{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Custom Layers and Models with TensorFlow\n",
    "\n",
    "<!--\n",
    "Project: TensorFlow Deep Learning\n",
    "Author: RSK World\n",
    "Website: https://rskworld.in\n",
    "Email: help@rskworld.in\n",
    "Phone: +91 93305 39277\n",
    "-->\n",
    "\n",
    "This notebook demonstrates how to create custom layers and models in TensorFlow/Keras."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import os\n",
    "sys.path.append(os.path.join(os.path.dirname(os.getcwd()), 'src'))\n",
    "\n",
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "from tensorflow.keras import layers\n",
    "import numpy as np\n",
    "\n",
    "from custom_layers import (\n",
    "    DenseLayer,\n",
    "    AttentionLayer,\n",
    "    ResidualBlock,\n",
    "    CustomCNNModel,\n",
    "    CustomRNNModel,\n",
    "    create_model_with_custom_layers\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Model with Custom Layers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate sample data\n",
    "X_train = np.random.randn(1000, 784).astype('float32')\n",
    "y_train = np.random.randint(0, 10, 1000)\n",
    "\n",
    "# Create model with custom layers\n",
    "model = create_model_with_custom_layers(input_shape=(784,), num_classes=10)\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train Custom Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Train model\n",
    "history = model.fit(\n",
    "    X_train, y_train,\n",
    "    batch_size=32,\n",
    "    epochs=5,\n",
    "    verbose=1\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Custom CNN Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create custom CNN model\n",
    "cnn_model = CustomCNNModel(num_classes=10)\n",
    "cnn_model.build(input_shape=(None, 28, 28, 1))\n",
    "cnn_model.summary()"
   ]
  }
 ],
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