ScalarFloatFromTensor(fetchValues[1], &dxy_dyValue);
  EXPECT_EQ(X, dxy_dyValue);

  TF_DeleteTensor(fetchValues[0]);
  TF_DeleteTensor(fetchValues[1]);
}

// REGISTER_OP for CApiAttributesTest test cases.
// Registers two ops, each with a single attribute called 'v'.
// The attribute in one op will have a type 'type', the other
// will have list(type).
#define ATTR_TEST_REGISTER_OP(type)                           \

#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_server_lib.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/macros.h"
#include "tensorflow/core/platform/protobuf.h"

interfaces into a single place. The interfaces themselves are located in
sub-modules, as described below.

Note that the file `__init__.py` in the TensorFlow source code tree is actually
only a placeholder to enable test cases to run. The TensorFlow build replaces
this file with a file generated from [`api_template.__init__.py`](https://www.github.com/tensorflow/tensorflow/blob/master/tensorflow/api_template.__init__.py)
"""

vulnerabilities to the vendor of the affected hardware accelerator.

## Reporting vulnerabilities

### Vulnerabilities in TensorFlow

This document covers different use cases for TensorFlow together with comments
whether these uses were recommended or considered safe, or where we recommend
some form of isolation when dealing with untrusted data. As a result, this

*   Fixes a missing validation which causes denial of service via `GetSessionTensor` ([CVE-2022-29191](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-29191))
*   Fixes a missing validation which causes denial of service via `StagePeek` ([CVE-2022-29195](https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-29195))

    SINGLE_CASE(kF, TF_ATTR_FLOAT, -1);
    SINGLE_CASE(kB, TF_ATTR_BOOL, -1);
    SINGLE_CASE(kType, TF_ATTR_TYPE, -1);
    SINGLE_CASE(kShape, TF_ATTR_SHAPE,
                attr->shape().unknown_rank() ? -1 : attr->shape().dim_size());
    SINGLE_CASE(kTensor, TF_ATTR_TENSOR, -1);
#undef SINGLE_CASE

    case tensorflow::AttrValue::kList:
      metadata.is_list = 1;
      metadata.list_size = 0;

  switch (data_type) {
    case TF_DataType::TF_BOOL:
      dtype.code = DLDataTypeCode::kDLBool;
      break;
    case TF_DataType::TF_HALF:
    case TF_DataType::TF_FLOAT:
    case TF_DataType::TF_DOUBLE:
      dtype.code = DLDataTypeCode::kDLFloat;
      break;
    case TF_DataType::TF_INT8:
    case TF_DataType::TF_INT16:
    case TF_DataType::TF_INT32:
    case TF_DataType::TF_INT64:

// make sure all nodes are finished.
TF_CAPI_EXPORT extern void TFE_DeleteExecutor(TFE_Executor*);

// Returns true if the executor is in async mode.
TF_CAPI_EXPORT extern bool TFE_ExecutorIsAsync(TFE_Executor*);

// Causes the calling thread to block till all ops dispatched in this executor
// have been executed. Note that "execution" here refers to kernel execution /
// scheduling of copies, etc. Similar to sync execution, it doesn't guarantee

# limitations under the License.
# ==============================================================================

set -euxo pipefail

function resultstore_extract_fallback {
  # In case the main script fails somehow.
  cat <<EOF
IMPORTANT: For bazel invocations that uploaded to ResultStore (e.g. RBE), you
can view more detailed results that are probably easier to read than this log.
Try the links below:
EOF

# ==============================================================================
#
# Builds a devtoolset cross-compiler targeting manylinux2014 (glibc 2.17 / libstdc++ 4.8).

VERSION="$1"
TARGET="$2"

case "${VERSION}" in
devtoolset-9)
  LIBSTDCXX_VERSION="6.0.28"
  LIBSTDCXX_ABI="new"
  ;;
devtoolset-10)
  LIBSTDCXX_VERSION="6.0.28"
  LIBSTDCXX_ABI="new"
  ;;
*)