std::string translated_name = TranslateName(fname);
  ops_->new_read_only_memory_region_from_file(
      filesystem_.get(), translated_name.c_str(), region.get(),
      plugin_status.get());

  if (TF_GetCode(plugin_status.get()) == TF_OK)
    *result = std::make_unique<ModularReadOnlyMemoryRegion>(
        std::move(region), read_only_memory_region_ops_.get());

  return StatusFromTF_Status(plugin_status.get());
}

limitations under the License.
==============================================================================*/
#include "tensorflow/c/experimental/filesystem/plugins/gcs/ram_file_block_cache.h"

#include <cstring>
#include <memory>
#include <sstream>
#include <utility>

#include "absl/synchronization/mutex.h"
#include "tensorflow/c/experimental/filesystem/plugins/gcs/cleanup.h"

namespace tf_gcs_filesystem {

  TF_EXPECT_OK(ReadCache(&cache1, "", 0, 1, &out));
  EXPECT_EQ(calls, 1);
  // Now advance the clock one second at a time and redo the read. The call
  // count should advance every 3 seconds (i.e. every time the staleness is
  // greater than 2).
  for (int i = 1; i <= 10; i++) {
    env->SetNowSeconds(i + 1);
    TF_EXPECT_OK(ReadCache(&cache1, "", 0, 1, &out));
    EXPECT_EQ(calls, 1 + i / 3);
  }

limitations under the License.
==============================================================================*/

#include "tensorflow/c/eager/c_api_unified_experimental.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"

    TFE_TensorHandle* h, TF_Status* status);

// This function will block till the operation that produces `h` has
// completed. The memory returned might alias the internal memory used by
// TensorFlow. Hence, callers should not mutate this memory (for example by
// modifying the memory region pointed to by TF_TensorData() on the returned
// TF_Tensor).
TF_CAPI_EXPORT extern TF_Tensor* TFE_TensorHandleResolve(TFE_TensorHandle* h,

// bytes of the memory pointed to by the device pointer returned above.
TF_CAPI_EXPORT extern size_t TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle*,
                                                              TF_Status*);

// Creates a new TensorHandle from memory residing in the physical device
// device_name. Takes ownership of the memory, and will call deleter to release

https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/tf_sig_build_dockerfiles/devel.usertools/code_check_full.bats
Here are the affected tests:
EOF
    while read dep; do
      echo "For dependency $dep:"
      # For every missing dependency, find the tests which directly depend on
      # it, and print that list for debugging. Not really clear if this is
      # helpful since the only examples I've seen are enormous.

### Typical Pull Request Workflow -

**1. New PR**

- As a contributor, you submit a New PR on GitHub.
- We inspect every incoming PR and add certain labels to the PR such as `size:`,
  `comp:` etc.  At this stage we check if the PR is valid and meets certain
  quality requirements. For example, we check if the CLA is signed, PR has

  // and not for correctness. The only downside of keeping this 1 seems to be
  // that the gradient accumulation is unbounded and we will never
  // aggressively aggregate accumulated gradients to recover memory.
  // Revisit and fix.
  return 1;
}

// Consumes references to the tensors in the gradient_tensors list and returns
// a tensor with the result.
AbstractTensorHandle* TapeVSpace::AggregateGradients(

limitations under the License.
==============================================================================*/

// A simple logging device to test custom device registration.
#include <memory>

#include "absl/strings/match.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_test_util.h"