```

#### Requirements Updater Script
This script automates the process of updating TensorFlow requirements for a
specific Python version.

##### Parameters
`path_to_tensorflow_wheel`: The local path to the TensorFlow wheel file.
Example: `/tmp/tensorflow-2.14.0-cp311-cp311-linux_x86_64.whl`

`python_version`: The target Python version, replacing `.` with `_`.

#include "tensorflow/core/platform/status.h"

namespace tensorflow {

// Builds and returns a `TracingContext` using the default tracing impl.
AbstractContext* BuildFunction(const char* fn_name);

// Creates parameters (placeholders) in the tracing `ctx` using the shape and
// dtype of `inputs`.
Status CreateParamsForInputs(AbstractContext* ctx,
                             absl::Span<AbstractTensorHandle* const> inputs,

  export -p | grep TFCI

  # Load those stored pre-existing TFCI_ vars, if any
  if [[ -s "$FROM_ENV" ]]; then
    echo '==TFCI==: NOTE: Loading the following env parameters, which were'
    echo 'already set in the shell environment. If you want to disable this'
    echo 'behavior, create a new shell.'
    cat "$FROM_ENV"
    source "$FROM_ENV"
    rm "$FROM_ENV"
  fi
fi

'''
 Repository rule to set some environment variables.
 Can be set via build parameter "--repo_env=<VARIABLE_NAME>=<value>"
 e.g "--repo_env=REQUIREMENTS_FILE_NAME=requirements.in"

 List of variables:
 REQUIREMENTS_FILE_NAME
'''

def _updater_config_repository_impl(repository_ctx):
    repository_ctx.file("BUILD", "")
    requirements_file_name = repository_ctx.os.environ.get("REQUIREMENTS_FILE_NAME", "requirements.in")
    repository_ctx.file(

ln -s "/usr/include/asm-generic" "${TARGET}/usr/include/asm-generic"
ln -s "/usr/include/aarch64-linux-gnu/asm" "${TARGET}/usr/include/asm"

# Download glibc's shared and development libraries based on the value of the
# `VERSION` parameter.
# Note: 'Templatizing' this and the other conditional branches would require
# defining several variables (version, os, path) making it difficult to maintain
# and extend for future modifications.
mkdir -p glibc-src

   While this isn't necessary for running the updater, it is required for
   actually using the new version with Tensorflow.

2) In the `WORKSPACE` file, add the new version to the `python_versions`
   parameter of the `python_register_multi_toolchains` function.

3) In the `BUILD.bazel` file, add a load statement for the new version, e.g.

   ```
      load("@python//3.11:defs.bzl",

  vector<AbstractTensorHandle*> theta_inputs(inputs.size());
  for (int i{}; i < inputs.size(); ++i) {
    theta_inputs[i] = inputs[i];
  }

  AbstractTensorHandle* theta =
      theta_inputs[input_index];  // parameter we are grad checking

  // Convert from AbstractTensor to TF_Tensor.
  TF_Tensor* theta_tensor;
  TF_RETURN_IF_ERROR(GetValue(theta, &theta_tensor));

  // Get number of elements and fill data.