}

void RamFileBlockCache::RemoveFile_Locked(const std::string& filename) {
  Key begin = std::make_pair(filename, 0);
  auto it = block_map_.lower_bound(begin);
  while (it != block_map_.end() && it->first.first == filename) {
    auto next = std::next(it);
    RemoveBlock(it);
    it = next;
  }
}

void RamFileBlockCache::RemoveBlock(BlockMap::iterator entry) {

If you open a GitHub Issue, here is our policy:

1.  It must be a bug/performance issue or a feature request or a build issue or
    a documentation issue (for small doc fixes please send a PR instead).
1.  Make sure the Issue Template is filled out.
1.  The issue should be related to the repo it is created in.

**Here's why we have this policy:** We want to focus on the work that benefits
the whole community, e.g., fixing bugs and adding features. Individual support

to the `../wheel_test/` directory.


### How it Works in the Presubmit Job

`_requirements_lock` files will be generated by the presubmit job. A detailed
description will be provided once it's integrated into presubmit.

### test_import_api_packages

This Python test verifies whether the API v2 packages can be imported from the
current build. It utilizes the `_api/v2/api_packages.txt` list of packages from

  EXPECT_EQ(cache.CacheSize(), 0);
}

TEST(RamFileBlockCacheTest, ParallelReads) {
  // This fetcher won't respond until either `callers` threads are calling it
  // concurrently (at which point it will respond with success to all callers),
  // or 10 seconds have elapsed (at which point it will respond with an error).
  const int callers = 4;
  BlockingCounter counter(callers);

// Transfers up to `size` bytes from `dst_fd` to `src_fd`.
//
// This method uses a temporary buffer to hold contents.
int CopyFileContents(int dst_fd, int src_fd, off_t size) {
  // Use a copy buffer of 128KB but don't store it on the stack.
  constexpr static size_t kPosixCopyFileBufferSize = 128 * 1024;
  std::unique_ptr<char[]> buffer(new char[kPosixCopyFileBufferSize]);

  off_t offset = 0;
  int bytes_transferred = 0;
  int rc = 1;

  // Although, `ops::SparseSoftmaxCrossEntropyWithLogits` returns 2 tensors, the
  // second tensor isn't needed for computing gradient so we could safely drop
  // it.
  outputs[0] = loss;
  backprop->Unref();
  return absl::OkStatus();
}

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

# an entry in tensorflow/.bazelrc for build:rbe_TFCI_BAZEL_TARGET...
#                                           ^^^^
# This env is only valid when RBE is available on the selected platform, since
# it enables a derived --config setting.  If RBE is not available (i.e. there
# is no --config setting), bazel would fail and quit. This script does a quick
# check This script checks for such errors early

  std::atomic<bool> extend_before_run;
};

struct TF_ImportGraphDefOptions {
  tensorflow::ImportGraphDefOptions opts;

  // Backing memory for TensorId fields in opts.
  // TODO(skyewm): it'd be better if ImportGraphDefOptions owned this.
  std::vector<tensorflow::string> tensor_id_data;
};

struct TF_ImportGraphDefResults {
  std::vector<TF_Output> return_tensors;

  virtual const char* DeviceType(Status* status) const = 0;
  // Returns the device ID which created the handle.
  virtual int DeviceId(Status* status) const = 0;
  // Returns a tensor for the handle. If tensor is remote, it will be copied.
  virtual AbstractTensorInterface* Resolve(Status* status) = 0;

  std::string DebugString() const override;

  // Returns a Boolean hint indicating whether callers should prefer

  // Import it in a fresh graph.
  TF_DeleteGraph(graph);
  graph = TF_NewGraph();
  TF_ImportGraphDefOptions* opts = TF_NewImportGraphDefOptions();
  TF_GraphImportGraphDef(graph, graph_def, opts, s);
  ASSERT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

  TF_Operation* scalar = TF_GraphOperationByName(graph, "scalar");

  // Import it in a fresh graph with an unused input mapping.