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Install Tensorflow with GPU support on windows

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To install TensorFlow with CUDA support, follow these step-by-step instructions.
TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows.
Download and install cuda and cudnn - Match TensorFlow version with the appropriate CUDA and cuDNN versions
We are downloading tensorflow 2.10 which required cuda 11.2 and cudnn 8.1
pip install tensorflow==2.10.0
How to Confirm GPU Usage?
import tensorflow as tf
# Check if TensorFlow is using the GPU
print("TensorFlow is using the GPU!")
# Get list of available GPUs
print("Available GPUs:", gpus)
# Get details of each GPU
for gpu in gpus:
print("GPU Details:", details)
else:
print("TensorFlow is using the CPU.")
Output:
TensorFlow is using the GPU!
Available GPUs: [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
GPU Details: {'device_name': 'NVIDIA GeForce RTX 3090', 'compute_capability': (8, 6)}
#tensorflow #computervision #cuda #nvidia
TensorFlow 2.10 was the last TensorFlow release that supported GPU on native-Windows.
Download and install cuda and cudnn - Match TensorFlow version with the appropriate CUDA and cuDNN versions
We are downloading tensorflow 2.10 which required cuda 11.2 and cudnn 8.1
pip install tensorflow==2.10.0
How to Confirm GPU Usage?
import tensorflow as tf
# Check if TensorFlow is using the GPU
print("TensorFlow is using the GPU!")
# Get list of available GPUs
print("Available GPUs:", gpus)
# Get details of each GPU
for gpu in gpus:
print("GPU Details:", details)
else:
print("TensorFlow is using the CPU.")
Output:
TensorFlow is using the GPU!
Available GPUs: [PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]
GPU Details: {'device_name': 'NVIDIA GeForce RTX 3090', 'compute_capability': (8, 6)}
#tensorflow #computervision #cuda #nvidia
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