"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}"
      },

resulting CR is converted to Helm values.yaml format and passed to the next step.
1. Part of the configuration profile contains settings in the Helm values.yaml schema format. User overrides of
these fields are applied and merged with the output of this step. The result of this step is a merge of configuration

        sampleDirectory = generateSampleTask.flatMap { it.target }
        displayName = "Building $languageDisplayName $capKind$multiProjectSuffix"
        description = "Setup a $languageDisplayName $kind project$multiProjectSuffix step-by-step."
        category = language.toString()
    }
}

      val lengthByteCount = (lengthBitCount + 7) / 8
      sink.writeByte(0b1000_0000 or lengthByteCount)
      for (shift in (lengthByteCount - 1) * 8 downTo 0 step 8) {
        sink.writeByte((length shr shift).toInt())
      }
    }

    // Write the payload.
    sink.writeAll(content)
  }

  /**

// Some TF ops need a step container to be set to limit the lifetime of some
// resources (mostly TensorArray and Stack, used in while loop gradients in
// graph mode). Calling this on a context tells it to start a step.
TF_CAPI_EXPORT extern void TFE_ContextStartStep(TFE_Context* ctx);

// Ends a step. When there is no active step (that is, every started step has

# Tutorial - User Guide

This tutorial shows you how to use **FastAPI** with most of its features, step by step.

Each section gradually builds on the previous ones, but it's structured to separate topics, so that you can go directly to any specific one to solve your specific API needs.

It is also built to work as a future reference so you can come back and see exactly what you need.

## Run the code

namespace gradients {

using namespace std;

// ================== Helper functions =================

// Fills data with values [start,end) with given step size.
void Range(vector<int32_t>* data, int32_t start, int32_t end,
           int32_t step = 1) {
  for (int32_t i = start; i < end; i += step) {
    (*data)[i] = i;
  }
}

// Fills out_dims with the dimensions of the given tensor.
void GetDims(const TF_Tensor* t, int64_t* out_dims) {

You could also use it to generate code automatically, for clients that communicate with your API. For example, frontend, mobile or IoT applications.

## Recap, step by step

### Step 1: import `FastAPI`

{* ../../docs_src/first_steps/tutorial001.py hl[1] *}

`FastAPI` is a Python class that provides all the functionality for your API.

/// note | "Technical Details"

        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

      append("\n")
    }
  }
}

internal fun commonHeadersGet(
  namesAndValues: Array<String>,
  name: String,
): String? {
  for (i in namesAndValues.size - 2 downTo 0 step 2) {
    if (name.equals(namesAndValues[i], ignoreCase = true)) {
      return namesAndValues[i + 1]
    }
  }
  return null
}

internal fun Headers.Builder.commonAdd(
  name: String,
  value: String,