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VOOZH | about |
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VOOZH | about |
An open-source machine learning software library, TensorFlow is used to train neural networks. Expressed in the form of stateful dataflow graphs, each node in the graph represents the operations performed by neural networks on multi-dimensional arrays. These multi-dimensional arrays are commonly known as “tensors,” hence the name TensorFlow.
In this tutorial, you’ll install TensorFlow in a Python virtual environment with virtualenv. This approach isolates the TensorFlow installation and gets things up and running quickly. Once you complete the installation, you’ll validate your installation by importing Tensorflow to ensure you have no errors.
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Community and Developer Education expert. Former Senior Manager, Community at DigitalOcean. Focused on topics including Ubuntu 22.04, Ubuntu 20.04, Python, Django, and more.
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preliminary step is to install latest nvidia drivers and cuda which happens at https://developer.nvidia.com/cuda-downloads
interestingly if you install from this download it will give you matching nvidia drivers, namely when you choose cuda 11.6 it install that and nvidia driver 510 which is super … thanks for this tutorial
if get an error after typing in “import tensorflow as tf”. Unable to figure it out
">>> import tensorflow as tf 2024-01-14 19:30:18.202052: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered 2024-01-14 19:30:18.202267: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered 2024-01-14 19:30:18.204603: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered 2024-01-14 19:30:18.214772: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. 2024-01-14 19:30:19.617811: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT "
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