infer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import miditoolkit\n",
    "import utils"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import torch.nn as nn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "cuda\n"
     ]
    }
   ],
   "source": [
    "# 1. GPU configuration\n",
    "import os\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"1\"\n",
    "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')\n",
    "print(device)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Load model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "class Encoder(nn.Module):\n",
    "    def __init__(self, input_dim, emb_dim, hid_dim, n_layers, dropout):\n",
    "        super().__init__()\n",
    "        \n",
    "        self.hid_dim = hid_dim\n",
    "        self.n_layers = n_layers\n",
    "        \n",
    "        self.embedding = nn.Embedding(input_dim, emb_dim)\n",
    "        \n",
    "        self.rnn = nn.LSTM(emb_dim, hid_dim, n_layers, dropout = dropout)\n",
    "        \n",
    "        self.dropout = nn.Dropout(dropout)\n",
    "        \n",
    "    def forward(self, src):\n",
    "        \n",
    "        #src = [src len, batch size]\n",
    "        \n",
    "        embedded = self.dropout(self.embedding(src))\n",
    "        \n",
    "        #embedded = [src len, batch size, emb dim]\n",
    "        \n",
    "        outputs, (hidden, cell) = self.rnn(embedded)\n",
    "        \n",
    "        #outputs = [src len, batch size, hid dim * n directions]\n",
    "        #hidden = [n layers * n directions, batch size, hid dim]\n",
    "        #cell = [n layers * n directions, batch size, hid dim]\n",
    "        \n",
    "        #outputs are always from the top hidden layer\n",
    "        \n",
    "        return hidden, cell\n",
    "class Decoder(nn.Module):\n",
    "    def __init__(self, output_dim, emb_dim, hid_dim, n_layers, dropout):\n",
    "        super().__init__()\n",
    "        \n",
    "        self.output_dim = output_dim\n",
    "        self.hid_dim = hid_dim\n",
    "        self.n_layers = n_layers\n",
    "        \n",
    "        self.embedding = nn.Embedding(output_dim, emb_dim)\n",
    "        \n",
    "        self.rnn = nn.LSTM(emb_dim, hid_dim, n_layers, dropout = dropout)\n",
    "        \n",
    "        self.fc_out = nn.Linear(hid_dim, output_dim)\n",
    "        \n",
    "        self.dropout = nn.Dropout(dropout)\n",
    "        \n",
    "    def forward(self, input, hidden, cell):\n",
    "        \n",
    "        #input = [batch size]\n",
    "        #hidden = [n layers * n directions, batch size, hid dim]\n",
    "        #cell = [n layers * n directions, batch size, hid dim]\n",
    "        \n",
    "        #n directions in the decoder will both always be 1, therefore:\n",
    "        #hidden = [n layers, batch size, hid dim]\n",
    "        #context = [n layers, batch size, hid dim]\n",
    "        \n",
    "        input = input.unsqueeze(0)\n",
    "        \n",
    "        #input = [1, batch size]\n",
    "        \n",
    "        embedded = self.dropout(self.embedding(input))\n",
    "        \n",
    "        #embedded = [1, batch size, emb dim]\n",
    "                \n",
    "        output, (hidden, cell) = self.rnn(embedded, (hidden, cell))\n",
    "        \n",
    "        #output = [seq len, batch size, hid dim * n directions]\n",
    "        #hidden = [n layers * n directions, batch size, hid dim]\n",
    "        #cell = [n layers * n directions, batch size, hid dim]\n",
    "        \n",
    "        #seq len and n directions will always be 1 in the decoder, therefore:\n",
    "        #output = [1, batch size, hid dim]\n",
    "        #hidden = [n layers, batch size, hid dim]\n",
    "        #cell = [n layers, batch size, hid dim]\n",
    "        \n",
    "        prediction = self.fc_out(output.squeeze(0))\n",
    "        #prediction = [batch size, output dim]\n",
    "        \n",
    "        return prediction, hidden, cell\n",
    "class Seq2Seq(nn.Module):\n",
    "    def __init__(self, encoder, decoder, device):\n",
    "        super().__init__()\n",
    "        \n",
    "        self.encoder = encoder\n",
    "        self.decoder = decoder\n",
    "        self.device = device\n",
    "        \n",
    "        assert encoder.hid_dim == decoder.hid_dim, \\\n",
    "            \"Hidden dimensions of encoder and decoder must be equal!\"\n",
    "        assert encoder.n_layers == decoder.n_layers, \\\n",
    "            \"Encoder and decoder must have equal number of layers!\"\n",
    "        \n",
    "    def forward(self, src):\n",
    "        \n",
    "        #src = [src len, batch size]\n",
    "        #trg = [trg len, batch size]\n",
    "        #teacher_forcing_ratio is probability to use teacher forcing\n",
    "        #e.g. if teacher_forcing_ratio is 0.75 we use ground-truth inputs 75% of the time\n",
    "        \n",
    "        ########################################\n",
    "        ### inference\n",
    "        ########################################\n",
    "        #pdb.set_trace()\n",
    "        \n",
    "        hidden, cell = self.encoder(src)\n",
    "        \n",
    "        input = torch.IntTensor([int(0)]).cuda() ## sos\n",
    "        eos = False\n",
    "        infer_melody_list = []\n",
    "        \n",
    "        cnt = 0\n",
    "        while not(eos):\n",
    "            output, hidden, cell = self.decoder(input, hidden, cell)\n",
    "            top1 = output.argmax(1)\n",
    "            infer_melody_list.append(top1.item())\n",
    "            input = top1\n",
    "            print(top1.item())\n",
    "            cnt+=1\n",
    "            if top1.item() == 308:\n",
    "                eos = True\n",
    "            if cnt == 5000:\n",
    "                break\n",
    "        return infer_melody_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "'''\n",
    "INPUT_DIM = 60\n",
    "ENC_EMB_DIM = 16\n",
    "\n",
    "OUTPUT_DIM = 309\n",
    "DEC_EMB_DIM = 32\n",
    "\n",
    "HID_DIM = 512\n",
    "N_LAYERS = 2\n",
    "'''\n",
    "INPUT_DIM = 60\n",
    "ENC_EMB_DIM = 32\n",
    "\n",
    "OUTPUT_DIM = 309\n",
    "DEC_EMB_DIM = 64\n",
    "\n",
    "HID_DIM = 512\n",
    "N_LAYERS = 3\n",
    "\n",
    "ENC_DROPOUT = 0.5\n",
    "DEC_DROPOUT = 0.5\n",
    "\n",
    "enc = Encoder(INPUT_DIM, ENC_EMB_DIM, HID_DIM, N_LAYERS, ENC_DROPOUT)\n",
    "dec = Decoder(OUTPUT_DIM, DEC_EMB_DIM, HID_DIM, N_LAYERS, DEC_DROPOUT)\n",
    "\n",
    "model = Seq2Seq(enc, dec, device).to(device)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Seq2Seq(\n",
       "  (encoder): Encoder(\n",
       "    (embedding): Embedding(60, 32)\n",
       "    (rnn): LSTM(32, 512, num_layers=3, dropout=0.5)\n",
       "    (dropout): Dropout(p=0.5, inplace=False)\n",
       "  )\n",
       "  (decoder): Decoder(\n",
       "    (embedding): Embedding(309, 64)\n",
       "    (rnn): LSTM(64, 512, num_layers=3, dropout=0.5)\n",
       "    (fc_out): Linear(in_features=512, out_features=309, bias=True)\n",
       "    (dropout): Dropout(p=0.5, inplace=False)\n",
       "  )\n",
       ")"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "saved_model_path =  './model_ckpt/0628_12_epoch_6000_step.pt'\n",
    "model.load_state_dict(torch.load(saved_model_path))\n",
    "model.eval()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Inference"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "list"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pickle5 as pickle\n",
    "\n",
    "chord_dict_path = \"./data/chord2idx_dict.pkl\"\n",
    "chord2idx = pickle.load(open(chord_dict_path, 'rb'))\n",
    "\n",
    "input_data_path =  \"./data/all_chord_4_bars.pkl\"\n",
    "all_chord_event_list = pickle.load(open(input_data_path, 'rb'))\n",
    "type(all_chord_event_list[0][\"Chord\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'C#:maj': 0, 'B:maj': 1, 'C#:min': 2, 'A:maj': 3, 'F:maj': 4, 'C:maj': 5, 'D:maj': 6, 'G:maj': 7, 'A#:maj': 8, 'G:min': 9, 'E:min': 10, 'A:min': 11, 'F#:maj': 12, 'D#:maj': 13, 'D:aug': 14, 'D#:aug': 15, 'C:min': 16, 'G#:maj': 17, 'F#:min': 18, 'B:min': 19, 'G#:min': 20, 'D#:min': 21, 'F:dom': 22, 'F:min': 23, 'D:min': 24, 'B:dim': 25, 'E:dom': 26, 'E:maj': 27, 'D#:dim': 28, 'A#:min': 29, 'D:dom': 30, 'A#:dom': 31, 'A:aug': 32, 'C:dim': 33, 'A:dom': 34, 'G:dom': 35, 'G#:dim': 36, 'E:dim': 37, 'C#:dim': 38, 'D#:dom': 39, 'F:aug': 40, 'G:dim': 41, 'C#:aug': 42, 'C:aug': 43, 'F#:dim': 44, 'A#:dim': 45, 'G#:dom': 46, 'G:aug': 47, 'B:aug': 48, 'D:dim': 49, 'F:dim': 50, 'B:dom': 51, 'C:dom': 52, 'A:dim': 53, 'F#:aug': 54, 'E:aug': 55, 'G#:aug': 56, 'F#:dom': 57, 'C#:dom': 58, 'A#:aug': 59}\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[2, 27, 1, 3]"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## -- generate test chord sequence\n",
    "#test_chord_sequence = ['E:dom', 'B:dom','C#:min','A:dom','E:dom', 'B:dom','C#:min','A:dom']\n",
    "#test_chord_sequence = ['C:maj','A:min','D:min','G:maj']\n",
    "test_chord_sequence = ['C#:min','E:maj','B:maj','A:maj']\n",
    "test_chord_idx_sequence = [chord2idx[x] for x in test_chord_sequence]\n",
    "all_chord_event_list[0][\"Chord\"]\n",
    "print(chord2idx)\n",
    "test_chord_idx_sequence\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--Return--\n",
      "None\n",
      "> \u001b[0;32m/tmp/ipykernel_60796/958066533.py\u001b[0m(6)\u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32m      4 \u001b[0;31m\u001b[0;32mimport\u001b[0m \u001b[0mpdb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m      5 \u001b[0;31m\u001b[0minput\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtensor\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtest_chord_idx_sequence\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munsqueeze\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;31m# [seq_len, 1]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m----> 6 \u001b[0;31m\u001b[0mpdb\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_trace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m      7 \u001b[0;31m\u001b[0minfer_melody_list\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\u001b[0;32m      8 \u001b[0;31m\u001b[0mlen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minfer_melody_list\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0m\n"
     ]
    },
    {
     "name": "stdin",
     "output_type": "stream",
     "text": [
      "ipdb>  c\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    },
    {
     "data": {
      "text/plain": [
       "524"
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## -- inference loop\n",
    "random_seed = 200\n",
    "torch.manual_seed(random_seed)\n",
    "import pdb\n",
    "input = torch.tensor(test_chord_idx_sequence).unsqueeze(-1).cuda() # [seq_len, 1]\n",
    "pdb.set_trace()\n",
    "infer_melody_list = model(input)\n",
    "len(infer_melody_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    },
    "tags": []
   },
   "outputs": [
    {
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       " 308]"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## -- melody token to MIDI\n",
    "event_dict_path =  \"./REMI-tempo-chord-checkpoint/dictionary.pkl\"\n",
    "event2word, word2event = pickle.load(open(event_dict_path, 'rb'))\n",
    "\n",
    "infer_melody_list.insert(0,0)\n",
    "infer_melody_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Bar_None',\n",
       " 'Position_1/16',\n",
       " 'Chord_E:maj',\n",
       " 'Position_1/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_30',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_44',\n",
