/** File system errors (not found, access denied, etc.) */
        FILE_SYSTEM,
        /** Protocol errors (invalid message, unsupported operation, etc.) */
        PROTOCOL,
        /** Resource errors (out of memory, disk space, etc.) */
        RESOURCE,
        /** Configuration errors */
        CONFIGURATION,
        /** Transient errors that may succeed on retry */
        TRANSIENT,
        /** Unknown or unclassified errors */

models or graphs is equivalent to running untrusted code.

If you need to run untrusted models, execute them inside a
[**sandbox**](https://developers.google.com/code-sandboxing). Memory corruptions
in TensorFlow ops can be recognized as security issues only if they are
reachable and exploitable through production-grade, benign models.

### Compilation

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.io.DataInput;
import java.io.IOException;
import org.jspecify.annotations.Nullable;

/**
 * An extension of {@code DataInput} for reading from in-memory byte arrays; its methods offer
 * identical functionality but do not throw {@link IOException}.
 *
 * <p><b>Warning:</b> The caller is responsible for not attempting to read past the end of the

        // Since it costs IO to compute this, and is done at configuration time we want to cache this if possible
        // It's safe to store this in a static variable since it's just a primitive so leaking memory isn't an issue
        if (_defaultParallel == null) {
            File cpuInfoFile = new File("/proc/cpuinfo");
            if (cpuInfoFile.exists()) {

 * <p>This class should not be assumed to be universally superior to {@code java.util.HashSet}.
 * Generally speaking, this class reduces object allocation and memory consumption at the price of
 * moderately increased constant factors of CPU. Only use this class when there is a specific reason
 * to prioritize memory over CPU.
 *
 * @author Dimitris Andreou
 * @author Jon Noack
 */
@GwtIncompatible // not worth using in GWT for now

# ADR-0002 - Avoid using Java serialization

## Status

- ACCEPTED on 2023-12-01

## Context

In Gradle we often need to serialize in-memory objects for caching, or to transmit them across process barriers, etc.
Java serialization is one way to implement this, however, despite its simplicity of implementation, it has several drawbacks:

- **Performance:**
Java's built-in serialization mechanism is often slower compared to other serialization solutions.

                String.format(Locale.ROOT, "Caught an exception in %s.  Shutting down.", t),
                e);
      } catch (Throwable errorInLogging) { // sneaky checked exception
        // If logging fails, e.g. due to missing memory, at least try to log the
        // message and the cause for the failed logging.
        System.err.println(e.getMessage());
        System.err.println(errorInLogging.getMessage());
      } finally {
        runtime.exit(1);

   - sanjoy
# filesystem path
filesystem_path:
   - tensorflow/c/experimental/filesystem
# security path
security_path:
   - tensorflow/security
# words checklist
segfault_memory:
   - segfault
   - memory leaks
# assignees
filesystem_security_assignee:
   - mihaimaruseac
   
# Cuda Comment
cuda_comment: >
   From the template it looks like you are installing **TensorFlow** (TF) prebuilt binaries:

Each <code>DATA</code> directive initializes a section of the
corresponding memory.
The memory not explicitly initialized is zeroed.
The general form of the <code>DATA</code> directive is

<pre>
DATA	symbol+offset(SB)/width, value
</pre>

<p>
which initializes the symbol memory at the given offset and width with the given value.

	Items []madmin.HealResultItem `json:"Items"`
}

// structure to hold state of all heal sequences in server memory
type allHealState struct {
	sync.RWMutex

	// map of heal path to heal sequence
	healSeqMap map[string]*healSequence // Indexed by endpoint
	// keep track of the healing status of disks in the memory
	//   false: the disk needs to be healed but no healing routine is started
	//    true: the disk is currently healing