 2.8140 - flanger_on_off_loss: 0.5651 - reverb_on_off_loss: 1.7952 - val_loss: 7.2283 - val_filter_on_off_loss: 0.4571 - val_delay_on_off_loss: 1.0389 - val_disto_on_off_loss: 3.9114 - val_flanger_on_off_loss: 0.4113 - val_reverb_on_off_loss: 1.4096\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 341us/step - loss: 5.9620 - filter_on_off_loss: 0.3877 - delay_on_off_loss: 0.5437 - disto_on_off_loss: 2.7332 - flanger_on_off_loss: 0.5584 - reverb_on_off_loss: 1.7390 - val_loss: 7.0927 - val_filter_on_off_loss: 0.4435 - val_delay_on_off_loss: 1.0308 - val_disto_on_off_loss: 3.8274 - val_flanger_on_off_loss: 0.4189 - val_reverb_on_off_loss: 1.3721\n",
      "7/7 [==============================] - 1s 154ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 1, 'filter_on_off', 'class', -5.9619674682617188, 0.8571428571428571)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 1, 'delay_on_off', 'class', -5.9619674682617188, 0.14285714285714285)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 1, 'disto_on_off', 'class', -5.9619674682617188, 1.0)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 1, 'flanger_on_off', 'class', -5.9619674682617188, 0.5714285714285714)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 1, 'reverb_on_off', 'class', -5.9619674682617188, 0.42857142857142855)\n",
      "(37, 20)\n",
      "0\n",
      "1\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_21 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_2 (Conv1D)               (None, 34, 8)        648         input_21[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_2 (MaxPooling1D)  (None, 16, 8)        0           conv1d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_3 (Conv1D)               (None, 13, 16)       528         max_pooling1d_2[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_3 (MaxPooling1D)  (None, 5, 16)        0           conv1d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling1d_2 (GlobalM (None, 16)           0           max_pooling1d_3[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dense_15 (Dense)                (None, 8)            136         global_max_pooling1d_2[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            18          dense_15[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            18          dense_15[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            18          dense_15[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            18          dense_15[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            18          dense_15[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 1,402\n",
      "Trainable params: 1,402\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 6s 258ms/step - loss: 5.1549 - filter_on_off_loss: 0.8379 - delay_on_off_loss: 0.9613 - disto_on_off_loss: 0.6697 - flanger_on_off_loss: 1.1764 - reverb_on_off_loss: 1.5095 - val_loss: 6.6354 - val_filter_on_off_loss: 0.4497 - val_delay_on_off_loss: 1.4327 - val_disto_on_off_loss: 0.5670 - val_flanger_on_off_loss: 1.3502 - val_reverb_on_off_loss: 2.8359\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 368us/step - loss: 4.8663 - filter_on_off_loss: 0.7992 - delay_on_off_loss: 0.9501 - disto_on_off_loss: 0.6681 - flanger_on_off_loss: 1.0870 - reverb_on_off_loss: 1.3619 - val_loss: 6.2211 - val_filter_on_off_loss: 0.4334 - val_delay_on_off_loss: 1.4047 - val_disto_on_off_loss: 0.5728 - val_flanger_on_off_loss: 1.2253 - val_reverb_on_off_loss: 2.5849\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 338us/step - loss: 4.5028 - filter_on_off_loss: 0.7507 - delay_on_off_loss: 0.9355 - disto_on_off_loss: 0.6659 - flanger_on_off_loss: 0.9783 - reverb_on_off_loss: 1.1723 - val_loss: 5.8672 - val_filter_on_off_loss: 0.4194 - val_delay_on_off_loss: 1.3813 - val_disto_on_off_loss: 0.5764 - val_flanger_on_off_loss: 1.1283 - val_reverb_on_off_loss: 2.3618\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 403us/step - loss: 4.1963 - filter_on_off_loss: 0.7103 - delay_on_off_loss: 0.9219 - disto_on_off_loss: 0.6630 - flanger_on_off_loss: 0.8907 - reverb_on_off_loss: 1.0104 - val_loss: 5.5077 - val_filter_on_off_loss: 0.4047 - val_delay_on_off_loss: 1.3588 - val_disto_on_off_loss: 0.5783 - val_flanger_on_off_loss: 1.0411 - val_reverb_on_off_loss: 2.1248\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 364us/step - loss: 3.8896 - filter_on_off_loss: 0.6695 - delay_on_off_loss: 0.9069 - disto_on_off_loss: 0.6593 - flanger_on_off_loss: 0.8073 - reverb_on_off_loss: 0.8466 - val_loss: 5.1845 - val_filter_on_off_loss: 0.3901 - val_delay_on_off_loss: 1.3405 - val_disto_on_off_loss: 0.5779 - val_flanger_on_off_loss: 0.9750 - val_reverb_on_off_loss: 1.9011\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 