# Writing Custom Providers

Create custom diagnostics providers by subclassing `DiagnosticsProvider`.

## Example

```python
import onnx_ir as ir
import onnx_doctor
from onnx_doctor import Rule

MY_RULE = Rule(
    code="CUSTOM001",
    name="large-model",
    message="Model has more than 1000 nodes.",
    default_severity="warning",
    category="spec",
    target_type="graph",
    suggestion="Consider optimizing or splitting the model.",
)

class MyProvider(onnx_doctor.DiagnosticsProvider):
    def check_graph(self, graph: ir.Graph):
        node_count = sum(1 for _ in graph)
        if node_count > 1000:
            yield onnx_doctor.DiagnosticsMessage(
                target_type="graph",
                target=graph,
                message=f"Graph has {node_count} nodes.",
                severity=MY_RULE.default_severity,
                producer="MyProvider",
                error_code=MY_RULE.code,
                rule=MY_RULE,
            )

# Use it
model = ir.load("model.onnx")
messages = onnx_doctor.diagnose(model, [MyProvider()])
```

## Available Check Methods

Override any of these methods in your provider:

- `check_model(model)` — Called once per model.
- `check_graph(graph)` — Called for each graph.
- `check_function(function)` — Called for each function.
- `check_node(node)` — Called for each node.
- `check_value(value)` — Called for each value.
- `check_tensor(tensor)` — Called for each tensor.
- `check_attribute(attribute)` — Called for each attribute.