return grads;
}

std::vector<string> GetFuncNames(const tensorflow::GraphDef& graph_def) {
  std::vector<string> names;
  auto functions = graph_def.library().function();
  names.reserve(functions.size());
  for (const tensorflow::FunctionDef& func : functions) {
    names.push_back(func.signature().name());
  }
  std::sort(names.begin(), names.end());
  return names;
}

package clusters

import (
	admin "github.com/envoyproxy/go-control-plane/envoy/admin/v3"

	"istio.io/istio/pkg/util/protomarshal"
)

// Wrapper is a wrapper around the Envoy Clusters
// It has extra helper functions for handling any/struct/marshal protobuf pain
type Wrapper struct {
	*admin.Clusters
}

// MarshalJSON is a custom marshaller to handle protobuf pain
func (w *Wrapper) MarshalJSON() ([]byte, error) {

We are not restricted to having only one dependency that can return that type of data.

///

## Other models

You can now get the current user directly in the *path operation functions* and deal with the security mechanisms at the **Dependency Injection** level, using `Depends`.

And you can use any model or data for the security requirements (in this case, a Pydantic model `User`).

#include "tensorflow/c/experimental/ops/math_ops.h"
#include "tensorflow/c/tf_tensor.h"

namespace tensorflow {
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) {

    assertThrows(
        NullPointerException.class,
        () -> Multimaps.index((List<Integer>) values, Functions.identity()));
  }

  public void testIndex_nullKey() {
    List<Integer> values = Arrays.asList(1, 2);
    assertThrows(
        NullPointerException.class, () -> Multimaps.index(values, Functions.constant(null)));
  }

  @GwtIncompatible(value = "untested")
  public void testTransformValues() {

  // it in this context.
  virtual AbstractOperation* CreateOperation() = 0;

  // Registers a function with this context, after this the function is
  // available to be called/referenced by its name in this context.
  virtual absl::Status RegisterFunction(AbstractFunction*) = 0;
  // Remove a function. 'func' argument is the name of a previously added
  // FunctionDef. The name is in fdef.signature.name.

and the called function begins execution.
The return parameters of the function are passed by value
back to the caller when the function returns.
</p>

<p>
Calling a <code>nil</code> function value
causes a <a href="#Run_time_panics">run-time panic</a>.
</p>

<p>
As a special case, if the return values of a function or method

{* ../../docs_src/custom_docs_ui/tutorial001.py hl[8] *}

### Include the custom docs

Now you can create the *path operations* for the custom docs.

You can reuse FastAPI's internal functions to create the HTML pages for the docs, and pass them the needed arguments:

* `openapi_url`: the URL where the HTML page for the docs can get the OpenAPI schema for your API. You can use here the attribute `app.openapi_url`.

// aggregation.
//
// Aggregation functions - An expression that involves aggregation of
// rows in some manner. Requires all input rows to be processed,
// before a result is returned.
//
// Row function - An expression that depends on a value in the
// row. They have an output for each input row.
//
// Some types of a queries are not valid. For example, an aggregation

/// note | "Technical Details"

When you import `Query`, `Path` and others from `fastapi`, they are actually functions.

That when called, return instances of classes of the same name.

So, you import `Query`, which is a function. And when you call it, it returns an instance of a class also named `Query`.

These functions are there (instead of just using the classes directly) so that your editor doesn't mark errors about their types.