514us/step - loss: 3.6197 - filter_on_off_loss: 0.6327 - delay_on_off_loss: 0.8918 - disto_on_off_loss: 0.6551 - flanger_on_off_loss: 0.7386 - reverb_on_off_loss: 0.7016 - val_loss: 4.8972 - val_filter_on_off_loss: 0.3750 - val_delay_on_off_loss: 1.3253 - val_disto_on_off_loss: 0.5760 - val_flanger_on_off_loss: 0.9280 - val_reverb_on_off_loss: 1.6929\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 555us/step - loss: 3.3837 - filter_on_off_loss: 0.5990 - delay_on_off_loss: 0.8762 - disto_on_off_loss: 0.6503 - flanger_on_off_loss: 0.6824 - reverb_on_off_loss: 0.5757 - val_loss: 4.6444 - val_filter_on_off_loss: 0.3596 - val_delay_on_off_loss: 1.3143 - val_disto_on_off_loss: 0.5725 - val_flanger_on_off_loss: 0.8962 - val_reverb_on_off_loss: 1.5019\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 636us/step - loss: 3.1838 - filter_on_off_loss: 0.5692 - delay_on_off_loss: 0.8601 - disto_on_off_loss: 0.6439 - flanger_on_off_loss: 0.6395 - reverb_on_off_loss: 0.4711 - val_loss: 4.4260 - val_filter_on_off_loss: 0.3438 - val_delay_on_off_loss: 1.3068 - val_disto_on_off_loss: 0.5674 - val_flanger_on_off_loss: 0.8770 - val_reverb_on_off_loss: 1.3310\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 565us/step - loss: 3.0178 - filter_on_off_loss: 0.5419 - delay_on_off_loss: 0.8430 - disto_on_off_loss: 0.6363 - flanger_on_off_loss: 0.6087 - reverb_on_off_loss: 0.3878 - val_loss: 4.2410 - val_filter_on_off_loss: 0.3277 - val_delay_on_off_loss: 1.3034 - val_disto_on_off_loss: 0.5605 - val_flanger_on_off_loss: 0.8683 - val_reverb_on_off_loss: 1.1810\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 853us/step - loss: 2.8842 - filter_on_off_loss: 0.5171 - delay_on_off_loss: 0.8250 - disto_on_off_loss: 0.6273 - flanger_on_off_loss: 0.5885 - reverb_on_off_loss: 0.3263 - val_loss: 4.0842 - val_filter_on_off_loss: 0.3122 - val_delay_on_off_loss: 1.3074 - val_disto_on_off_loss: 0.5522 - val_flanger_on_off_loss: 0.8650 - val_reverb_on_off_loss: 1.0474\n",
      "7/7 [==============================] - 1s 175ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 2, 'filter_on_off', 'class', -2.8842432498931885, 0.7142857142857143)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 2, 'delay_on_off', 'class', -2.8842432498931885, 0.5714285714285714)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 2, 'disto_on_off', 'class', -2.8842432498931885, 0.5714285714285714)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 2, 'flanger_on_off', 'class', -2.8842432498931885, 0.5714285714285714)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 8, 2, 'reverb_on_off', 'class', -2.8842432498931885, 1.0)\n",
      "(37, 20)\n",
      "0\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_22 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_4 (Conv1D)               (None, 34, 16)       1296        input_22[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_4 (MaxPooling1D)  (None, 16, 16)       0           conv1d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling1d_3 (GlobalM (None, 16)           0           max_pooling1d_4[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dense_16 (Dense)                (None, 16)           272         global_max_pooling1d_3[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            34          dense_16[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            34          dense_16[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            34          dense_16[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            34          dense_16[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            34          dense_16[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 1,738\n",
      "Trainable params: 1,738\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 4s 172ms/step - loss: 6.7558 - filter_on_off_loss: 1.3555 - delay_on_off_loss: 0.9633 - disto_on_off_loss: 2.0384 - flanger_on_off_loss: 1.3030 - reverb_on_off_loss: 1.0956 - val_loss: 8.9616 - val_filter_on_off_loss: 2.1890 - val_delay_on_off_loss: 2.3591 - val_disto_on_off_loss: 1.5490 - val_flanger_on_off_loss: 2.5425 - val_reverb_on_off_loss: 0.3220\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 411us/step - loss: 6.3926 - filter_on_off_loss: 1.2736 - delay_on_off_loss: 0.9358 - disto_on_off_loss: 1.9322 - flanger_on_off_loss: 1.2082 - reverb_on_off_loss: 1.0428 - val_loss: 8.6879 - val_filter_on_off_loss: 2.0983 - val_delay_on_off_loss: 2.3258 - val_disto_on_off_loss: 1.4012 - val_flanger_on_off_loss: 2.5553 - val_reverb_on_off_loss: 0.3072\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 506us/step - loss: 6.0452 - filter_on_off_loss: 1.1955 - delay_on_off_loss: 0.9096 - disto_on_off_loss: 