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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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CODE_OF_CONDUCT.md
## Scope
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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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tensorflow/c/eager/c_api.h
TF_CAPI_EXPORT extern void TFE_ContextClearCaches(TFE_Context* ctx); // Sets a thread-local device placement policy. After this call, other calls to // TFE_Execute in the same thread will use the device policy specified here // instead of the device policy used to construct the context. This has no // effect on the device policy used by other program threads. TF_CAPI_EXPORT extern void TFE_ContextSetThreadLocalDevicePlacementPolicy(
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tensorflow/c/eager/immediate_execution_distributed_manager.h
int keep_alive_secs) = 0; // Set up a multi-client distributed execution environment. Must be called // on all tasks in the cluster. This call internally coordinates with other // tasks to initialize the eager context and TF server for multi-client // execution. virtual Status EnableCollectiveOps(const ServerDef& server_def) = 0; // Check if the remote task is alive.
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tensorflow/c/c_api.cc
// We have a convoluted scheme here: Using the C++ graph construction API // to add potentially many nodes to the graph without running the checks // (such as uniqueness of the names of nodes) we run with other functions // that add a node to the graph (like TF_FinishOperation). if (!g->name_map.insert(std::make_pair(n->name(), n)).second) { status->status = tensorflow::errors::Internal(
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.github/ISSUE_TEMPLATE/tflite-other.md
name: TensorFlow Lite Other Issue description: Use this template to report any issue in TensorFlow Lite that is not about Converters, Play Services or Ops body: - type: dropdown id: issue-type attributes: label: Issue Type description: What type of issue would you like to report? multiple: false options: - Bug - Build/Install - Performance - Support - Feature Request - Documentation Feature Request - Documentation Bug - Others validations: required: true - type:
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.github/workflows/arm-ci.yml
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