}
                }),
            executor);

    // Pause in step 2.
    step2Waiter.awaitStarted();

    // Everything should still be open.
    assertStillOpen(closeable1, closeable2, closeable3, closeable4);

    // Cancel step 3, resume step 2, and pause in step 4.
    assertWithMessage("step3.cancel()").that(step3.cancel(false)).isTrue();
    step2Waiter.awaitReturned();

### Step 1: Ensure Elasticsearch minimum requirements are met

MinIO requires a 5.x series version of Elasticsearch. This is the latest major release series. Elasticsearch provides version upgrade migration guidelines [here](https://www.elastic.co/guide/en/elasticsearch/reference/current/setup-upgrade.html).

### Step 2: Add Elasticsearch endpoint to MinIO

        Doc(
            """
            'Whitelist' validation step. The parameter field will be the single one
            allowed by the alias or set of aliases defined.
            """
        ),
    ] = None,
    serialization_alias: Annotated[
        Union[str, None],
        Doc(
            """
            'Blacklist' validation step. The vanilla parameter field will be the

              "format": "time_series",
              "instant": false,
              "intervalFactor": 2,
              "legendFormat": "Virtual Memory",
              "refId": "I",
              "step": 2
            },
            {
              "datasource": {
                "type": "prometheus",
                "uid": "${datasource}"
              },

build:cross_compile_linux_arm64 --crosstool_top=//tensorflow/tools/toolchains/cross_compile/cc:cross_compile_toolchain_suite

# XLA uses different paths for platforms and crosstool_top.
build:cross_compile_linux_arm64_xla --config=cross_compile_base_xla
build:cross_compile_linux_arm64_xla --platforms=//tools/toolchains/cross_compile/config:linux_aarch64

          "instant": true,
          "interval": "",
          "intervalFactor": 1,
          "legendFormat": "{{instance}}",
          "metric": "process_start_time_seconds",
          "refId": "A",
          "step": 60
        }
      ],
      "title": "Uptime",
      "type": "stat"
    },
    {
      "datasource": {
        "type": "prometheus",
        "uid": "${DS_PROMETHEUS}"
      },

		buf[n-7] = '\x00'
	})
}

func BenchmarkCountSingle(b *testing.B) {
	benchBytes(b, indexSizes, func(b *testing.B, n int) {
		buf := bmbuf[0:n]
		step := 8
		for i := 0; i < len(buf); i += step {
			buf[i] = 1
		}
		expect := (len(buf) + (step - 1)) / step
		for i := 0; i < b.N; i++ {
			j := Count(buf, []byte{1})
			if j != expect {
				b.Fatal("bad count", j, expect)
			}
		}

   * | `http://host/?a=apple&b`          | `"apple"`             |
   */
  fun queryParameter(name: String): String? {
    if (queryNamesAndValues == null) return null
    for (i in 0 until queryNamesAndValues.size step 2) {
      if (name == queryNamesAndValues[i]) {
        return queryNamesAndValues[i + 1]
      }
    }
    return null
  }

  /**

    return f"baz_{route.name}"


class Item(BaseModel):
    name: str
    price: float


class Message(BaseModel):
    title: str
    description: str


def test_top_level_generate_unique_id():
    app = FastAPI(generate_unique_id_function=custom_generate_unique_id)
    router = APIRouter()

    @app.post("/", response_model=List[Item], responses={404: {"model": List[Message]}})

import glob
import json
import os
import platform
import re
import subprocess
import sys

# pylint: disable=g-import-not-at-top
try:
  from shutil import which
except ImportError:
  from distutils.spawn import find_executable as which
# pylint: enable=g-import-not-at-top

_DEFAULT_CUDA_VERSION = '11'
_DEFAULT_CUDNN_VERSION = '2'
_DEFAULT_TENSORRT_VERSION = '6'
_DEFAULT_CUDA_COMPUTE_CAPABILITIES = '3.5,7.0'