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Attention Row Mask Density Tool

Calculate attention row mask density from explicit caller-supplied inputs.

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Description

Return attention-row allowed-mask density.

Attention masks mark which query-to-key relationships are visible. Implementations can use opposite Boolean polarities, so true need not always mean allowed. A mask share depends on the chosen row or head and its denominator; an empty selection has no defined share rather than proving that attention is absent.

Return attention-row allowed-mask density.

When to use this tool

Use Attention Row Mask Density when checking the stated attention coordinate, visibility, angle or head-layout convention.

How to use the tool and how it works

  1. Enter allowed. Use the units and conventions below.
  2. Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
  3. Read allowedCount, density, defined. Inspect defined before interpreting the associated values.

Return attention-row allowed-mask density. allowedCount counts true entries, density = count/length or zero with defined false for empty input.1

Input fieldMeaning and unitsAccepted input
allowedAllowedRequired. Array of boolean; maximum items 256.
Output fieldInterpretationReturned shape
allowedCountAllowed CountRequired. Safe integer.
densityallowedCount/allowed.length, or zero placeholder when defined=false.Required. Finite number.
definedWhether the associated denominator or reporting quantity is defined; inspect before interpreting zero placeholders.Required. Boolean.
json
{
  "input": {
    "allowed": [
      true,
      false,
      true,
      false
    ]
  },
  "output": {
    "allowedCount": 2,
    "density": 0.5,
    "defined": true
  }
}

Limitations and assumptions

  • This counts supplied flags without constructing a mask, applying attention or validating an actual sequence.
  • 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

Inspect the complete model configuration and implementation for positional schedules, masking, softmax and actual inference behavior.

References

  1. Calculation and input contract: artificial-intelligence/attention-row-mask-density — tool.io

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