and their sizes must match in all dimensions except `concat_dim`.}]>:$values
  );

  let results = (outs
    Res<TF_Tensor, [{A `Tensor` with the concatenation of values stacked along the
`concat_dim` dimension.  This tensor's shape matches that of `values` except
in `concat_dim` where it has the sum of the sizes.}]>:$output
  );

// and is comparable (supports == and being a map key).
package netip

import (
	"cmp"
	"errors"
	"internal/bytealg"
	"internal/byteorder"
	"internal/itoa"
	"math"
	"strconv"
	"unique"
)

// Sizes: (64-bit)
//   net.IP:     24 byte slice header + {4, 16} = 28 to 40 bytes
//   net.IPAddr: 40 byte slice header + {4, 16} = 44 to 56 bytes + zone length
//   netip.Addr: 24 bytes (zone is per-name singleton, shared across all users)

	PartETags          []string          `json:"PartETags" msg:"PartETags,allownil"`             // Part ETags
	PartSizes          []int64           `json:"PartSizes" msg:"PartSizes"`                      // Part Sizes
	PartActualSizes    []int64           `json:"PartASizes,omitempty" msg:"PartASizes,allownil"` // Part ActualSizes (compression)

	// pauseNS is the total STW time this cycle, measured as the time between
	// when stopping began (just before trying to stop Ps) and just after the
	// world started again.
	pauseNS int64

	// debug.gctrace heap sizes for this cycle.
	heap0, heap1, heap2 uint64

	// Cumulative estimated CPU usage.
	cpuStats
}

// GC runs a garbage collection and blocks the caller until the

  let summary = "Select operator";

  let description = [{
    Select values of 'x' if the corresponding value of 'condition' is true or
    the value of 'y' if false. There are valid condition input sizes:

    1. Either the same shape (in which case the select is elementwise), or
    2. condition must be Rank 1 and match over the first dimension.
  }];

  let arguments = (ins

    keyEquivalence = builder.getKeyEquivalence();
    this.entryHelper = entryHelper;

    int initialCapacity = Math.min(builder.getInitialCapacity(), MAXIMUM_CAPACITY);

    // Find power-of-two sizes best matching arguments. Constraints:
    // (segmentCount > concurrencyLevel)
    int segmentShift = 0;
    int segmentCount = 1;
    while (segmentCount < concurrencyLevel) {
      ++segmentShift;

	rsOpts volume.NodeResizeOptions) (bool, error) {

	supportsExpansion, expandableVolumePlugin := og.checkIfSupportsNodeExpansion(volumeToMount)

	if supportsExpansion {
		// lets use sizes handed over to us by caller for comparison
		if rsOpts.NewSize.Cmp(rsOpts.OldSize) > 0 {
			pv := volumeToMount.VolumeSpec.PersistentVolume

		// Counters for pod creation status (used by the job_pods_creation_total metric)
		var creationsSucceeded, creationsFailed int32 = 0, 0

		// Batch the pod creates. Batch sizes start at SlowStartInitialBatchSize
		// and double with each successful iteration in a kind of "slow start".
		// This handles attempts to start large numbers of pods that would

    keyEquivalence = builder.getKeyEquivalence();
    this.entryHelper = entryHelper;

    int initialCapacity = Math.min(builder.getInitialCapacity(), MAXIMUM_CAPACITY);

    // Find power-of-two sizes best matching arguments. Constraints:
    // (segmentCount > concurrencyLevel)
    int segmentShift = 0;
    int segmentCount = 1;
    while (segmentCount < concurrencyLevel) {
      ++segmentShift;

           "Maximum shape inference iterations">,
    Option<"input_arg_shapes_", "input-arg-shapes", "std::string", /*default=*/"",
           "Input tensor shapes. Shapes for different tensors are separated by ':', and dimension sizes for the same tensor are separated by ','">,
  ];
}

def StripNoinlineAttributePass : Pass<"tf-strip-noinline-attribute", "ModuleOp"> {
  let summary = "Strip the tf._noinline attribute from top-level functions.";