From 4e80759b3944fa02b7c8c31389e8584f957bf36d Mon Sep 17 00:00:00 2001
From: Shubbair <hussainsalih.github@gmail.com>
Date: Tue, 30 Jul 2024 02:06:52 +0300
Subject: [PATCH] Updating GAN Code...

---
 gan/playground.ipynb | 155 +++++++++++++++++++++----------------------
 1 file changed, 77 insertions(+), 78 deletions(-)

diff --git a/gan/playground.ipynb b/gan/playground.ipynb
index 8500a551..40949f7d 100644
--- a/gan/playground.ipynb
+++ b/gan/playground.ipynb
@@ -9,7 +9,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 244,
+   "execution_count": 369,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 245,
+   "execution_count": 370,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -47,7 +47,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 246,
+   "execution_count": 371,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -55,20 +55,20 @@
     "   \n",
     "    return nn.Sequential(\n",
     "        nn.Linear(in_dim,out_dim),\n",
-    "        nn.BatchNorm(out_dim),\n",
-    "        nn.ReLU()\n",
+    "        nn.BatchNorm(out_dim, 0.8),\n",
+    "        nn.LeakyReLU(0.2)\n",
     "    )"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 247,
+   "execution_count": 393,
    "metadata": {},
    "outputs": [],
    "source": [
     "class Generator(nn.Module):\n",
     "\n",
-    "    def __init__(self, z_dim:int = 10, im_dim:int = 784, hidden_dim: int = 128):\n",
+    "    def __init__(self, z_dim:int = 10, im_dim:int = 784, hidden_dim: int = 256):\n",
     "        super(Generator, self).__init__()\n",
     "        # Build the neural network\n",
     "        self.gen = nn.Sequential(\n",
@@ -79,17 +79,16 @@
     "\n",
     "\n",
     "            nn.Linear(hidden_dim * 8,im_dim),\n",
-    "            nn.Sigmoid()\n",
     "        )\n",
     "        \n",
     "    def __call__(self, noise):\n",
-    "\n",
-    "        return self.gen(noise)"
+    "        x = self.gen(noise)\n",
+    "        return mx.tanh(x)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 248,
+   "execution_count": 394,
    "metadata": {},
    "outputs": [
     {
@@ -98,32 +97,31 @@
        "Generator(\n",
        "  (gen): Sequential(\n",
        "    (layers.0): Sequential(\n",
-       "      (layers.0): Linear(input_dims=100, output_dims=128, bias=True)\n",
-       "      (layers.1): BatchNorm(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
-       "      (layers.2): ReLU()\n",
+       "      (layers.0): Linear(input_dims=100, output_dims=256, bias=True)\n",
+       "      (layers.1): BatchNorm(256, eps=0.8, momentum=0.1, affine=True, track_running_stats=True)\n",
+       "      (layers.2): LeakyReLU()\n",
        "    )\n",
        "    (layers.1): Sequential(\n",
-       "      (layers.0): Linear(input_dims=128, output_dims=256, bias=True)\n",
-       "      (layers.1): BatchNorm(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
-       "      (layers.2): ReLU()\n",
+       "      (layers.0): Linear(input_dims=256, output_dims=512, bias=True)\n",
+       "      (layers.1): BatchNorm(512, eps=0.8, momentum=0.1, affine=True, track_running_stats=True)\n",
+       "      (layers.2): LeakyReLU()\n",
        "    )\n",
        "    (layers.2): Sequential(\n",
-       "      (layers.0): Linear(input_dims=256, output_dims=512, bias=True)\n",
-       "      (layers.1): BatchNorm(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
-       "      (layers.2): ReLU()\n",
+       "      (layers.0): Linear(input_dims=512, output_dims=1024, bias=True)\n",
+       "      (layers.1): BatchNorm(1024, eps=0.8, momentum=0.1, affine=True, track_running_stats=True)\n",
+       "      (layers.2): LeakyReLU()\n",
