# 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

    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/)

#include "absl/types/variant.h"
#include "google/cloud/storage/client.h"
#include "tensorflow/c/env.h"
#include "tensorflow/c/experimental/filesystem/plugins/gcs/gcs_helper.h"
#include "tensorflow/c/logging.h"
#include "tensorflow/c/tf_status.h"

// Implementation of a filesystem for GCS environments.
// This filesystem will support `gs://` URI schemes.
namespace gcs = google::cloud::storage;

TFCI_BUILD_PIP_PACKAGE_ARGS="--repo_env=WHEEL_NAME=tensorflow_tpu"
TFCI_LIB_SUFFIX="-tpu-linux-x86_64"
TFCI_WHL_BAZEL_TEST_ENABLE=0
TFCI_WHL_IMPORT_TEST_ENABLE=0
TFCI_WHL_SIZE_LIMIT=580M