# limitations under the License.
# ==============================================================================
# Release jobs are very basic. They don't use any caching or RBE,
# but they do upload logs to resultstore.
# IMPORTANT: trailing slash is required on GCS URIs, as it tells gcloud to
# pretend the path is a directory.
TFCI_ARTIFACT_FINAL_GCS_ENABLE=1

  absl::StatusOr<core::RefCountPtr<FunctionRecord>> GetFunctionRecord()
      override {
    return func_record_.GetNewRef();
  }

  // For LLVM style RTTI.
  static bool classof(const AbstractFunction* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  core::RefCountPtr<FunctionRecord> func_record_;
};
}  // namespace graph
}  // namespace tracing
}  // namespace tensorflow

# accordingly.

# -e: abort script if one command fails
# -u: error if undefined variable used
# -o pipefail: entire command fails if pipe fails. watch out for yes | ...
# -o history: record shell history
set -euo pipefail -o history

# Check for required arguments
if [ -z "$1" ]; then
  echo "Usage: $0 <path_to_tensorflow_wheel> <python_version>"
  exit 1
fi

TENSORFLOW_WHEEL_PATH="$1"

*   Performance improvements
*   Many bugfixes
*   Many documentation fixes
*   TensorBoard fixes: graphs with only one data point, Nan values, reload
    button and auto-reload, tooltips in scalar charts, run filtering, stable
    colors
*   Tensorboard graph visualizer now supports run metadata. Clicking on nodes

  if (TF_GetCode(status) == TF_OK) {
    // This modification only updates the destination node for
    // the purposes of running this graph in a session. Thus, we don't
    // record the source node as being modified.
    RecordMutation(graph, *dst.oper, "updating input tensor");
  }
}

// Apis that are corresponding to python c api. --------------------------

# Description:
# C API for TensorFlow, for use by client language bindings.

load("@bazel_skylib//lib:selects.bzl", "selects")
load("@local_config_tensorrt//:build_defs.bzl", "if_tensorrt")
load("@local_tsl//tsl/platform:rules_cc.bzl", "cc_library")
load(
    "//tensorflow:tensorflow.bzl",
    "check_deps",
    "if_google",
    "if_not_mobile",
    "tf_cc_test",
    "tf_copts",
    "tf_cuda_library",
    "tf_custom_op_library",

# limitations under the License.
# ==============================================================================
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Record GPU count and CUDA version status
if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then
  tfrun nvidia-smi
fi

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then

# limitations under the License.
# ==============================================================================
source "${BASH_SOURCE%/*}/utilities/setup.sh"

# Record GPU count and CUDA version status
if [[ "$TFCI_NVIDIA_SMI_ENABLE" == 1 ]]; then
  tfrun nvidia-smi
fi

# Update the version numbers for Nightly only
if [[ "$TFCI_NIGHTLY_UPDATE_VERSION_ENABLE" == 1 ]]; then

  tensorflow::core::RefCountPtr<tensorflow::FunctionRecord> record =
      tensorflow::unwrap(ctx)->FindRecord(name);

  if (record == nullptr) {
    status->status = tensorflow::errors::NotFound(
        "Unable to find Function with name: ", name);
    return nullptr;
  }

  TF_Function* result = new TF_Function();
  record->Ref();
  result->record = record.get();
  return result;
}

  // Verify that FunctionDef has 2 attributes, "v1" and "v2".
  ASSERT_EQ(func_->record->fdef().signature().attr().size(), 2);
  EXPECT_EQ(func_->record->fdef().signature().attr(0).name(), "v1");
  EXPECT_EQ(func_->record->fdef().signature().attr(0).type(), "int");
  EXPECT_EQ(func_->record->fdef().signature().attr(1).name(), "v2");
  EXPECT_EQ(func_->record->fdef().signature().attr(1).type(), "int");
}