notebooks-1/2-autograd.ipynb

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   "source": [
    "# Automatic Differentiation"
   ]
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   "source": [
    "from mxnet import autograd, np, npx  \n",
    "npx.set_np()\n",
    "\n",
    "x = np.arange(4)\n",
    "x"
   ]
  },
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    "Allocate space to store the gradient with respect to ``x``."
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    "x.attach_grad()"
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    "Record the computation within the `record` scope."
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   "source": [
    "with autograd.record():\n",
    "    y = 2.0 * np.dot(x, x)\n",
    "y"
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   "source": [
    "The gradient of the function $y = 2\\mathbf{x}^{\\top}\\mathbf{x}$ with respect to $\\mathbf{x}$ should be $4\\mathbf{x}$. "
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   "source": [
    "y.backward()\n",
    "x.grad - 4 * x"
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