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tensorflow/c/eager/abstract_op_attrs.h
class AbstractOpAttrs { protected: enum AbstractOpAttrsKind { kEager, kTfrt }; explicit AbstractOpAttrs(AbstractOpAttrsKind kind) : kind_(kind) {} public: // Returns which subclass is this instance of. AbstractOpAttrsKind getKind() const { return kind_; } virtual ~AbstractOpAttrs() = default; // Returns the AbstractFunction as a FunctionDef. virtual void GetNameAttrList(
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.github/ISSUE_TEMPLATE/tflite-other.md
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: markdown attributes: value: | Please make sure that this is a bug. As per our
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ci/official/wheel_test/README.md
the local wheel file specified in the `requirements_lock_<python_version>.txt`. Packages are imported one by one in alphabetical order during runtime. The test doesn't identify package's order-dependent issues; for instance, importing "tf.foo" followed by "tf.bar" won't reveal that "tf.bar" depends on "tf.foo" being imported first. The `_api/v2/api_packages.txt` file is generated during the TensorFlow API v2
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tensorflow/c/c_api_test.cc
feed2_ = Placeholder(graph_, s_, "feed2"); ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_); constant_ = ScalarConst(10, graph_, s_); ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_); desc_ = TF_NewOperation(graph_, "AddN", "add"); TF_Output inputs[] = {{feed1_, 0}, {constant_, 0}}; TF_AddInputList(desc_, inputs, TF_ARRAYSIZE(inputs)); } ~CApiColocationTest() override {
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ci/official/containers/linux_arm64/Dockerfile
FROM ubuntu:20.04 as builder ################################################################################ # Install devtoolset build dependencies COPY setup.packages.sh setup.packages.sh COPY builder.packages.txt builder.packages.txt RUN /setup.packages.sh /builder.packages.txt RUN update-ca-certificates # Install devtoolset-9 in /dt10 with glibc 2.17 and libstdc++ 4.8, for building # manylinux2014-compatible packages.
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.github/workflows/pylint-presubmit.yml
- name: Set up Python 3.9 uses: actions/setup-python@2c3dd9e7e29afd70cc0950079bde6c979d1f69f9 # v4.3.1 with: python-version: "3.9" - name: Install Python dependencies run: | python -m pip install --upgrade pip pip install pylint==2.13.9 numpy wheel - name: Run PyLint on changed files run: |
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ci/official/requirements_updater/WORKSPACE
py_repositories() load("@rules_python//python:repositories.bzl", "python_register_multi_toolchains") # buildifier: disable=same-origin-load load("@rules_python//python/pip_install:repositories.bzl", "pip_install_dependencies") default_python_version = "3.10" load( "//:updater_config_repository.bzl", "updater_config_repository", # @unused )
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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/containers/linux_arm64/devel.usertools/setup_venv_test.sh
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tensorflow/c/eager/immediate_execution_distributed_manager.h
// Check if the remote task is alive. virtual Status CheckRemoteAlive(const std::string& remote_task_name, bool* is_alive) = 0; // Get pointer to the coordination service agent instance. virtual tsl::CoordinationServiceAgent* GetCoordinationServiceAgent() = 0; }; } // namespace tensorflow
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