//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test.py
//tensorflow/lite/python:interpreter

// Atomically increments the value of the cell. The value must be non-negative.
TF_CAPI_EXPORT extern void TFE_MonitoringCounterCellIncrementBy(
    TFE_MonitoringCounterCell* cell, int64_t value);

// Retrieves the current value of the cell.
TF_CAPI_EXPORT extern int64_t TFE_MonitoringCounterCellValue(
    TFE_MonitoringCounterCell* cell);

// APIs for Counter without label.

  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TF_DeleteStatus(status);
  auto* cell = TFE_MonitoringGetCellCounter0(counter);
  TFE_MonitoringCounterCellIncrementBy(cell, 1);
  EXPECT_EQ(TFE_MonitoringCounterCellValue(cell), 1);
  auto* collection_registry = monitoring::CollectionRegistry::Default();
  monitoring::CollectionRegistry::CollectMetricsOptions options;

  *result = filename_;
  return OkStatus();
}

Status ModularWritableFile::Tell(int64_t* position) {
  if (ops_->tell == nullptr)
    return errors::Unimplemented(
        tensorflow::strings::StrCat("Tell() not implemented for ", filename_));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  *position = ops_->tell(file_.get(), plugin_status.get());
  return StatusFromTF_Status(plugin_status.get());
}

  length = tf_writable_file::Tell(file, status_);
  ASSERT_EQ(length, 4);
  ASSERT_TF_OK(status_);
  tf_writable_file::Flush(file, status_);
  ASSERT_TF_OK(status_);
  ASSERT_TRUE(
      CompareWithServer(filepath, 0, 4, &gcs_file->gcs_client, status_));

  tf_writable_file::Append(file, content + 4, 4, status_);
  ASSERT_TF_OK(status_);
  length = tf_writable_file::Tell(file, status_);
  ASSERT_EQ(length, 8);

learning and neural networks. However, the framework is versatile enough to be
used in other areas as well.

TensorFlow provides stable [Python](https://www.tensorflow.org/api_docs/python)
and [C++](https://www.tensorflow.org/api_docs/cc) APIs, as well as a
non-guaranteed backward compatible API for
[other languages](https://www.tensorflow.org/api_docs).

#include "tensorflow/core/platform/test.h"

// NOTE(allenl): These tests currently go through TFE_Execute and so are
// integration testing rather than purely testing the parallel device. They
// correspond fairly well to the implementation, but testing the C++ directly is
// another option.

namespace tensorflow {
namespace parallel_device {

Variable* Variable::Create(TFE_Context* context, TF_DataType type,

#include "tensorflow/core/platform/test.h"

// NOTE(allenl): These tests currently go through TFE_Execute and so are
// integration testing rather than purely testing the parallel device. They
// correspond fairly well to the implementation, but testing the C++ directly is
// another option.

namespace tensorflow {
namespace parallel_device {

using ::testing::HasSubstr;

TEST(PARALLEL_DEVICE, TestBasicCPU) {

//tensorflow/python/debug:grpc_tensorflow_server.par
//tensorflow/python/feature_column:vocabulary_testdata
//tensorflow/python/util:nest_test_main_lib
//tensorflow/lite/experimental/examples/lstm:rnn_cell
//tensorflow/lite/experimental/examples/lstm:rnn_cell.py
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test
//tensorflow/lite/experimental/examples/lstm:unidirectional_sequence_lstm_test.py
//tensorflow/lite/python:interpreter

      plugin_memory_allocate(TF_WRITABLE_FILE_OPS_SIZE));
  ops->writable_file_ops->cleanup = tf_writable_file::Cleanup;
  ops->writable_file_ops->append = tf_writable_file::Append;
  ops->writable_file_ops->tell = tf_writable_file::Tell;
  ops->writable_file_ops->flush = tf_writable_file::Flush;
  ops->writable_file_ops->sync = tf_writable_file::Sync;
  ops->writable_file_ops->close = tf_writable_file::Close;