The error “Cannot convert a symbolic Tensor (2nd_target:0) to a Numpy Array” occurs when there is a “version mismatch between Numpy and TensorFlow.”
Mixing symbolic tensors with non-symbolic types, like NumPy arrays, can lead to this error. In TensorFlow, symbolic tensors are used to define a computational graph, and their values are not immediately known. On the other hand, NumPy arrays have concrete values.
When you try to perform operations between these two types, TensorFlow doesn’t know how to handle the mixture of symbolic and non-symbolic data, leading to the error.
How to fix it?
Here are two ways to fix the NotImplementedError: Cannot convert a symbolic Tensor to a Numpy Array error:
- By upgrading the TensorFlow and Numpy
- Install the specific version of Numpy
Solution 1: Upgrading the TensorFlow and Numpy
You can upgrade TensorFlow and Numpy using pip:
pip install --upgrade numpy
pip install --upgrade tensorflowThis will fix the error.
If you still face the error, uninstall and install the TensorFlow library.
pip uninstall tensorflow
pip install tensorflowSolution 2: Install the specific version of Numpy
If you are facing the issue when upgrading from numpy 1.19 to 1.20, Simply downgrade the numpy using this command:
pip install numpy==1.19.5You can also update to a newer TensorFlow (2.6+) version now that resolves the problem:
pip install -U tensorflow
And I hope the error will be fixed now!
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Krunal Lathiya is a seasoned Computer Science expert with over eight years in the tech industry. He boasts deep knowledge in Data Science and Machine Learning. Versed in Python, JavaScript, PHP, R, and Golang. Skilled in frameworks like Angular and React and platforms such as Node.js. His expertise spans both front-end and back-end development. His proficiency in the Python language stands as a testament to his versatility and commitment to the craft.
