Refactoring data with attrs and refactor conf for hydra

1 files changed, 257 insertions, 18 deletions

diff --git a/notebooks/00-scratch-pad.ipynb b/notebooks/00-scratch-pad.ipynb
index 16c6533..1e30038 100644
--- a/notebooks/00-scratch-pad.ipynb
+++ b/notebooks/00-scratch-pad.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -30,7 +30,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -39,7 +39,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -48,41 +48,280 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 44,
    "metadata": {},
    "outputs": [],
    "source": [
     "@attr.s\n",
-    "class B:\n",
-    "    batch_size = attr.ib()\n",
-    "    num_workers = attr.ib()"
+    "class B(nn.Module):\n",
+    "    input_dim = attr.ib()\n",
+    "    hidden = attr.ib()\n",
+    "    xx = attr.ib(init=False, default=\"hek\")\n",
+    "    \n",
+    "    def __attrs_post_init__(self):\n",
+    "        super().__init__()\n",
+    "        self.fc = nn.Linear(self.input_dim, self.hidden)\n",
+    "        self.xx = \"da\"\n",
+    "    \n",
+    "    def forward(self, x):\n",
+    "        return self.fc(x)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 49,
    "metadata": {},
    "outputs": [],
    "source": [
-    "@attr.s\n",
-    "class T(B):\n",
+    "def f(x):\n",
+    "    return 2\n",
     "\n",
-    "    def __attrs_post_init__(self) -> None:\n",
-    "        super().__init__(self.batch_size, self.num_workers)\n",
-    "        self.hej = None\n",
+    "@attr.s(auto_attribs=True)\n",
+    "class T(B):\n",
     "    \n",
-    "    batch_size = attr.ib()\n",
-    "    num_workers = attr.ib()\n",
-    "    h: Path = attr.ib(converter=Path)"
+    "    h: Path = attr.ib(converter=Path)\n",
+    "    p: int = attr.ib(init=False, default=f(3))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 53,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "__init__() missing 1 required positional argument: 'hidden'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-53-ef8b390156f4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mt\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mT\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput_dim\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m16\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"hej\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m: __init__() missing 1 required positional argument: 'hidden'"
+     ]
+    }
+   ],
+   "source": [
+    "t = T(input_dim=16, h=\"hej\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'da'"
+      ]
+     },
+     "execution_count": 51,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t.xx"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "2"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t.p"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "16"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t.input_dim"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = torch.rand(16, 16)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([16, 16])"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "x.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "T(input_dim=16, hidden=24, h=PosixPath('hej'))"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t.cuda()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
