WaveNet/WaveNet_Gluon.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "import mxnet as mx\n",
    "from mxnet import gluon, autograd, nd\n",
    "from mxnet.gluon import nn,utils \n",
    "import mxnet.ndarray as F\n",
    "from IPython.display import Audio\n",
    "from scipy.io import wavfile"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "class One_Hot(nn.Block):\n",
    "    def __init__(self, depth):\n",
    "        super(One_Hot,self).__init__()\n",
    "        self.depth = depth\n",
    "        self.ones = nd.one_hot(nd.arange(depth),depth)\n",
    "        #self.ones = torch.sparse.torch.eye(depth) # pytorch version\n",
    "    def forward(self, X_in):\n",
    "        X_in = X_in\n",
    "        return self.ones[X_in,:]\n",
    "        #return Variable(self.ones.index_select(0,X_in.data))\n",
    "    def __repr__(self):\n",
    "        return self.__class__.__name__ + \"({})\".format(self.depth)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class WaveNet(nn.Block):\n",
    "    def __init__(self, mu=256,n_residue=32, n_skip= 512, dilation_depth=10, n_repeat=5):\n",
    "        # mu: audio quantization size\n",
    "        # n_residue: residue channels\n",
    "        # n_skip: skip channels\n",
    "        # dilation_depth & n_repeat: dilation layer setup\n",
    "        super(WaveNet, self).__init__()\n",
    "        self.dilation_depth = dilation_depth\n",
    "        self.dilations = [2**i for i in range(dilation_depth)] * n_repeat\n",
    "        self.one_hot = One_Hot(mu)\n",
    "        with self.name_scope():\n",
    "            self.from_input = nn.Conv1D(in_channels=mu, channels=n_residue, kernel_size=1)\n",
    "            self.conv_sigmoid = nn.Sequential()\n",
    "            self.conv_tanh = nn.Sequential()\n",
    "            self.skip_scale = nn.Sequential()\n",
    "            self.residue_scale = nn.Sequential()\n",
    "            for d in self.dilations:\n",
    "                self.conv_sigmoid.add(nn.Conv1D(in_channels=n_residue, channels=n_residue, kernel_size=2, dilation=d))\n",
    "                self.conv_tanh.add(nn.Conv1D(in_channels=n_residue, channels=n_residue, kernel_size=2, dilation=d))\n",
    "                self.skip_scale.add(nn.Conv1D(in_channels=n_residue, channels=n_skip, kernel_size=1, dilation=d))\n",
    "                self.residue_scale.add(nn.Conv1D(in_channels=n_residue, channels=n_residue, kernel_size=1, dilation=d))\n",
    "            self.conv_post_1 = nn.Conv1D(in_channels=n_skip, channels=n_skip, kernel_size=1)\n",
    "            self.conv_post_2 = nn.Conv1D(in_channels=n_skip, channels=mu, kernel_size=1)\n",
    "        \n",
    "    def forward(self,x):\n",
    "        output = self.preprocess(x)\n",
    "        skip_connections = [] # save for generation purposes\n",
    "        for s, t, skip_scale, residue_scale in zip(self.conv_sigmoid, self.conv_tanh, self.skip_scale, self.residue_scale):\n",
    "            output, skip = self.residue_forward(output, s, t, skip_scale, residue_scale)\n",
    "            skip_connections.append(skip)\n",
    "        # sum up skip connections\n",
    "        output = sum([s[:,:,-output.shape[2]:] for s in skip_connections])\n",
    "        output = self.postprocess(output)\n",
    "        return output\n",
    "        \n",
    "    def preprocess(self, x):\n",
    "        output = F.transpose(self.one_hot(x).expand_dims(0),axes=(0,2,1))\n",
    "        output = self.from_input(output)\n",
    "        return output\n",
    "\n",
    "    def postprocess(self, x):\n",
    "        output = F.relu(x)\n",
    "        output = self.conv_post_1(output)\n",
    "        output = F.relu(output)\n",
    "        output = self.conv_post_2(output)\n",
    "        output = nd.reshape(output,(output.shape[1],output.shape[2]))\n",
    "        output = F.transpose(output,axes=(1,0))\n",
    "        return output\n",
    "    \n",
    "    def residue_forward(self, x, conv_sigmoid, conv_tanh, skip_scale, residue_scale):\n",
    "        output = x\n",
    "        output_sigmoid, output_tanh = conv_sigmoid(output), conv_tanh(output)\n",
    "        output = F.sigmoid(output_sigmoid) * F.tanh(output_tanh)\n",
    "        skip = skip_scale(output)\n",
    "        output = residue_scale(output)\n",
    "        output = output + x[:,:,-output.shape[2]:]\n",
    "        return output, skip\n",
    "    \n",
    "    def generate_slow(self, x, n=100):\n",
    "        res = list(x.asnumpy())\n",
    "        for _ in range(n):\n",
    "            x = nd.array(res[-sum(self.dilations)-1:])\n",
    "            y = self.forward(x)\n",
    "            #_, i = y.max(dim=1)\n",
    "            res.append(y.argmax(1).asnumpy()[-1])\n",
    "        return res\n",
    "    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sample test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "net = WaveNet(mu=128)\n",
