*   XLA reduction emitter is deterministic when the environment variable
        `TF_DETERMINISTIC_OPS` is set to "true" or "1". This extends
        deterministic `tf.nn.bias_add` back-prop functionality (and therefore
        also deterministic back-prop of bias-addition in Keras layers) to
        include when XLA JIT compilation is enabled.
    *   Fix problem, when running on a CUDA GPU and when either environment

        "//tensorflow/core:test_main",
    ],
)

tf_cc_test(
    name = "parallel_device_remote_test",
    srcs = ["parallel_device_remote_test.cc"],
    # TODO(b/136478427): Enable global heap checking when servers shut down
    # cleanly.
    args = ["--heap_check="],
    deps = [
        ":parallel_device",
        ":parallel_device_testlib",
        "//tensorflow/c:c_api",

  * If you are an individual writing original source code and you're sure you own the intellectual property, then you'll need to sign an [individual CLA](https://code.google.com/legal/individual-cla-v1.0.html).
  * If you work for a company that wants to allow you to contribute your work, then you'll need to sign a [corporate CLA](https://code.google.com/legal/corporate-cla-v1.0.html).

    steps:
      - name: Stop old running containers (if any)
        shell: bash
        run: |
          running_containers=$(docker ps -q) && \
          if [[ $running_containers == "" ]]; then
            echo "No running containers";
          else
            echo "Running container(s) found" && \
            docker stop $running_containers;
          fi
          docker container prune -f

# Delete modules that should be hidden from dir().
# Don't fail if these modules are not available.
# For e.g. this file will be originally placed under tensorflow/_api/v1 which
# does not have "python", "core" directories. Then, it will be copied
# to tensorflow/ which does have these two directories.
try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler

      if (prefix != nullptr && !absl::StartsWith(n->name(), prefix_cmp)) {
        status->status = tensorflow::errors::Internal(
            "BUG: The gradients prefix have been unexpectedly altered when "
            "adding the nodes to the graph. This is a bug. Please file an "
            "issue at https://github.com/tensorflow/tensorflow/issues.");
        return;
      }

#
# The cascade of load() statements and tf_workspace?() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "tf_workspace3")

tf_workspace3()

load("@//tensorflow:workspace2.bzl", "tf_workspace2")

tf_workspace2()

    visibility = ["//tensorflow/python:__pkg__"],
    deps = [
        ":c_api",
        ":c_api_internal",
        "//tensorflow/core:protos_all_cc",
        # TODO(b/74620627): remove when _USE_C_SHAPES is removed
    ],
    alwayslink = 1,
)

cc_library(
    name = "conversion_macros",
    hdrs = [
        "conversion_macros.h",
    ],

      d="$${d#bazel-out/*/bin/}"

      if [[ $${d} == *local_config_* ]]; then
        continue
      fi

      if [[ $${d} == external* ]]; then
        extname="$${d#*external/}"
        extname="$${extname%%/*}"
        if [[ $${TF_SYSTEM_LIBS:-} == *$${extname}* ]]; then
          continue
        fi

        d="$${d#*external/farmhash_archive/src}"

# Puts new wheel through auditwheel to rename and verify it, deletes the old
# one, checks the filesize, and then ensures the new wheel is installable.
set -euxo pipefail

cd "$TFCI_OUTPUT_DIR"

# Move extra wheel files somewhere out of the way. This script
# expects just one wheel file to exist.
if [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then
  echo "More than one wheel file is present: moving the oldest to"