Router Capacity Overflow Term Tool

Description

Return per-expert assigned-load overflow.

Language-model bookkeeping separates scores, probabilities, dimensions, capacity and positional transforms. A local ranking, padding or coordinate operation can illustrate a model component without running a model, sampling a token, fitting calibration or demonstrating output quality.

Return per-expert assigned-load overflow.

When to use this tool

Use Router Capacity Overflow Term when checking the stated model-dimension, ranking, probability-prefix or local transform convention.

How to use the tool and how it works

Enter assigned, capacities. Follow any array-alignment requirements below. Use the units and conventions below.
Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
Read overflow, totalOverflow. Use the output convention below.

Return per-expert assigned-load overflow. Require aligned nonnegative assigned/capacities arrays; overflow[i] = max(0,assigned-capacity), totalOverflow sums it.^[1]

Input field	Meaning and units	Accepted input
assigned	Assigned	Required. Array of safe integer; maximum items 256.
capacities	Capacities	Required. Array of safe integer; maximum items 256.

Output field	Interpretation	Returned shape
overflow	Overflow	Required. Array of safe integer; maximum items 256.
totalOverflow	Total Overflow	Required. Safe integer.

json

{
  "input": {
    "assigned": [
      12,
      8
    ],
    "capacities": [
      10,
      10
    ]
  },
  "output": {
    "overflow": [
      2,
      0
    ],
    "totalOverflow": 2
  }
}

Limitations and assumptions

Assignments and capacities must be nonnegative whole counts; no routing, reassignment, load balancing or actual model execution is provided.
Inputs must satisfy both the field types and the cross-field conditions above. Invalid input causes an error; a successful false flag or documented placeholder is a different result.

Alternative or Complementary methods

Use a complete implementation with verified tensor/token conventions and appropriate model evaluation when actual inference, memory, sampling or quality results are required.

References

Calculation and input contract: artificial-intelligence/router-capacity-overflow-term — tool.io

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