virtual absl::Status TensorHandleStatus() const;

  // Returns tensor shape. If tensor has unknown rank, shape remains untouched.
  virtual absl::Status Shape(tensorflow::PartialTensorShape* shape) const = 0;

  // Returns tensor (full) type.
  // While there is no immediate plan to deprecate dtype and shape in favor
  // of only using full type type information, this is a future possibility.
  //

        }

        features {
            // https://www.jetbrains.com/help/teamcity/shared-resources.html#Viewing+Shared+Resources+Usage
            // https://blog.jetbrains.com/teamcity/2013/05/explaining-the-shared-resources-plugin/
            // we only allow 1 promotion job running at the same time to avoid website xml conflicts
            feature {

  CHECK_EQ(TF_OK, TF_GetCode(status_)) << TF_Message(status_);

  // Infer shape when everything is known.
  CheckOutputShapes(matmul_op,
                    /*input_shapes*/ {make_shape({3, 2}), make_shape({2, 4})},
                    /*input_tensors*/ {},
                    /*expected_shape*/ make_shape({3, 4}));

  // Infer shape when second operand has unknown shape.
  CheckOutputShapes(matmul_op,

    TF_RETURN_IF_ERROR(operation->SetAttrType("dtype", dtype));
    if (!shape.unknown_rank()) {
      TF_RETURN_IF_ERROR(operation->SetAttrShape(
          "shape", reinterpret_cast<int64_t*>(shape.dim_sizes().data()),
          shape.dims()));
    }
    int num_outputs = 1;
    std::vector<AbstractTensorHandle*> outputs(num_outputs);
    TF_RETURN_IF_ERROR(operation->Execute(

import (
	"context"
)

const (
	memTotal     = "total"
	memUsed      = "used"
	memFree      = "free"
	memBuffers   = "buffers"
	memCache     = "cache"
	memUsedPerc  = "used_perc"
	memShared    = "shared"
	memAvailable = "available"
)

var (
	memTotalMD     = NewGaugeMD(memTotal, "Total memory on the node")
	memUsedMD      = NewGaugeMD(memUsed, "Used memory on the node")

 *
 *  * **Read/write:** read and write using the same operator.
 *  * **Random access:** access any position within the file.
 *  * **Shared channels:** read and write a file channel that's shared between
 * multiple operators. Note that although the underlying [FileChannel] may be shared,
 * each [FileOperator] should not be.
 */
internal class FileOperator(
  private val fileChannel: FileChannel,
) {

	-dynlink
		Support references to Go symbols defined in other shared libraries.
	-e
		No limit on number of errors reported.
	-gensymabis
		Write symbol ABI information to output file. Don't assemble.
	-o file
		Write output to file. The default is foo.o for /a/b/c/foo.s.
	-p pkgpath
		Set expected package import to pkgpath.
	-shared
		Generate code that can be linked into a shared library.
	-spectre list

* fix detach azure disk back off issue which has too big lock in failure retry condition ([#76573](https://github.com/kubernetes/kubernetes/pull/76573), [@andyzhangx](https://github.com/andyzhangx))
* specify azure file share name in azure file plugin ([#76988](https://github.com/kubernetes/kubernetes/pull/76988), [@andyzhangx](https://github.com/andyzhangx))

esac

mkdir -p "${TARGET}"

# Download glibc's shared and development libraries based on the value of the
# `VERSION` parameter.
# Note: 'Templatizing' this and the other conditional branches would require
# defining several variables (version, os, path) making it difficult to maintain
# and extend for future modifications.
case "${VERSION}" in
devtoolset-7)
  # Download binary glibc 2.12 shared library release.

      new ParallelTensor(parallel_device, std::move(components), dtype));
}

absl::Status ParallelTensor::Shape(const std::vector<int64_t>** shape) const {
  if (!shape_.has_value()) {
    TF_Status status;
    PartialTensorShape combined_shape;
    TF_RETURN_IF_ERROR(unwrap(tensors_[0].get())->Shape(&combined_shape));

    for (const TensorHandlePtr& component : tensors_) {
      PartialTensorShape component_shape;