Description
🐛 Describe the bug
When using eval() with a restricted environment (builtins = None), only torch.tensor() creation fails with an internal assertion failure at DynamicTypes.cpp:71. Other tensor creation methods like torch.randn() and torch.randint() work correctly in the same environment.
import torch
env = {
"torch": torch,
"__builtins__": None #Critical trigger
}
x = eval("torch.randn(5)", env) # Works
print("x:", x)
y = eval("torch.randint(0, 10, (5, )) ", env) # Works
print("y:", y)
z = eval("torch.tensor(3, dtype=torch.int64)", env) # Fails
print("z:", z)Error Message
x: tensor([ 0.8359, 0.2416, 1.8487, -0.2097, -0.5932])
y: tensor([5, 1, 4, 5, 1])
Traceback (most recent call last):
File "test.py", line 14, in <module>
z = eval("torch.tensor(3, dtype=torch.int64)", env)
File "<string>", line 1, in <module>
RuntimeError: storage_module && PyModule_Check(storage_module) INTERNAL ASSERT FAILED at "C:\\actions-runner\\_work\\pytorch\\pytorch\\pytorch\\torch\\csrc\\DynamicTypes.cpp":71, please report a bug to PyTorch.
Versions
Collecting environment information...
PyTorch version: 2.7.0+cpu
Is debug build: False
CUDA used to build PyTorch: None
ROCM used to build PyTorch: N/A
OS: Microsoft Windows 11
GCC version: Could not collect
Clang version: Could not collect
CMake version: version 4.0.2
Libc version: N/A
Python version: 3.10.10 (tags/v3.10.10:aad5f6a, Feb 7 2023, 17:20:36) [MSC v.1929 64 bit (AMD64)] (64-bit runtime)
Python platform: Windows-10-10.0.26100-SP0
Is CUDA available: False
CUDA runtime version: No CUDA
CUDA_MODULE_LOADING set to: N/A
GPU models and configuration: No CUDA
Nvidia driver version: No CUDA
cuDNN version: No CUDA
HIP runtime version: N/A
MIOpen runtime version: N/A
Is XNNPACK available: True
CPU:
Name: AMD Ryzen 5 7500F 6-Core Processor
Manufacturer: AuthenticAMD
Family: 107
Architecture: 9
ProcessorType: 3
DeviceID: CPU0
CurrentClockSpeed: 3701
MaxClockSpeed: 3701
L2CacheSize: 6144
L2CacheSpeed: None
Revision: 24834
Versions of relevant libraries:
[pip3] mypy_extensions==1.1.0
[pip3] numpy==2.2.4
[pip3] nvidia-cuda-runtime-cu12==12.9.37
[pip3] >
[pip3] onnx-coreml==1.3
[pip3] onnx-tf==1.10.0
[pip3] >
[pip3] >
[pip3] >
[pip3] optree==0.15.0
[pip3] pytorch-lightning==2.5.1
[pip3] torch==2.7.0
[pip3] torch-directml==0.2.5.dev240914
[pip3] torch-geometric==2.6.1
[pip3] torch_scatter==2.1.2
[pip3] torch_tensorrt==2.7.0
[pip3] torchani==2.2.4
[pip3] torchao==0.11.0
[pip3] torchaudio==2.7.0
[pip3] torchdata==0.11.0
[pip3] torchfx==0.1.0
[pip3] torchmetrics==1.7.1
[pip3] torchrec==0.1.0
[pip3] torchsummary==1.5.1
[pip3] torchtext==0.18.0
[pip3] torchvision==0.19.1
[pip3] torchviz==0.0.3
[pip3] torchx-nightly==2025.5.28
[pip3] vector-quantize-pytorch==1.22.16
[conda] Could not collect