# Set TFCI_GIT_DIR, the root directory for all commands, to two directories
# above the location of this file (setup.sh). We could also use "git rev-parse
# --show-toplevel", but that wouldn't work for non-git repos (like if someone
# downloaded TF as a zip archive).
export TFCI_GIT_DIR=$(cd $(dirname "$0"); realpath ../../)
cd "$TFCI_GIT_DIR"

# "TFCI" may optionally be set to the name of an env-type file with TFCI

// Usually this happens automatically in TF_SessionRun. After this is called,
// TF_SessionRun will no longer extend the session on every call.
//
// We expose this here to allow fine-grained synchronization in multi-threaded
// workloads, which is required since the Python implementation depends on the
// above mutation methods. This allows us to prevent modifications to nodes in

// that provides the filesystem functionality. However, the POSIX filesystem
// needs to be statically registered in some tests and utilities for building
// the API files at the time of creating the pip package. Hence, we need to
// expose this function so that this filesystem can be statically registered
// when needed.
void TF_InitPlugin(TF_FilesystemPluginInfo* info);

        ":tf_attrtype",
        ":tf_buffer_hdrs",
        ":tf_datatype_hdrs",
        ":tf_status_headers",
        ":tf_tensor_hdrs",
        # TODO: Only include tf_tstring_hdrs. Don't expose the implementation of TF_TString to API
        # users.
        ":tf_tstring",
        "//tensorflow/core:protos_all_cc",
    ],
)

tf_cuda_library(
    name = "c_api_internal",
    hdrs = [

// `c_api_unified_experimental.h` header.
// =============================================================================

// Represents either a MlirTensor or a GraphTensor.
// This base class does not expose any public methods other than to distinguish
// which subclass it actually is. The user is responsible to use the right
// type of AbstractTensor in their context (do not pass an MlirTensor to a
// GraphContext and vice-versa).

  // Update the Eager Executor for current thread.
  virtual void SetExecutorForThread(EagerExecutor* executor) = 0;

  // Return a list of local tensorflow::Device*.
  // TODO(tfrt-devs): We shouldn't expose legacy device in this API.
  virtual std::vector<tensorflow::Device*> ListLocalTfDevices() = 0;

  // Return a list of all tensorflow::Device*.
  virtual std::vector<tensorflow::Device*> ListAllTfDevices() = 0;

// SECTION 4. Implementation for `TF_Filesystem`, the actual filesystem
// ----------------------------------------------------------------------------
namespace tf_gcs_filesystem {
// TODO(vnvo2409): Use partial reponse for better performance.
// TODO(vnvo2409): We could do some cleanups like `return TF_SetStatus`.
// TODO(vnvo2409): Refactor the filesystem implementation when
// https://github.com/googleapis/google-cloud-cpp/issues/4482 is done.

    *   ResourceVariable support for `gather_nd`.
    *   `ResourceVariable` and `Variable` no longer accepts `constraint` in the
        constructor, nor expose it as a @property.
    *   Added gradient for `SparseToDense` op.
    *   Expose a flag that allows the number of threads to vary across Python
        benchmarks.
    *   `image.resize` in 2.0 now supports gradients for the new resize kernels.

///   1. A new method is added _at the end_ of the function table.
///   2. Preconditions or postconditions for one operation in these function
///   table change. Note that only core TensorFlow is able to impose these
///   invariants (i.e., guarantee the preconditions before calling the operation
///   and check the postconditions after the operation returns). If plugins need