Upgrade minimum python version from 3.8 to 3.10

[Eleven1Liu]

What does this PR do?

Upgrade minimum python version from 3.8 to 3.10 (related PR: #19). Code changes includes:

• System files and documents: as files changed
• Dependencies
  • lightning: The ckpt issue (see Make saving 'last' checkpoint as symbolic link opt-in Lightning-AI/pytorch-lightning#19191 and last.ckpt is a soft link of best.ckpt Lightning-AI/pytorch-lightning#19189)) has been solved, so there's no need to fix the version to 2.0.9.
  • numpy: np.Inf is deprecated (see numpy 2.0.0 release note).
  • scipy: scipy.sparse.csr_matrix.A is deprecated since 1.11.0 (see sparse.csr_matrix.A).
  • transformers/torch CVE: transformers should load files with safetensors (see We now require users to upgrade torch to at least v2.6 in order to use the function. huggingface/transformers#38464), set version to <=4.51.3.

Test CLI & API (bash tests/autotest.sh)

Test APIs used by main.py.

• Test Pass
  • (Copy and paste the last outputted line here.)
• Not Applicable (i.e., the PR does not include API changes.)

Check API Document

If any new APIs are added, please check if the description of the APIs is added to API document.

• API document is updated (linear, nn)
• Not Applicable (i.e., the PR does not include API changes.)

Test quickstart & API (bash tests/docs/test_changed_document.sh)

If any APIs in quickstarts or tutorials are modified, please run this test to check if the current examples can run correctly after the modified APIs are released.

[Eleven1Liu]

merge before #19

[zhi-bao]

Since the .A function is removed in SciPy 1.14+, we can define a to_dense(matrix) function to convert both NumPy matrix and SciPy sparse matrices into dense Numpy arrays, as shown in the following

def to_dense(matrix) -> np.ndarray:
    if scipy.sparse.issparse(matrix):
           return matrix.toarray()
   elif isinstance(matrix, numpy.matrix ):
          return matrix.A

Or, we can directly convert the result based on the type of x@self.weights in

LibMultiLabel/libmultilabel/linear/linear.py

Line 72 in 7fa3734

return (x * self.weights).A + self.thresholds