burn/examples/notebook/basic-tensor-op.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# This notebook demonstrates basic tensor operations in Burn."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "vscode": {
     "languageId": "rust"
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   "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 = \"../../burn\"}\n",
    ":dep burn-ndarray = {path = \"../../burn-ndarray\"}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "vscode": {
     "languageId": "rust"
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   "outputs": [],
   "source": [
    "// Import packages\n",
    "use burn::tensor::Tensor;\n",
    "use burn::backend::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": 38,
   "metadata": {
    "vscode": {
     "languageId": "rust"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Empty tensor: Tensor {\n",
      "  data: [[[0.0, 0.0, 0.0], [0.0, 0.0, 0.0]]],\n",
      "  shape:  [1, 2, 3],\n",
      "  device:  Cpu,\n",
      "  backend:  \"ndarray\",\n",
      "  kind:  \"Float\",\n",
      "  dtype:  \"f32\",\n",
      "}\n",
      "Tensor from slice: Tensor {\n",
      "  data: [[1.0, 2.0], [3.0, 4.0]],\n",
      "  shape:  [2, 2],\n",
      "  device:  Cpu,\n",
      "  backend:  \"ndarray\",\n",
      "  kind:  \"Float\",\n",
      "  dtype:  \"f32\",\n",
      "}\n",
      "Random tensor: Tensor {\n",
      "  data: [0.16685265, 0.7217095, 0.35741878, 0.49403405, 0.27360022],\n",
      "  shape:  [5],\n",
      "  device:  Cpu,\n",
      "  backend:  \"ndarray\",\n",
      "  kind:  \"Float\",\n",
      "  dtype:  \"f32\",\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "// Create an empty tensor for a given shape\n",
    "let tensor: Tensor<B, 3> = Tensor::empty([1, 2, 3]);\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]).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);\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);\n",
    "let tensor: Tensor<B,2> = Tensor::zeros([2, 2]);\n",
    "let tensor: Tensor<B,2> = Tensor::ones([2, 2]);\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tensor Operations\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "vscode": {
     "languageId": "rust"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x3 = Tensor {\n",
      "  data: [[8.0, 8.0], [8.0, 8.0]],\n",
      "  shape:  [2, 2],\n",
      "  device:  Cpu,\n",
      "  backend:  \"ndarray\",\n",
      "  kind:  \"Float\",\n",
      "  dtype:  \"f32\",\n",
      "}\n"
     ]
    }
   ],
   "source": [
    "let x1: Tensor<B,2> = Tensor::ones([2, 2]);\n",
    "let x2: Tensor<B,2> = Tensor::full([2, 2], 7.0);\n",
    "\n",
    "let x3 = x1 + x2;\n",
    "\n",
    "println!(\"x3 = {}\", x3);"
   ]
  }
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