int datasetSize;

  @Param QuantilesAlgorithm algorithm;

  private final double[][] datasets = new double[0x100][];

  @BeforeExperiment
  void setUp() {
    Random rng = new Random();
    for (int i = 0; i < 0x100; i++) {
      datasets[i] = new double[datasetSize];
      for (int j = 0; j < datasetSize; j++) {
        datasets[i][j] = rng.nextDouble();
      }
    }
  }

  private double[] dataset(int i) {

You can also use `dataclasses` in the `response_model` parameter:

{* ../../docs_src/dataclasses/tutorial002.py hl[1,7:13,19] *}

The dataclass will be automatically converted to a Pydantic dataclass.

This way, its schema will show up in the API docs user interface:

<img src="/img/tutorial/dataclasses/image01.png">

     */
    private static byte[] createBuffer(int dataLen, byte[] dataBytes, String params) throws UnsupportedEncodingException {
        final byte[] paramBytes = params.getBytes(SmbConstants.DEFAULT_OEM_ENCODING);
        byte[] buffer = new byte[10 + paramBytes.length + dataLen];
        // copy params
        System.arraycopy(paramBytes, 0, buffer, 10, paramBytes.length);

///

## Dataclasses en `response_model`

También puedes usar `dataclasses` en el parámetro `response_model`:

{* ../../docs_src/dataclasses/tutorial002.py hl[1,7:13,19] *}

El dataclass será automáticamente convertido a un dataclass de Pydantic.

De esta manera, su esquema aparecerá en la interfaz de usuario de la documentación de la API:

<img src="/img/tutorial/dataclasses/image01.png">

///

## Dataclasses em `response_model`

Você também pode usar `dataclasses` no parâmetro `response_model`:

{* ../../docs_src/dataclasses/tutorial002.py hl[1,7:13,19] *}

A dataclass será automaticamente convertida para uma dataclass Pydantic.

Dessa forma, seu esquema aparecerá na interface de documentação da API:

<img src="/img/tutorial/dataclasses/image01.png">

## Dataclasses em Estruturas de Dados Aninhadas

                dstIndex += 4;
                SMBUtil.writeInt4(0, dst, dstIndex);
                dstIndex += 4; // Reserved
                final int dataLen = size8(nc.encode(dst, dstIndex));
                SMBUtil.writeInt2(dataLen, dst, lenOffset);
                dstIndex += dataLen;
            }
        }
        return dstIndex - start;
    }

    /**
     * {@inheritDoc}
     *

#### Option A: Reference colab notebooks

1)  Reference [TensorFlow Model Colab](https://colab.research.google.com/gist/ymodak/e96a4270b953201d5362c61c1e8b78aa/tensorflow-datasets.ipynb?authuser=1): Demonstrate how to build your TF model.

module&&module.exports?module.exports=b(require("jquery")):b(a.jQuery)}(this,function(a){!function(a){"use strict";a.formUtils.registerLoadedModule("html5");var b="placeholder"in document.createElement("INPUT"),c="options"in document.createElement("DATALIST"),d=!1,e=function(e){e.each(function(){var e=a(this),f=e.find("input,textarea,select"),g=!1;f.each(function(){var b=[],e=a(this),f=e.attr("required"),h={};switch(f&&b.push("required"),(e.attr("type")||"").toLowerCase()){case"time":b.push("time")...

Russ Cox <******@****.***> 1410149331 -0400

        // Test when data length exceeds outputBuffer size
        byte[] buffer = new byte[2000];
        int dataLen = outputBuffer.length + 100; // Exceeds outputBuffer size

        SMBProtocolDecodingException exception =
                assertThrows(SMBProtocolDecodingException.class, () -> response.readDataWireFormat(buffer, 0, dataLen));

        assertEquals("Payload exceeds buffer size", exception.getMessage());
    }