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",
           compile_pip_requirements_3_11 = "compile_pip_requirements")
   ```

   Add a new entry for the loaded `compile_pip_requirements`, e.g.

   ```

# Description:
# C API for TensorFlow, for use by client language bindings.

load("@bazel_skylib//lib:selects.bzl", "selects")
load("@local_config_tensorrt//:build_defs.bzl", "if_tensorrt")
load("@local_tsl//tsl/platform:rules_cc.bzl", "cc_library")
load(
    "//tensorflow:tensorflow.bzl",
    "check_deps",
    "if_google",
    "if_not_mobile",
    "tf_cc_test",
    "tf_copts",
    "tf_cuda_library",
    "tf_custom_op_library",

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

    ```

    For a single/parameterized test e.g. `test_capture_variables` in
    `tensorflow/python/saved_model/load_test.py`:

    (Requires `python>=3.7`)

    ```bash
    bazel test ${flags} //tensorflow/python/saved_model:load_test --test_filter=*LoadTest.test_capture_variables*
    ```

    **Note:** You can add `--test_sharding_strategy=disabled` to the `flags` to

    "tf_additional_profiler_deps",
)
load("@bazel_skylib//:bzl_library.bzl", "bzl_library")

# Do not sort: Copybara rule
# copybara:uncomment_begin
# # buildifier: disable=out-of-order-load
# load("//devtools/build_cleaner/skylark:action_config_test.bzl", "action_config_test")
# load("//devtools/copybara/rules:copybara.bzl", "copybara_config_test")
# load("@rules_license//rules:license.bzl", "license")

# Experimental extensions to the C API for eager execution of kernels.

load(
    "//tensorflow:tensorflow.bzl",
    "tf_cc_test",
    "tf_copts",
    "tf_cuda_cc_test",
    "tf_cuda_library",
)
load("//tensorflow:tensorflow.default.bzl", "cc_header_only_library", "filegroup")
load(
    "//tensorflow/core/platform:build_config_root.bzl",
    "tf_cuda_tests_tags",
)
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(

        `tf.not_equal`, `tf.sin`, `tf.sinh`, `tf.tan`
    *   Deprecate `tf.data.Dataset.shard`.
    *   Deprecate `saved_model.loader.load` which is replaced by
        `saved_model.load` and `saved_model.main_op`, which will be replaced by
        `saved_model.main_op` in V2.
    *   Deprecate tf.QUANTIZED_DTYPES. The official new symbol is
        tf.dtypes.QUANTIZED_DTYPES.

load("@python_version_repo//:py_version.bzl", "TF_PYTHON_VERSION")

# Register multi toolchains
load("@rules_python//python:repositories.bzl", "python_register_toolchains")  # buildifier: disable=same-origin-load

python_register_toolchains(
    name = "python",
    ignore_root_user_error = True,
    python_version = TF_PYTHON_VERSION,
)

load("@python//:defs.bzl", "interpreter")

load(
    "//tensorflow:tensorflow.bzl",
    "if_libtpu",
    "tf_cuda_cc_test",
)
load("//tensorflow:tensorflow.default.bzl", "filegroup")
load(
    "//tensorflow/core/platform:build_config_root.bzl",
    "tf_cuda_tests_tags",
)
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

# Library of gradient functions.
package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    licenses = ["notice"],

# Experimental posix filesystem plugin.
load("//tensorflow:tensorflow.bzl", "tf_cc_shared_object")
load("//tensorflow/core/platform:rules_cc.bzl", "cc_library")

package(
    # copybara:uncomment default_applicable_licenses = ["//tensorflow:license"],
    default_visibility = ["//visibility:private"],
    licenses = ["notice"],
)

# Filesystem implementation for POSIX environments: Linux, MacOS, Android, etc.
tf_cc_shared_object(