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ci/official/containers/linux_arm64/builder.devtoolset/build_devtoolset.sh
# Note that the installation path for libstdc++ here is ${TARGET}/usr/lib64/ mv "${TARGET}/usr/lib64/libstdc++.so.${LIBSTDCXX_VERSION}" \ "${TARGET}/usr/lib64/libstdc++.so.${LIBSTDCXX_VERSION}.backup" echo -e "OUTPUT_FORMAT(elf64-littleaarch64)\nINPUT ( libstdc++.so.6.0.18 -lstdc++_nonshared44 )" \ > "${TARGET}/usr/lib64/libstdc++.so.${LIBSTDCXX_VERSION}" cp "./aarch64-unknown-linux-gnu/libstdc++-v3/src/.libs/libstdc++_nonshared44.a" \
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CONTRIBUTING.md
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 ``` #### Python coding style Changes to TensorFlow Python code should conform to
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tensorflow/c/eager/c_api_experimental.h
// devices, so executing tf.functions which contain operations placed on the // custom devices will fail. // // `device_name` must not name an existing physical or custom device. It must // follow the format: // // /job:<name>/replica:<replica>/task:<task>/device:<type>:<device_num> // // If the device is successfully registered, `status` is set to TF_OK. Otherwise
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tensorflow/c/BUILD
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ci/official/containers/linux_arm64/devel.usertools/repack_libtensorflow.sh
# # ============================================================================== # # Repacks libtensorflow tarballs into $DIR with provided $TARBALL_SUFFIX, # and also repacks libtensorflow-src.jar into a standardized format. # Helper function to copy a srcjar after moving any source files # directly under the root to the "maven-style" src/main/java layout # # Source files generated by annotation processors appear directly
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ci/official/utilities/rename_and_verify_wheels.sh
# other than the most recently-modified one (the new one). ls -t *.whl | tail -n +2 | xargs rm fi # Check if size is too big. TFCI_WHL_SIZE_LIMIT is in find's format, which can be # 'k' for kilobytes, 'M' for megabytes, or 'G' for gigabytes, and the + to indicate # "anything greater than" is added by the script.
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SECURITY.md
should be used with caution when working with untrusted models. ### Saved graphs and checkpoints When loading untrusted serialized computation graphs (in form of a `GraphDef`, `SavedModel`, or equivalent on-disk format), the set of computation primitives available to TensorFlow is powerful enough that you should assume that the TensorFlow process effectively executes arbitrary code.
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LICENSE
replaced with your own identifying information. (Don't include the brackets!) The text should be enclosed in the appropriate comment syntax for the file format. We also recommend that a file or class name and description of purpose be included on the same "printed page" as the copyright notice for easier identification within third-party archives.
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tensorflow/c/eager/BUILD
"//tensorflow/core/distributed_runtime/rpc:rpc_rendezvous_mgr", "//tensorflow/core/distributed_runtime/rpc/eager:grpc_eager_client", "@com_google_absl//absl/memory", "@com_google_absl//absl/strings:str_format", "@local_xla//xla/tsl/c:tsl_status_internal", ], alwayslink = 1, ) filegroup( name = "pywrap_required_hdrs", srcs = [ "abstract_context.h",
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tensorflow/c/c_api_function_test.cc
v.push_back(IOSpec(name, DT_INVALID)); } return v; } // Specification for an expected edge. // src is either: // - input name (as it appears in FunctionDef) // - name of output tensor (in nested "add:z:0" format) // dst is either: // - output name (as it appears in FunctionDef) // - <name_of_node>:<index_of_this_input_into_node> (this looks the same as // output tensor naming, but it the index is actually an input index)
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