        "    )\n",
        "    (layers.3): Sequential(\n",
-       "      (layers.0): Linear(input_dims=512, output_dims=1024, bias=True)\n",
-       "      (layers.1): BatchNorm(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
-       "      (layers.2): ReLU()\n",
+       "      (layers.0): Linear(input_dims=1024, output_dims=2048, bias=True)\n",
+       "      (layers.1): BatchNorm(2048, eps=0.8, momentum=0.1, affine=True, track_running_stats=True)\n",
+       "      (layers.2): LeakyReLU()\n",
        "    )\n",
-       "    (layers.4): Linear(input_dims=1024, output_dims=784, bias=True)\n",
-       "    (layers.5): Sigmoid()\n",
+       "    (layers.4): Linear(input_dims=2048, output_dims=784, bias=True)\n",
        "  )\n",
        ")"
       ]
      },
-     "execution_count": 248,
+     "execution_count": 394,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -135,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 249,
+   "execution_count": 374,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -146,12 +144,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 250,
+   "execution_count": 375,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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YBQBAYBQAAIFRAAAERgEAEBgFAEBgFAAAgVEAAARGAQAQGAUAQGAUAAAh6ytMPT099psfP37cbr72ta/ZjSSdOHHCbjZv3mw3N998s908+OCDdrN+/Xq7kaSmpia7STny19bWZjfjxo2zGyntuN3w4cPtZtasWXbz/PPP283KlSvtRpJ6e3vtJuX31NnZaTcpx+22bdtmN5J09epVu5k4caLdjBo1ym5S//1688037aaqqirps/rCkwIAIDAKAIDAKAAAAqMAAAiMAgAgMAoAgMAoAAACowAACIwCACAwCgCAwCgAAAKjAAAIWR/EO3v2rP3mKUeo3n33XbuRpJaWFrspKyuzm8997nN209zcbDcpx9kk6cyZM3ZTVFRkN1OmTLGb/v3T/j9Iyt/Rrl277CbliF5ra6vdzJgxw24k6caNG3aTcsiyuLjYbk6dOmU3K1assBtJKikpsZuf//zndlNdXW03Kd8/Sbr77rvt5ujRo0mf1ReeFAAAgVEAAARGAQAQGAUAQGAUAACBUQAABEYBABAYBQBAYBQAAIFRAAAERgEAEBgFAEDI+iBee3u7/eZjx461m/r6eruRpMcee8xuHn/8cbsZP3683Rw+fPg/8jmStGTJErsZOXKk3ezdu9dumpqa7EaS/v73v9tNys/v2LFjdpNyNG3EiBF2I0kvvfSS3dx2221209DQYDdr1661m9raWruRpCNHjtjN4MGD7ebEiRN209HRYTeSdPXqVbs5dOiQ3TzyyCN9voYnBQBAYBQAAIFRAAAERgEAEBgFAEBgFAAAgVEAAARGAQAQGAUAQGAUAACBUQAABEYBABD6ZTKZTDYvfPrpp+0337p1q93cdNNNdiNJ58+ft5s5c+bYze9//3u7+eEPf2g3FRUVdiNJr776qt1MnDjRboqKiuyms7PTblI/a+fOnXZz33332c0HH3xgNynHzyTp+vXrdrNlyxa7eeCBB+ymvLzcbrZt22Y3kjR//ny7KSwstJsBAwbYzZ133mk3UtqRv7q6Ort5/fXX+3wNTwoAgMAoAAACowAACIwCACAwCgCAwCgAAAKjAAAIjAIAIDAKAIDAKAAAAqMAAAiMAgAgMAoAgJCb7QvLysrsN0+5Qtre3m43Utp1wgkTJthNU1OT3fTv72/vD37wA7uRpFtvvdVuUi5c1tfX201paandSFJeXp7d3HvvvXaTn59vNykXXFO+S5JUUlJiN7fffrvdjBgxwm6OHz9uN/fcc4/dSNKCBQvsprGx0W5u3LhhN+vWrbMbSZo8ebLddHV1JX1WX3hSAAAERgEAEBgFAEBgFAAAgVEAAARGAQAQGAUAQGAUAACBUQAABEYBABAYBQBAYBQAAKFfJpPJZPPCRx991H7zHTt22E3KYTsp7TDZX//6V7sZOXKk3bS1tdnNQw89ZDeSNHr0aLtJOW7X09NjN5WVlXYjSXV1dXazcuVKu2loaLCbzs5Ou0k9BDd8+HC7efnll+1m+vTpdnPlyhW7STlIKUkFBQV2c/ToUbu5cOGC3XzyySd2I6UdD73pppvsZvXq1X2+hicFAEBgFAAAgVEAAARGAQAQGAUAQGAUAACBUQAABEYBABAYBQBAYBQAAIFRAAAERgEAELI+iPfkk0/ab15YWGg3OTk5diNJ/fv7+3b69Gm7aW1ttZuUA2MlJSV2I0n79u2zm7y8PLu5ceOG3aQcE5Sks2fP2s2pU6fspqKiwm5S/tuOHz9uN5LU1dVlNytWrLCblpYWuzlw4IDdDBo0yG4kad68eXbzl7/8xW4uXbpkN/fdd5/dSNLmzZvtJuX7tGHDhj5fw5MCACAwCgCAwCgAAAKjAAAIjAIAIDAKAIDAKAAAAqMAAAiMAgAgMAoAgMAoAAACowAACLnZvjDluF1lZaXd1NXV2Y0k1dTU2E3K8b29e/fazYcffmg33d3ddiNJixcvtpuUg33r1q2zm4KCAruRpKFDh9rNsGHD7Ka0tNRuUo7oFRcX242Udrjwj3/8o9088sgjdnPixAm7KSoqshtJ+tvf/mY3n/3sZ+0m5eddVlZmN5K0YMECuxk8eHDSZ/WFJwUAQGAUAACBUQAABEYBABAYBQBAYBQAAIFRAAAERgEAEBgFAEBgFAAAgVEAAARGAQAQGAUAQMj6Surp06ftNz948KDdpF6QfOWVV+ymvLzcbh5++GG72bNnj92cO3fObiSpo6PDbt599127mT17tt2kXDuV0q5ijhkzxm7a2trspqenx27Gjh1rN5L06aef2s3SpUvt5vLly3aTchF58uTJdiNJTU1NdtPQ0GA3Q4YMsZuqqiq7kaQrV67YzbJly5I+qy88KQAAAqMAAAiMAgAgMAoAgMAoAAACowAACIwCACAwCgCAwCgAAAKjAAAIjAIAIDAKAIDQL5PJZLJ54YIFC+w3nzZtmt309vbajSTNmzfPbj766CO7STnYd/36dbvp6uqyG0k6fPiw3SxZssRu3nvvPbupqamxGyntoGBFRYXdpPyeDh06ZDepv9u7777bblKOEK5fv95uFi5caDcbN260GyntO5hyhLC6utpuUv5WJWncuHF2c/ToUbtZu3Ztn6/hSQEAEBgFAEBgFAAAgVEAAARGAQAQGAUAQGAUAACBUQAABEYBABAYBQBAYBQAAIFRAACErA/iAQD+/+NJAQAQGAUAQGAUAACBUQAABEYBABAYBQBAYBQAAIFRAAAERgEAEP4LQdu121Bjz+sAAAAASUVORK5CYII=",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -176,7 +174,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 251,
