"60b420bb3851d9d47acb933dbe70399bf6c92da33af01d4fb770e98c0325f41d3ebaf8986da71" +
          "2c82bcd4d554bf0b54023c2"
      ).decodeHex()
    serverWriter.writeMessageFrame(OPCODE_BINARY, payload)
    assertData("8232")
    assertData(payload)
  }

  @Test fun serverMessageLengthShort() {
    // Create a payload which will overflow the normal payload byte size.
    val payload = Buffer()

        long bHi = b >>> 32; // < 2^31
        long aLo = a & 0xFFFFFFFFL; // < 2^32
        long bLo = b & 0xFFFFFFFFL; // < 2^32

        /*
         * a * b == aHi * bHi * 2^64 + (aHi * bLo + aLo * bHi) * 2^32 + aLo * bLo.
         *       == (aHi * bHi * 2^32 + aHi * bLo + aLo * bHi) * 2^32 + aLo * bLo
         *

        long bHi = b >>> 32; // < 2^31
        long aLo = a & 0xFFFFFFFFL; // < 2^32
        long bLo = b & 0xFFFFFFFFL; // < 2^32

        /*
         * a * b == aHi * bHi * 2^64 + (aHi * bLo + aLo * bHi) * 2^32 + aLo * bLo.
         *       == (aHi * bHi * 2^32 + aHi * bLo + aLo * bHi) * 2^32 + aLo * bLo
         *

1.23.2...

# CuDNN: https://docs.nvidia.com/deeplearning/sdk/cudnn-install/index.html#ubuntu-network-installation
libcudnn9-dev-cuda-12=9.1.1.17-1
libcudnn9-cuda-12=9.1.1.17-1

# This can be removed once NVIDIA publishes a cuda-12.3.2 Docker image.
# For now it ensures that we install at least version 12.3.107 of PTXAS,
# since 12.3.103 has a bug.

keras-nightly ~= 3.0.0.dev
tb-nightly ~= 2.19.0.a
# Test dependencies
grpcio >= 1.24.3, < 2.0
portpicker == 1.6.0
scipy >= 1.13.0
requests >= 2.31.0
packaging==23.2
setuptools==70.0.0
jax==0.4.7
# The dependencies below are needed for TF wheel testing.
tensorflow-io-gcs-filesystem==0.37.1
libclang >= 13.0.0
google_pasta ~= 0.2

@test "Pip package doesn't depend on CUDA" {
  bazel cquery \
    --experimental_cc_shared_library \
    --@local_config_cuda//:enable_cuda \
    --repo_env=HERMETIC_CUDA_VERSION="12.3.2" \
    --repo_env=HERMETIC_CUDNN_VERSION="8.9.7.29" \
    "somepath(//tensorflow/tools/pip_package:build_pip_package, " \
    "@local_config_cuda//cuda:cudart + "\
    "@local_config_cuda//cuda:cudart + "\

  }

  @AfterEach
  @Throws(Exception::class)
  fun tearDown() {
    TimeZone.setDefault(originalDefault)
  }

  @Test
  @Throws(Exception::class)
  fun parseStandardFormats() {
    // RFC 822, updated by RFC 1123 with GMT.
    assertThat("Thu, 01 Jan 1970 00:00:00 GMT".toHttpDateOrNull()!!.time).isEqualTo(0L)
    assertThat("Fri, 06 Jun 2014 12:30:30 GMT".toHttpDateOrNull()!!.time).isEqualTo(1402057830000L)

    testRotate(new byte[] {1, 2, 3}, -3, new byte[] {1, 2, 3});
    testRotate(new byte[] {1, 2, 3}, -2, new byte[] {3, 1, 2});
    testRotate(new byte[] {1, 2, 3}, -1, new byte[] {2, 3, 1});
    testRotate(new byte[] {1, 2, 3}, 0, new byte[] {1, 2, 3});
    testRotate(new byte[] {1, 2, 3}, 1, new byte[] {3, 1, 2});
    testRotate(new byte[] {1, 2, 3}, 2, new byte[] {2, 3, 1});
    testRotate(new byte[] {1, 2, 3}, 3, new byte[] {1, 2, 3});

## Change Default Swagger UI Parameters

FastAPI includes some default configuration parameters appropriate for most of the use cases.

It includes these default configurations:

{* ../../fastapi/openapi/docs.py ln[8:23] hl[17:23] *}

You can override any of them by setting a different value in the argument `swagger_ui_parameters`.

For example, to disable `deepLinking` you could pass these settings to `swagger_ui_parameters`: