This is a known error, you need to uninstall numpy by:

pip uninstall numpy

then install "numpy<1.26.4" afresh.

pip install "numpy<1.26.4"

References:

https://github.com/huggingface/diffusers/issues/9069#issuecomment-2267596351

https://github.com/pytorch/pytorch/issues/135836#issuecomment-2347209235

Essentially, the numpy array can be converted into a Tensor using just from_numpy(), it is not required to use .type() again.

Example:

X = numpy.array([1, 2, 3])
X = torch.from_numpy(X)
print(X) # tensor([ 1,  2,  3])

Please check this Torch documentation page for detailed reference. https://pytorch.org/docs/stable/generated/torch.from_numpy.html

I can't completely understand your problem as your code is not formatted properly in your question but the error is just an expected datatype error.

You need to convert your dataframe to a np array. Just add .values at the end of your dataframe. So if your input was a sample dataframe like so:

df = pd.DataFrame({"Col1":[1,2,3,4], "Col2":[2,2,3,4]})

Convert the whole thing to a numpy array like so:

sample_array = df.values

or convert one column to a np array like so:

sample_array_2 = df["Col1"].values

Update: As mentioned in the comments, pandas recommends .to_numpy() instead, so use something like:

sample_array = df.to_numpy()

Here is what I would do:

import torch
import numpy as np
n = np.arange(10)
print(n) #[0 1 2 3 4 5 6 7 8 9]
t1 = torch.Tensor(n)  # as torch.float32
print(t1) #tensor([0., 1., 2., 3., 4., 5., 6., 7., 8., 9.])
t2 = torch.from_numpy(n)  # as torch.int32
print(t2) #tensor([0, 1, 2, 3, 4, 5, 6, 7, 8, 9], dtype=torch.int32)