Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

What is this warning about? Modern CPUs provide a lot of low-level instructions, besides the usual arithmetic and logic, known as extensions, e.g. SSE2, SSE4, AVX, etc. From the Wikipedia: Advanced Vector Extensions (AVX) are extensions to the x86 instruction set architecture for microprocessors from Intel and AMD proposed by Intel in March 2008 and … Read more

How to find which version of TensorFlow is installed in my system?

This depends on how you installed TensorFlow. I am going to use the same headings used by TensorFlow’s installation instructions to structure this answer. Pip installation Run: Note that python is symlinked to /usr/bin/python3 in some Linux distributions, so use python instead of python3 in these cases. pip list | grep tensorflow for Python 2 … Read more

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

What is this warning about? Modern CPUs provide a lot of low-level instructions, besides the usual arithmetic and logic, known as extensions, e.g. SSE2, SSE4, AVX, etc. From the Wikipedia: Advanced Vector Extensions (AVX) are extensions to the x86 instruction set architecture for microprocessors from Intel and AMD proposed by Intel in March 2008 and … Read more

Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX AVX2

What is this warning about? Modern CPUs provide a lot of low-level instructions, besides the usual arithmetic and logic, known as extensions, e.g. SSE2, SSE4, AVX, etc. From the Wikipedia: Advanced Vector Extensions (AVX) are extensions to the x86 instruction set architecture for microprocessors from Intel and AMD proposed by Intel in March 2008 and first supported … Read more

What is the difference between model.fit() an model.evaluate() in Keras?

fit() is for training the model with the given inputs (and corresponding training labels). evaluate() is for evaluating the already trained model using the validation (or test) data and the corresponding labels. Returns the loss value and metrics values for the model. predict() is for the actual prediction. It generates output predictions for the input … Read more