-    "t = T(batch_size=16, num_workers=2, h=\"hej\")"
+    "x = x.cuda()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "scrolled": true
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "tensor([[ 3.6047e-01,  1.0200e+00,  3.6786e-01,  1.6077e-01,  3.9281e-02,\n",
+       "          3.2830e-01,  1.3433e-01, -9.0334e-02, -3.8712e-01,  8.1547e-01,\n",
+       "         -5.4483e-01, -9.7471e-01,  3.3706e-01, -9.5283e-01, -1.6271e-01,\n",
+       "          3.8504e-01, -5.0106e-01, -4.8638e-01,  3.7033e-01, -4.9557e-01,\n",
+       "          2.6555e-01,  5.1245e-01,  6.6751e-01, -2.6291e-01],\n",
+       "        [ 1.3811e-01,  7.4522e-01,  4.9935e-01,  3.3878e-01,  1.8501e-01,\n",
+       "          2.2269e-02, -2.0328e-01,  1.4629e-01, -2.2957e-01,  4.1197e-01,\n",
+       "         -1.9555e-01, -4.7609e-01,  9.0206e-02, -8.8568e-01, -2.1618e-01,\n",
+       "          2.8882e-01, -5.4335e-01, -6.6301e-01,  4.9990e-01, -4.0144e-01,\n",
+       "          3.6403e-01,  5.3901e-01,  8.6665e-01, -7.8312e-02],\n",
+       "        [ 1.6493e-02,  4.6157e-01,  2.9500e-02,  2.4190e-01,  6.5753e-01,\n",
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+       "          3.1175e-01,  4.2857e-01,  1.6501e-01, -2.4118e-01],\n",
+       "        [ 9.2361e-02,  6.0196e-01,  1.3081e-02, -8.1091e-02,  4.2342e-01,\n",
+       "         -8.8457e-02, -8.1851e-02, -1.1562e-01, -1.5049e-01,  4.9972e-01,\n",
+       "         -3.0432e-01, -7.8619e-01,  2.1060e-01, -1.0598e+00, -4.6542e-01,\n",
+       "          4.2382e-01, -6.5671e-01, -4.8589e-01,  5.5977e-02, -2.9478e-02,\n",
+       "          8.5718e-02,  4.7685e-01,  4.8351e-01, -2.8142e-01],\n",
+       "        [ 1.3377e-01,  5.4434e-01,  3.4505e-01,  1.1307e-01,  4.4057e-01,\n",
+       "         -7.6075e-03,  1.3841e-01, -1.1497e-01, -1.3177e-01,  8.0254e-01,\n",
+       "         -3.0627e-01, -6.8437e-01,  1.9035e-01, -1.0208e+00, -1.3259e-01,\n",
+       "          5.3231e-01, -4.7814e-01, -5.1266e-01,  2.4646e-02, -3.0552e-01,\n",
+       "          2.7398e-01,  5.8269e-01,  6.5481e-01, -4.2041e-01],\n",
+       "        [ 1.9604e-01,  4.0597e-01,  1.9071e-01, -2.5535e-01,  1.1915e-01,\n",
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+       "          5.6046e-02,  4.1773e-01,  4.9894e-01, -3.1945e-01],\n",
+       "        [ 1.2657e-01,  3.3224e-01,  6.2830e-02,  1.5718e-01,  4.8844e-01,\n",
+       "         -1.1476e-01, -1.5044e-01,  2.5265e-02, -2.0351e-01,  5.5770e-01,\n",
+       "         -3.6036e-01, -7.4406e-01,  1.6962e-01, -9.6185e-01, -2.9334e-01,\n",
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+       "         -1.9598e-02,  3.8727e-01,  3.6892e-01, -3.3071e-01],\n",
+       "        [ 5.2178e-01,  6.9704e-01,  5.0093e-01,  1.1157e-01,  8.0012e-02,\n",
+       "          3.6931e-01, -6.4927e-02,  1.1126e-01, -2.5117e-01,  5.3017e-01,\n",
+       "         -2.6488e-01, -8.4056e-01,  2.2374e-01, -6.6831e-01, -1.9402e-01,\n",
+       "          7.4174e-02, -4.7763e-01, -2.6912e-01,  5.1009e-01, -5.4239e-01,\n",
+       "          3.0123e-01,  3.7529e-01,  4.1625e-01, -2.0141e-01],\n",
+       "        [ 3.7968e-01,  4.9387e-01,  3.6786e-01, -1.3131e-01,  2.4445e-02,\n",
+       "          2.2155e-01, -4.0087e-02, -1.4872e-01, -5.5030e-01,  6.8958e-01,\n",
