}

	cache := store.lock()
	defer store.unlock()

	// We should only update the in-memory cache if there were no changes
	// to the in-memory cache since the disk loading began. If there
	// were changes to the in-memory cache we should wait for the next
	// cycle until we can safely update the in-memory cache.
	//
	// An in-memory cache must be replaced only if we know for sure that the

// bytes of the memory pointed to by the device pointer returned above.
TF_CAPI_EXPORT extern size_t TFE_TensorHandleDeviceMemorySize(TFE_TensorHandle*,
                                                              TF_Status*);

// Creates a new TensorHandle from memory residing in the physical device
// device_name. Takes ownership of the memory, and will call deleter to release

 */
package org.apache.maven.building;

import java.io.IOException;
import java.io.InputStream;

/**
 * Provides access to the contents of a source independently of the backing store (e.g. file system, database, memory).
 *
 */
public interface Source {

    /**
     * Gets a byte stream to the source contents. Closing the returned stream is the responsibility of the caller.
     *

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

    false

-   type: input id: Cuda attributes: label: CUDA/cuDNN version description:
    placeholder: validations: required: false

-   type: input id: Gpu attributes: label: GPU model and memory description: if
    compiling from source placeholder: validations: required: false

-   type: textarea id: what-happened attributes: label: Current Behaviour?

import com.google.errorprone.annotations.CanIgnoreReturnValue;
import java.io.DataInput;
import java.io.IOException;
import javax.annotation.CheckForNull;

/**
 * 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

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import java.io.DataOutput;
import java.io.IOException;

/**
 * An extension of {@code DataOutput} for writing to in-memory byte arrays; its methods offer
 * identical functionality but do not throw {@link IOException}.
 *
 * @author Jayaprabhakar Kadarkarai
 * @since 1.0
 */
@J2ktIncompatible
@GwtIncompatible

   - 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:

 * <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

        case WEB -> ComponentUtil.getProtocolHelper().getWebProtocols();
        case FILE -> ComponentUtil.getProtocolHelper().getFileProtocols();
        default -> throw new ConstraintDefinitionException("protocolType is emtpy.");
        };
    }

    @Override
    public boolean isValid(final String value, final ConstraintValidatorContext context) {
        if (StringUtil.isNotBlank(value)) {
            return check(protocols, value);