// set maxUsedPct to the value from the disk with the least space percentage.
			if pctUsed := int(disk.Used * 100 / disk.Total); pctUsed > maxUsedPct {
				maxUsedPct = pctUsed
			}
		}

		// Since we are comparing pools that may have a different number of sets
		// we multiply by the number of sets in the pool.
		// This will compensate for differences in set sizes
		// when choosing destination pool.

            SmbFile f = (SmbFile)obj;
            boolean ret;

            if (this == f)
                return true;

            /* If uncertain, pathNamesPossiblyEqual returns true.
             * Comparing canonical paths is definitive.
             */
            if (pathNamesPossiblyEqual(url.getPath(), f.url.getPath())) {

                getUncPath0();
                f.getUncPath0();

These examples show when a Go implementation can use that instruction:
</p>

<pre>
// FMA allowed for computing r, because x*y is not explicitly rounded:
r  = x*y + z
r  = z;   r += x*y
t  = x*y; r = t + z
*p = x*y; r = *p + z
r  = x*y + float64(z)

// FMA disallowed for computing r, because it would omit rounding of x*y:
r  = float64(x*y) + z
r  = z; r += float64(x*y)
t  = float64(x*y); r = t + z

func equals(k1 string, keys ...string) bool {
	for _, k2 := range keys {
		if strings.EqualFold(k1, k2) {
			return true
		}
	}
	return false
}

// returns replicationAction by comparing metadata between source and target
func getReplicationAction(oi1 ObjectInfo, oi2 minio.ObjectInfo, opType replication.Type) replicationAction {

These examples show when a Go implementation can use that instruction:
</p>

<pre>
// FMA allowed for computing r, because x*y is not explicitly rounded:
r  = x*y + z
r  = z;   r += x*y
t  = x*y; r = t + z
*p = x*y; r = *p + z
r  = x*y + float64(z)

// FMA disallowed for computing r, because it would omit rounding of x*y:
r  = float64(x*y) + z
r  = z; r += float64(x*y)
t  = float64(x*y); r = t + z

in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

### Compilation

Compiling models via the recommended entry points described in
[XLA](https://www.tensorflow.org/xla) and
[JAX](https://jax.readthedocs.io/en/latest/jax-101/02-jitting.html)

    placeholder: e.g., 3.9 validations: required: false

-   type: input id: Bazel attributes: label: Bazel version description: if
    compiling from source placeholder: validations: required: false

-   type: input id: Compiler attributes: label: GCC/Compiler version
    description: if compiling from source placeholder: validations: required:
    false

-   type: input id: Cuda attributes: label: CUDA/cuDNN version description:

      label: Bazel version
      description: If compiling from source
  - type: input
    id: Compiler
    attributes:
      label: GCC/compiler version
      description: If compiling from source
  - type: input
    id: Cuda
    attributes:
      label: CUDA/cuDNN version
  - type: input
    id: Gpu
    attributes:
      label: GPU model and memory
      description: If compiling from source
  - type: textarea

 *
 * @author Bob Lee
 * @since 2.0
 * @deprecated This exception is no longer thrown by {@code com.google.common}. Previously, it was
 *     thrown by {@link MapMaker} computing maps. When support for computing maps was removed from
 *     {@code MapMaker}, it was added to {@code CacheBuilder}, which throws {@code
 *     ExecutionException}, {@code UncheckedExecutionException}, and {@code ExecutionError}. Any

  std::string shape_string;
  if (Shape(&shape).ok()) {
    shape_string = shape.DebugString();
  } else {
    shape_string = "<error computing shape>";
  }
  std::string value_string;
  if (!SummarizeValue(value_string).ok()) {
    value_string = "<error computing value>";
  }
  if (value_string.length() > 100) {
    // The default NumPy-style output can be distractingly long in error
    // messages.