1.8270 - flanger_on_off_loss: 1.1208 - reverb_on_off_loss: 0.9923 - val_loss: 8.4431 - val_filter_on_off_loss: 2.0148 - val_delay_on_off_loss: 2.2970 - val_disto_on_off_loss: 1.2711 - val_flanger_on_off_loss: 2.5657 - val_reverb_on_off_loss: 0.2945\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 343us/step - loss: 5.7412 - filter_on_off_loss: 1.1267 - delay_on_off_loss: 0.8863 - disto_on_off_loss: 1.7322 - flanger_on_off_loss: 1.0476 - reverb_on_off_loss: 0.9484 - val_loss: 8.1864 - val_filter_on_off_loss: 1.9249 - val_delay_on_off_loss: 2.2655 - val_disto_on_off_loss: 1.1363 - val_flanger_on_off_loss: 2.5784 - val_reverb_on_off_loss: 0.2814\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 351us/step - loss: 5.4208 - filter_on_off_loss: 1.0540 - delay_on_off_loss: 0.8613 - disto_on_off_loss: 1.6298 - flanger_on_off_loss: 0.9733 - reverb_on_off_loss: 0.9025 - val_loss: 7.9429 - val_filter_on_off_loss: 1.8359 - val_delay_on_off_loss: 2.2342 - val_disto_on_off_loss: 1.0113 - val_flanger_on_off_loss: 2.5921 - val_reverb_on_off_loss: 0.2694\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 331us/step - loss: 5.1154 - filter_on_off_loss: 0.9840 - delay_on_off_loss: 0.8373 - disto_on_off_loss: 1.5298 - flanger_on_off_loss: 0.9056 - reverb_on_off_loss: 0.8586 - val_loss: 7.7093 - val_filter_on_off_loss: 1.7466 - val_delay_on_off_loss: 2.2027 - val_disto_on_off_loss: 0.9003 - val_flanger_on_off_loss: 2.6018 - val_reverb_on_off_loss: 0.2579\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 333us/step - loss: 4.8250 - filter_on_off_loss: 0.9171 - delay_on_off_loss: 0.8139 - disto_on_off_loss: 1.4327 - flanger_on_off_loss: 0.8439 - reverb_on_off_loss: 0.8174 - val_loss: 7.4936 - val_filter_on_off_loss: 1.6606 - val_delay_on_off_loss: 2.1701 - val_disto_on_off_loss: 0.8055 - val_flanger_on_off_loss: 2.6099 - val_reverb_on_off_loss: 0.2475\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 346us/step - loss: 4.5502 - filter_on_off_loss: 0.8533 - delay_on_off_loss: 0.7913 - disto_on_off_loss: 1.3394 - flanger_on_off_loss: 0.7872 - reverb_on_off_loss: 0.7790 - val_loss: 7.2929 - val_filter_on_off_loss: 1.5764 - val_delay_on_off_loss: 2.1363 - val_disto_on_off_loss: 0.7242 - val_flanger_on_off_loss: 2.6174 - val_reverb_on_off_loss: 0.2385\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 345us/step - loss: 4.2918 - filter_on_off_loss: 0.7926 - delay_on_off_loss: 0.7697 - disto_on_off_loss: 1.2509 - flanger_on_off_loss: 0.7348 - reverb_on_off_loss: 0.7439 - val_loss: 7.1064 - val_filter_on_off_loss: 1.4936 - val_delay_on_off_loss: 2.1014 - val_disto_on_off_loss: 0.6558 - val_flanger_on_off_loss: 2.6244 - val_reverb_on_off_loss: 0.2312\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 364us/step - loss: 4.0502 - filter_on_off_loss: 0.7356 - delay_on_off_loss: 0.7495 - disto_on_off_loss: 1.1668 - flanger_on_off_loss: 0.6860 - reverb_on_off_loss: 0.7122 - val_loss: 6.9328 - val_filter_on_off_loss: 1.4130 - val_delay_on_off_loss: 2.0670 - val_disto_on_off_loss: 0.5988 - val_flanger_on_off_loss: 2.6283 - val_reverb_on_off_loss: 0.2257\n",
      "7/7 [==============================] - 1s 156ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 1, 'filter_on_off', 'class', -4.0501618385314941, 0.5714285714285714)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 1, 'delay_on_off', 'class', -4.0501618385314941, 0.0)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 1, 'disto_on_off', 'class', -4.0501618385314941, 0.42857142857142855)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 1, 'flanger_on_off', 'class', -4.0501618385314941, 0.2857142857142857)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 1, 'reverb_on_off', 'class', -4.0501618385314941, 0.5714285714285714)\n",
      "(37, 20)\n",
      "0\n",
      "1\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_23 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_5 (Conv1D)               (None, 34, 16)       1296        input_23[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_5 (MaxPooling1D)  (None, 16, 16)       0           conv1d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_6 (Conv1D)               (None, 13, 32)       2080        max_pooling1d_5[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_6 (MaxPooling1D)  (None, 5, 32)        0           conv1d_6[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling1d_4 (GlobalM (None, 32)           0           max_pooling1d_6[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dense_17 (Dense)                (None, 16)           528         global_max_pooling1d_4[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            34          dense_17[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            34          dense_17[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            34          dense_17[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            34          dense_17[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            34          dense_17[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 4,074\n",
