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  1. docs/en/docs/tutorial/schema-extra-example.md

        You can set `schema_extra` with a `dict` containing any additional data you would like to show up in the generated JSON Schema, including `examples`.
    
    !!! tip
        You could use the same technique to extend the JSON Schema and add your own custom extra info.
    
        For example you could use it to add metadata for a frontend user interface, etc.
    
    !!! info
    Plain Text
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  2. android/guava/src/com/google/common/collect/MultimapBuilder.java

      /*
       * Leaving K and V as upper bounds rather than the actual key and value types allows type
       * parameters to be left implicit more often. CacheBuilder uses the same technique.
       */
    
      private MultimapBuilder() {}
    
      private static final int DEFAULT_EXPECTED_KEYS = 8;
    
      /** Uses a hash table to map keys to value collections. */
    Java
    - Registered: Fri May 03 12:43:13 GMT 2024
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  3. docs/en/docs/tutorial/dependencies/dependencies-with-yield.md

    The same way, you could raise an `HTTPException` or similar in the exit code, after the `yield`.
    
    !!! tip
    
        This is a somewhat advanced technique, and in most of the cases you won't really need it, as you can raise exceptions (including `HTTPException`) from inside of the rest of your application code, for example, in the *path operation function*.
    
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  4. okhttp/src/main/kotlin/okhttp3/Cache.kt

     * if (forceCacheResponse.code() != 504) {
     *   // The resource was cached! Show it.
     * } else {
     *   // The resource was not cached.
     * }
     * ```
     *
     * This technique works even better in situations where a stale response is better than no response.
     * To permit stale cached responses, use the `max-stale` directive with the maximum staleness in
     * seconds:
     *
     * ```java
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  5. android/guava/src/com/google/common/math/IntMath.java

          // But in gcd(a - b, b), a - b is even and b is odd, so we can divide out powers of two.
    
          // We bend over backwards to avoid branching, adapting a technique from
          // http://graphics.stanford.edu/~seander/bithacks.html#IntegerMinOrMax
    
          int delta = a - b; // can't overflow, since a and b are nonnegative
    
    Java
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  6. maven-core/src/test/resources/apiv4-repo/commons-logging/commons-logging/1.0.3/commons-logging-1.0.3.jar

    LogFactory also offers a static method getLog() that combines the typical two-step pattern: Log log = LogFactory.getFactory().getInstance("Foo"); into a single method call: Log log = LogFactory.getLog("Foo"); For example, you might use the following technique to initialize and use a Log instance in an application component: import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; public class MyComponent { protected static Log log = LogFactory.getLog("my.component"); // Called...
    Archive
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  7. android/guava/src/com/google/common/math/LongMath.java

          // But in gcd(a - b, b), a - b is even and b is odd, so we can divide out powers of two.
    
          // We bend over backwards to avoid branching, adapting a technique from
          // http://graphics.stanford.edu/~seander/bithacks.html#IntegerMinOrMax
    
          long delta = a - b; // can't overflow, since a and b are nonnegative
    
    Java
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  8. maven-core/src/test/resources/apiv4-repo/commons-logging/commons-logging/1.0.4/commons-logging-1.0.4.jar

    also offers a static method getLog() that combines the typical two-step pattern: Log log = LogFactory.getFactory().getInstance(Foo.class); into a single method call: Log log = LogFactory.getLog(Foo.class); For example, you might use the following technique to initialize and use a Log instance in an application component: import org.apache.commons.logging.Log; import org.apache.commons.logging.LogFactory; public class MyComponent { protected static Log log = LogFactory.getLog(MyComponent.class); //...
    Archive
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  9. RELEASE.md

            [`tf.keras.models.experimental.SharpnessAwareMinimization`](https://www.tensorflow.org/api_docs/python/tf/keras/models/experimental/SharpnessAwareMinimization).
            This class implements the sharpness-aware minimization technique, which
            boosts model performance on various tasks, e.g., ResNet on image
            classification.
    
    *   `tf.data`:
    
        *   Added support for cross-trainer data caching in tf.data service. This
    Plain Text
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    - Last Modified: Mon Apr 29 19:17:57 GMT 2024
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