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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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CONTRIBUTING.md
Changes to TensorFlow C++ code should conform to [Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html). Use `clang-tidy` to check your C/C++ changes. To install `clang-tidy` on ubuntu:16.04, do: ```bash apt-get install -y clang-tidy ``` You can check a C/C++ file by doing: ```bash clang-format <my_cc_file> --style=google > /tmp/my_cc_file.cc diff <my_cc_file> /tmp/my_cc_file.cc
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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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ci/devinfra/docker_windows/Dockerfile
choco install jdk8; \ choco install KB2533623; \ choco install KB2919355; \ choco install KB2919442; \ choco install KB2999226; \ choco install KB3033929; \ choco install KB3035131; \ choco install maven; \ choco install ninja; \ choco install nodejs --version 9.3.0; \ choco install nodejs.install --version 9.3.0; \
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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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WORKSPACE
annotations = NUMPY_ANNOTATIONS, python_interpreter_target = interpreter, requirements = "//:requirements_lock_" + TF_PYTHON_VERSION.replace(".", "_") + ".txt", ) load("@pypi//:requirements.bzl", "install_deps") install_deps() # Initialize the TensorFlow repository and all dependencies. # # The cascade of load() statements and tf_workspace?() calls works around the
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ci/official/requirements_updater/requirements.in
h5py >= 3.10.0 lit ~= 17.0.2 opt_einsum == 3.3.0 astunparse == 1.6.3 dill == 0.3.7 astor == 0.7.1 typing_extensions == 4.8.0 gast == 0.4.0 termcolor == 2.3.0 wrapt == 1.16.0 tblib == 2.0.0 # Install tensorboard, and keras # Note that here we want the latest version that matches TF major.minor version # Note that we must use nightly here as these are used in nightly jobs # For release jobs, we will pin these on the release branch
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README.md
## Install See the [TensorFlow install guide](https://www.tensorflow.org/install) for the [pip package](https://www.tensorflow.org/install/pip), to [enable GPU support](https://www.tensorflow.org/install/gpu), use a [Docker container](https://www.tensorflow.org/install/docker), and [build from source](https://www.tensorflow.org/install/source). To install the current release, which includes support for
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ci/official/envs/macos_x86
TFCI_LIB_SUFFIX="-cpu-darwin-x86_64" TFCI_MACOS_BAZEL_TEST_DIR_ENABLE=1 TFCI_MACOS_BAZEL_TEST_DIR_PATH="/System/Volumes/Data/bazel_output" TFCI_MACOS_INSTALL_BAZELISK_ENABLE=1 TFCI_MACOS_INSTALL_BAZELISK_URL="https://github.com/bazelbuild/bazelisk/releases/download/v1.11.0/bazelisk-darwin-amd64" TFCI_MACOS_TWINE_INSTALL_ENABLE=1 TFCI_OUTPUT_DIR=build_output TFCI_WHL_BAZEL_TEST_ENABLE=1 TFCI_WHL_SIZE_LIMIT=255M TFCI_WHL_SIZE_LIMIT_ENABLE=1
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