TF_Buffer* buf) {
  string content;
  cell->cell.value().SerializeToString(&content);
  void* data = tensorflow::port::Malloc(content.length());
  content.copy(static_cast<char*>(data), content.length(), 0);
  buf->data = data;
  buf->length = content.length();
  buf->data_deallocator = [](void* data, size_t length) {
    tensorflow::port::Free(data);
  };

)

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

NUMPY_ANNOTATIONS = {
    "numpy": package_annotation(
        additive_build_content = """\
filegroup(
    name = "includes",
    srcs = glob(["site-packages/numpy/core/include/**/*.h"]),
)
cc_library(
    name = "numpy_headers",
    hdrs = [":includes"],

on:
  push:
    branches:
      - master
      
permissions: {}

jobs:
  create-issue-on-pr-rollback:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      issues: write
      pull-requests: read
    if: |
      github.repository == 'tensorflow/tensorflow' &&
      startsWith(github.event.head_commit.message, 'Rollback of PR #')
    steps:

TFE_Op* CloneOp(const TFE_Op* other) {
  TF_Status* status = TF_NewStatus();
  TFE_Context* context = TFE_OpGetContext(other, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  const char* op_name = TFE_OpGetName(other, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_Op* ret = TFE_NewOp(context, op_name, status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

      names, trademarks, service marks, or product names of the Licensor,
      except as required for reasonable and customary use in describing the
      origin of the Work and reproducing the content of the NOTICE file.

   7. Disclaimer of Warranty. Unless required by applicable law or
      agreed to in writing, Licensor provides the Work (and each
      Contributor provides its Contributions) on an "AS IS" BASIS,

    srcs = [
        "array_ops.cc",
    ],
    hdrs = [
        "array_ops.h",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        "//tensorflow/c/eager:abstract_context",
        "//tensorflow/c/eager:abstract_operation",
        "//tensorflow/c/eager:abstract_tensor_handle",
        "//tensorflow/c/eager:c_api_unified_internal",
        "//tensorflow/c/eager:tracing_utils",

  TFE_CancelCallback callback2;
  bool callback2_invoked = false;
  callback2.context = &callback2_invoked;
  callback2.callback = [](void* context) {
    *reinterpret_cast<bool*>(context) = true;
  };
  TFE_CancellationToken token2 = TFE_CancellationManagerGetToken(c_mgr);
  EXPECT_TRUE(TFE_CancellationManagerRegisterCallback(c_mgr, token2, &callback2,

==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_UNIFIED_API_TESTUTIL_H_
#define TENSORFLOW_C_EAGER_UNIFIED_API_TESTUTIL_H_

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental.h"

   *     my_add2 = b + b
   *     return my_add1, my_add2
   *
   * Now we will execute this function with an eager context:
   *
   *   output1, output2 = two_adds(2.0, 3.0)
   *
   * and check that we got 5.0 and 6.0 as results.
   */

  // Build eager context.
  TFE_ContextOptions* opts = TFE_NewContextOptions();
  TFE_ContextOptionsSetTfrt(opts, std::get<1>(GetParam()));

        "//tensorflow/c/eager:c_api_experimental",
        "//tensorflow/c/eager:tfe_context_internal",
        "//tensorflow/core:framework",
        "//tensorflow/core:protos_all_cc",
        "//tensorflow/core:test",
        "//tensorflow/core:test_main",
        "//tensorflow/core/common_runtime/eager:context",
    ],
)

cc_library(
    name = "parallel_device_testlib",
    testonly = 1,