+   "execution_count": 376,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -189,7 +187,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 252,
+   "execution_count": 377,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -199,11 +197,15 @@
     "        super(Discriminator, self).__init__()\n",
     "\n",
     "        self.disc = nn.Sequential(\n",
-    "            DisBlock(im_dim, hidden_dim * 4),\n",
-    "            DisBlock(hidden_dim * 4, hidden_dim * 2),\n",
+    "            # DisBlock(im_dim, hidden_dim * 4),\n",
+    "            # DisBlock(hidden_dim * 4, hidden_dim * 2),\n",
+    "            # DisBlock(hidden_dim * 2, hidden_dim),\n",
+    "            \n",
+    "            DisBlock(im_dim, hidden_dim * 2),\n",
     "            DisBlock(hidden_dim * 2, hidden_dim),\n",
     "\n",
     "            nn.Linear(hidden_dim,1),\n",
+    "            nn.Sigmoid()\n",
     "        )\n",
     "        \n",
     "    def __call__(self, noise):\n",
@@ -212,7 +214,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 253,
+   "execution_count": 378,
    "metadata": {},
    "outputs": [
     {
@@ -221,23 +223,20 @@
        "Discriminator(\n",
        "  (disc): Sequential(\n",
        "    (layers.0): Sequential(\n",
-       "      (layers.0): Linear(input_dims=784, output_dims=512, bias=True)\n",
+       "      (layers.0): Linear(input_dims=784, output_dims=256, bias=True)\n",
        "      (layers.1): LeakyReLU()\n",
        "    )\n",
        "    (layers.1): Sequential(\n",
-       "      (layers.0): Linear(input_dims=512, output_dims=256, bias=True)\n",
-       "      (layers.1): LeakyReLU()\n",
-       "    )\n",
-       "    (layers.2): Sequential(\n",
        "      (layers.0): Linear(input_dims=256, output_dims=128, bias=True)\n",
        "      (layers.1): LeakyReLU()\n",
        "    )\n",
-       "    (layers.3): Linear(input_dims=128, output_dims=1, bias=True)\n",
+       "    (layers.2): Linear(input_dims=128, output_dims=1, bias=True)\n",
+       "    (layers.3): Sigmoid()\n",
        "  )\n",
        ")"
       ]
      },
-     "execution_count": 253,
+     "execution_count": 378,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -270,7 +269,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 254,
+   "execution_count": 379,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -283,14 +282,14 @@
     "    \n",
     "    fake_labels = mx.zeros((fake_images.shape[0],1))\n",
     "        \n",
-    "    fake_loss = nn.losses.binary_cross_entropy(fake_disc,fake_labels,with_logits=True)\n",
+    "    fake_loss = nn.losses.binary_cross_entropy(fake_disc,fake_labels)\n",
     "    \n",
     "    real_disc = disc(real)\n",
     "    real_labels = mx.ones((real.shape[0],1))\n",
     "\n",
-    "    real_loss = nn.losses.binary_cross_entropy(real_disc,real_labels,with_logits=True)\n",
+    "    real_loss = nn.losses.binary_cross_entropy(real_disc,real_labels)\n",
     "\n",
-    "    disc_loss = (fake_loss + real_loss) / 2.0\n",
+    "    disc_loss = (fake_loss + real_loss) / 2\n",
     "\n",
     "    return disc_loss"
    ]
@@ -304,26 +303,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 255,