+       "         -3.8156e-01, -7.5760e-01,  3.2085e-01, -6.4571e-01,  1.1268e-03,\n",
+       "          3.4251e-02, -2.6440e-01, -2.6374e-01,  5.9787e-01, -4.6502e-01,\n",
+       "          2.0074e-01,  4.5471e-01,  2.4238e-01, -4.3247e-01],\n",
+       "        [ 2.9364e-01,  4.8659e-01,  9.0845e-02,  1.6348e-01,  5.7636e-01,\n",
+       "          4.5485e-01, -1.6781e-01, -1.4557e-01, -8.8814e-02,  6.6351e-01,\n",
+       "         -5.3669e-01, -8.2818e-01,  6.0474e-01, -9.4558e-01, -3.0133e-01,\n",
+       "          3.0310e-01, -5.2493e-01, -2.5948e-01,  1.5857e-01, -4.2695e-01,\n",
+       "          2.1311e-01,  4.6502e-01,  8.7946e-02, -5.5815e-01],\n",
+       "        [ 9.2208e-02,  2.9731e-01,  3.3849e-01, -5.1049e-02,  2.7834e-01,\n",
+       "         -1.1120e-01,  1.1835e-01,  1.3665e-01, -2.1291e-01,  3.5107e-01,\n",
+       "         -9.8108e-02, -5.0180e-01,  2.9894e-01, -7.7726e-01, -8.1317e-02,\n",
+       "          3.5704e-01, -3.6759e-01, -2.2148e-01,  1.1019e-01, -1.4452e-02,\n",
+       "          1.5092e-02,  3.3405e-01,  1.2765e-01, -4.0411e-01],\n",
+       "        [ 2.8927e-02,  4.4180e-01,  1.0994e-01,  5.6124e-01,  4.7174e-01,\n",
+       "          1.9914e-01, -9.5047e-02,  3.1277e-02, -1.8656e-01,  5.0631e-01,\n",
+       "         -3.4353e-01, -5.7425e-01,  4.3409e-01, -8.3343e-01, -1.1627e-01,\n",
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+       "          2.8559e-02,  3.0587e-01,  3.6717e-01, -4.4303e-01],\n",
+       "        [-1.0741e-01,  1.3539e-01,  1.5746e-01,  2.1208e-01,  6.3745e-01,\n",
+       "         -2.1864e-01, -1.8820e-01,  2.1184e-01, -3.6832e-02,  3.0890e-01,\n",
+       "         -2.4719e-03, -3.3573e-01,  1.8479e-01, -9.2119e-01, -2.3361e-01,\n",
+       "          8.9827e-02, -5.4372e-01, -4.4935e-01,  3.2967e-01, -9.2807e-02,\n",
+       "          9.9241e-02,  4.1705e-01,  2.4728e-01, -4.8119e-01],\n",
+       "        [ 2.8125e-01,  5.3276e-01,  5.0110e-02,  2.0471e-01,  5.7750e-01,\n",
+       "          4.6670e-02, -2.1400e-01,  6.8794e-03, -6.8737e-02,  4.2138e-01,\n",
+       "         -3.1261e-01, -7.3709e-01,  4.2001e-01, -9.9757e-01, -4.8091e-01,\n",
+       "          2.9960e-01, -6.2133e-01, -4.0566e-01,  3.2191e-01, -1.0219e-02,\n",
+       "          1.2901e-01,  3.9601e-01,  1.6291e-01, -3.3871e-01],\n",
+       "        [ 2.9181e-01,  5.5400e-01,  3.0462e-01,  2.2431e-02,  2.8480e-01,\n",
+       "          4.4624e-01, -2.8859e-01, -1.4629e-01, -4.3573e-02,  2.9742e-01,\n",
+       "         -1.0100e-01, -4.3070e-01,  4.6713e-01, -3.7132e-01, -8.6748e-02,\n",
+       "          2.5666e-01, -3.5361e-01, -2.3917e-02,  3.0071e-01, -3.2420e-01,\n",
+       "          1.3375e-01,  3.4475e-01,  3.0642e-01, -4.3496e-01],\n",
+       "        [-7.7723e-04,  2.3828e-01,  2.3124e-01,  4.1347e-01,  6.8455e-01,\n",
+       "         -9.8319e-03,  1.3403e-01,  1.8460e-02, -1.4025e-01,  5.9780e-01,\n",
+       "         -3.7015e-01, -5.7865e-01,  4.9211e-01, -1.1262e+00, -2.1693e-01,\n",
+       "          3.2002e-01, -2.9313e-01, -3.1941e-01,  9.8446e-02, -6.2767e-02,\n",
+       "         -9.8636e-03,  3.5712e-01,  2.8833e-01, -5.3506e-01]], device='cuda:0',\n",
+       "       grad_fn=<AddmmBackward>)"
+      ]
+     },
+     "execution_count": 25,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "t(x)"
    ]
   },
   {