key = re.sub(r"0x\w+", "", p.getparent().get("name", "")) + p.text
      if key in seen:
        testsuite._elem.remove(p.getparent())
      seen[key] += 1
    # Remove this testsuite if it doesn't have anything in it any more
    if len(testsuite) == 0:  # pylint: disable=g-explicit-length-test
      r._elem.remove(testsuite._elem)
  if len(r) > 0:  # pylint: disable=g-explicit-length-test
    result += r

limitations under the License.
==============================================================================*/

#include "tensorflow/cc/training/queue_runner.h"
#include "tensorflow/core/kernels/ops_util.h"
#include "tensorflow/core/platform/env.h"

namespace tensorflow {

Status QueueRunner::New(const QueueRunnerDef& queue_runner_def,
                        std::unique_ptr<QueueRunner>* result) {

// assigned per mhlo communcation op, and frontend attributes (modified keys)
// and op shardings are added. Sink tokens are created
// if there are more than one operand or more than one result.
//
// The following op sharding assigns full tensors to TPU core 0.
// Proto debug string:
//   type: MAXIMAL
//   tile_assignment_dimensions: 1
//   tile_assignment_devices: 0
// Serialized string:
//   "\08\01\1A\01\01\22\01\00"

    return failure();
  }
  const double fraction = std::frexp(double_multiplier, &shift);
  quantized_fraction = static_cast<int32_t>(std::round(fraction * (1L << 15)));
  // Clip extreme values.  These are more than enough to overflow int8, the
  // storage type for quantized values, and the final values will be clamped
  // no matter what.
  if (quantized_fraction == (1L << 15)) {
    quantized_fraction /= 2;
    ++shift;
  }

#include "tensorflow/core/framework/shape_inference.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/graph/graph.h"
#include "tensorflow/core/graph/node_builder.h"
#include "tensorflow/core/platform/blocking_counter.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/init_main.h"
#include "tensorflow/core/platform/mutex.h"

  LogicalResult matchAndRewrite(FakeQuantOp op,
                                PatternRewriter &rewriter) const override {
    // TODO: If this pattern comes up more frequently, consider adding core
    // support for failable rewrites.
    if (failableRewrite(op, rewriter)) {
      *hadFailure = true;
      return failure();
    }
    return success();
  }

 private:

#include "tensorflow/core/common_runtime/graph_constructor.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/node_def_util.h"
#include "tensorflow/core/framework/op.h"
#include "tensorflow/core/framework/op_kernel.h"
#include "tensorflow/core/graph/algorithm.h"
#include "tensorflow/core/graph/while_context.h"
#include "tensorflow/core/lib/gtl/map_util.h"

namespace mlir {
namespace TFDevice {
namespace {

constexpr char kBadDecompositionMessage[] =
    "Resource ops decomposition did not converge";

// Decomposing resource ops should not take more than a few iterations (2-3) to
// converge as only a few patterns create new resource ops that can be further
// decomposed. The rest of the iterations are enough to clean up any dead ops
// created by decomposition.

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 [[ "$(ls *.whl | wc -l | tr -d ' ')" != "1" ]]; then
  echo "More than one wheel file is present: moving the oldest to"
  echo "$TFCI_OUTPUT_DIR/extra_wheels."
  # List all .whl files by their modification time (ls -t) and move anything

# 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
except NameError:
  pass