private:
  TF_Graph* graph_;
  int counter_;
};

// Helper macros for the TF_OperationGetAttr* tests.
// TODO(ashankar): Use gmock matchers instead?
// (https://github.com/google/googletest/blob/master/googlemock/docs/CookBook.md#writing-new-parameterized-matchers-quickly)
// That will require setting up the tensorflow build with gmock.
#define EXPECT_TF_META(attr_name, expected_list_size, expected_type, \

potentially exploit a vulnerability in the TensorFlow code that handles videos,
which could allow them to execute arbitrary code on the system running
TensorFlow.

It is important to keep TensorFlow up to date with the latest security patches
and follow the sandboxing guideline above to protect against these types of
vulnerabilities.

## Security properties of execution modes

TensorFlow has several execution modes, with Eager-mode being the default in v2.

*   `tf.distribute.experimental.MultiWorkerMirroredStrategy` adds support for
    partial batches. Workers running out of data now continue to participate in
    the training with empty inputs, instead of raising an error. Learn more
    about
    [partial batches here](https://www.tensorflow.org/tutorials/distribute/input#partial_batches).
*   Improve the performance of reading metrics eagerly under

        "@com_google_absl//absl/log:check",
        "@com_google_googletest//:gtest_main",
        "@local_tsl//tsl/lib/core:status_test_util",
        "@local_tsl//tsl/platform:casts",
        "@local_tsl//tsl/platform:status_matchers",
        "@local_tsl//tsl/protobuf:error_codes_proto_impl_cc",
        "@local_xla//xla:shape_util",
        "@local_xla//xla/pjrt:pjrt_api",
        "@local_xla//xla/pjrt:pjrt_c_api_client",

    sdkmanager 'extras;m2repository;com;android;support;constraint;constraint-layout;1.0.0'; \
    sdkmanager 'extras;m2repository;com;android;support;constraint;constraint-layout-solver;1.0.2'; \
    sdkmanager 'patcher;v4'; \
    sdkmanager 'ndk;25.1.8937393'; \
    sdkmanager 'build-tools;27.0.3';

# Install Scoop and packages
RUN iex \"& {$(irm get.scoop.sh)} -RunAsAdmin\"; \
    scoop install perl; \

  )
except subprocess.CalledProcessError as e:
  print("No failures found to log!")
  exit(0)

# For test cases, only show the ones that failed that have text (a log)
seen = collections.Counter()
runfiles_matcher = re.compile(r"(/.*\.runfiles/)")


for f in files.strip().splitlines():
  # Just ignore any failures, they're probably not important
  try:
    r = JUnitXml.fromfile(f)

#include "tensorflow/core/tfrt/common/async_value_tensor.h"
#include "tensorflow/core/tfrt/common/pjrt_util.h"
#include "tsl/lib/core/status_test_util.h"
#include "tsl/platform/casts.h"
#include "tsl/platform/status_matchers.h"
#include "tsl/protobuf/error_codes.pb.h"

namespace tensorflow {
namespace {

using ::testing::HasSubstr;
using ::testing::NotNull;
using ::tsl::testing::StatusIs;

PJRT_Buffer* CreateCBuffer() {

  if (!status->status.ok()) {
    return nullptr;
  }

  TF_DataType dtype = TFE_TensorHandleDataType(components[0].get());
  // Verify that the combined TensorHandle's dtype matches all of the component
  // dtypes.
  for (TensorHandlePtr& component : components) {
    TFE_TensorHandleGetStatus(component.get(), status);
    if (!status->status.ok()) {
      return nullptr;
    }

} TF_Output;

// TF_Function is a grouping of operations with defined inputs and outputs.
// Once created and added to graphs, functions can be invoked by creating an
// operation whose operation type matches the function name.
typedef struct TF_Function TF_Function;

// Function definition options. TODO(iga): Define and implement
typedef struct TF_FunctionOptions TF_FunctionOptions;