      "Trainable params: 4,074\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 4s 192ms/step - loss: 4.8349 - filter_on_off_loss: 0.6682 - delay_on_off_loss: 0.6873 - disto_on_off_loss: 0.9645 - flanger_on_off_loss: 1.7705 - reverb_on_off_loss: 0.7443 - val_loss: 3.7126 - val_filter_on_off_loss: 0.5284 - val_delay_on_off_loss: 0.7634 - val_disto_on_off_loss: 0.5634 - val_flanger_on_off_loss: 1.2277 - val_reverb_on_off_loss: 0.6297\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 416us/step - loss: 4.3292 - filter_on_off_loss: 0.6072 - delay_on_off_loss: 0.6666 - disto_on_off_loss: 0.8725 - flanger_on_off_loss: 1.5128 - reverb_on_off_loss: 0.6701 - val_loss: 3.4937 - val_filter_on_off_loss: 0.4919 - val_delay_on_off_loss: 0.7951 - val_disto_on_off_loss: 0.5157 - val_flanger_on_off_loss: 1.1477 - val_reverb_on_off_loss: 0.5433\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 400us/step - loss: 3.8771 - filter_on_off_loss: 0.5519 - delay_on_off_loss: 0.6461 - disto_on_off_loss: 0.7905 - flanger_on_off_loss: 1.2841 - reverb_on_off_loss: 0.6046 - val_loss: 3.3383 - val_filter_on_off_loss: 0.4581 - val_delay_on_off_loss: 0.8259 - val_disto_on_off_loss: 0.4787 - val_flanger_on_off_loss: 1.1017 - val_reverb_on_off_loss: 0.4739\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 389us/step - loss: 3.4787 - filter_on_off_loss: 0.5025 - delay_on_off_loss: 0.6261 - disto_on_off_loss: 0.7192 - flanger_on_off_loss: 1.0831 - reverb_on_off_loss: 0.5478 - val_loss: 3.2473 - val_filter_on_off_loss: 0.4273 - val_delay_on_off_loss: 0.8557 - val_disto_on_off_loss: 0.4532 - val_flanger_on_off_loss: 1.0888 - val_reverb_on_off_loss: 0.4223\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 377us/step - loss: 3.1314 - filter_on_off_loss: 0.4591 - delay_on_off_loss: 0.6063 - disto_on_off_loss: 0.6585 - flanger_on_off_loss: 0.9081 - reverb_on_off_loss: 0.4993 - val_loss: 3.2062 - val_filter_on_off_loss: 0.3992 - val_delay_on_off_loss: 0.8833 - val_disto_on_off_loss: 0.4361 - val_flanger_on_off_loss: 1.1039 - val_reverb_on_off_loss: 0.3838\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 425us/step - loss: 2.8314 - filter_on_off_loss: 0.4213 - delay_on_off_loss: 0.5870 - disto_on_off_loss: 0.6073 - flanger_on_off_loss: 0.7602 - reverb_on_off_loss: 0.4556 - val_loss: 3.2017 - val_filter_on_off_loss: 0.3736 - val_delay_on_off_loss: 0.9080 - val_disto_on_off_loss: 0.4261 - val_flanger_on_off_loss: 1.1379 - val_reverb_on_off_loss: 0.3561\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 411us/step - loss: 2.5706 - filter_on_off_loss: 0.3877 - delay_on_off_loss: 0.5679 - disto_on_off_loss: 0.5622 - flanger_on_off_loss: 0.6375 - reverb_on_off_loss: 0.4153 - val_loss: 3.2291 - val_filter_on_off_loss: 0.3501 - val_delay_on_off_loss: 0.9305 - val_disto_on_off_loss: 0.4209 - val_flanger_on_off_loss: 1.1918 - val_reverb_on_off_loss: 0.3358\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 389us/step - loss: 2.3459 - filter_on_off_loss: 0.3576 - delay_on_off_loss: 0.5487 - disto_on_off_loss: 0.5225 - flanger_on_off_loss: 0.5394 - reverb_on_off_loss: 0.3776 - val_loss: 3.2776 - val_filter_on_off_loss: 0.3292 - val_delay_on_off_loss: 0.9488 - val_disto_on_off_loss: 0.4195 - val_flanger_on_off_loss: 1.2589 - val_reverb_on_off_loss: 0.3212\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 385us/step - loss: 2.1566 - filter_on_off_loss: 0.3318 - delay_on_off_loss: 0.5305 - disto_on_off_loss: 0.4874 - flanger_on_off_loss: 0.4642 - reverb_on_off_loss: 0.3428 - val_loss: 3.3388 - val_filter_on_off_loss: 0.3097 - val_delay_on_off_loss: 0.9639 - val_disto_on_off_loss: 0.4207 - val_flanger_on_off_loss: 1.3346 - val_reverb_on_off_loss: 0.3099\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 388us/step - loss: 1.9902 - filter_on_off_loss: 0.3085 - delay_on_off_loss: 0.5126 - disto_on_off_loss: 0.4547 - flanger_on_off_loss: 0.4051 - reverb_on_off_loss: 0.3094 - val_loss: 3.4035 - val_filter_on_off_loss: 0.2922 - val_delay_on_off_loss: 0.9757 - val_disto_on_off_loss: 0.4233 - val_flanger_on_off_loss: 1.4105 - val_reverb_on_off_loss: 0.3018\n",
