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ci/official/envs/linux_x86_cuda
source ci/official/envs/linux_x86 TFCI_BAZEL_COMMON_ARGS="--repo_env=TF_PYTHON_VERSION=$TFCI_PYTHON_VERSION --config release_gpu_linux" TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_cuda TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ARGS="--gpus all" TFCI_LIB_SUFFIX="-gpu-linux-x86_64"
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.github/ISSUE_TEMPLATE/tflite-other.md
- type: input id: Compiler attributes: label: GCC/Compiler version description: if compiling from source placeholder: validations: required: false - type: input id: Cuda attributes: label: CUDA/cuDNN version description: placeholder: validations: required: false - type: input id: Gpu attributes: label: GPU model and memory description: if
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ci/official/containers/linux_arm64/devel.usertools/aarch64.bazelrc
# Change the value of CACHEBUSTER when upgrading the toolchain, or when testing # different compilation methods. E.g. for a PR to test a new CUDA version, set # the CACHEBUSTER to the PR number. build --action_env=CACHEBUSTER=20220325 # Use Python 3.X as installed in container image build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
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ci/official/containers/linux_arm64/cuda.packages.txt
libcudnn8=8.9.6.50-1+cuda12.2 libcudnn8-dev=8.9.6.50-1+cuda12.2 # This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image. # For now it ensures that we install at least version 12.3.107 of PTXAS, # since 12.3.103 has a bug.
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ci/official/README.md
# build. This should also match the system you're using--you cannot build # the TF MacOS package from Linux. # Ex. linux_x86 -- x86_64 Linux platform # Ex. linux_x86_cuda -- x86_64 Linux platform, with Nvidia CUDA support # Ex. macos_arm64 -- arm64 MacOS platform # 3. Add modifiers. Some modifiers for local execution are: # Ex. disk_cache -- Use a local cache
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ci/official/containers/linux_arm64/Dockerfile
# Install devtoolset devel dependencies COPY setup.sources.sh /setup.sources.sh COPY setup.packages.sh /setup.packages.sh COPY devel.packages.txt /devel.packages.txt COPY cuda.packages.txt /cuda.packages.txt RUN /setup.sources.sh && /setup.packages.sh /devel.packages.txt # Install various tools. # - bats: bash unit testing framework # NOTE: v1.6.0 seems to have a bug that made "git" in setup_file break
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ci/official/envs/linux_arm64
TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=linux_arm64 # Note: this is not set to "--cpu", because that changes the package name # to tensorflow_cpu. These ARM builds are supposed to have the name "tensorflow" # despite lacking Nvidia CUDA support. TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow" TFCI_DOCKER_ENABLE=1 TFCI_DOCKER_IMAGE=gcr.io/tensorflow-sigs/build-arm64:tf-2-16-multi-python TFCI_DOCKER_PULL_ENABLE=1
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ci/official/containers/linux_arm64/devel.usertools/aarch64_clang.bazelrc
# Change the value of CACHEBUSTER when upgrading the toolchain, or when testing # different compilation methods. E.g. for a PR to test a new CUDA version, set # the CACHEBUSTER to the PR number. build --action_env=CACHEBUSTER=20220325 # Use Python 3.X as installed in container image build --action_env PYTHON_BIN_PATH="/usr/local/bin/python3"
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tensorflow/c/experimental/gradients/BUILD
"//tensorflow/core:test", "//tensorflow/core:test_main", ], ) tf_cuda_cc_test( name = "nn_grad_test", size = "small", srcs = [ "nn_grad_test.cc", ], args = ["--heap_check="], # TODO(b/174752220): Remove tags = tf_cuda_tests_tags() + ["no_cuda_asan"], # b/173654156, deps = [ ":grad_test_helper", ":nn_grad",
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