torch使用自己的数据集

在torch中使用自己的数据集

• 先将数据转化为tensor

• 然后将tensor数据转为torch能识别的Dataset

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  import torch.utils.data as Data tensor_x,tensor_y= torch.Tensor(x),torch.Tensor(y) dataset = Data.TensorDataset(data_tensor=tensor_x, target_tensor=tensor_y) loader = Data.DataLoader( dataset=dataset, batch_size=128, shuffle=True, num_workers=2, # 多线程读取数据 ) # 在整套数据上训练3次 for epoch in range(3): for step, (batch_x, batch_y) in enumerate(loader): print (batch_x.size(), batch_y.size()) # 真正训练时还要放到Variable中 b_x = Variable(batch_x) b_y = Variable(batch_y)