TF_FilesystemPluginInfo info;
  TF_InitPlugin(&info);
  Status status = filesystem_registration::RegisterFilesystemPluginImpl(&info);
  if (!status.ok()) {
    VLOG(0) << "Static POSIX filesystem could not be registered: " << status;
    return false;
  }
  return true;
}

// Perform the actual registration
static bool unused = StaticallyRegisterLocalFilesystems();

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/immediate_execution_operation.h"

// Wraps a pointer to an operation implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this
// interface cannot destruct the underlying operation object. Instead, call
// TFE_DeleteOp who calls Release() on the operation pointer and deletes
// the TFE_Op structure.

#include "tensorflow/c/conversion_macros.h"
#include "tensorflow/c/eager/immediate_execution_tensor_handle.h"

// Wraps a pointer to a tensor handle implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this
// interface cannot destruct the underlying handle object. Instead, call
// TFE_DeleteTensorHandle who calls Release() on the handle pointer and deletes
// the TFE_TensorHandle structure.

# Download glibc's shared and development libraries based on the value of the
# `VERSION` parameter.
# Note: 'Templatizing' this and the other conditional branches would require
# defining several variables (version, os, path) making it difficult to maintain
# and extend for future modifications.
mkdir -p glibc-src
mkdir -p glibc-build
cd glibc-src

  tensorflow::core::CppShapeInferenceResult::HandleData handle_data;
  if (!handle_data.ParseFromArray(proto, proto_len)) {
    status->status =
        absl::InvalidArgumentError("Couldn't deserialize HandleData proto");
    return;
  }
  DCHECK(handle_data.is_set());

  tensorflow::mutex_lock l(graph->mu);
  tensorflow::shape_inference::InferenceContext* ic =

// APIs for generically dealing with op attributes (e.g. when forwarding them
// through custom device implementations).
//
// TODO(allenl): Currently these are black boxes, but we should have some way to
// inspect values. This would let people e.g. copy over most attributes and then
// modify some based on their values.

// A reference to an op's name -> attribute mapping
typedef struct TFE_OpAttrs TFE_OpAttrs;

    TF_NewWritableFile(filepath.c_str(), &handle, s);
    ASSERT_TF_OK(s) << "NewWritableFile failed for " << filepath << ": "
                    << TF_Message(s);

    const char* data = "Hello, world!\n";
    TF_AppendWritableFile(handle, data, strlen(data), s);
    ASSERT_TF_OK(s) << "TF_AppendWritableFile failed to append data to file at "
                    << filepath << ": " << TF_Message(s);

    it may slow down the tests for not running in parallel and may cause the
    test to timeout but it could be useful when you need to execute a single
    test or more in general your filtered/selected tests have a very low
    execution time and the sharding
    [could create an overhead on the test execution](https://github.com/bazelbuild/bazel/issues/2113#issuecomment-264054799).

including tensorflow-io should be sandboxed if used to process untrusted data.

For example, if an attacker were to upload a malicious video file, they could
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

# limitations under the License.
# ==============================================================================
#
# Usage: get_test_list.sh OUTPUT BAZEL_TEST_COMMAND...
# Writes the list of tests that would be run from BAZEL_TEST_COMMAND to OUTPUT.
# Hides all extra output and always exits with success for now.

OUTPUT=$1
shift