      "7/7 [==============================] - 1s 188ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 2, 'filter_on_off', 'class', -1.9902026653289795, 0.5714285714285714)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 2, 'delay_on_off', 'class', -1.9902026653289795, 0.14285714285714285)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 2, 'disto_on_off', 'class', -1.9902026653289795, 0.14285714285714285)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 2, 'flanger_on_off', 'class', -1.9902026653289795, 0.5714285714285714)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 16, 2, 'reverb_on_off', 'class', -1.9902026653289795, 0.7142857142857143)\n",
      "(37, 20)\n",
      "0\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_24 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_7 (Conv1D)               (None, 34, 32)       2592        input_24[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_7 (MaxPooling1D)  (None, 16, 32)       0           conv1d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling1d_5 (GlobalM (None, 32)           0           max_pooling1d_7[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dense_18 (Dense)                (None, 32)           1056        global_max_pooling1d_5[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            66          dense_18[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            66          dense_18[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            66          dense_18[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            66          dense_18[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            66          dense_18[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 3,978\n",
      "Trainable params: 3,978\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 4s 199ms/step - loss: 4.7914 - filter_on_off_loss: 1.1377 - delay_on_off_loss: 0.7959 - disto_on_off_loss: 0.9900 - flanger_on_off_loss: 0.9397 - reverb_on_off_loss: 0.9281 - val_loss: 5.3361 - val_filter_on_off_loss: 1.8338 - val_delay_on_off_loss: 1.0157 - val_disto_on_off_loss: 1.0847 - val_flanger_on_off_loss: 0.7249 - val_reverb_on_off_loss: 0.6771\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 471us/step - loss: 4.3248 - filter_on_off_loss: 1.0134 - delay_on_off_loss: 0.7295 - disto_on_off_loss: 0.8961 - flanger_on_off_loss: 0.8363 - reverb_on_off_loss: 0.8494 - val_loss: 4.9932 - val_filter_on_off_loss: 1.6404 - val_delay_on_off_loss: 1.0321 - val_disto_on_off_loss: 0.9686 - val_flanger_on_off_loss: 0.7265 - val_reverb_on_off_loss: 0.6255\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 460us/step - loss: 3.9024 - filter_on_off_loss: 0.8988 - delay_on_off_loss: 0.6703 - disto_on_off_loss: 0.8159 - flanger_on_off_loss: 0.7396 - reverb_on_off_loss: 0.7778 - val_loss: 4.6909 - val_filter_on_off_loss: 1.4571 - val_delay_on_off_loss: 1.0481 - val_disto_on_off_loss: 0.8671 - val_flanger_on_off_loss: 0.7399 - val_reverb_on_off_loss: 0.5787\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 439us/step - loss: 3.5247 - filter_on_off_loss: 0.7952 - delay_on_off_loss: 0.6172 - disto_on_off_loss: 0.7476 - flanger_on_off_loss: 0.6523 - reverb_on_off_loss: 0.7124 - val_loss: 4.4293 - val_filter_on_off_loss: 1.2837 - val_delay_on_off_loss: 1.0646 - val_disto_on_off_loss: 0.7793 - val_flanger_on_off_loss: 0.7639 - val_reverb_on_off_loss: 0.5378\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 421us/step - loss: 3.1957 - filter_on_off_loss: 0.7033 - delay_on_off_loss: 0.5703 - disto_on_off_loss: 0.6900 - flanger_on_off_loss: 0.5779 - reverb_on_off_loss: 0.6541 - val_loss: 4.2079 - val_filter_on_off_loss: 1.1219 - val_delay_on_off_loss: 1.0809 - val_disto_on_off_loss: 0.7063 - val_flanger_on_off_loss: 0.7951 - val_reverb_on_off_loss: 0.5037\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 388us/step - loss: 2.9127 - filter_on_off_loss: 0.6231 - delay_on_off_loss: 0.5282 - disto_on_off_loss: 0.6414 - flanger_on_off_loss: 0.5171 - reverb_on_off_loss: 0.6030 - val_loss: 4.0346 - val_filter_on_off_loss: 0.9753 - val_delay_on_off_loss: 1.0969 - val_disto_on_off_loss: 0.6468 - val_flanger_on_off_loss: 0.8382 - val_reverb_on_off_loss: 0.4775\n",
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 397us/step - loss: 2.6727 - filter_on_off_loss: 0.5541 - delay_on_off_loss: 0.4902 - disto_on_off_loss: 0.6005 - flanger_on_off_loss: 0.4687 - reverb_on_off_loss: 0.5592 - val_loss: 3.9053 - val_filter_on_off_loss: 0.8458 - val_delay_on_off_loss: 1.1124 - val_disto_on_off_loss: 0.6001 - val_flanger_on_off_loss: 0.8895 - val_reverb_on_off_loss: 0.4574\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 635us/step - loss: 2.4712 - filter_on_off_loss: 0.4962 - delay_on_off_loss: 0.4560 - disto_on_off_loss: 0.5668 - flanger_on_off_loss: 0.4304 - reverb_on_off_loss: 0.5218 - val_loss: 3.8131 - val_filter_on_off_loss: 0.7342 - val_delay_on_off_loss: 1.1274 - val_disto_on_off_loss: 0.5656 - val_flanger_on_off_loss: 0.9438 - val_reverb_on_off_loss: 0.4421\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 484us/step - loss: 2.3013 - filter_on_off_loss: 0.4476 - delay_on_off_loss: 0.4251 - disto_on_off_loss: 0.5387 - flanger_on_off_loss: 0.4007 - reverb_on_off_loss: 0.4892 - val_loss: 3.7480 - val_filter_on_off_loss: 0.6399 - val_delay_on_off_loss: 1.1421 - val_disto_on_off_loss: 0.5396 - val_flanger_on_off_loss: 0.9968 - val_reverb_on_off_loss: 0.4296\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 461us/step - loss: 2.1577 - filter_on_off_loss: 0.4071 - delay_on_off_loss: 0.3969 - disto_on_off_loss: 0.5148 - flanger_on_off_loss: 0.3778 - reverb_on_off_loss: 0.4612 - val_loss: 3.7054 - val_filter_on_off_loss: 0.5606 - val_delay_on_off_loss: 1.1571 - val_disto_on_off_loss: 0.5214 - val_flanger_on_off_loss: 1.0465 - val_reverb_on_off_loss: 0.4197\n",
      "7/7 [==============================] - 1s 196ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 1, 'filter_on_off', 'class', -2.1577389240264893, 1.0)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 1, 'delay_on_off', 'class', -2.1577389240264893, 0.0)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 1, 'disto_on_off', 'class', -2.1577389240264893, 0.14285714285714285)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 1, 'flanger_on_off', 'class', -2.1577389240264893, 0.42857142857142855)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 1, 'reverb_on_off', 'class', -2.1577389240264893, 0.5714285714285714)\n",
      "(37, 20)\n",
      "0\n",
      "1\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_25 (InputLayer)           (None, 37, 20)       0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_8 (Conv1D)               (None, 34, 32)       2592        input_25[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_8 (MaxPooling1D)  (None, 16, 32)       0           conv1d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "conv1d_9 (Conv1D)               (None, 13, 64)       8256        max_pooling1d_8[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling1d_9 (MaxPooling1D)  (None, 5, 64)        0           conv1d_9[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "global_max_pooling1d_6 (GlobalM (None, 64)           0           max_pooling1d_9[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "dense_19 (Dense)                (None, 32)           2080        global_max_pooling1d_6[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "filter_on_off (Dense)           (None, 2)            66          dense_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "delay_on_off (Dense)            (None, 2)            66          dense_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "disto_on_off (Dense)            (None, 2)            66          dense_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "flanger_on_off (Dense)          (None, 2)            66          dense_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "reverb_on_off (Dense)           (None, 2)            66          dense_19[0][0]                   \n",
      "==================================================================================================\n",
      "Total params: 13,258\n",
      "Trainable params: 13,258\n",
      "Non-trainable params: 0\n",
      "__________________________________________________________________________________________________\n",
      "None\n",
      "filter_on_off (25, 2)\n",
      "delay_on_off (25, 2)\n",
      "disto_on_off (25, 2)\n",
      "flanger_on_off (25, 2)\n",
      "reverb_on_off (25, 2)\n",
      "filter_on_off (7, 2)\n",
      "delay_on_off (7, 2)\n",
      "disto_on_off (7, 2)\n",
      "flanger_on_off (7, 2)\n",
      "reverb_on_off (7, 2)\n",
      "Train on 22 samples, validate on 3 samples\n",
      "Epoch 1/10\n",
      "22/22 [==============================] - 6s 261ms/step - loss: 6.2863 - filter_on_off_loss: 1.1035 - delay_on_off_loss: 1.3368 - disto_on_off_loss: 1.9985 - flanger_on_off_loss: 0.9678 - reverb_on_off_loss: 0.8798 - val_loss: 2.6808 - val_filter_on_off_loss: 0.5479 - val_delay_on_off_loss: 0.1243 - val_disto_on_off_loss: 0.4302 - val_flanger_on_off_loss: 0.9075 - val_reverb_on_off_loss: 0.6709\n",
      "Epoch 2/10\n",
      "22/22 [==============================] - 0s 572us/step - loss: 4.8652 - filter_on_off_loss: 0.7117 - delay_on_off_loss: 0.8524 - disto_on_off_loss: 1.6009 - flanger_on_off_loss: 0.8843 - reverb_on_off_loss: 0.8158 - val_loss: 2.4901 - val_filter_on_off_loss: 0.3693 - val_delay_on_off_loss: 0.2267 - val_disto_on_off_loss: 0.3578 - val_flanger_on_off_loss: 0.9145 - val_reverb_on_off_loss: 0.6219\n",
      "Epoch 3/10\n",
