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ci/official/README.md
# container and start fresh, run "docker rm -f tf". Removing the container # destroys some temporary bazel data and causes longer builds. # # You will need the NVIDIA Container Toolkit for GPU testing: # https://github.com/NVIDIA/nvidia-container-toolkit # # Note: if you interrupt a bazel command on docker (ctrl-c), you # will need to run `docker exec tf pkill bazel` to quit bazel. #
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RELEASE.md
* Performance improvements * Many bugfixes * Many documentation fixes * TensorBoard fixes: graphs with only one data point, Nan values, reload button and auto-reload, tooltips in scalar charts, run filtering, stable colors * Tensorboard graph visualizer now supports run metadata. Clicking on nodes while viewing a stats for a particular run will show runtime statistics,
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configure.py
print('Found NCCL %s in:' % config['nccl_version']) print(' %s' % config['nccl_library_dir']) print(' %s' % config['nccl_include_dir']) print('\n') environ_cp['CUDA_TOOLKIT_PATH'] = config['cuda_toolkit_path'] return True def get_gcc_compiler(environ_cp): gcc_env = environ_cp.get('CXX') or environ_cp.get('CC') or which('gcc') if gcc_env is not None:
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ci/devinfra/docker_windows/Dockerfile
google-auth google-auth-httplib2 grpcio httplib2 idna ipython-genutils \ kiwisolver macholib matplotlib nose numpy packaging pandas pickleshare pip \ prompt-toolkit protobuf psutil pyasn1 pyasn1-modules pycparser Pygments \ pyparsing pyreadline python-dateutil pytz pywin32 requests rsa setuptools \ simplegeneric six Tempita traitlets uritemplate urllib3 virtualenv wcwidth \
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.bazelrc
build:cuda_clang_official --config=cuda_clang build:cuda_clang_official --action_env=TF_CUDA_VERSION="12" build:cuda_clang_official --action_env=TF_CUDNN_VERSION="8" build:cuda_clang_official --action_env=CUDA_TOOLKIT_PATH="/usr/local/cuda-12.3" build:cuda_clang_official --action_env=GCC_HOST_COMPILER_PATH="/dt9/usr/bin/gcc" build:cuda_clang_official --action_env=CLANG_CUDA_COMPILER_PATH="/usr/lib/llvm-17/bin/clang"
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README.md
* [TensorFlow model optimization roadmap](https://www.tensorflow.org/model_optimization/guide/roadmap) * [TensorFlow White Papers](https://www.tensorflow.org/about/bib) * [TensorBoard Visualization Toolkit](https://github.com/tensorflow/tensorboard) * [TensorFlow Code Search](https://cs.opensource.google/tensorflow/tensorflow) Learn more about the [TensorFlow community](https://www.tensorflow.org/community) and how to
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