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  - url: https://github.com/scalar/scalar/?utm_source=fastapi&utm_medium=website&utm_campaign=main-badge
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    </div>
    <div class="item">
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        <span class="sponsor-badge">sponsor</span>
        <img class="sponsor-image" src="/img/sponsors/scalar-banner.svg" />
      </a>
    </div>

// maximum possible integer value will be returned
func (s *scanner) remaining() int64 {
	if atomic.LoadInt64(&s.end) == maxInt {
		return maxInt
	}
	return atomic.LoadInt64(&s.end) - s.pos
}

// read byte at current position (without advancing)
func (s *scanner) cur() byte { return s.buf[s.ipos] }

// read next byte
func (s *scanner) next() byte {
	if s.pos >= atomic.LoadInt64(&s.end) {
		return nullByte
	}

				p.errorf("%s doesn't support scaled register format", p.arch.Name)
			} else {
				a.Scale = int16(scale)
			}
		}
		p.get(')')
	} else if scale != 0 {
		if p.arch.Family == sys.ARM64 {
			p.errorf("arm64 doesn't support scaled register format")
		}
		// First (R) was missing, all we have is (R*scale).
		a.Reg = 0
		a.Index = r1
		a.Scale = int16(scale)
	}
}

  // Construct a parallel tensor consisting of the scalar values from `values`.
  template <typename DataType>
  std::unique_ptr<ParallelTensor> ScalarsFromSequence(
      absl::Span<const DataType> values, TFE_Context* context,
      TF_Status* status) const;

  // A parallel tensor with scalar integers numbering component devices.
  std::unique_ptr<ParallelTensor> DeviceIDs(TFE_Context* context,

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	scannerExcessFolders                 = uatomic.NewInt64(50000)
)

// initDataScanner will start the scanner in the background.
func initDataScanner(ctx context.Context, objAPI ObjectLayer) {
	go func() {
		r := rand.New(rand.NewSource(time.Now().UnixNano()))
		// Run the data scanner in a loop
		for {
			runDataScanner(ctx, objAPI)
			duration := time.Duration(r.Float64() * float64(scannerCycle.Load()))

// Abstract interface to a context.
//
// A context is responsible for creating key objects such as Tensors,
// TensorHandles & Operations.
class ImmediateExecutionContext : public AbstractContext {
 public:
  // Optimized scalar creation functions
  virtual AbstractTensorInterface* CreateInt64Scalar(int64_t value) = 0;
  virtual AbstractTensorInterface* CreateUint64Scalar(uint64 value) = 0;

  TF_ImportGraphDefOptionsAddInputMapping(opts, "scalar", 0, {scalar, 0});
  TF_ImportGraphDefOptionsAddReturnOutput(opts, "feed", 0);
  TF_ImportGraphDefOptionsAddReturnOutput(opts, "scalar", 0);
  EXPECT_EQ(2, TF_ImportGraphDefOptionsNumReturnOutputs(opts));
  TF_ImportGraphDefOptionsAddReturnOperation(opts, "scalar");
  EXPECT_EQ(1, TF_ImportGraphDefOptionsNumReturnOperations(opts));

name: OSV-Scanner Scheduled Scan

on:
  schedule:
    - cron: 0 4 * * 1

permissions:
  # Require writing security events to upload SARIF file to security tab
  security-events: write
  # Only need to read contents
  contents: read

jobs:
  scan-scheduled:
    if: github.repository == 'tensorflow/tensorflow'