// SECTION 3. Implementation for `TF_ReadOnlyMemoryRegion`
// ----------------------------------------------------------------------------
namespace tf_read_only_memory_region {

// TODO(b/139060984): Implement later

}  // namespace tf_read_only_memory_region

// SECTION 4. Implementation for `TF_Filesystem`, the actual filesystem
// ----------------------------------------------------------------------------

  ops->read_only_memory_region_ops = static_cast<TF_ReadOnlyMemoryRegionOps*>(
      plugin_memory_allocate(TF_READ_ONLY_MEMORY_REGION_OPS_SIZE));
  ops->read_only_memory_region_ops->cleanup =
      tf_read_only_memory_region::Cleanup;
  ops->read_only_memory_region_ops->data = tf_read_only_memory_region::Data;
  ops->read_only_memory_region_ops->length = tf_read_only_memory_region::Length;

              &num_retvals, &forward_op, tape.get(), registry);
  ASSERT_EQ(errors::OK, s.code()) << s.message();

  string read_message;
  s = forward_op.attrs.Get("message", &read_message);
  ASSERT_EQ(errors::OK, s.code()) << s.message();
  ASSERT_EQ(read_message, message);
}

Status RecordOperationWithNullGradientFunctionModel(
    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> inputs,

  TFE_ExecutorWaitForAllPendingNodes(executor, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_DeleteExecutor(executor);
  TF_DeleteStatus(status);
}

// Read the value of variable `var` and save it into `out_value`.
void ReadVariable(TFE_Context* ctx, TFE_TensorHandle* var,
                  TFE_TensorHandle** out_value) {
  TF_Status* status = TF_NewStatus();

}

Status ModularRandomAccessFile::Read(uint64 offset, size_t n,
                                     StringPiece* result, char* scratch) const {
  if (ops_->read == nullptr)
    return errors::Unimplemented(
        tensorflow::strings::StrCat("Read() not implemented for ", filename_));

  UniquePtrTo_TF_Status plugin_status(TF_NewStatus(), TF_DeleteStatus);
  int64_t read =

  std::unique_ptr<RandomAccessFile> read_file;
  status = env_->NewRandomAccessFile(filepath, &read_file);
  if (!status.ok())
    GTEST_SKIP() << "NewRandomAccessFile() not supported: " << status;

  char scratch[64 /* must be bigger than test_data */] = {0};
  StringPiece result;
  // read at least 1 byte more than test_data
  status = read_file->Read(0, test_data.size() + 1, &result, scratch);

    ASSERT_TRUE(std::find(device_names.begin(), device_names.end(),
                          remote_device) != device_names.end());
  }

  // Create a variable using `ctx_0`.
  // Read the variable using `ctx_1`. This read should succeed.
  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var2");

                          remote_device) != device_names.end());
  }

  // Create a variable using `ctx_0`.
  // Replace worker1 using a new worker, and update the contexts.
  // Read the variable using `ctx_1`. This read should succeed.
  //
  // 1. Create a variable on `remote_device`, using `ctx_0`.
  TFE_TensorHandle* handle_0 =
      CreateVariable(ctx_0, 1.2, remote_device, /*variable_name=*/"var");

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

namespace tensorflow {
namespace gradients {
namespace {

// TODO(b/172558015): Using the pointer address as the identifier for the tensor
// 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));
}

                                TF_WRITABLE_FILE_OPS_ABI, "writable file"));

  if (ops->read_only_memory_region_ops != nullptr)
    TF_RETURN_IF_ERROR(CheckABI(ops->read_only_memory_region_ops_abi,
                                TF_READ_ONLY_MEMORY_REGION_OPS_ABI,
                                "read only memory region"));

  return OkStatus();
}