pranavbrkr ebf1f1629b update
2023-10-14 23:39:57 -07:00

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{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"from utils import *\n",
"warnings.filterwarnings('ignore')\n",
"%matplotlib inline\n"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"fd_collection = getCollection(\"team_5_mwdb_phase_2\", \"fd_collection\")\n"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Applying CP decomposition on the resnet_fd space to get 5 latent semantics (showing only top 10 image-weight pairs for each latent semantic)...\n",
"(4339, 1000, 101)\n",
"Showing image-weight latent semantic\n",
"Latent semantic no. 0\n",
"image\t16\t-\tweight\t0.09457863290867145\n",
"image\t33\t-\tweight\t0.09431358165046931\n",
"image\t8\t-\tweight\t0.09383106409263509\n",
"image\t31\t-\tweight\t0.0909314099940096\n",
"image\t77\t-\tweight\t0.08944321537104273\n",
"image\t60\t-\tweight\t0.08919523673591125\n",
"image\t117\t-\tweight\t0.08863817716328135\n",
"image\t190\t-\tweight\t0.08742826964165426\n",
"image\t61\t-\tweight\t0.08740880468847693\n",
"image\t4\t-\tweight\t0.08658248985130698\n",
"Latent semantic no. 1\n",
"image\t0\t-\tweight\t0.0\n",
"image\t1\t-\tweight\t0.0\n",
"image\t2\t-\tweight\t0.0\n",
"image\t3\t-\tweight\t0.0\n",
"image\t4\t-\tweight\t0.0\n",
"image\t5\t-\tweight\t0.0\n",
"image\t6\t-\tweight\t0.0\n",
"image\t7\t-\tweight\t0.0\n",
"image\t8\t-\tweight\t0.0\n",
"image\t9\t-\tweight\t0.0\n",
"Latent semantic no. 2\n",
"image\t901\t-\tweight\t0.06704958761044195\n",
"image\t821\t-\tweight\t0.06679275183308425\n",
"image\t560\t-\tweight\t0.0664275386647296\n",
"image\t617\t-\tweight\t0.0662151403988761\n",
"image\t797\t-\tweight\t0.06443320486788845\n",
"image\t899\t-\tweight\t0.06434223110660761\n",
"image\t892\t-\tweight\t0.06428385401777054\n",
"image\t893\t-\tweight\t0.064267819006683\n",
"image\t553\t-\tweight\t0.06396933419584953\n",
"image\t688\t-\tweight\t0.06322044784443977\n",
"Latent semantic no. 3\n",
"image\t0\t-\tweight\t0.0\n",
"image\t1\t-\tweight\t0.0\n",
"image\t2\t-\tweight\t0.0\n",
"image\t3\t-\tweight\t0.0\n",
"image\t4\t-\tweight\t0.0\n",
"image\t5\t-\tweight\t0.0\n",
"image\t6\t-\tweight\t0.0\n",
"image\t7\t-\tweight\t0.0\n",
"image\t8\t-\tweight\t0.0\n",
"image\t9\t-\tweight\t0.0\n",
"Latent semantic no. 4\n",
"image\t0\t-\tweight\t0.0\n",
"image\t1\t-\tweight\t0.0\n",
"image\t2\t-\tweight\t0.0\n",
"image\t3\t-\tweight\t0.0\n",
"image\t4\t-\tweight\t0.0\n",
"image\t5\t-\tweight\t0.0\n",
"image\t6\t-\tweight\t0.0\n",
"image\t7\t-\tweight\t0.0\n",
"image\t8\t-\tweight\t0.0\n",
"image\t9\t-\tweight\t0.0\n",
"Showing feature-weight latent semantic\n",
"Latent semantic no. 0\n",
"feature\t0\t-\tweight\t0.011984002180022709\n",
