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.github/workflows/arm-ci-extended-cpp.yml
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ci/official/envs/linux_arm64
# 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 TFCI_DOCKER_REBUILD_ARGS="--target=tf ci/official/containers/linux_arm64" TFCI_INDEX_HTML_ENABLE=1 TFCI_LIB_SUFFIX="-cpu-linux-arm64" TFCI_OUTPUT_DIR=build_output
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.github/workflows/arm-cd.yml
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ci/official/containers/linux_arm64/cuda.packages.txt
# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation 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
# 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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tensorflow/c/eager/abstract_operation.h
public: AbstractOperationKind getKind() const { return kind_; } // Release any underlying resources, including the interface object. // // WARNING: The destructor of this class is marked as protected to disallow // clients from directly destroying this object since it may manage it's own // lifetime through ref counting. Thus this must be allocated on the heap and
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CONTRIBUTING.md
execution time and the sharding [could create an overhead on the test execution](https://github.com/bazelbuild/bazel/issues/2113#issuecomment-264054799). 2. Using [Docker](https://www.docker.com) and TensorFlow's CI scripts. ```bash # Install Docker first, then this will build and run cpu tests tensorflow/tools/ci_build/ci_build.sh CPU bazel test //tensorflow/... ``` See
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tensorflow/c/eager/c_api.h
TFE_DEVICE_PLACEMENT_EXPLICIT = 0, // Copy the tensor to the right device but log a warning. TFE_DEVICE_PLACEMENT_WARN = 1, // Silently copy the tensor, which has a performance cost since the operation // will be blocked till the copy completes. This is the default placement // policy. TFE_DEVICE_PLACEMENT_SILENT = 2, // Placement policy which silently copies int32 tensors but not other dtypes. TFE_DEVICE_PLACEMENT_SILENT_FOR_INT32 = 3,
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.github/workflows/arm-ci-extended.yml
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tensorflow/c/eager/immediate_execution_context.h
DEVICE_PLACEMENT_EXPLICIT = 0, // Copy the tensor to the right device but log a warning. DEVICE_PLACEMENT_WARN = 1, // Silently copy the tensor, which has a performance cost since the operation // will be blocked till the copy completes. This is the default policy. DEVICE_PLACEMENT_SILENT = 2, // Placement policy which silently copies int32 tensors but not other dtypes. DEVICE_PLACEMENT_SILENT_FOR_INT32 = 3, };
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