{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This notebook demonstrates basic tensor operations in Burn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "rust"
    }
   },
   "outputs": [],
   "source": [
    "// Dependency declarations for the notebook. WARNING: It may take a while to compile the first time.\n",
    "\n",
    "// The syntax is similar to the one used in the Cargo.toml file. Just prefix with :dep\n",
    "// See: https://github.com/evcxr/evcxr/blob/main/COMMON.md\n",
    "\n",
    ":dep burn = {path = \"../../crates/burn\"}\n",
    ":dep burn-ndarray = {path = \"../../crates/burn-ndarray\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "rust"
    }
   },
   "outputs": [],
   "source": [
    "// Import packages\n",
    "use burn::prelude::*;\n",
    "use burn_ndarray::NdArray;\n",
    "\n",
    "// Type alias for the backend\n",
    "type B = NdArray<f32>;"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tensor creation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "rust"
    }
   },
   "outputs": [],
   "source": [
    "// A device the tensors will be stored on\n",
    "let device = <B as Backend>::Device::default();\n",
    "// Create an empty tensor for a given shape\n",
    "let tensor: Tensor<B, 3> = Tensor::empty([1, 2, 3], &device);\n",
    "println!(\"Empty tensor: {}\", tensor);\n",
    "\n",
    "// Create a tensor from a slice of floats\n",
    "let tensor: Tensor<B, 2> = Tensor::from_floats([1.0, 2.0, 3.0, 4.0], &device).reshape([2, 2]);\n",
    "println!(\"Tensor from slice: {}\", tensor);\n",
    "\n",
    "// Create a random tensor\n",
    "use burn::tensor::Distribution;\n",
    "let tensor: Tensor<B, 1> = Tensor::random([5], Distribution::Default, &device);\n",
    "println!(\"Random tensor: {}\", tensor);\n",
    "\n",
    "// Create a tensor using fill values, zeros, or ones\n",
    "let tensor: Tensor<B,2> = Tensor::full([2, 2], 7.0, &device);\n",
    "let tensor: Tensor<B,2> = Tensor::zeros([2, 2], &device);\n",
    "let tensor: Tensor<B,2> = Tensor::ones([2, 2], &device);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tensor Operations\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "rust"
    }
   },
   "outputs": [],
   "source": [
    "let x1: Tensor<B,2> = Tensor::ones([2, 2], &device);\n",
    "let x2: Tensor<B,2> = Tensor::full([2, 2], 7.0, &device);\n",
    "\n",
    "let x3 = x1 + x2;\n",
    "\n",
    "println!(\"x3 = {}\", x3);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "rust"
    }
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Rust",
   "language": "rust",
   "name": "rust"
  },
  "language_info": {
   "codemirror_mode": "rust",
   "file_extension": ".rs",
   "mimetype": "text/rust",
   "name": "Rust",
   "pygment_lexer": "rust",
   "version": ""
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
