<span class="badge bg-primary"><la:message
                                                                            key="labels.enabled"/></span>
                                                    </c:if> <c:if test="${data.available=='false'}">
																	<span class="badge bg-gray"><la:message

  @Override
  public ImmutableRangeSet<C> subRangeSet(Range<C> range) {
    if (!isEmpty()) {
      Range<C> span = span();
      if (range.encloses(span)) {
        return this;
      } else if (range.isConnected(span)) {
        return new ImmutableRangeSet<>(intersectRanges(range));
      }
    }
    return of();
  }

  /**

      if (rangeMap.asMapOfRanges().isEmpty()) {
        return;
      }
      Range<K> span = rangeMap.span();
      checkArgument(
          subRange.encloses(span),
          "Cannot putAll rangeMap with span %s into a subRangeMap(%s)",
          span,
          subRange);
      TreeRangeMap.this.putAll(rangeMap);
    }

    @Override
    public void clear() {

namespace tensorflow {
namespace gradients {
namespace {
class IdentityNGradientFunction : public GradientFunction {
 public:
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    for (int i = 0; i < grad_outputs.size(); i++) {
      auto grad_input = grad_outputs[i];

}
caption a:link, caption a:hover, caption a:active, caption a:visited {
    color:#FFFFFF;
}
.overviewSummary caption span, .packageSummary caption span, .contentContainer ul.blockList li.blockList caption span, .summary caption span, .classUseContainer caption span, .constantValuesContainer caption span {
    white-space:nowrap;
    padding-top:8px;
    padding-left:8px;
    display:block;
    float:left;

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_STABLEHLO_CC_CALIBRATION_REPRESENTATIVE_DATASET_H_

#include <string>

#include "absl/container/flat_hash_map.h"
#include "absl/status/statusor.h"
#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/quantization_options.pb.h"

namespace stablehlo::quantization {

#define TENSORFLOW_COMPILER_MLIR_QUANTIZATION_TENSORFLOW_CALIBRATOR_CALIBRATION_STATISTICS_COLLECTOR_MIN_MAX_H_

#include <cstdint>
#include <optional>

#include "absl/types/span.h"
#include "tensorflow/compiler/mlir/quantization/stablehlo/quantization_config.pb.h"
#include "tensorflow/compiler/mlir/quantization/tensorflow/calibrator/calibration_statistics.pb.h"

  bool UseFunction() const { return std::get<2>(GetParam()); }
};

// Checks that inputs[0] is a scalar.
Status TestScalarShape(AbstractContext* ctx,
                       absl::Span<AbstractTensorHandle* const> inputs,
                       absl::Span<AbstractTensorHandle*> outputs) {
  PartialTensorShape shape;
  TF_RETURN_IF_ERROR(inputs[0]->Shape(&shape));
  if (shape.dims() != 0) {
    return errors::InvalidArgument(

plugins: forked-1.1.3, xdist-1.31.0, cov-2.8.1
collected 6 items

---> 100%

test_main.py <span style="color: green; white-space: pre;">......                            [100%]</span>

<span style="color: green;">================= 1 passed in 0.03s =================</span>
```

#include <optional>
#include <string>
#include <unordered_set>
#include <vector>

#include "absl/base/macros.h"
#include "absl/strings/string_view.h"
#include "absl/types/span.h"
#include "mlir/Dialect/Func/IR/FuncOps.h"  // from @llvm-project
#include "mlir/IR/BuiltinOps.h"  // from @llvm-project
#include "mlir/IR/MLIRContext.h"  // from @llvm-project
#include "tensorflow/cc/saved_model/loader.h"