}

@test "Pip package generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow/tools/pip_package:build_pip_package" \
    "//tensorflow/tools/pip_package:licenses"
}

@test "Libtensorflow generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow:libtensorflow.so" \
    "//tensorflow/tools/lib_package:clicenses_generate"

}

@test "Pip package generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow/tools/pip_package:wheel" \
    "//tensorflow/tools/pip_package:licenses"
}

@test "Libtensorflow generated license includes all dependencies' licenses" {
  do_external_licenses_check \
    "//tensorflow:libtensorflow.so" \
    "//tensorflow/tools/lib_package:clicenses_generate"
}

    Key fmax = std::make_pair(key.first, std::numeric_limits<size_t>::max());
    auto fcmp = block_map_.upper_bound(fmax);
    if (fcmp != block_map_.begin() && key < (--fcmp)->first) {
      return TF_SetStatus(status, TF_INTERNAL,
                          "Block cache contents are inconsistent.");
    }
  }

  Trim();

  return TF_SetStatus(status, TF_OK, "");
}

void RamFileBlockCache::MaybeFetch(const Key& key,

  EXPECT_EQ(out.size(), 1);
  // Now read the first block; this should yield an INTERNAL error because we
  // had already cached a partial block at a later position.
  Status status = ReadCache(&cache, "", 0, block_size, &out);
  EXPECT_EQ(status.code(), error::INTERNAL);
}

TEST(RamFileBlockCacheTest, LRU) {
  const size_t block_size = 16;
  std::list<size_t> calls;

                                           TransactionToken* token,
                                           std::vector<std::string>* result) {
  if (ops_->get_matching_paths == nullptr)
    return internal::GetMatchingPaths(this, Env::Default(), pattern, result);

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  // Note that `matches` is allocated by the plugin and freed by core

#include "tensorflow/c/eager/c_api_experimental.h"

#include <string.h>

#include <string>

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_server_lib.h"
#include "tensorflow/core/distributed_runtime/server_lib.h"

#include <memory>

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/framework/full_type.pb.h"

-   In such situations, we may request you to make further changes to your PR
    for the tests to pass.
-   Once the tests pass, we now bring all the code into the internal code base,
    using a job called "copybara".

**5. Copy to Google Internal codebase and run internal CI**

-   Once the PR is in the Google codebase, we make sure it integrates well with
    its dependencies and the rest of the system.

    textual_hdrs = [
        "c_api_internal.h",
        "c_api_macros.h",
        "conversion_macros.h",
        "python_api.h",
        "tensor_interface.h",
        "tf_status_helper.h",
        "tf_buffer_internal.h",
        "tf_status_internal.h",
        "tf_tensor_helper.h",
        "tf_tensor_internal.h",
        "@local_xla//xla/tsl/c:tsl_status_internal_headers",
    ],
    visibility = [

  void* context;
} TFE_CancelCallback;
TF_CAPI_EXPORT extern TFE_CancellationManager* TFE_NewCancellationManager();
TF_CAPI_EXPORT extern bool TFE_CancellationManagerIsCancelled(
    TFE_CancellationManager*);
TF_CAPI_EXPORT extern bool TFE_CancellationManagerIsCancelling(
    TFE_CancellationManager*);
TF_CAPI_EXPORT extern void TFE_CancellationManagerStartCancel(
    TFE_CancellationManager*);