      "22/22 [==============================] - 0s 536us/step - loss: 3.8693 - filter_on_off_loss: 0.5088 - delay_on_off_loss: 0.5666 - disto_on_off_loss: 1.2466 - flanger_on_off_loss: 0.7932 - reverb_on_off_loss: 0.7542 - val_loss: 2.4426 - val_filter_on_off_loss: 0.2589 - val_delay_on_off_loss: 0.3693 - val_disto_on_off_loss: 0.3152 - val_flanger_on_off_loss: 0.9265 - val_reverb_on_off_loss: 0.5727\n",
      "Epoch 4/10\n",
      "22/22 [==============================] - 0s 496us/step - loss: 3.2013 - filter_on_off_loss: 0.4043 - delay_on_off_loss: 0.4625 - disto_on_off_loss: 0.9473 - flanger_on_off_loss: 0.6936 - reverb_on_off_loss: 0.6935 - val_loss: 2.4870 - val_filter_on_off_loss: 0.1893 - val_delay_on_off_loss: 0.5252 - val_disto_on_off_loss: 0.3073 - val_flanger_on_off_loss: 0.9391 - val_reverb_on_off_loss: 0.5261\n",
      "Epoch 5/10\n",
      "22/22 [==============================] - 0s 481us/step - loss: 2.7254 - filter_on_off_loss: 0.3312 - delay_on_off_loss: 0.4420 - disto_on_off_loss: 0.7244 - flanger_on_off_loss: 0.5924 - reverb_on_off_loss: 0.6354 - val_loss: 2.5834 - val_filter_on_off_loss: 0.1417 - val_delay_on_off_loss: 0.6678 - val_disto_on_off_loss: 0.3344 - val_flanger_on_off_loss: 0.9549 - val_reverb_on_off_loss: 0.4846\n",
      "Epoch 6/10\n",
      "22/22 [==============================] - 0s 578us/step - loss: 2.3818 - filter_on_off_loss: 0.2664 - delay_on_off_loss: 0.4427 - disto_on_off_loss: 0.5927 - flanger_on_off_loss: 0.5004 - reverb_on_off_loss: 0.5797 - val_loss: 2.7064 - val_filter_on_off_loss: 0.1071 - val_delay_on_off_loss: 0.7826 - val_disto_on_off_loss: 0.3849 - val_flanger_on_off_loss: 0.9800 - val_reverb_on_off_loss: 0.4518\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 7/10\n",
      "22/22 [==============================] - 0s 679us/step - loss: 2.1360 - filter_on_off_loss: 0.2068 - delay_on_off_loss: 0.4411 - disto_on_off_loss: 0.5346 - flanger_on_off_loss: 0.4260 - reverb_on_off_loss: 0.5275 - val_loss: 2.8308 - val_filter_on_off_loss: 0.0825 - val_delay_on_off_loss: 0.8674 - val_disto_on_off_loss: 0.4390 - val_flanger_on_off_loss: 1.0148 - val_reverb_on_off_loss: 0.4270\n",
      "Epoch 8/10\n",
      "22/22 [==============================] - 0s 723us/step - loss: 1.9424 - filter_on_off_loss: 0.1565 - delay_on_off_loss: 0.4299 - disto_on_off_loss: 0.5070 - flanger_on_off_loss: 0.3681 - reverb_on_off_loss: 0.4809 - val_loss: 2.9369 - val_filter_on_off_loss: 0.0655 - val_delay_on_off_loss: 0.9187 - val_disto_on_off_loss: 0.4838 - val_flanger_on_off_loss: 1.0593 - val_reverb_on_off_loss: 0.4096\n",
      "Epoch 9/10\n",
      "22/22 [==============================] - 0s 490us/step - loss: 1.7710 - filter_on_off_loss: 0.1187 - delay_on_off_loss: 0.4087 - disto_on_off_loss: 0.4801 - flanger_on_off_loss: 0.3221 - reverb_on_off_loss: 0.4414 - val_loss: 3.0160 - val_filter_on_off_loss: 0.0537 - val_delay_on_off_loss: 0.9393 - val_disto_on_off_loss: 0.5146 - val_flanger_on_off_loss: 1.1096 - val_reverb_on_off_loss: 0.3987\n",
      "Epoch 10/10\n",
      "22/22 [==============================] - 0s 522us/step - loss: 1.6120 - filter_on_off_loss: 0.0921 - delay_on_off_loss: 0.3813 - disto_on_off_loss: 0.4447 - flanger_on_off_loss: 0.2845 - reverb_on_off_loss: 0.4094 - val_loss: 3.0693 - val_filter_on_off_loss: 0.0456 - val_delay_on_off_loss: 0.9349 - val_disto_on_off_loss: 0.5311 - val_flanger_on_off_loss: 1.1644 - val_reverb_on_off_loss: 0.3934\n",
      "7/7 [==============================] - 1s 187ms/step\n",
      "filter_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 2, 'filter_on_off', 'class', -1.6120197772979736, 0.8571428571428571)\n",
      "delay_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 2, 'delay_on_off', 'class', -1.6120197772979736, 0.0)\n",
      "disto_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 2, 'disto_on_off', 'class', -1.6120197772979736, 0.2857142857142857)\n",
      "flanger_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 2, 'flanger_on_off', 'class', -1.6120197772979736, 1.0)\n",
      "reverb_on_off\n",
      "(7, 2)\n",
      "('Conv', 'joint', 32, 2, 'reverb_on_off', 'class', -1.6120197772979736, 0.7142857142857143)\n"
     ]
    }
   ],
   "source": [
    "from keras.layers import Conv1D,MaxPooling1D,GlobalMaxPooling1D\n",
    "\n",
    "W = 4\n",
    "\n",
    "def modConvo(n_filters, n_layers):\n",
    "    # Input layer\n",
    "    in_shape = (X_test_mfcc.shape[1],X_test_mfcc.shape[2])\n",
    "    print in_shape\n",
    "    in_layer = Input(shape=in_shape)\n",
    "    \n",
    "    # Hidden layers\n",
    "    h_layer = in_layer\n",
    "    for i in range(n_layers):\n",
    "        print i\n",
    "        conv_layer = Conv1D(n_filters*(i+1), W)(h_layer)\n",
    "        h_layer = MaxPooling1D(W, strides=2)(conv_layer)\n",
    "    \n",
