Obtain torch.tensor from string of floats

Question

We can convert 1 dimensional array of floats, stored as a space separated numbers in text file, in to a numpy array or a torch tensor as follows.

line = "1 5 3 7 4"
np_array = np.fromstring(line, dtype='int', sep=" ")

np_array
>> array([1, 5, 3, 7, 4])

And to convert above numpy array to a torch tensor, we can do following :

torch_tensor = torch.tensor(np_array)
torch_tensor
>>tensor([1, 5, 3, 7, 4])

How can I convert a string of numbers separated by space in to a torch.Tensor directly without converting them to a numpy array? We can also do this by fist splitting the string at a space, mapping them to int or float, and then feeding it to torch.tensor. But like numpy's fromstring, is there any such method in pytorch?

Shai · Accepted Answer · 2020-05-10 11:46:13Z

4

What about

x = torch.tensor(list(map(float, line.split(' '))), dtype=torch.float32)

answered May 10, 2020 at 11:46

Shai

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2 Comments

Ruchit Patel Over a year ago

Yes, this is definitely a solution, but, I wanted to know if there is any builtin function in pytorch, like in numpy there is fromstring.

Shai Over a year ago

@MikePatel AFAIK the closest function in pytorch you have is from_numpy()

End genocide - save Gaza · Accepted Answer · 2021-03-23 16:00:18Z

0

PyTorch currently has no analogous function to numpy's fromstring. You can either use the numpy function itself, or by splitting and mapping as you say.

answered Mar 23, 2021 at 16:00

End genocide - save Gaza

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