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Leaky ReLU Slope Partial Derivative Tool

Return the negative-branch slope-parameter derivative of leaky ReLU, including zero at the origin.

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Description

For leaky ReLU, return x when x<0 and zero otherwise as the partial derivative with respect to the negative-branch slope.

Leaky ReLU uses x on its nonnegative branch and slope*x on its negative branch. A positive nonzero slope gives a single inverse, while a negative slope maps both branches to nonnegative outputs and can give two preimages. Input and slope derivatives differ.

For leaky ReLU, return x when x<0 and zero otherwise as the partial derivative with respect to the negative-branch slope.

When to use this tool

Use Leaky ReLU Slope Partial Derivative when checking the stated leaky-rectifier inverse or slope sensitivity convention.

How to use the tool and how it works

  1. Enter x. 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 derivative. Use the output convention below.

For leaky ReLU, return x when x<0 and zero otherwise as the partial derivative with respect to the negative-branch slope.1

Input fieldMeaning and unitsAccepted input
xFinite scalar input coordinate; use the mathematical scale specified above.Required. Finite number.
Output fieldInterpretationReturned shape
derivativeScalar derivative with respect to the variable and at the fixed coordinates specified above; not a tensor/model gradient.Required. Finite number.
json
{
  "input": {
    "x": -3
  },
  "output": {
    "derivative": -3
  }
}

Limitations and assumptions

  • Input x is fixed; this is not the input derivative or a derivative with respect to an output bias.
  • 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.
  • Numeric calculations use binary floating point unless exact decimal-integer arithmetic is explicitly stated. No hidden measurement tolerance or decimal rounding is added; nonfinite or out-of-contract results are rejected. Numeric signed-zero results are exported as zero.

Alternative or Complementary methods

Use the complete explicit function and the intended parameter, branch and numerical conventions for symbolic, tensor or model-level differentiation; assess training behavior independently.

References

  1. Calculation and input contract: activation/leaky-relu-slope-partial-derivative — tool.io

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