# See the License for the specific language governing permissions and
# limitations under the License.
# ==============================================================================
# Variables containing version strings extracted from the canonical sources:
# tensorflow/core/public/version.h and tools/pip_package/setup.py.
#
# These variables aren't available by default. Scripts must source this file

// Abstract interface to a TensorHandle.
//
// A TensorHandle is management class around a Tensor which may track additional
// metadata and synchronization.
//
// This allows us to hide concrete implementations of TensorHandle from header
// files. The interface lists the common functionality that must be provided by
// any concrete implementation. However, in cases where the true concrete class
// is needed a static_cast can be applied.

      TestScalarTensorHandle<T, datatype>(eager_ctx, value);
  *tensor =
      unwrap(TF_CreateAbstractTensorFromEagerTensor(input_eager, status.get()));
  return absl::OkStatus();
}

// Places data from `t` into *result_tensor.
Status GetValue(AbstractTensorHandle* t, TF_Tensor** result_tensor);
}  // namespace tensorflow

#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/file_system_helper.h"
#include "tsl/platform/errors.h"

// TODO(b/139060984): After all filesystems are converted, all calls to
// methods from `FileSystem` will have to be replaced to calls to private
// methods here, as part of making this class a singleton and the only way to
// register/use filesystems.

namespace tensorflow {

using UniquePtrTo_TF_Status =

# use the wheel's TensorFlow installation instead of the one made available
# through bazel. This must be done in a different root directory, //bazel_pip/...,
# because "import tensorflow" run from the root directory would instead import
# the folder instead of the venv package.
# 
# Pass --config=pip to run the same suite of tests. If you want to run just one

  TF_Graph* g1 = TF_NewGraph();
  TF_Graph* g2 = TF_NewGraph();

  TF_Operation* feed = Placeholder(g1, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  // Attempt to create node in g2 with input from g1
  Neg(feed, g2, s);
  EXPECT_EQ(TF_INVALID_ARGUMENT, TF_GetCode(s));
  EXPECT_STREQ("foo", TF_Message(s));

  TF_DeleteGraph(g1);
  TF_DeleteGraph(g2);
  TF_DeleteStatus(s);
}
*/

        TFE_TensorHandleCopyToDevice(hcpu, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {
      ADD_FAILURE() << tag << " -- " << TF_Message(status.get());
      continue;
    }
    // Copy from device to the same device.
    TFE_TensorHandle* hdevice2 =
        TFE_TensorHandleCopyToDevice(hdevice, ctx, name.c_str(), status.get());
    if (TF_GetCode(status.get()) != TF_OK) {

// Loads a shared object implementing filesystem functionality.
static bool LoadDSO(const std::string& dso) {
  tensorflow::Status status = RegisterFilesystemPlugin(dso);
  if (!status.ok())
    VLOG(0) << "Filesystems from '" << dso
            << "' could not be registered: " << status;
  return status.ok();
}

// Tests whether a URI scheme results in a filesystem that is supported.
//

from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow  # pylint: disable=unused-import
from tensorflow.python.tools import module_util as _module_util
from tensorflow.python.util.lazy_loader import KerasLazyLoader as _KerasLazyLoader

# Make sure code inside the TensorFlow codebase can use tf2.enabled() at import.
_os.environ["TF2_BEHAVIOR"] = "1"
from tensorflow.python import tf2 as _tf2

  TracingContext* tracing_ctx = dyn_cast<TracingContext>(unwrap(ctx));
  if (!tracing_ctx) {
    tsl::Set_TF_Status_from_Status(
        s, tensorflow::errors::InvalidArgument(
               "Only TracingContext can be converted into a function."));
    return nullptr;
  }
  tsl::Set_TF_Status_from_Status(s,
                                 tracing_ctx->Finalize(unwrap(outputs), &func));
  TF_DeleteExecutionContext(ctx);