       " 'Note Duration_32',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_56',\n",
       " 'Note Duration_11',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_11',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_68',\n",
       " 'Note Duration_11',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_37',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_7/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_56',\n",
       " 'Note Duration_7',\n",
       " 'Position_7/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_7/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_68',\n",
       " 'Note Duration_3',\n",
       " 'Position_7/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_3',\n",
       " 'Position_7/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_73',\n",
       " 'Note Duration_3',\n",
       " 'Position_9/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_35',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_56',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_11/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_3',\n",
       " 'Position_11/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Note On_75',\n",
       " 'Note Duration_3',\n",
       " 'Position_13/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_35',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_49',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_56',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_68',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_3',\n",
       " 'Position_15/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_3',\n",
       " 'Position_15/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_78',\n",
       " 'Note Duration_3',\n",
       " 'Bar_None',\n",
       " 'Position_1/16',\n",
       " 'Chord_G#:min',\n",
       " 'Position_1/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_32',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_32',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_35',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_44',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_51',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_56',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_30',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_49',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_54',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_30',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Bar_None',\n",
       " 'Position_1/16',\n",
       " 'Chord_G#:min',\n",
       " 'Position_1/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_32',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_32',\n",
       " 'Note Duration_0',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_32',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_44',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_51',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_56',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_30',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_49',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_54',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_30',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_49',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_54',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_56',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Bar_None',\n",
       " 'Position_1/16',\n",
       " 'Chord_G#:min',\n",
       " 'Position_1/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_32',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_30',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_68',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_1/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_32',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_16',\n",
       " 'Note On_40',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_49',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_54',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_5/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_78',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_32',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_49',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_54',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_75',\n",
       " 'Note Duration_7',\n",
       " 'Position_9/16',\n",
       " 'Tempo Class_mid',\n",
       " 'Tempo Value_30',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_30',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_42',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_54',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_58',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_17',\n",
       " 'Note On_61',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_8',\n",
       " 'Position_13/16',\n",
       " 'Note Velocity_18',\n",
       " 'Note On_71',\n",
       " 'Note Duration_8']"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "## -- check in REMI token\n",
    "infer_token_list = [word2event[x] for x in infer_melody_list[:-1]]\n",
    "infer_token_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "524"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "try:\n",
    "    infer_melody_item = [word2event[x] for x in infer_melody_list]\n",
    "except KeyError:\n",
    "    infer_melody_item = [word2event[x] for x in infer_melody_list[:-1]]\n",
    "    infer_melody_list = infer_melody_list[:-1]\n",
    "len(infer_melody_item)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "import utils\n",
    "MIDI_PATH = \"./CEBA.midi\"\n",
    "utils.write_midi(words = infer_melody_list,\n",
    "                word2event = word2event,\n",
    "                output_path = MIDI_PATH,\n",
    "                prompt_path = None)"
   ]
  }
 ],
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