onnx-ir 0.19.0

ONNX-IR is a pure Rust library for parsing ONNX models into an intermediate representation that can be used to generate code for various ML/DL frameworks
Documentation 
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use crate::ir::{Data, Node};

/// Configuration for Dropout operations
#[derive(Debug, Clone)]
pub struct DropoutConfig {
    /// Probability of dropping out a unit
    pub prob: f64,
}

impl DropoutConfig {
    /// Create a new DropoutConfig
    pub fn new(prob: f64) -> Self {
        Self { prob }
    }
}

/// Create a DropoutConfig from an attribute and state of the node
pub fn dropout_config(node: &Node) -> DropoutConfig {
    // Opset 7 and older store probability as an attribute
    if node.attrs.contains_key("ratio") {
        let prob = node.attrs.get("ratio").unwrap().clone().into_f32();
        return DropoutConfig::new(prob as f64);
    }

    if node.inputs.len() < 2 {
        panic!("Dropout configuration must have at least 2 inputs");
    }

    let ratio = node.inputs[1]
        .value
        .clone()
        .expect("Dropout ratio must be passed in the second input")
        .data
        .into_scalar();

    let prob = match ratio {
        Data::Float16(ratio) => f64::from(f32::from(ratio)),
        Data::Float32(ratio) => ratio as f64,
        Data::Float64(ratio) => ratio,
        _ => panic!("Dropout ratio must be a float"),
    };

    DropoutConfig::new(prob)
}

#[cfg(test)]
mod tests {
    use super::*;
    use crate::ir::NodeType;
    use crate::node::test_utils::NodeBuilder;

    fn create_test_node_with_attr(ratio: f32) -> Node {
        NodeBuilder::new(NodeType::Dropout, "test_dropout")
            .input_tensor_f32("data", 3, None)
            .output_tensor_f32("output", 3, None)
            .attr_float("ratio", ratio)
            .build()
    }

    fn create_test_node_with_input(ratio: f32) -> Node {
        NodeBuilder::new(NodeType::Dropout, "test_dropout")
            .input_tensor_f32("data", 3, None)
            .input_scalar_tensor_f32("ratio", Some(ratio))
            .output_tensor_f32("output", 3, None)
            .build()
    }

    #[test]
    fn test_dropout_config_with_attr() {
        let node = create_test_node_with_attr(0.3);
        let config = dropout_config(&node);
        assert!(f64::abs(config.prob - 0.3) < 1e-6);
    }

    #[test]
    fn test_dropout_config_with_input() {
        let node = create_test_node_with_input(0.5);
        let config = dropout_config(&node);
        assert!(f64::abs(config.prob - 0.5) < 1e-6);
    }

    #[test]
    #[should_panic(expected = "Dropout configuration must have at least 2 inputs")]
    fn test_dropout_config_missing_input() {
        let mut node = create_test_node_with_input(0.5);
        node.attrs.clear(); // Remove attributes
        node.inputs.remove(1); // Remove ratio input
        let _ = dropout_config(&node);
    }
}