from tensorflow.python.lib.io import file_io as _fi

# Get sitepackages directories for the python installation.
_site_packages_dirs = []
_site_packages_dirs += [] if _site.USER_SITE is None else [_site.USER_SITE]
_site_packages_dirs += [p for p in _sys.path if "site-packages" in p]
if "getsitepackages" in dir(_site):
  _site_packages_dirs += _site.getsitepackages()

if "sysconfig" in dir(_distutils):

    "python_repository",
)

python_repository(name = "python_version_repo")

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

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

load("@python//:defs.bzl", "interpreter")
load("@rules_python//python:pip.bzl", "package_annotation", "pip_parse")

NUMPY_ANNOTATIONS = {

      if (n == nullptr) continue;

      // Adding the gradients to the graph can alter the prefix to prevent
      // name collisions only if this prefix has not been provided explicitly
      // by the user. If it was provided, assert that it remained intact.
      if (prefix != nullptr && !absl::StartsWith(n->name(), prefix_cmp)) {
        status->status = tensorflow::errors::Internal(

    ```

    If the tests are to be run on the GPU, add CUDA paths to LD_LIBRARY_PATH and
    add the `cuda` option flag

    ```bash
    export LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/usr/local/cuda/lib64:/usr/local/cuda/extras/CUPTI/lib64:$LD_LIBRARY_PATH"
    export flags="--config=opt --config=cuda -k"
    ```

    For example, to run all tests under tensorflow/python, do:

    ```bash

      # Needed to attach tags into the PR
      issues: write
      contents: write
      pull-requests: write
    if: |
      github.event.pull_request.draft == false &&
      github.event.sender.type == 'User'
    steps:
      - name: Checkout repo
        uses: actions/checkout@755da8c3cf115ac066823e79a1e1788f8940201b # v3.2.0
      - name: Trusted-Partners-PR

  mkdir -p "${TFCI_MACOS_CROSS_COMPILE_SDK_DEST}/usr"
  mkdir -p "${TFCI_MACOS_CROSS_COMPILE_SDK_DEST}/System/Library/Frameworks/"
  cp -r "${TFCI_MACOS_CROSS_COMPILE_SDK_SOURCE}/usr/include" "${TFCI_MACOS_CROSS_COMPILE_SDK_DEST}/usr/include"
  cp -r "${TFCI_MACOS_CROSS_COMPILE_SDK_SOURCE}/usr/lib" "${TFCI_MACOS_CROSS_COMPILE_SDK_DEST}/usr/lib"

from anywhere, and executes the graphs it is sent without performing any checks.
Therefore, if you run a `tf.train.Server` in your network, anybody with access
to the network can execute arbitrary code with the privileges of the user
running the `tf.train.Server`.

## Untrusted inputs during training and prediction

TensorFlow supports a wide range of input data formats. For example it can

#!/usr/bin/env bash
# Copyright 2023 The TensorFlow Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,

// Represents either a MlirTensor or a GraphTensor.
// This base class does not expose any public methods other than to distinguish
// which subclass it actually is. The user is responsible to use the right
// type of AbstractTensor in their context (do not pass an MlirTensor to a
// GraphContext and vice-versa).
class TracingTensorHandle : public AbstractTensorHandle {
 protected:

// These tests should not be confused with `[*]_grad_test` which compare the
// result of `gradient_checker` and `[*]_grad`. The tests here test the
// functionality of `gradient_checker` by comparing the result with expected
// manual user-provided gradients.
class GradientCheckerTest
    : public ::testing::TestWithParam<std::tuple<const char*, bool, bool>> {
 protected:
  void SetUp() override {
    TF_StatusPtr status(TF_NewStatus());