Inplace normal_( ) bug

test.ipynb

{
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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.4.1\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "print(torch.__version__)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[0.2241, 0.1938, 0.6498,  ..., 0.4053, 0.1032, 0.1593],\n",
      "        [0.7699, 0.2154, 0.2844,  ..., 0.5927, 0.3669, 0.9740],\n",
      "        [0.4372, 0.6358, 0.5403,  ..., 0.9147, 0.2274, 0.8001],\n",
      "        ...,\n",
      "        [0.9509, 0.0036, 0.3583,  ..., 0.6677, 0.0050, 0.7659],\n",
      "        [0.9333, 0.6688, 0.4430,  ..., 0.9379, 0.4267, 0.6492],\n",
      "        [0.0214, 0.9866, 0.3556,  ..., 0.4019, 0.5550, 0.4936]])\n"
     ]
    }
   ],
   "source": [
    "a = torch.rand(5000, 4096)\n",
    "b = a.clone()\n",
    "c = a.clone()\n",
    "d = a.clone()\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[ 0.1454,  1.9271, -0.2900,  ..., -1.2863,  0.4496, -1.8988],\n",
      "        [ 0.7699,  0.2154,  0.2844,  ...,  0.5927,  0.3669,  0.9740],\n",
      "        [ 0.4372,  0.6358,  0.5403,  ...,  0.9147,  0.2274,  0.8001],\n",
      "        ...,\n",
      "        [ 0.9509,  0.0036,  0.3583,  ...,  0.6677,  0.0050,  0.7659],\n",
      "        [ 0.9333,  0.6688,  0.4430,  ...,  0.9379,  0.4267,  0.6492],\n",
      "        [ 0.0214,  0.9866,  0.3556,  ...,  0.4019,  0.5550,  0.4936]])\n"
     ]
    }
   ],
   "source": [
    "a[4999:5000].normal_(0, 1)\n",
    "print(a)\n",
    "# Note that first row has changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[ 0.2241,  0.1938,  0.6498,  ...,  0.4053,  0.1032,  0.1593],\n",
      "        [ 0.7699,  0.2154,  0.2844,  ...,  0.5927,  0.3669,  0.9740],\n",
      "        [ 0.4372,  0.6358,  0.5403,  ...,  0.9147,  0.2274,  0.8001],\n",
      "        ...,\n",
      "        [ 0.9509,  0.0036,  0.3583,  ...,  0.6677,  0.0050,  0.7659],\n",
      "        [ 0.9333,  0.6688,  0.4430,  ...,  0.9379,  0.4267,  0.6492],\n",
      "        [-1.0000, -1.0000, -1.0000,  ..., -1.0000, -1.0000, -1.0000]])\n"
     ]
    }
   ],
   "source": [
    "b[4999:5000] = -1\n",
    "print(b)\n",
    "# Note that last row has changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[ 0.2241,  0.1938,  0.6498,  ...,  0.4053,  0.1032,  0.1593],\n",
      "        [ 0.7699,  0.2154,  0.2844,  ...,  0.5927,  0.3669,  0.9740],\n",
      "        [ 0.4372,  0.6358,  0.5403,  ...,  0.9147,  0.2274,  0.8001],\n",
      "        ...,\n",
      "        [ 0.9509,  0.0036,  0.3583,  ...,  0.6677,  0.0050,  0.7659],\n",
      "        [ 0.9333,  0.6688,  0.4430,  ...,  0.9379,  0.4267,  0.6492],\n",
      "        [-1.0000, -1.0000, -1.0000,  ..., -1.0000, -1.0000, -1.0000]])\n"
     ]
    }
   ],
   "source": [
    "c[4999:5000].copy_(torch.rand(1, 4096).fill_(-1))\n",
    "print(c)\n",
    "# Note that last row has changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[ 0.2241,  0.1938,  0.6498,  ...,  0.4053,  0.1032,  0.1593],\n",
      "        [ 0.7699,  0.2154,  0.2844,  ...,  0.5927,  0.3669,  0.9740],\n",
      "        [ 0.4372,  0.6358,  0.5403,  ...,  0.9147,  0.2274,  0.8001],\n",
      "        ...,\n",
      "        [ 0.9509,  0.0036,  0.3583,  ...,  0.6677,  0.0050,  0.7659],\n",
      "        [ 0.9333,  0.6688,  0.4430,  ...,  0.9379,  0.4267,  0.6492],\n",
      "        [-1.0000, -1.0000, -1.0000,  ..., -1.0000, -1.0000, -1.0000]])\n"
     ]
    }
   ],
   "source": [
    "d[4999:5000].fill_(-1)\n",
    "print(d)\n",
    "# Note that last row has changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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