Keywords: python-3.x | numpy | tensorflow | anaconda | upgrade | error resolution
Abstract: This article addresses the common error 'No module named numpy.core._multiarray_umath' encountered when importing TensorFlow on Windows with Anaconda3. The primary cause is version incompatibility of numpy, and the solution involves upgrading numpy to a compatible version, such as 1.16.1. Additionally, potential conflicts with libraries like scikit-image are discussed and resolved, ensuring a stable development environment.
Introduction
When attempting to import TensorFlow in a Python environment on Windows 10, particularly with Anaconda3, users may encounter a ModuleNotFoundError stating: No module named 'numpy.core._multiarray_umath'. This error is often puzzling as numpy appears to be installed and functional in other contexts. The root cause typically lies in version mismatches between numpy and TensorFlow.
Root Cause Analysis
The error originates from numpy's internal modules failing to import correctly. Anaconda3 ships with numpy version 1.15.4 by default, which may not be compatible with certain TensorFlow versions or other dependencies. The numpy.core._multiarray_umath module is a critical component for numerical operations, and its absence indicates a corrupted or outdated installation.
Step-by-Step Solution
To resolve this issue, upgrading numpy to a newer version is recommended. Based on user reports, upgrading to numpy 1.16.1 often fixes the problem. The upgrade can be performed using pip:
pip install numpy --upgradeAfter executing this command, restart the Python environment and attempt to import TensorFlow again. The error should be resolved.
Compatibility Considerations
While upgrading numpy, users should be aware of potential conflicts with other libraries. For instance, if scikit-image is part of the project, upgrading numpy to version 1.16.3 might cause an ImportError such as ImportError: cannot import name '_validate_lengths'. In such cases, upgrading scikit-image alongside can resolve the issue:
pip install --upgrade scikit-imageThis ensures that all dependencies are synchronized and compatible.
Conclusion
In summary, the No module named 'numpy.core._multiarray_umath' error is primarily due to numpy version incompatibility. Upgrading numpy to a suitable version, such as 1.16.1, is an effective solution. Always check for and resolve any additional library conflicts to maintain a stable development environment.