assertSame(b, reused, "Buffer should be reused from cache");
        // And it should still be zeroed
        for (byte value : reused) {
            assertEquals(0, value, "Reused buffer must be zeroed");
        }
    }

    // Edge: cache size 0 means nothing is cached; release still zeroes argument
    @Test
    @DisplayName("Cache size 0: release zeroes but does not cache; getBuffer allocates new")

* action required: Deprecate the kubelet's cadvisor port. The default will change to 0 (disabled) in 1.12, and the cadvisor port will be removed entirely in 1.13. ([#59827](https://github.com/kubernetes/kubernetes/pull/59827), [@dashpole](https...

### Server Memory { #server-memory }

For example, if your code loads a Machine Learning model with **1 GB in size**, when you run one process with your API, it will consume at least 1 GB of RAM. And if you start **4 processes** (4 workers), each will consume 1 GB of RAM. So in total, your API will consume **4 GB of RAM**.

        buffer[bufferIndex] = 0x00;
        buffer[bufferIndex + 1] = 0x00;
        buffer[bufferIndex + 2] = 0x00;
        SMBUtil.writeInt4(1500, buffer, bufferIndex + 3);

        // Fill rest of required fields
        for (int i = 7; i < 37; i++) {
            buffer[bufferIndex + i] = 0x00;
        }

        response.readParameterWordsWireFormat(buffer, bufferIndex);

        These advantages can take
        [many forms](https://github.com/google/guava/wiki/PhilosophyExplained#utility), but taking
        the time to discuss them in detail will make it much clearer why this feature should be
        added to Guava.


        Please fill out the following fields to give us a better understanding of your proposed
        feature and its potential value for other Guava users.

  - type: textarea
    attributes:

      Iterable<E> expectedElements,
      KnownOrder knownOrder,
      int startIndex) {
    // periodically we should manually try (steps * 3 / 2) here; all tests but
    // one should still pass (testVerifyGetsCalled()).
    stimuli = (Stimulus<E, ? super I>[]) new Stimulus<?, ?>[steps];
    if (!elementsToInsertIterable.iterator().hasNext()) {
      throw new IllegalArgumentException();
    }

**Note**: You can mix `def` and `async def` in your *path operation functions* as much as you need and define each one using the best option for you. FastAPI will do the right thing with them.

Anyway, in any of the cases above, FastAPI will still work asynchronously and be extremely fast.

But by following the steps above, it will be able to do some performance optimizations.

## Technical Details { #technical-details }

FastAPI will use this `response_model` to do all the data documentation, validation, etc. and also to **convert and filter the output data** to its type declaration.

/// tip

If you have strict type checks in your editor, mypy, etc, you can declare the function return type as `Any`.

# Requirements for NumPy 1.x
numpy ~= 1.26.0
wheel ~= 0.41.2
h5py >= 3.11.0, < 3.15.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras
# Note that here we want the latest version that matches TF major.minor version

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