{ "cells": [ { "cell_type": "code", "execution_count": 95, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "The autoreload extension is already loaded. To reload it, use:\n", " %reload_ext autoreload\n" ] } ], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": 114, "metadata": {}, "outputs": [], "source": [ "import os\n", "import glob\n", "\n", "from experiments import ExperimentRunner\n", "import params" ] }, { "cell_type": "code", "execution_count": 115, "metadata": {}, "outputs": [], "source": [ "ex = ExperimentRunner(params.experiment_test, n_jobs=1)" ] }, { "cell_type": "code", "execution_count": 116, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Running param set: {'data_path_base': 'vtest_new2', 'conv_model_name': 'resnet', 'num_epochs': 10, 'feature_extract': False, 'batch_size': 64, 'lr': 0.001, 'use_vggish': True, 'momentum': 0.9}\n", "Running uuid c6cd69a63c6b7670802afa33af35b13d6c687340f71bf7e299e5711c\n" ] }, { "name": "stdout", "output_type": "stream", "text": [ "Updating ALL params\n" ] }, { "ename": "KeyboardInterrupt", "evalue": "", "output_type": "error", "traceback": [ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", "\u001b[0;32m\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mex\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m", "\u001b[0;32m~/Dropbox/github/cs231n-project/experiments.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 61\u001b[0m \u001b[0mrun_output\u001b[0m \u001b[0;34m=\u001b[0m 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\u001b[0mcopier\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmemo\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 162\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 163\u001b[0m \u001b[0mreductor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdispatch_table\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/anaconda3/lib/python3.7/site-packages/torch/tensor.py\u001b[0m in \u001b[0;36m__deepcopy__\u001b[0;34m(self, memo)\u001b[0m\n\u001b[1;32m 29\u001b[0m \u001b[0mnew_tensor\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclone\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 30\u001b[0m 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\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstorage_offset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstride\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/anaconda3/lib/python3.7/site-packages/torch/storage.py\u001b[0m in \u001b[0;36m__deepcopy__\u001b[0;34m(self, memo)\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_cdata\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mmemo\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 27\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mmemo\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_cdata\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m \u001b[0mnew_storage\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mclone\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 29\u001b[0m \u001b[0mmemo\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_cdata\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnew_storage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mnew_storage\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;32m/anaconda3/lib/python3.7/site-packages/torch/storage.py\u001b[0m in \u001b[0;36mclone\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 42\u001b[0m \u001b[0mdevice\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_device\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_cuda\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 43\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mtorch\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcuda\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdevice\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 44\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcopy_\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 45\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 46\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mtolist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", "\u001b[0;31mKeyboardInterrupt\u001b[0m: " ] } ], "source": [ "ex.run()" ] }, { "cell_type": "code", "execution_count": 88, "metadata": {}, "outputs": [], "source": [ "import pandas as pd" ] }, { "cell_type": "code", "execution_count": 89, "metadata": {}, "outputs": [], "source": [ "paths = glob.glob('results/*.csv') # * means all if need specific format then *.csv\n", "latest = max(paths, key=os.path.getctime)\n", "df = pd.read_csv(latest)" ] }, { "cell_type": "code", "execution_count": 90, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-rw-r--r-- 1 aziai staff 4.6K Jun 2 23:21 results/results_20190602232142.csv\r\n", "-rw-r--r--@ 1 aziai staff 2.1K Jun 2 20:25 results/results_20190602195657.csv\r\n", "-rw-r--r--@ 1 aziai staff 1.4K Jun 2 19:48 results/results_20190602194822.csv\r\n", "-rw-r--r--@ 1 aziai staff 478B Jun 2 19:45 results/results_20190602194401.csv\r\n", "-rw-r--r--@ 1 aziai staff 846B Jun 2 19:28 results/results_20191402191416.csv\r\n" ] } ], "source": [ "!ls -lht results/*.csv" ] }, { "cell_type": "code", "execution_count": 91, "metadata": {}, "outputs": [ { "data": { "text/html": [ "
