Remove pinning protobuf version in requirements.txt.

Install NVIDIA wheels for Keras GPU builds instead of setting LD_LIBRARY_PATH.

PiperOrigin-RevId: 728402252

Author: tensorflower-gardener

requirements.txt

@@ -3,17 +3,23 @@
 pandas
 pydot
 scipy
-# Remove once both TensorFlow and TF-Keras nightly builds pass.
-# Temporarily enforce 3.20.3 version, as the only version which is compatible
-# with both new and old protobuf stubs. This is needed to resolve
-# Keras-TensorFlow circular dependency issue, when one of them gets a dependency
-# incompatible with another one (protobuf in this specific case).
-protobuf==3.20.3
 tf-nightly
 portpicker
 pyyaml
 Pillow
 numpy >= 1.26.0, < 2.1.0 # Sync with the numpy version used in TF
 black==22.3.0
 isort==5.10.1
-flake8==4.0.1
+flake8==4.0.1
+# NVIDIA CUDA dependencies
+nvidia-cublas-cu12 == 12.5.3.2
+nvidia-cuda-cupti-cu12 == 12.5.82
+nvidia-cuda-nvrtc-cu12 == 12.5.82
+nvidia-cuda-runtime-cu12 == 12.5.82
+nvidia-cudnn-cu12 == 9.3.0.75
+nvidia-cufft-cu12 == 11.2.3.61
+nvidia-curand-cu12 == 10.3.6.82
+nvidia-cusolver-cu12 == 11.6.3.83
+nvidia-cusparse-cu12 == 12.5.1.3
+nvidia-nccl-cu12 == 2.25.1
+nvidia-nvjitlink-cu12 == 12.5.82

tf_keras/kokoro/github/ubuntu/gpu/build.sh

@@ -40,9 +40,6 @@ pip install -r requirements.txt
 # Update this once we switch to `tf_keras-nightly` in TensorFlow.
 pip uninstall -y keras-nightly
 
-# LD Library Path needs to be same as TensorFlow Ubuntu Docker build -
-# https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/tf_sig_build_dockerfiles/
-export LD_LIBRARY_PATH="/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:/usr/local/tensorrt/lib"
 CUDA_TOOLKIT_PATH="/usr/local/cuda-11.8"
 TF_CUDA_CONFIG_REPO="@ubuntu20.04-gcc9_manylinux2014-cuda11.8-cudnn8.6-tensorrt8.4_config_cuda"
 TF_CUDA_COMPUTE_CAPABILITIES="sm_35,sm_50,sm_60,sm_70,sm_75,compute_80"