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CONTRIBUTING.md
development to avoid installing the packages directly on your system (in which case remember to change the directory from `/root` to `/tensorflow` once you get into the running container so `bazel` can find the `tensorflow` workspace). you can do this by using the following command. As an example- ```bash docker run -it --rm -v $PWD:/tmp -w /tmp tensorflow/build:2.15-python3.10
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tensorflow/c/BUILD
"//tensorflow/core:protos_all_cc", "//tensorflow/core:test", "//tensorflow/core:test_main", "//tensorflow/core/kernels:ops_testutil", "@com_google_absl//absl/container:inlined_vector", "@com_google_absl//absl/strings:str_format", "@eigen_archive//:eigen3", ], ) tf_cc_test( name = "ops_test", size = "medium",
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tensorflow/c/eager/BUILD
"//tensorflow/core/common_runtime/eager:tensor_handle", "//tensorflow/core/profiler/lib:traceme", "@com_google_absl//absl/algorithm:container", "@com_google_absl//absl/types:span", "@com_google_absl//absl/types:variant", ], }) + [ ":abstract_tensor_handle", "//tensorflow/c:c_api_macros_hdrs",
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LICENSE
(d) If the Work includes a "NOTICE" text file as part of its distribution, then any Derivative Works that You distribute must include a readable copy of the attribution notices contained within such NOTICE file, excluding those notices that do not pertain to any part of the Derivative Works, in at least one of the following places: within a NOTICE text file distributed
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ci/official/containers/linux_arm64/devel.usertools/code_check_full.bats
# targets matching the provided query, which start with // or @ but not # //tensorflow (so it looks for //third_party, //external, etc.), and then # gathers the list of all packages (i.e. directories) which contain those # targets. license_query() { bazel cquery --experimental_cc_shared_library "$1" --keep_going \ | grep -e "^//" -e "^@" \ | grep -E -v "^//tensorflow" \ | sed -e 's|:.*||' \ | sort -u }
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ci/official/utilities/code_check_full.bats
# targets matching the provided query, which start with // or @ but not # //tensorflow (so it looks for //third_party, //external, etc.), and then # gathers the list of all packages (i.e. directories) which contain those # targets. license_query() { bazel cquery --experimental_cc_shared_library "$1" --keep_going \ | grep -e "^//" -e "^@" \ | grep -E -v "^//tensorflow" \ | sed -e 's|:.*||' \ | sort -u }
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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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