tags = [
        "no_cuda_asan",  # TODO(b/181771536)
        "no_windows",  # TODO(b/155444728)
    ],
    # We must ensure that the dependencies can be dynamically linked since
    # the shared library must be able to use core:framework.
    deps = [
        ":c_api",
        ":c_api_internal",
        ":c_test_util",
        ":test_op_kernel",
        ":tf_buffer",
        ":tf_buffer_internal",

Follow either of the two links above to access the appropriate CLA and instructions for how to sign and return it. Once we receive it, we'll be able to accept your pull requests.

***NOTE***: Only original source code from you and other people that have signed the CLA can be accepted into the main repository.

### Contributing code

    vocabulary file.
*   Added `index_to_string_table` which returns a lookup table that maps indices
    to strings.
*   Add `string_to_index_table`, which returns a lookup table that matches
    strings to indices.
*   Add a `ParallelForWithWorkerId` function.
*   Add `string_to_index_table`, which returns a lookup table that matches
    strings to indices.

# configure script unconditionally); otherwise if it is false or undefined, the
# build is static and TensorFlow symbols (in Python only) are loaded into the
# global symbol table in order to support op registration. This means that
# projects building with Bazel and importing TensorFlow as a dependency will not
# depend on libtensorflow_framework.so unless they opt in.
tf_cc_shared_library(

# only executabe on the RBE (x86) machine, so the strategy_regexp options are
# added to override and run the actions using remote strategy.
build:rbe_cross_compile_base_xla --strategy_regexp='Generating code from table.*=remote'
build:rbe_cross_compile_base_xla --strategy_regexp='Generating flatbuffer files.*=remote'
build:rbe_cross_compile_base_xla --strategy_regexp='Executing genrule @llvm-project.*=remote'