//
// 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.

// have any visibility into the graph/eager implementation and is only providing
// C bindings to the abstract classes defined in the
// c_api_unified_experimental_internal.h header.
//
// =============================================================================

using tensorflow::AbstractFunction;
using tensorflow::AbstractTensorHandle;
using tensorflow::DataType;

// backends (graph/MLIR).
//
// This defines a set of abstract classes that are intended to provide the
// functionality of the opaque C types exposed in the public APIs defined in the
// `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

 private:
  absl::flat_hash_map<string, GradientFunctionFactory> registry_;
};

// TODO(srbs): Figure out if we can avoid declaring this in the public header.
// Wrapper for a tensor output of an operation executing under a tape.
//
// `GetID` returns a unique id for the wrapped tensor which is used to maintain

        "//tensorflow/c:conversion_macros",
    ],
)

cc_header_only_library(
    name = "tfe_tensorhandle_internal_hdrs_only",
    extra_deps = [
        "@com_google_absl//absl/strings",
    ],
    visibility = [
        "//tensorflow:internal",
    ],
    deps = [
        ":tfe_tensorhandle_internal",
    ],
)

cc_header_only_library(
    name = "tfe_cancellationmanager_internal_hdrs_only",

    // GCS will return an empty header (e.g no `content-length` header). In this
    // case, we will set read to `0` and continue.
    read = 0;
  } else if (!absl::SimpleAtoi(content_length->second, &read)) {
    TF_SetStatus(status, TF_UNKNOWN, "Could not get content-length header");
    return -1;
  }
  // `TF_OUT_OF_RANGE` isn't considered as an error. So we clear it here.

#include <stdint.h>

#include "tensorflow/c/tf_file_statistics.h"
#include "tensorflow/c/tf_status.h"

/// This is the interop header between core TensorFlow and modular filesystem
/// plugins (see initial RFC https://github.com/tensorflow/community/pull/101).
///
/// Both core TensorFlow and every plugin will use this header. The associated
/// `.cc` file is only used by core TensorFlow to implement checking needed for

# the stream executor cuda plugins. Targets that want to use cuda APIs should
# instead depend on the dummy plugins in @local_tsl//tsl/platform/default/build_config
# and use header only targets.
# TODO(ddunleavy): This seems completely broken. :tensorflow_cc depends on
# cuda_platform from tf_additional_binary_deps and this doesn't break.
check_deps(
    name = "cuda_plugins_check_deps",

Chollet, Frederic Bastien, Fredrik Knutsson, Gabriele Macchi, Gaurav Shukla,
Gauri1 Deshpande, geetachavan1, Georgiy Manuilov, H, Hengwen Tong, Henri
Woodcock, Hiran Sarkar, Ilya Arzhannikov, Janghoo Lee, jdematos, Jens Meder,
Jerry Shih, jgehw, Jim Fisher, Jingbei Li, Jiri Podivin, Joachim Gehweiler,
Johannes Lade, Jonas I. Liechti, Jonas Liechti, Jonas Ohlsson, Jonathan
Dekhtiar, Julian Gross, Kaixi Hou, Kevin Cheng, Koan-Sin Tan, Kulin Seth,

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"

// Initialize the POSIX filesystem.
//
// In general, the `TF_InitPlugin` symbol doesn't need to be exposed in a header
// file, since the plugin registration will look for the symbol in the DSO file
// that provides the filesystem functionality. However, the POSIX filesystem