    "    h_layer_pool = GlobalMaxPooling1D()(h_layer)\n",
    "    h_layer_full = Dense(n_filters)(h_layer_pool)\n",
    "    \n",
    "    # Output layers and losses\n",
    "    out_layers = []\n",
    "    losses = {}\n",
    "    metrics = {}\n",
    "    for name,infos in Y_info.iteritems():\n",
    "        \n",
    "        if infos['type'] == 'float64':\n",
    "            out_layer = Dense(1, name=name)(h_layer_full)\n",
    "            losses[name] = 'mean_absolute_error'\n",
    "            metrics[name] = 'mean_absolute_error'\n",
    "            \n",
    "        elif infos['type'] == 'object':\n",
    "            out_dim = len(infos['char2int'])\n",
    "            out_layer = Dense(out_dim, activation='softmax', name=name)(h_layer_full)\n",
    "            losses[name] = 'categorical_crossentropy'\n",
    "            metrics[name] = 'accuracy'\n",
    "\n",
    "        else:\n",
    "            raise ValueError\n",
    "        out_layers.append(out_layer)\n",
    "\n",
    "    model = Model(inputs = in_layer, outputs = out_layers)\n",
    "    model.compile(loss=losses, optimizer='adam')\n",
    "    \n",
    "    print model.summary()\n",
    "    return model\n",
    "\n",
    "for N_FILTERS in [8,16,32]:\n",
    "    for N_LAYERS in [1,2]:\n",
    "        model = modConvo(N_FILTERS, N_LAYERS)\n",
    "        out = test_model('Conv', N_FILTERS, N_LAYERS, model)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing the results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/thib/.virtualenvs/mir/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: Loading tidyverse: ggplot2\n",
      "Loading tidyverse: tibble\n",
      "Loading tidyverse: tidyr\n",
      "Loading tidyverse: readr\n",
      "Loading tidyverse: purrr\n",
      "Loading tidyverse: dplyr\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/Users/thib/.virtualenvs/mir/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: Conflicts with tidy packages ---------------------------------------------------\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n",
      "/Users/thib/.virtualenvs/mir/lib/python2.7/site-packages/rpy2/rinterface/__init__.py:185: RRuntimeWarning: filter(): dplyr, stats\n",
      "lag():    dplyr, stats\n",
      "\n",
      "  warnings.warn(x, RRuntimeWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "  algo  type algo_instance_reg algo_instance_class train_score\n",
       "1 Conv joint                32                   2   -1.612020\n",
       "2 LSTM joint               128                   2   -1.302034\n",
       "3  MLP joint                64                   1   -0.232729\n",
       "           algo metric     score\n",
       "1          Conv  class 0.5714286\n",
       "2 Decision Tree  class 0.7714286\n",
       "3          LSTM  class 0.7428571\n",
       "4           MLP  class 0.8000000\n",
       "5         Naive  class 0.2571429\n",
       "6           kNN  class 0.5714286\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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5URoBBBBAAIFAAgRwIDYKIYAAAgggEE6AAA7nR2kEEEAAAQQCCRDAgdgohAAC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\ntgkQwG1z4lUIIIAAAggUVeD/AR1loNKoSHgAAAAAAElFTkSuQmCC\n"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%%R -i RESULTS_FILE\n",
    "\n",
    "library(tidyverse)\n",
    "\n",
    "# Processing\n",
    "csv <- read.csv(RESULTS_FILE)\n",
    "\n",
    "indep_models <- csv %>% filter(type == 'per_output')\n",
    "\n",
    "joint_models <- csv %>% filter(type == 'joint')\n",
    "to_keep <- joint_models %>% \n",
    "                group_by(algo, type, algo_instance_reg, algo_instance_class) %>%\n",
    "                summarize(train_score = mean(train_score)) %>%\n",
    "                group_by(algo) %>%\n",
    "                filter(train_score == max(train_score)) %>% data.frame()\n",
    "print(to_keep)\n",
    "\n",
    "joint_models <- semi_join(joint_models, to_keep, by=c(\"algo\",\"algo_instance_reg\",\"algo_instance_class\")) %>%\n",
    "                distinct()\n",
    "\n",
    "all_models <- rbind(indep_models, joint_models)\n",
    "\n",
    "# Plotting\n",
    "to_plot <- all_models %>%\n",
    "            select(algo, metric, test_score) %>%\n",
    "            group_by(algo, metric) %>%\n",
    "            summarize(score = mean(test_score)) %>%\n",
    "            as.data.frame\n",
    "print(to_plot)\n",
    "\n",
    "to_plot$metric <- factor(to_plot$metric)\n",
    "\n",
    "p <- ggplot(to_plot, aes(x=factor(algo), y=score)) +\n",
    "    geom_bar(stat='identity') +\n",
    "    facet_grid(metric~., scales='free')\n",
    "p\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}