// once unless the tape is persistent) and produces the gradient of the target
  // tensors with respect to the source tensors. The output gradients are used
  // if not empty and not null. The result is populated with one tensor per
  // target element.
  absl::Status ComputeGradient(
      AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> targets,
      absl::Span<AbstractTensorHandle* const> sources,

  static bool classof(const AbstractTensorHandle* ptr) {
    return ptr->getKind() == kGraph;
  }

 private:
  TF_Graph* graph_;  // For shape inference.
};

// GraphOperation wraps and populates a TF_OperationDescription.
class GraphOperation : public TracingOperation {
 public:
  explicit GraphOperation(TF_Graph* g) : TracingOperation(kGraph), g_(g) {}
  void Release() override { delete this; }

}

// TargetStat is the stats of a single target.
type TargetStat struct {
	CurrentSendCalls int64 // CurrentSendCalls is the number of concurrent async Send calls to all targets
	CurrentQueue     int   // Populated if target has a store.
	TotalEvents      int64
	FailedEvents     int64 // Number of failed events per target
}

// TargetList - holds list of targets indexed by target ID.
type TargetList struct {

## Previous tools

### <a href="https://www.djangoproject.com/" class="external-link" target="_blank">Django</a>

It's the most popular Python framework and is widely trusted. It is used to build systems like Instagram.

        .containsExactly(
            EndpointPair.unordered(2, 1),
            EndpointPair.unordered(1, 1),
            EndpointPair.unordered(1, 3))
        .inOrder();
  }

  /**
   * Populates the graph with nodes and edges in a star shape with node `1` in the middle.
   *
   * <p>Note that the edges are added in a shuffled order to properly test the effect of the
   * insertion order.
   */

## Design

Then I spent some time designing the developer "API" I wanted to have as a user (as a developer using FastAPI).

I tested several ideas in the most popular Python editors: PyCharm, VS Code, Jedi based editors.

labels.failureCountThreshold=Failure Count
labels.fileConfigName=File System Config Name
labels.fileName=File name
labels.handlerName=Handler Name
labels.handlerParameter=Parameters
labels.handlerScript=Scripts
labels.popularWord=Popular words
labels.ignoreFailureType=Ignored Failure Type
labels.lastAccessTime=Last Accessed
labels.notificationTo=Notification To
labels.num=Num
labels.pn=Page Number
labels.protocolScheme=Scheme

                                    "Encountered while creating function '",
                                    fn_name, "'");
    output_tensors->emplace_back(node, idx);
  }
  return absl::OkStatus();
}

// Populates `body_nodes` with the nodes that will become function's body.
// Performs various checks.
absl::Status ComputeBodyNodes(
    const TF_Graph* fn_body, const char* fn_name, int num_opers,
    const TF_Operation* const* opers,

		if err != nil {
			authZLogIf(ctx, err, logger.ErrorKind)
			return ErrMalformedXML
		}

		// Populate payload to extract location constraint.
		r.Body = io.NopCloser(bytes.NewReader(payload))
		region, s3Err = parseLocationConstraint(r)
		if s3Err != ErrNone {
			return s3Err
		}

		// Populate payload again to handle it in HTTP handler.
		r.Body = io.NopCloser(bytes.NewReader(payload))
	}

  private SetMultimap<String, Integer> create() {
    return TreeMultimap.create(StringLength.COMPARATOR, DECREASING_INT_COMPARATOR);
  }

  /** Create and populate a {@code TreeMultimap} with explicit comparators. */
  private TreeMultimap<@Nullable String, @Nullable Integer> createPopulate() {
    TreeMultimap<@Nullable String, @Nullable Integer> multimap =