// may lead to collisions. Introduce another way to get a unique id for this
// tensor.
int64_t ToId(const AbstractTensorHandle* t) {
  return static_cast<int64_t>(reinterpret_cast<uintptr_t>(t));
}

Status ZerosLike(AbstractContext* ctx, AbstractTensorHandle* t,
                 AbstractTensorHandle** result) {
  AbstractOperationPtr op(ctx->CreateOperation());

# See the License for the specific language governing permissions and
# 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

    std::string& summary) const {
  Status status;
  AbstractTensorPtr resolved(
      // TODO(allenl): Resolve should be const, and the caches that get updated
      // marked mutable.
      const_cast<ImmediateExecutionTensorHandle*>(this)->Resolve(&status));
  if (!status.ok()) {
    return status;
  }
  summary = resolved->SummarizeValue();
  return absl::OkStatus();
}

    --hash=sha256:f7ac31b9aecccb2c6e1ab29706f6ded3eba0c2c69c770322c9c685929c3d6afb \
    --hash=sha256:fa42a605d099ee7d41ba2b5fb75e21423951fd26e5d50583a00471238fb3021d
    # via keras-nightly
gast==0.4.0 \
    --hash=sha256:40feb7b8b8434785585ab224d1568b857edb18297e5a3047f1ba012bc83b42c1 \
    --hash=sha256:b7adcdd5adbebf1adf17378da5ba3f543684dbec47b1cda1f3997e573cd542c4
    # via -r requirements.in
grpcio==1.60.1 \

  delete[] static_cast<bool*>(data);
}

static void Int32Deallocator(void* data, size_t, void* arg) {
  delete[] static_cast<int32_t*>(data);
}

static void DoubleDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<double*>(data);
}

static void FloatDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<float*>(data);
}

TF_Tensor* BoolTensor(bool v) {

// in the memory of the device name 'device_name'.
// If source and destination are the same device, then this creates a new handle
// that shares the underlying buffer. Otherwise, it currently requires at least
// one of the source or destination devices to be CPU (i.e., for the source or
// destination tensor to be placed in host memory).
// If async execution is enabled, the copy may be enqueued and the call will

    ASSERT_TF_OK(s) << "TF_DeleteDir failed for " << dirpath << ": "
                    << TF_Message(s);

    TF_DeleteStatus(s);
    break;
  }

  ASSERT_TRUE(found) << "expected at least one temp dir";

  TF_StringStreamDone(tempdirs);
}

TEST(TestEnv, TestTimeFunctions) {
  ASSERT_GE(TF_NowSeconds(), 946684800);  // Midnight Jan 1, 2000
  ASSERT_GE(TF_NowMicros(), 946684800 * 1e6);

  /// Guards access to the cache and the LRU list.
  absl::Mutex mu_;

  /// The cache (a map from string key to Entry).
  std::map<std::string, Entry> cache_ ABSL_GUARDED_BY(mu_);

  /// The LRU list of entries. The front of the list identifies the most
  /// recently accessed entry.
  std::list<std::string> lru_list_ ABSL_GUARDED_BY(mu_);
};

}  // namespace tf_gcs_filesystem

      TFE_TensorHandleResolve(var_value_unpacked, status.get()),
      TF_DeleteTensor);
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_EQ(111., *static_cast<float*>(TF_TensorData(resolved_value.get())));

  // Free the backing buffer for the variable.
  op.reset(TFE_NewOp(context.get(), "DestroyResourceOp", status.get()));
  TFE_OpAddInput(op.get(), var_handle, status.get());

  /// Guards access to the block map, LRU list, and cached byte count.
  mutable absl::Mutex mu_;

  /// The block map (map from Key to Block).
  BlockMap block_map_ ABSL_GUARDED_BY(mu_);

  /// The LRU list of block keys. The front of the list identifies the most
  /// recently accessed block.
  std::list<Key> lru_list_ ABSL_GUARDED_BY(mu_);

  /// The LRA (least recently added) list of block keys. The front of the list