invoke-ai/InvokeAI · error · ValueError

Cannot divide by zero

Error message

Cannot divide by zero

What it means

The IntegerMathInvocation's pydantic field_validator no_unrepresentable_results validates operand b before invoke. When operation == 'DIV' and b == 0, raising ValueError('Cannot divide by zero') prevents an unrepresentable ZeroDivisionError at invoke time. Pydantic surfaces this as a field validation error when the invocation node is created.

Source

Thrown at invokeai/app/invocations/math.py:192

        "min",
        "max",
    ],
    category="math",
    version="1.0.1",
)
class IntegerMathInvocation(BaseInvocation):
    """Performs integer math."""

    operation: INTEGER_OPERATIONS = InputField(
        default="ADD", description="The operation to perform", ui_choice_labels=INTEGER_OPERATIONS_LABELS
    )
    a: int = InputField(default=1, description=FieldDescriptions.num_1)
    b: int = InputField(default=1, description=FieldDescriptions.num_2)

    @field_validator("b")
    def no_unrepresentable_results(cls, v: int, info: ValidationInfo):
        if info.data["operation"] == "DIV" and v == 0:
            raise ValueError("Cannot divide by zero")
        elif info.data["operation"] == "MOD" and v == 0:
            raise ValueError("Cannot divide by zero")
        elif info.data["operation"] == "EXP" and v < 0:
            raise ValueError("Result of exponentiation is not an integer")
        return v

    def invoke(self, context: InvocationContext) -> IntegerOutput:
        # Python doesn't support switch statements until 3.10, but InvokeAI supports back to 3.9
        if self.operation == "ADD":
            return IntegerOutput(value=self.a + self.b)
        elif self.operation == "SUB":
            return IntegerOutput(value=self.a - self.b)
        elif self.operation == "MUL":
            return IntegerOutput(value=self.a * self.b)
        elif self.operation == "DIV":
            return IntegerOutput(value=int(self.a / self.b))
        elif self.operation == "EXP":
            return IntegerOutput(value=self.a**self.b)

View on GitHub (pinned to 0b6a024f2f)

Solutions

1. Set the b input on the IntegerMathInvocation node to a non-zero value
2. If b is wired from another node, add a guard node to clamp the value before division
3. Catch the pydantic ValidationError at graph-submit time and show a clear message in your client

Example fix

// before
node = IntegerMathInvocation(a=10, b=0, operation="DIV")
// after
node = IntegerMathInvocation(a=10, b=2, operation="DIV")

if operation == "DIV" and b == 0:
    raise ValueError("Cannot divide by zero: fix the b input before queueing")

def is_safe_divisor(b: int) -> bool:
    return b != 0

try:
    graph.validate()
    session = api.queue(graph)
except ValidationError as e:
    if "Cannot divide by zero" in str(e):
        node.b = 1
        session = api.queue(graph)
    else:
        raise

When it happens

Trigger: Creating/enqueueing an IntegerMathInvocation with operation='DIV' and b=0 (e.g. default b never changed, or a prior node output wired in as 0).

Common situations: Workflows where a division node's b input is fed by another node whose value happens to be 0 at run time; users forgetting to set the b input from its default then switching operation to DIV.

Related errors

• cfg_scale values must be finite.
• shift must be finite.
• source_url must be a string
• source_url must be an http or https URL
• unknown override field: {field_name}

AI-assisted analysis of invoke-ai/InvokeAI@0b6a024f2f (2026-08-29). Data as JSON: /api/errors/8d7906dcfe18e51a. Report an issue: GitHub.