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08_1_dataset_loader.py
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08_1_dataset_loader.py
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# References
# https://github.com/yunjey/pytorch-tutorial/blob/master/tutorials/01-basics/pytorch_basics/main.py
# http://pytorch.org/tutorials/beginner/data_loading_tutorial.html#dataset-class
from torch.utils.data import Dataset, DataLoader
from torch import from_numpy, tensor
import numpy as np
class DiabetesDataset(Dataset):
""" Diabetes dataset."""
# Initialize your data, download, etc.
def __init__(self):
xy = np.loadtxt('./data/diabetes.csv.gz',
delimiter=',', dtype=np.float32)
self.len = xy.shape[0]
self.x_data = from_numpy(xy[:, 0:-1])
self.y_data = from_numpy(xy[:, [-1]])
def __getitem__(self, index):
return self.x_data[index], self.y_data[index]
def __len__(self):
return self.len
dataset = DiabetesDataset()
train_loader = DataLoader(dataset=dataset,
batch_size=32,
shuffle=True,
num_workers=2)
for epoch in range(2):
for i, data in enumerate(train_loader, 0):
# get the inputs
inputs, labels = data
# wrap them in Variable
inputs, labels = tensor(inputs), tensor(labels)
# Run your training process
print(f'Epoch: {i} | Inputs {inputs.data} | Labels {labels.data}')