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import os
import torch
import pandas as pd
import numpy as np
from torch.utils.data import Dataset, random_split, DataLoader
from PIL import Image
import torchvision.models as models
import matplotlib.pyplot as plt
from tqdm.notebook import tqdm
import torchvision.transforms as T
from sklearn.metrics import f1_score
import torch.nn.functional as F
import torch.nn as nn
from torchvision.utils import make_grid
%matplotlib inline

Preparing the Data

DATA_DIR = '../input/jovian-pytorch-z2g/Human protein atlas'

TRAIN_DIR = DATA_DIR + '/train'                           
TEST_DIR = DATA_DIR + '/test'                             

TRAIN_CSV = DATA_DIR + '/train.csv'                       
TEST_CSV = '../input/jovian-pytorch-z2g/submission.csv' 
data_df = pd.read_csv(TRAIN_CSV)
data_df.head()
labels = {
    0: 'Mitochondria',
    1: 'Nuclear bodies',
    2: 'Nucleoli',
    3: 'Golgi apparatus',
    4: 'Nucleoplasm',
    5: 'Nucleoli fibrillar center',
    6: 'Cytosol',
    7: 'Plasma membrane',
    8: 'Centrosome',
    9: 'Nuclear speckles'
}