(.venv) ~/src/repos/gpu_tests$ . config_tf_env.sh
✅ TensorFlow GPU environment configured
LD_LIBRARY_PATH set to:
.venv/lib/python3.13/site-packages/nvidia/cublas/lib
.venv/lib/python3.13/site-packages/nvidia/cudnn/lib
.venv/lib/python3.13/site-packages/nvidia/cuda_runtime/lib
.venv/lib/python3.13/site-packages/nvidia/cufft/lib
.venv/lib/python3.13/site-packages/nvidia/curand/lib
.venv/lib/python3.13/site-packages/nvidia/cusolver/lib
.venv/lib/python3.13/site-packages/nvidia/cusparse/lib
.venv/lib/python3.13/site-packages/nvidia/cuda_nvrtc/lib
/usr/lib/x86_64-linux-gnu
(.venv) dever@ubiskee:~/src/repos/gpu_tests$ python tensorflow_cuda_test.py
======================================================================
TensorFlow CUDA/GPU Test Program
======================================================================
TensorFlow Version: 2.21.0-dev20251126
Python Version: 3.13.9
======================================================================
GPU AVAILABILITY TEST
======================================================================
✅ GPU(s) detected: 1 device(s)
======================================================================
GPU INFORMATION
======================================================================
Number of GPUs: 1
GPU 0:
Device: /physical_device:GPU:0
Device Type: GPU
Compute Capability: (12, 0)
Name: NVIDIA GeForce RTX 5080
Memory Growth: None
TensorFlow Version: 2.21.0-dev20251126
Built with CUDA: True
GPU Support Available: True
======================================================================
GPU COMPUTATION TEST
======================================================================
Creating two 5000x5000 random matrices...
Performing matrix multiplication on GPU...
✅ GPU computation completed in 0.0382 seconds
Comparing with CPU computation...
CPU computation completed in 0.1333 seconds
🚀 GPU Speedup: 3.49x faster than CPU
Verifying correctness with smaller matrices...
Maximum difference between CPU and GPU results: 1.18e-02
✅ Results match (within tolerance for TF32 execution)!
======================================================================
TENSOR OPERATIONS TEST
======================================================================
Test 1: Basic tensor operations...
Addition: [ 3. 5. 7. 9. 11.]
Multiplication: [ 2. 6. 12. 20. 30.]
Test 2: Neural network operations...
Input shape: (32, 10)
Output shape: (32, 5)
✅ Neural network operations work!
Test 3: Gradient computation...
Variable created: (5, 5)
Gradient computed: True
Gradient shape: (5, 5)
✅ Gradient computation works!
======================================================================
KERAS MODEL TEST
======================================================================
Creating a simple neural network...
Model created with 9729 parameters
Training model for 3 epochs...
✅ Training completed in 0.7144 seconds
Final loss: 0.6724
Final accuracy: 0.5940
Test predictions shape: (10, 1)
✅ Keras model works on GPU!
======================================================================
MIXED PRECISION TEST
======================================================================
Current mixed precision policy: float32
New mixed precision policy: mixed_float16
Input dtype: <dtype: 'float32'>
Output dtype: <dtype: 'float16'>
Weights dtype: float32
✅ Mixed precision works!
======================================================================
MNIST DATA TEST
Verifying Keras nightly is installed with TensorFlow nightly...
Training set shape: (60000, 28, 28)
Test set shape: (10000, 28, 28)
✅ MNIST dataset loaded successfully!
======================================================================
TEST SUMMARY
======================================================================
✅ All tests passed!
Your TensorFlow CUDA installation is working correctly.
======================================================================