}

// NamedEdgeMap contains all unique call edges in the profile and their
// edge weight.
type NamedEdgeMap struct {
	Weight map[NamedCallEdge]int64

	// ByWeight lists all keys in Weight, sorted by edge weight from
	// highest to lowest.
	ByWeight []NamedCallEdge
}

func emptyProfile() *Profile {
	// Initialize empty maps/slices for easier use without a requiring a

    # output shape: [-1, 1024]
    fc1 = gen_mnist_ops.new_fully_connected(reshape, self.weights['f3'],
                                            self.biases['b3'], 'RELU')
    # output shape: [-1, 10]
    return gen_mnist_ops.new_fully_connected(fc1, self.weights['f4'],
                                             self.biases['b4'])


def main(strategy):

	g, err := community.NewUndirectedLayers(friends, enemies)
	if err != nil {
		log.Fatal(err)
	}
	weights := []float64{1, -1}

	// Get the profile of internal node weight for resolutions
	// between 0.1 and 10 using logarithmic bisection.
	p, err := community.Profile(
		community.ModularMultiplexScore(g, weights, true, community.WeightMultiplex, 10, src),
		true, 1e-3, 0.1, 10,
	)
	if err != nil {
		log.Fatal(err)

apiVersion: release-notes/v2
kind: bug-fix
area: traffic-management
issue:
  - 33536
releaseNotes:
  - |

from fastapi import FastAPI

app = FastAPI()


@app.get("/keyword-weights/", response_model=dict[str, float])
async def read_keyword_weights():

	g, err := community.NewUndirectedLayers(friends, enemies)
	if err != nil {
		log.Fatal(err)
	}
	weights := []float64{1, -1}

	// Get the profile of internal node weight for resolutions
	// between 0.1 and 10 using logarithmic bisection.
	p, err := community.Profile(
		community.ModularMultiplexScore(g, weights, true, community.WeightMultiplex, 10, src),
		true, 1e-3, 0.1, 10,
	)
	if err != nil {
		log.Fatal(err)

apiVersion: release-notes/v2
kind: bug-fix
area: networking
issue:
- 28970
releaseNotes:
- |

from typing import Dict

from fastapi import FastAPI

app = FastAPI()


@app.get("/keyword-weights/", response_model=Dict[str, float])
async def read_keyword_weights():

area: traffic-management

releaseNotes:
  - |
    **Updated** Istio's default load balancing algorithm from `ROUND_ROBIN` to `LEAST_REQUEST`.
    The `ROUND_ROBIN` algorithm can lead to overburdened endpoints, especially when weights
    are used. The `LEAST_REQUEST` algorithm, distributes more evenly across and is far less
    likely to overburden endpoints. A number of experiments (by both the Istio and

      "composite_conv.*");

  // Enable per-channel quantization for convolution weights.
  QuantizedType conv_weight_quantized_type{};

  // Assumes NHWC format, specifying the channel dimension (3) as the
  // quantized axis.
  conv_weight_quantized_type.mutable_dimension_specs()->set_dimension(3);

  // The index of weight operands passed to lifted functions for convolution
  // is 1.