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JuKoernerJuKoerner
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1 parent 66a0c53 commit 7541f2b

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-1452
lines changed

‎config.yaml

+1-1
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epochs: 4
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epochs: 10
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batch_size: 64
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learning_rate: 0.0001
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logs: logs

‎dataset.ipynb

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"outputs": [],
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"source": [
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"from torch.utils.data import Dataset\n",
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"from Datasets import load\n",
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"from src.Datasets import load\n",
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"import matplotlib.pyplot as plt\n",
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"import numpy as np\n",
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"from torch.utils.data import DataLoader\n",
@@ -16,20 +16,6 @@
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"import torch"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 30,
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"metadata": {},
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"outputs": [],
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"source": [
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"dataset = datasets.MNIST(\n",
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" root=\".\",\n",
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" train=True,\n",
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" download=True,\n",
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" transform=transforms.ToTensor(),\n",
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" )"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
@@ -241,138 +227,6 @@
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"mean, std"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"metadata": {},
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"outputs": [
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{
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"data": {
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252-
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287-
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288-
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289-
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290-
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291-
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292-
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293-
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294-
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295-
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296-
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297-
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298-
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301-
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302-
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303-
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304-
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305-
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306-
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308-
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309-
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310-
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312-
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313-
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314-
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316-
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317-
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320-
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321-
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322-
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323-
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324-
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325-
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326-
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327-
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328-
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329-
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330-
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331-
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332-
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333-
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334-
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335-
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336-
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337-
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338-
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339-
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340-
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341-
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342-
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343-
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344-
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345-
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346-
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347-
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348-
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349-
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350-
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351-
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352-
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353-
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354-
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355-
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356-
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357-
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358-
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359-
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360-
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361-
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" 0.4118, 0.6471, 0.5255, 0.3765]]]),\n",
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" 6)"
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]
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},
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"execution_count": 14,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"dataset[0]"
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]
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},
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"cell_type": "code",
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"execution_count": 9,

‎energy.ipynb

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"cells": [
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"import torch\n",
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"import torch.nn as nn\n",
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"import torch.nn.functional as F\n",
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"from Datasets import load\n",
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"from src.Datasets import load\n",
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"from torch.utils.data import DataLoader\n",
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"from model import Conv_Net_Dropout, Conv_Net_FC_Dropout\n",
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"from src.model import Conv_Net_Dropout, Conv_Net_FC_Dropout\n",
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"import matplotlib.pyplot as plt\n",
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"from tqdm import tqdm\n",
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"import seaborn as sns\n",
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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")"
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]
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},
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"execution_count": 2,
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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"text": [
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"100%|██████████| 79/79 [00:00<00:00, 121.75it/s]\n"
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"100%|██████████| 79/79 [00:00<00:00, 126.62it/s]\n"
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"100%|██████████| 79/79 [00:00<00:00, 92.24it/s]\n"
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"((10000, 10), (10000, 10))"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"cifar_logits.shape, mnist_logits.shape"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 9,
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"metadata": {},
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"data": {
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"cell_type": "code",
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"execution_count": 10,
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"metadata": {},
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"outputs": [
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{

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