Description
Return min(6,max(0,x)), clipping the scalar input into the closed interval [0,6].
ReLU clips negative input to zero; ReLU6 also clips above six. Saturated outputs have entire input rays as preimages, unlike interior values with single inverses. At a ReLU kink a selected subgradient is not an ordinary two-sided derivative.
Return min(6,max(0,x)), clipping the scalar input into the closed interval [0,6].
When to use this tool
Use Activation: ReLU6 Scalar Value when checking the stated rectifier value, inverse region or subgradient convention.
How to use the tool and how it works
- Enter x. Use the units and conventions below.
- Run the tool. Correct any format, range, or cross-field input error before interpreting the output.
- Read result. Expand result to inspect the returned fields.
Return min(6,max(0,x)), clipping the scalar input into the closed interval [0,6].1
| Input field | Meaning and units | Accepted input |
|---|---|---|
| x | Finite scalar input coordinate; use the mathematical scale specified above. | Required. Finite number. |
| Output field | Interpretation | Returned shape |
|---|---|---|
| result | Object containing the operation-specific returned members listed below. | Required. Object. |
| result.value | Value | Calculated result member: number. |
{
"input": {
"x": 8
},
"output": {
"result": {
"value": 6
}
}
}Limitations and assumptions
- This is a value calculation; derivative choices at zero/six, tensor execution and quantization are not implemented.
- Outputs are nested inside result. 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
Similar or alternative tools
- ReLU6 Output Preimage Interval
Return lower=upper=output with unbounded flags at zero/six; interior outputs have singleton=true.
- ReLU Zero Subgradient Choice
Return slope one for positive x, zero for negative x and the supplied slope at zero; flag x=0 as nondifferentiable.