Pytorch DataLoader switch item to List and cause several errors

data
1

My source code is using pytorch and like this:

def Embed(sequenceSet):
  output = []
  for s in sequenceSet:
    PseDNCSequence = Embedding.PseDNC(str(s))
    ANFSequence = Embedding.ANF(str(s))
    EIIPSequence = Embedding.EIIP(str(s))
    emdbededSequence = PseDNCSequence+ANFSequence+EIIPSequence
    output.append(emdbededSequence)
  return np.array(output)

text = file.read()
lines = text.strip().split('\n')
embededS = Embed(lines)
embeddedSequences = torch.tensor(embededS)
my_dataset = TensorDataset(embeddedSequences)
loader = data.DataLoader(my_dataset, batch_size=batch_size, shuffle=True)

for epoch in range(num_epochs):
   for training_sample in loader:
      training_sample = training_sample.view(-1, sequenceLength)
      batch_size = training_sample.shape[0]
      ....

It is getting error " AttributeError: ‘list’ object has no attribute ‘view’ " at the line:

training_sample = training_sample.view(-1, sequenceLength)

I tried to change it into:

training_sample = torch.tensor(training_sample)
training_sample = training_sample.view(-1, sequenceLength)

… then I I received another error “ValueError: only one element tensors can be converted to Python scalars”

I already checked the other places and make sure that the input data to the loader is tensor. Can anybody help me how to solve it

Thank you so much !!!

2

Use torch.stack or torch.cat depending on the desired output shape instead of torch.tensor(training_sample).

3

hi @ptrblck ,

After tried it, but seem not work. For instead, I add one more fake column like this:

y = torch.ones(len(embededSequence), 1).float()
dataset = TensorDataset(embededSequence, y)

then it work