# 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
# Change the value of CACHEBUSTER when upgrading the toolchain, or when testing

                                   size_t* storage_size, TF_Status* status) {
  TF_SetStatus(status, TF_OK, "");
  const std::unordered_set<std::string>& nodes =
      reinterpret_cast<const tensorflow::grappler::GrapplerItem*>(item)
          ->NodesToPreserve();
  *num_values = nodes.size();
  *storage_size = 0;
  for (const std::string& str : nodes) {
    *storage_size += str.size();
  }
}

// must point to an array of length at least `num_values`.
//
// The elements of values will point to addresses in `storage` which must be at
// least `storage_size` bytes in length.  `num_values` and `storage` can be
// obtained from TF_GetNodesToPreserveSize
//
// Fails if storage_size is too small to hold the requested number of strings.
TF_CAPI_EXPORT extern void TF_GetNodesToPreserveList(

    std::vector<size_t> lens(expected.size());
    std::unique_ptr<char[]> storage(new char[m.total_size]);
    TF_OperationGetAttrStringList(op, tensorflow::kColocationAttrName,
                                  values.data(), lens.data(), expected.size(),
                                  storage.get(), m.total_size, s_);
    EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

http_archive(
    name = "bazel_skylib",
    sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506",
    urls = [
        "https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
        "https://github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
    ],

  char* p = static_cast<char*>(storage);
  for (int i = 0; i < len; ++i) {
    const string& s = attr->list().s(i);
    values[i] = p;
    lengths[i] = s.size();
    if ((p + s.size()) > (static_cast<char*>(storage) + storage_size)) {
      status->status = InvalidArgument(
          "Not enough storage to hold the requested list of strings");
      return;
    }

load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive")

http_archive(
    name = "bazel_skylib",
    sha256 = "74d544d96f4a5bb630d465ca8bbcfe231e3594e5aae57e1edbf17a6eb3ca2506",
    urls = [
        "https://storage.googleapis.com/mirror.tensorflow.org/github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
        "https://github.com/bazelbuild/bazel-skylib/releases/download/1.3.0/bazel-skylib-1.3.0.tar.gz",
    ],

# 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
# Change the value of CACHEBUSTER when upgrading the toolchain, or when testing

# run all the tests. Since TFCI Mac VMs execute Bazel test commands in a
# partition with insufficient storage, we specify the
# 'TFCI_MACOS_BAZEL_TEST_DIR_PATH' environment variable to point to a partition
# with ample storage. When this variable is empty (i.e by default), Bazel will
# use the output base directory to run tests.
if [[ "${TFCI_MACOS_BAZEL_TEST_DIR_ENABLE}" == 1 ]]; then

**Linux CPU**                 | [![Status](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.svg)](https://storage.googleapis.com/tensorflow-kokoro-build-badges/ubuntu-cc.html)           | [PyPI](https://pypi.org/project/tf-nightly/)