+   "execution_count": 380,
    "metadata": {},
    "outputs": [],
    "source": [
     "def gen_loss(gen, disc, num_images, z_dim):\n",
     "\n",
     "    noise = mx.array(get_noise(num_images, z_dim))\n",
+    "    \n",
     "    fake_images = gen(noise)\n",
     "    fake_disc = disc(fake_images)\n",
     "\n",
     "    fake_labels = mx.ones((fake_images.shape[0],1))\n",
     "            \n",
-    "    gen_loss = nn.losses.binary_cross_entropy(fake_disc,fake_labels,with_logits=True)\n",
+    "    gen_loss = nn.losses.binary_cross_entropy(fake_disc,fake_labels)\n",
     "\n",
     "    return gen_loss"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 256,
+   "execution_count": 381,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -333,7 +333,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 257,
+   "execution_count": 382,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -343,16 +343,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 258,
+   "execution_count": 383,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x302feb1f0>"
+       "<matplotlib.image.AxesImage at 0x157b0bb80>"
       ]
      },
-     "execution_count": 258,
+     "execution_count": 383,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -373,7 +373,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 259,
+   "execution_count": 384,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -386,7 +386,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 260,
+   "execution_count": 385,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -410,12 +410,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 261,
+   "execution_count": 386,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x500 with 25 Axes>"
       ]
@@ -431,22 +431,6 @@
     "    break"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 262,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "z_dim = 64\n",
-    "gen = Generator(z_dim)\n",
-    "mx.eval(gen.parameters())\n",
-    "gen_opt = optim.Adam(learning_rate=lr)\n",
-    "\n",
-    "disc = Discriminator()\n",
-    "mx.eval(disc.parameters())\n",
-    "disc_opt = optim.Adam(learning_rate=lr)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -456,26 +440,41 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 263,
+   "execution_count": 391,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lr = 0.002\n",
+    "z_dim = 100\n",
+    "\n",
+    "gen = Generator(z_dim)\n",
+    "mx.eval(gen.parameters())\n",
+    "gen_opt = optim.Adam(learning_rate=lr,betas=[0.5, 0.999])\n",
+    "\n",
+    "disc = Discriminator()\n",
+    "mx.eval(disc.parameters())\n",
+    "disc_opt = optim.Adam(learning_rate=lr,betas=[0.5, 0.999])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 395,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "  0%|          | 0/200 [00:00<?, ?it/s]"
+      "  4%|▍         | 9/200 [00:59<21:10,  6.65s/it]"
      ]
     }
    ],
    "source": [
     "# Set your parameters\n",
     "n_epochs = 200\n",
-    "z_dim = 64\n",
     "display_step = 5000\n",
     "cur_step = 0\n",
     "\n",
-    "lr = 0.00001\n",
-    "\n",
     "batch_size = 128\n",
     "\n",
     "D_loss_grad = nn.value_and_grad(disc, disc_loss)\n",
@@ -487,7 +486,7 @@
     "    for real in batch_iterate(batch_size, train_images):\n",
     "                \n",
     "        # TODO Train Discriminator\n",
-    "        D_loss,D_grads = D_loss_grad(gen, disc, mx.array(real), batch_size, z_dim)\n",
+    "        D_loss,D_grads = D_loss_grad(gen, disc,mx.array(real), batch_size, z_dim)\n",
     "\n",
     "        # Update optimizer\n",
     "        disc_opt.update(disc, D_grads)\n",