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batch_sizeconv_model_namedata_path_baseexperiment_uuidfeature_extractlrmomentumnum_epochsrunner_uuiduse_vggishval_accval_f1
1764resnetvtest_new220190602232142False0.0100.9510b5d41c44c98e2fa432656659c4fbcb77ef2a66d30dbe51...False0.9176470.946565
2264resnetvtest_new220190602232142False0.0010.9010c6cd69a63c6b7670802afa33af35b13d6c687340f71bf7...True0.8941180.936170
664NaNvtest_new220190602232142False0.0010.901057fac69720ed9689a5805e15ddbb89ee26d9b64fbd2cf2...True0.8823530.929577
364NaNvtest_new220190602232142False0.0100.9510bc7e48700485911fd1dcfa46fb408e93d744c2ec3afd26...True0.8588240.916667
2464resnetvtest_new220190602232142True0.0100.90109715fe9781571c61eb6bf38cbc5173df40e9e41ae3eaec...False0.8705880.916031
2664resnetvtest_new220190602232142True0.0100.9010454e165857fea306cac78a54c635a15545fab0e7a5f606...True0.8588240.907692
2364resnetvtest_new220190602232142False0.0010.9510af38e4c808ff3998977167f1e5138bdd0301f92a2dc206...True0.8352940.893939
2764resnetvtest_new220190602232142True0.0100.95104566c335e71f215a1110a36a7cfec1882c86f86dbb7e3e...True0.8235290.893617
264NaNvtest_new220190602232142False0.0100.90100fd6f6ebe947c54bdcb0340e244f0a27254f0a358be9a0...True0.8117650.891892
3164resnetvtest_new220190602232142True0.0010.9510b0ba9005b21c06336b8a58c2ed784dcf5fec6028dd7bca...True0.8117650.887324
1864resnetvtest_new220190602232142False0.0100.9010a60fa62389b6418273ca349479228d39e55b7b357ba2e7...True0.8235290.887218
1964resnetvtest_new220190602232142False0.0100.9510dcb42ec2f883718f58a1612e4afff99249aa628afa8442...True0.8000000.880000
2964resnetvtest_new220190602232142True0.0010.951081bf2d2fb5c8083afc54b43f8c561e6c5c36304a2d0024...False0.8000000.877698
1164NaNvtest_new220190602232142True0.0100.9510db6e5ff043c83f9643e5fa4aecb3c85a03e2be1c8de569...True0.7764710.874172
764NaNvtest_new220190602232142False0.0010.95108686806f634f6da4be6bf84cca80c305e8a7f751dd8ca8...True0.7764710.874172
1464NaNvtest_new220190602232142True0.0010.9010c2c04441a29f2bcf11fade126cd304849d3d5e9a1c98fa...True0.7764710.874172
1564NaNvtest_new220190602232142True0.0010.95104d227fadf14ff66ea2c7f253a96c2111a78234f95089d0...True0.7764710.874172
1064NaNvtest_new220190602232142True0.0100.901010ece59983d31536981268d1e8bbdf4460e65b24a7567b...True0.7764710.874172
2564resnetvtest_new220190602232142True0.0100.951021f4a1394a48e89171341403ff9eccc6e080a9acb66005...False0.8117650.873016
2164resnetvtest_new220190602232142False0.0010.9510091aaed6d121608dc449c2f33a7c74bbe835ccc5abadc9...False0.8000000.872180
3064resnetvtest_new220190602232142True0.0010.90105f938c364c0de0bc3ab556f1b48971520006d0ed581d53...True0.7764710.868966
1664resnetvtest_new220190602232142False0.0100.9010a9d9eb5afabbea4dff607846fe1a0782c760f44cfbd0f9...False0.7882350.867647
2064resnetvtest_new220190602232142False0.0010.90108c4da8f6f9157db4dbd6f70b67c1db469ea034730c12eb...False0.7882350.854839
2864resnetvtest_new220190602232142True0.0010.90106fcff331f0df5ded20113ae3e7f2d1568e3f3fba9f2a92...False0.7294120.818898
164NaNvtest_new220190602232142False0.0100.9510c7b84e8c420a3be3a333ba41c2618399c2baebb470fc6a...False-1.000000-1.000000
1364NaNvtest_new220190602232142True0.0010.951041fd07df53b8400f9386cf6d6fd5e400290fc19cc96bd1...False-1.000000-1.000000
1264NaNvtest_new220190602232142True0.0010.901033ac0b6c3357fb2cfc22194be83a872435a7b3495506b8...False-1.000000-1.000000
964NaNvtest_new220190602232142True0.0100.95101613a061bc0ee4cb3e89ff00d7b183241ee4fccf84420c...False-1.000000-1.000000
864NaNvtest_new220190602232142True0.0100.9010dddc0808ccee29d6d96d7922bdce1e66e319ad29cd7206...False-1.000000-1.000000
564NaNvtest_new220190602232142False0.0010.95109af39512bef330a9bbab90f91063597b4d3d798a0a7dec...False-1.000000-1.000000
464NaNvtest_new220190602232142False0.0010.901054aaa1ed52b83839a188927adb63f64a6e8cc8f9d5ce37...False-1.000000-1.000000
064NaNvtest_new220190602232142False0.0100.90103d4d0ae6efebf77f6b7f5a4163558c892daae15e174c5b...False-1.000000-1.000000
\n", "
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False -1.000000 -1.000000\n", "9 64 NaN vtest_new2 20190602232142 True 0.010 0.95 10 1613a061bc0ee4cb3e89ff00d7b183241ee4fccf84420c... False -1.000000 -1.000000\n", "8 64 NaN vtest_new2 20190602232142 True 0.010 0.90 10 dddc0808ccee29d6d96d7922bdce1e66e319ad29cd7206... False -1.000000 -1.000000\n", "5 64 NaN vtest_new2 20190602232142 False 0.001 0.95 10 9af39512bef330a9bbab90f91063597b4d3d798a0a7dec... False -1.000000 -1.000000\n", "4 64 NaN vtest_new2 20190602232142 False 0.001 0.90 10 54aaa1ed52b83839a188927adb63f64a6e8cc8f9d5ce37... False -1.000000 -1.000000\n", "0 64 NaN vtest_new2 20190602232142 False 0.010 0.90 10 3d4d0ae6efebf77f6b7f5a4163558c892daae15e174c5b... False -1.000000 -1.000000" ] }, "execution_count": 91, "metadata": {}, "output_type": "execute_result" } ], "source": [ "df.sort_values(by='val_f1', ascending=False)" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.2" } }, "nbformat": 4, "nbformat_minor": 2 }