Basics/oneDTensors.ipynb

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  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "d49d04b9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import torch\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c3a9b133",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([1, 2, 3]) <class 'torch.Tensor'> torch.LongTensor\n"
     ]
    }
   ],
   "source": [
    "v = torch.tensor([1,2,3])\n",
    "print(v,type(v),v.type())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "f622a8cc",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([1., 2., 3.]) torch.FloatTensor\n"
     ]
    }
   ],
   "source": [
    "v = torch.FloatTensor([1,2,3])\n",
    "print(v,v.type())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "5e239719",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([1, 2, 3, 4, 5, 6]) <class 'torch.Tensor'> torch.LongTensor\n"
     ]
    }
   ],
   "source": [
    "v = torch.tensor([1,2,3,4,5,6])\n",
    "print(v,type(v),v.type())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "7448712e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[1],\n",
      "        [2],\n",
      "        [3],\n",
      "        [4],\n",
      "        [5],\n",
      "        [6]])\n"
     ]
    }
   ],
   "source": [
    "print(v.view(6,1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7d93c0d6",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensor([[1, 2],\n",
      "        [3, 4],\n",
      "        [5, 6]])\n"
     ]
    }
   ],
   "source": [
    "print(v.view(3,-1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "63d3372f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([1, 2, 3, 4, 5, 6]), numpy.ndarray)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.array([1,2,3,4,5,6])\n",
    "a,type(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "360b7ca1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([1, 2, 3, 4, 5, 6], dtype=torch.int32)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = torch.from_numpy(a)\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "31e533e1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'torch.IntTensor'"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b.type()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "da6d2e59",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5, 6])"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c = b.numpy()\n",
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "83748b6b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "numpy.ndarray"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(c)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "165b2758",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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