1.6.tensors.and.numpy.ipynb

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   "source": [
    "# Deep Learning with PyTorch\n",
    "\n",
    "\n",
    "Author: [Anand Saha](http://teleported.in/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1.6 Working with PyTorch and NumPy"
   ]
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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert a NumPy array to Tensor"
   ]
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   "outputs": [],
   "source": [
    "n = np.array([2, 3])\n",
    "t = torch.from_numpy(n)\n",
    "print(n)\n",
    "print(t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Change a Tensor value, and see the change in \n",
    "corresponding NumPy array"
   ]
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "n[0] = 100\n",
    "print(t)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert a Tensor to NumPy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t = torch.FloatTensor([5, 6])\n",
    "n = t.numpy()\n",
    "print(t)\n",
    "print(n)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Change a Tensor value, and see the change in corresponding NumPy array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "t[0] = 100\n",
    "print(n)"
   ]
  }
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