    "net.initialize()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "batch = nd.array(np.random.randint(0,128,10000).astype(np.long))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "y = net(batch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(4885, 128)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CPU times: user 21.6 s, sys: 1.58 s, total: 23.2 s\n",
      "Wall time: 12.9 s\n"
     ]
    }
   ],
   "source": [
    "%time y_gen2 = net.generate_slow(batch, 20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10020"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(y_gen2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## $\\mu$-law encode and decode"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def encode_mu_law(x, mu=256):\n",
    "    mu = mu-1\n",
    "    fx = np.sign(x)*np.log(1+mu*np.abs(x))/np.log(1+mu)\n",
    "    return np.floor((fx+1)/2*mu+0.5).astype(np.long)\n",
    "\n",
    "def decode_mu_law(y, mu=256):\n",
    "    mu = mu-1\n",
    "    fx = (y-0.5)/mu*2-1\n",
    "    x = np.sign(fx)/mu*((1+mu)**np.abs(fx)-1)\n",
    "    return x  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sign wave generation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fdae58972b0>]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdae8314550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def sine_generator(seq_size = 6000, mu=256):\n",
    "    framerate = 44100\n",
    "    t = np.linspace(0,5,framerate*5)\n",
    "    data = np.sin(2*np.pi*220*t) + np.sin(2*np.pi*224*t)\n",
    "    data = data/2\n",
    "    while True:\n",
    "        start = np.random.randint(0,data.shape[0]-seq_size)\n",
    "        ys = data[start:start+seq_size]\n",
    "        ys = encode_mu_law(ys,mu)\n",
    "        yield nd.array(ys[:seq_size])\n",
    "        \n",
    "g = sine_generator(mu=64, seq_size=20000)\n",
    "x = next(g)\n",
    "plt.figure(figsize=[15,3])\n",
    "plt.plot(list(x.asnumpy()),'.', ms=1)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## listen to signal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio controls=\"controls\" >\n",
       "                    <source 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\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#y = np.array(x)\n",
    "y = x.asnumpy()\n",
    "y = decode_mu_law(y, 64)\n",
    "Audio(y,rate=44100)\n",
    "#Audio(y,rate=22000)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## network training\n",
    "\n",
    "This network tries to generate the vibrating sine wave above. \n",
    "- The audio signal is quantized to 64 discrete integers.\n",
    "- 24 channels in residue outputs\n",
    "- 128 channels in skip outputs\n",
    "- 20 dilation layers (n_repeat=2, dilation_depth=10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "net = WaveNet(mu=64,n_residue=24,n_skip=128,dilation_depth=10,n_repeat=2)\n",
    "net.collect_params().initialize()\n",
    "#set optimizer\n",
    "trainer = gluon.Trainer(net.collect_params(),optimizer='adam',optimizer_params={'learning_rate':0.01 })\n",
    "g = sine_generator(seq_size=2200,mu=64)\n",
    "batch_size = 64\n",
    "loss_fn = gluon.loss.SoftmaxCrossEntropyLoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tqdm import tqdm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/1000 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 0, loss 569.0245971679688\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdae8226f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  1%|          | 10/1000 [02:34<4:15:30, 15.49s/it]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch 10, loss 210.47340393066406\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fdae81efdd8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "  1%|          | 12/1000 [03:06<4:15:41, 15.53s/it]"
     ]
    }
   ],
   "source": [
    "loss_save = []\n",
    "max_epoch = 1000\n",
    "for epoch in tqdm(range(max_epoch)):\n",
    "    loss = 0.0\n",
    "    for _ in range(batch_size):\n",
    "        batch = next(g)\n",
    "        x = batch[:-1]\n",
    "        with autograd.record():\n",
    "            logits = net(x)\n",
    "            sz = logits.shape[0]\n",
    "            loss = loss + loss_fn(logits, batch[-sz:])\n",
    "            #loss = loss/batch_size\n",
    "        loss.backward()\n",
    "        trainer.step(1,ignore_stale_grad=True)\n",
    "    loss_save.append(nd.sum(loss).asscalar()/batch_size)\n",
    "    # monitor progress\n",
    "    if epoch%10==0:\n",
    "        print('epoch {}, loss {}'.format(epoch, nd.sum(loss).asscalar()/batch_size))\n",
    "        batch = next(g)\n",
    "        logits = net(batch[:-1])\n",
    "        #_, i = logits.max(dim=1)\n",
    "        i = logits.argmax(1).asnumpy()\n",
    "        plt.figure(figsize=[16,4])\n",
    "        plt.plot(list(i))\n",
    "        plt.plot(list(batch.asnumpy())[sum(net.dilations)+1:],'.',ms=1)\n",
    "        plt.title('epoch {}'.format(epoch))\n",
    "        plt.tight_layout()\n",
    "        plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}