#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/nn_ops.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/tensor_float_32_utils.h"
#include "tensorflow/core/platform/test.h"

                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.
  // REQUIRES: "v2_reader_ != nullptr && v2_reader_.status().ok()".
  std::pair<std::unique_ptr<TensorSliceReader::VarToShapeMap>,
            std::unique_ptr<TensorSliceReader::VarToDataTypeMap> >

};

struct TF_Graph {
  TF_Graph();

  mutable tensorflow::mutex mu;
  tensorflow::Graph graph TF_GUARDED_BY(mu);

  // Runs shape inference.
  tensorflow::ShapeRefiner refiner TF_GUARDED_BY(mu);

  // Maps from name of an operation to the Node* in 'graph'.
  std::unordered_map<tensorflow::string, tensorflow::Node*> name_map
      TF_GUARDED_BY(mu);

  // The keys of this map are all the active sessions using this graph. Each

// A TF_ExecutionContext stores knowledge about how to execute an operation.
// E.g. it could know whether we're in eager mode or graph mode, keeps track
// of gradient tapes, etc.
typedef struct TF_ExecutionContext TF_ExecutionContext;

// A TF_AbstractTensor is an input to an operation. E.g. it could be a union
// type of eager and graph tensors. It is also the result of executing an

# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================

name: ARM CD

on:
  push:
    tags:
      - v2.**
    branches:
      - r2.**
  schedule:
    - cron: '0 8 * * *'

permissions:
  contents: read

jobs:
  build:

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

name: ARM CI Extended C++

on:
  push:
    tags:
      - v2.**
  schedule:
    - cron: '0 2 * * *'

permissions:
  contents: read

jobs:
  build:
    if: github.repository == 'tensorflow/tensorflow' # Don't do this in forks

#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"
#include "tensorflow/c/experimental/ops/array_ops.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/platform/tensor_float_32_utils.h"
#include "tensorflow/core/platform/test.h"

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

# Check and rename wheels with auditwheel. Inserts the platform tags like
# "manylinux_xyz" into the wheel filename.
set -euxo pipefail

for wheel in /tf/pkg/*.whl; do
  echo "Checking and renaming $wheel..."

    ],
)

# Compliance test for modules and for interface
tf_cc_test(
    name = "modular_filesystem_test",
    size = "small",
    srcs = ["modular_filesystem_test.cc"],
    linkopts = ["-ldl"],
    tags = [
        "manual",  # Requires DSOs as arguments, eventual setup
        "notap",  # b/139060984, requires implementing modular support for Google filesystem
    ],
    deps = [
        ":modular_filesystem",

  AbstractTensorHandle* GetHandle() const;

 private:
  AbstractTensorHandle* handle_;
};

// A tracing/immediate-execution agnostic tape.
//
// Gradient functions defined for this tape must support handling null incoming
// gradients.
class Tape : protected eager::GradientTape<AbstractTensorHandle,
                                           GradientFunction, TapeTensor> {
 public: