To Bool¶
Converts an incoming value to a boolean. Tensors are treated as False only if all elements are zero; otherwise True. An optional invert flag flips the final result.
Usage¶
Use this node when you need a boolean signal from any prior output to drive logic branches or condition checks. Typical workflows include validating non-empty strings, non-zero numbers, or non-all-zero tensors before routing execution.
Inputs¶
| Field | Required | Type | Description | Example |
|---|---|---|---|---|
| value | True | WILDCARD | Any input value to evaluate as a boolean. For tensors, the result is False if all elements are zero, otherwise True. For other types, standard truthiness is used. | A tensor, number, string, list, or any object |
| invert | False | BOOLEAN | If True, inverts the computed boolean result. | False |
Outputs¶
| Field | Type | Description | Example |
|---|---|---|---|
| result | BOOLEAN | The computed boolean value after optional inversion. | True |
Important Notes¶
- Tensors are considered False only when both their max and min are 0 (i.e., all elements are zero). Any non-zero element makes it True.
- Non-tensor values use normal truthiness rules (e.g., empty string/list -> False; non-empty -> True; zero -> False; non-zero -> True).
- If the node cannot convert a non-tensor value to bool due to a ValueError or TypeError, it defaults to True.
- Any unexpected runtime error during processing results in False.
- Setting invert to True flips the final boolean outcome.
Troubleshooting¶
- Result is False for a tensor you expected to be True: Ensure the tensor contains at least one non-zero element. All-zero tensors evaluate to False.
- Result is unexpectedly True for a custom object: If the object's boolean conversion raises an error, the node defaults to True. Implement a bool method or provide a different input type.
- Result is False due to an internal error: Check upstream inputs for invalid or unsupported values (e.g., tensors with problematic states). The node returns False on unhandled exceptions.
- Performance concerns with very large tensors: The check uses min/max; if performance is an issue, consider pre-reducing or summarizing the tensor before this node.