# Sourcing this enables local disk cache
if [[ $(uname -s) == "Darwin" ]]; then
  echo "Please note that using disk cache on macOS is not recommended because the"
  echo "cache can end up being pretty big and make the build process inefficient."
fi

  tf_gcs_filesystem::ExpiringLRUCache<int> cache(1, 4);
  cache.Insert("a", 1);
  cache.Insert("b", 2);
  cache.Insert("c", 3);
  cache.Insert("d", 4);
  int value = 0;
  EXPECT_TRUE(cache.Lookup("a", &value));
  EXPECT_EQ(value, 1);
  EXPECT_TRUE(cache.Lookup("b", &value));
  EXPECT_EQ(value, 2);
  EXPECT_TRUE(cache.Lookup("c", &value));
  EXPECT_EQ(value, 3);
  EXPECT_TRUE(cache.Lookup("d", &value));

  new_entry->timestamp = timer_seconds_();
  block_map_.emplace(std::make_pair(key, new_entry));
  return new_entry;
}

// Remove blocks from the cache until we do not exceed our maximum size.
void RamFileBlockCache::Trim() {
  while (!lru_list_.empty() && cache_size_ > max_bytes_) {
    RemoveBlock(block_map_.find(lru_list_.back()));
  }
}

/// Move the block to the front of the LRU list if it isn't already there.

  calls.push_back(block_size);
  // Cache miss followed by cache hit.
  TF_EXPECT_OK(ReadCache(&cache, "", block_size, 1, &out));
  TF_EXPECT_OK(ReadCache(&cache, "", block_size, 1, &out));
  calls.push_back(2 * block_size);
  // Cache miss followed by cache hit.  Causes eviction of LRU element.
  TF_EXPECT_OK(ReadCache(&cache, "", 2 * block_size, 1, &out));

# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false

#   export TF_ANY_TARGETS="quoted list of targets, like on the command line"
#   export TF_ANY_MODE=test
set -euxo pipefail
cd "$(dirname "$0")/../../"  # tensorflow/
export TFCI="$(echo $TFCI | sed 's/,nightly_upload/,public_cache,disk_cache/')"
git bisect start "$TF_BISECT_BAD" "$TF_BISECT_GOOD"

  TFE_ContextAddFunctionDef(ctx, function_def.data(), function_def.size(),
                            status);
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  for (bool clear_cache : {true, false, true}) {
    if (clear_cache) {
      TFE_ContextClearCaches(ctx);
    }
    TFE_TensorHandle* m = TestMatrixTensorHandle(ctx);
    TFE_TensorHandle* retval[1] = {nullptr};
    int num_retvals = 1;

    auto it = cache_.find(key);
    if (it == cache_.end()) {
      return false;
    }
    lru_list_.erase(it->second.lru_iterator);
    cache_.erase(it);
    return true;
  }

  /// The maximum age of entries in the cache, in seconds. A value of 0 means
  /// that no entry is ever placed in the cache.
  const uint64_t max_age_;

  /// The maximum number of entries in the cache. A value of 0 means there is no

# This bazelrc can build a CPU-supporting TF package.

# Convenient cache configurations
# Use a cache directory mounted to /tf/cache. Very useful!
build:sigbuild_local_cache --disk_cache=/tf/cache
# Use the public-access TF DevInfra cache (read only)
build:sigbuild_remote_cache --remote_cache="https://storage.googleapis.com/tensorflow-devinfra-bazel-cache/manylinux2014" --remote_upload_local_results=false

#      Ex. macos_arm64      -- arm64 MacOS platform
# 3. Add modifiers. Some modifiers for local execution are:
#      Ex. disk_cache -- Use a local cache
#      Ex. public_cache -- Use TF's public cache (read-only)
#      Ex. public_cache_push -- Use TF's public cache (read and write, Googlers only)
#      Ex. rbe        -- Use RBE for faster builds (Googlers only; see below)