Reputation: 93
I have been working with Torch. And my current program requires to export a Tensor containing reduced feature matrix. I tried doing the following:
torch.save('t.csv',torch.Tensor({{1,2},{3,4}}),'ascii')
and the output was:
4
1
3
V 1
18
torch.DoubleTensor
2
2 3
3 1
1
4
2
3
V 1
19
torch.DoubleStorage
6
1 2 3 4 5 6
Expected output:
1, 2, 3
4, 5, 6
I'm hoping somebody has an idea as to how I can do this?
Upvotes: 7
Views: 35626
Reputation: 1180
For simple tables, you can also export by converting the tensor to a Numpy array and then to a Pandas dataframe.
import pytorch as torch
import numpy as np
import pandas as pd
t = torch.tensor([[1,2],[3,4]]) #dummy data
t_np = t.numpy() #convert to Numpy array
df = pd.DataFrame(t_np) #convert to a dataframe
df.to_csv("testfile",index=False) #save to file
#Then, to reload:
df = pd.read_csv("testfile")
Upvotes: 10
Reputation: 2430
You can first convert the tensor to a Lua table using torch.totable. Then use the csvigo library to save the table as a csv file. This may be a workaround but I haven't had any problem with it.
Upvotes: -1
Reputation: 436
When saving tensor, torch saves not only data but also -- as you can see -- several other useful information for later deserialisation.
If you need csv serialisation, you are good to implement it yourself.
Fortunately, this is very straightforward.
Here is a quick example :
require 'torch'
matrix = torch.Tensor(5,3) -- a 5x3 matrix
matrix:random(1,10) -- matrix initialized with random numbers in [1,10]
print(matrix) -- let's see the matrix content
subtensor = matrix[{{1,3}, {2,3}}] -- let's create a view on the row 1 to 3, for which we take columns 2 to 3 (the view is a 3x2 matrix, note that values are bound to the original tensor)
local out = assert(io.open("./dump.csv", "w")) -- open a file for serialization
splitter = ","
for i=1,subtensor:size(1) do
for j=1,subtensor:size(2) do
out:write(subtensor[i][j])
if j == subtensor:size(2) then
out:write("\n")
else
out:write(splitter)
end
end
end
out:close()
The output on my computer for the matrix is :
10 10 6
4 8 3
3 8 5
5 5 5
1 6 8
[torch.DoubleTensor of size 5x3]
and the file dumped content :
10,6
8,3
8,5
HTH
Upvotes: 6