"Latent semantic no. 1\n",
"feature\t0\t-\tweight\t-0.015847730845197867\n",
"Latent semantic no. 2\n",
"feature\t0\t-\tweight\t0.003755764372246337\n",
"Latent semantic no. 3\n",
"feature\t0\t-\tweight\t-0.015820605365729715\n",
"Latent semantic no. 4\n",
"feature\t0\t-\tweight\t0.006783847616503207\n",
"Showing label-weight latent semantic\n",
"Latent semantic no. 0\n",
"label\t0\t-\tweight\t0.9999999999999998\n",
"label\t1\t-\tweight\t0.0\n",
"label\t2\t-\tweight\t0.0\n",
"label\t3\t-\tweight\t0.0\n",
"label\t4\t-\tweight\t0.0\n",
"label\t5\t-\tweight\t0.0\n",
"label\t6\t-\tweight\t0.0\n",
"label\t7\t-\tweight\t0.0\n",
"label\t8\t-\tweight\t0.0\n",
"label\t9\t-\tweight\t0.0\n",
"Latent semantic no. 1\n",
"label\t1\t-\tweight\t1.0000000000000004\n",
"label\t0\t-\tweight\t0.0\n",
"label\t2\t-\tweight\t0.0\n",
"label\t3\t-\tweight\t0.0\n",
"label\t4\t-\tweight\t0.0\n",
"label\t5\t-\tweight\t0.0\n",
"label\t6\t-\tweight\t0.0\n",
"label\t7\t-\tweight\t0.0\n",
"label\t8\t-\tweight\t0.0\n",
"label\t9\t-\tweight\t0.0\n",
"Latent semantic no. 2\n",
"label\t3\t-\tweight\t1.0000000000000009\n",
"label\t0\t-\tweight\t0.0\n",
"label\t1\t-\tweight\t0.0\n",
"label\t2\t-\tweight\t0.0\n",
"label\t4\t-\tweight\t0.0\n",
"label\t5\t-\tweight\t0.0\n",
"label\t6\t-\tweight\t0.0\n",
"label\t7\t-\tweight\t0.0\n",
"label\t8\t-\tweight\t0.0\n",
"label\t9\t-\tweight\t0.0\n",
"Latent semantic no. 3\n",
"label\t5\t-\tweight\t0.9999999999999998\n",
"label\t0\t-\tweight\t0.0\n",
"label\t1\t-\tweight\t0.0\n",
"label\t2\t-\tweight\t0.0\n",
"label\t3\t-\tweight\t0.0\n",
"label\t4\t-\tweight\t0.0\n",
"label\t6\t-\tweight\t0.0\n",
"label\t7\t-\tweight\t0.0\n",
"label\t8\t-\tweight\t0.0\n",
"label\t9\t-\tweight\t0.0\n",
"Latent semantic no. 4\n",
"label\t94\t-\tweight\t1.0000000000000004\n",
"label\t0\t-\tweight\t0.0\n",
"label\t1\t-\tweight\t0.0\n",
"label\t2\t-\tweight\t0.0\n",
"label\t3\t-\tweight\t0.0\n",
"label\t4\t-\tweight\t0.0\n",
"label\t5\t-\tweight\t0.0\n",
"label\t6\t-\tweight\t0.0\n",
"label\t7\t-\tweight\t0.0\n",
"label\t8\t-\tweight\t0.0\n"
]
}
],
"source": [
"selected_feature_model = valid_feature_models[\n",
" str(input(\"Enter feature model - one of \" + str(list(valid_feature_models.keys()))))\n",
"]\n",
"\n",
"k = int(input(\"Enter value of k: \"))\n",
"if k < 1:\n",
" raise ValueError(\"k should be a positive integer\")\n",
"\n",
"extract_CP_semantics_from_feature_model(\n",
" fd_collection,\n",
" k,\n",
" selected_feature_model,\n",
" top_images=10\n",
")"
]
}
],
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"display_name": "Python 3",
"language": "python",
"name": "python3"
},
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"file_extension": ".py",
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