uv venv --python=3.13; source .venv/bin/activate Using CPython 3.13.8 Creating virtual environment at: .venv Activate with: source .venv/bin/activate

uv pip install torch==2.11
Resolved 10 packages in 1.84s Prepared 4 packages in 4.19s Installed 10 packages in 278ms

• filelock==3.25.2
• fsspec==2026.2.0
• jinja2==3.1.6
• markupsafe==3.0.3
• mpmath==1.3.0
• networkx==3.6.1
• setuptools==81.0.0
• sympy==1.14.0
• torch==2.11.0
• typing-extensions==4.15.0

python -c "import torch" Traceback (most recent call last): File "<string>", line 1, in <module> import torch File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/init.py", line 2229, in <module> from torch import _VF as _VF, functional as functional # usort: skip ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/functional.py", line 8, in <module> import torch.nn.functional as F File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/nn/init.py", line 8, in <module> from torch.nn.modules import * # usort: skip # noqa: F403 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/nn/modules/init.py", line 157, in <module> from .rnn import GRU, GRUCell, LSTM, LSTMCell, RNN, RNNBase, RNNCell, RNNCellBase File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/nn/modules/rnn.py", line 486, in <module> class RNN(RNNBase): ...<329 lines>... return output, self.permute_hidden(hidden, unsorted_indices) File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/nn/modules/rnn.py", line 657, in RNN @torch._jit_internal._overload_method # noqa: F811 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/_jit_internal.py", line 1100, in _overload_method _check_overload_body(func) ~~~~~~~~~~~~~~~~~~~~^^^^^^ File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/_jit_internal.py", line 1015, in _check_overload_body parsed_def = parse_def(func) File "/path/to/repo/.venv/lib/python3.13/site-packages/torch/_sources.py", line 127, in parse_def py_ast = ast.parse(dedent_src) File "~/.local/share/uv/python/cpython-3.13.8-macos-aarch64-none/lib/python3.13/ast.py", line 50, in parse return compile(source, filename, mode, flags, _feature_version=feature_version, optimize=optimize) File "<unknown>", line 9 ) -> tuple[Tensor, Tensor]: ^ IndentationError: expected an indented block after function definition on line 4

Fix Plan

The issue is caused by an incompatibility between PyTorch 2.11 and Python 3.13. To fix this, you can try the following steps:

• Downgrade Python to 3.12: Since the issue only occurs with Python 3.13, downgrading to Python 3.12 should resolve the problem.
• Upgrade PyTorch to a version compatible with Python 3.13: If downgrading Python is not feasible, you can try upgrading PyTorch to a version that is compatible with Python 3.13.

Here's an example of how to downgrade Python using uv:

uv venv --python=3.12
source .venv/bin/activate

And here's an example of how to upgrade PyTorch:

pip install --upgrade torch

However, since the issue is caused by a syntax error in the PyTorch code, it's likely that the PyTorch version you're using is not compatible with Python 3.13. In this case, downgrading Python to 3.12 is the most straightforward solution.

Verification

To verify that the fix worked, you can try importing PyTorch again:

python -c "import torch"

If the import is successful, it means the fix worked.

Extra Tips

• Make sure to check the PyTorch documentation for compatibility with different Python versions.
• If you're using a virtual environment, ensure that the correct Python version is being used.
• If you're experiencing issues with other libraries, try checking their documentation for compatibility with Python 3.13.

Example code to check Python version:

import sys
print(sys.version)