gradle["Gradle CLI client"]
    
        gradlew["Gradlew CLI client"]
    
        subgraph IDE    
            tapi["Tooling API client"]
        end
        
        daemon["Gradle daemon"]
        gradle --> daemon
        gradlew --> daemon
        tapi --> daemon
        
        worker["Worker process"]
        daemon --> worker

        worker2["Worker process"]
        daemon --> worker2

būšu     
būsi
būs
būsim
būsiet
tikt
tiku
tiki
tika
tikām
tikāt
tieku
tiec
tiek
tiekam
tiekat
tikšu
tiks
tiksim
tiksiet
tapt
tapi
tapāt
topat
tapšu
tapsi
taps
tapsim
tapsiet
kļūt
kļuvu
kļuvi
kļuva
kļuvām
kļuvāt
kļūstu
kļūsti
kļūst
kļūstam
kļūstat
kļūšu
kļūsi
kļūs
kļūsim
kļūsiet

disini
disinilah
sini
sinilah
sesuatu
sesuatunya
suatu
sesudah
sesudahnya
sudah
sudahkah
sudahlah
supaya
tadi
tadinya
tak
tanpa
setelah
telah
tentang
tentu
tentulah
tentunya
tertentu
seterusnya
tapi
tetapi
setiap
tiap
setidaknya
tidak
tidakkah
tidaklah
toh
waduh
wah
wahai
sewaktu
walau
walaupun

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_CONTEXT_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_CONTEXT_H_

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/experimental/gradients/tape/tape_operation.h"

namespace tensorflow {
namespace gradients {
class TapeContext : public AbstractContext {
 public:
  explicit TapeContext(AbstractContext*, Tape*, const GradientRegistry&);

#ifndef TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_OPERATION_H_
#define TENSORFLOW_C_EXPERIMENTAL_GRADIENTS_TAPE_TAPE_OPERATION_H_

#include "tensorflow/c/eager/abstract_operation.h"
#include "tensorflow/c/eager/gradients.h"

namespace tensorflow {
namespace gradients {
class TapeOperation : public AbstractOperation {
 public:
  explicit TapeOperation(AbstractOperation*, Tape*, const GradientRegistry&);
  void Release() override;

==============================================================================*/

#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/c_api_remote_test_util.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"

                                       remote_func_outputs, has_packed_input);
}

TEST(CAPI, RemoteExecuteSilentCopiesAsyncFunc) {
  TestRemoteExecuteSilentCopiesFunc(/*async=*/true, /*remote=*/true,
                                    /*heavy_load_on_streaming_rpc=*/false);
}
TEST(CAPI, RemoteExecuteSilentCopiesFuncRemoteOutputs) {
  TestRemoteExecuteSilentCopiesFunc(/*async=*/false, /*remote=*/true,

                       int64_t delta = 1);

TEST(CAPI, MonitoringCellReader0) {
  auto counter_name = "test/counter0";
  auto* counter = CreateCounter0(counter_name);
  auto* reader = TFE_MonitoringNewCounterReader(counter_name);
  IncrementCounter0(counter);

  int64_t actual = TFE_MonitoringReadCounter0(reader);

  CHECK_EQ(actual, 1);
}

TEST(CAPI, MonitoringCellReader1) {
  auto counter_name = "test/counter1";

#ifndef TENSORFLOW_C_EXPERIMENTAL_NEXT_PLUGGABLE_DEVICE_C_API_H_
#define TENSORFLOW_C_EXPERIMENTAL_NEXT_PLUGGABLE_DEVICE_C_API_H_

#include <cstdint>

#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/kernels.h"
#include "tensorflow/c/kernels_experimental.h"
#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_status.h"
#include "xla/pjrt/c/pjrt_c_api.h"

             absl::Span<AbstractTensorHandle*> outputs) -> Status {
    Tape tape(/*persistent=*/false);
    for (size_t i{}; i < inputs.size(); ++i) {
      tape.Watch(inputs[i]);
    }
    std::vector<AbstractTensorHandle*> temp_outputs(1);
    AbstractContextPtr tape_ctx(new TapeContext(ctx, &tape, grad_registry));
    TF_RETURN_IF_ERROR(
        forward_model(tape_ctx.get(), inputs, absl::MakeSpan(temp_outputs)));