scirs2_autograd/optimization/

constant_folding.rs

//! Constant folding optimization
//!
//! This module implements constant folding, which evaluates expressions with
//! constant operands at compile time rather than runtime.

use super::OptimizationError;
use crate::graph::{Graph, TensorID};
use crate::tensor::TensorInternal;
use crate::Float;
use std::collections::{HashMap, HashSet};

/// Constant folding optimizer
pub struct ConstantFolder<F: Float> {
    /// Cache of constant values
    constant_cache: HashMap<TensorID, F>,
    /// Set of nodes marked as constants
    constant_nodes: HashSet<TensorID>,
}

impl<F: Float> ConstantFolder<F> {
    /// Create a new constant folder
    pub fn new() -> Self {
        Self {
            constant_cache: HashMap::new(),
            constant_nodes: HashSet::new(),
        }
    }

    /// Apply constant folding to a graph
    pub fn fold_constants(&mut self, graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
        let folded_count = 0;

        // Implementation would:
        // 1. Identify all constant nodes (variables with fixed values, literal constants)
        // 2. Propagate constants through the graph
        // 3. Evaluate expressions with all constant inputs
        // 4. Replace the computation subtree with a constant node

        self.mark_constant_nodes(graph)?;
        let _propagated = self.propagate_constants(graph)?;
        let _evaluated = self.evaluate_constant_expressions(graph)?;

        Ok(folded_count)
    }

    /// Mark nodes that represent constants
    fn mark_constant_nodes(&mut self, _graph: &Graph<F>) -> Result<(), OptimizationError> {
        // Traverse the graph and identify:
        // - Literal constant nodes
        // - Variables that are marked as constant
        // - Nodes that only depend on constants

        Ok(())
    }

    /// Propagate constant information through the graph
    fn propagate_constants(&mut self, _graph: &Graph<F>) -> Result<usize, OptimizationError> {
        // For each node:
        // - Check if all inputs are constants
        // - If so, mark this node as a candidate for constant evaluation

        Ok(0)
    }

    /// Evaluate expressions that have all constant inputs
    fn evaluate_constant_expressions(
        &mut self,
        _graph: &mut Graph<F>,
    ) -> Result<usize, OptimizationError> {
        // For each constant expression:
        // - Evaluate it to get the constant result
        // - Replace the expression with a constant node
        // - Update references in the graph

        Ok(0)
    }

    /// Check if a tensor is constant
    pub fn is_constant(&self, tensor_id: TensorID) -> bool {
        self.constant_nodes.contains(&tensor_id)
    }

    /// Get the constant value of a tensor if it's constant
    pub fn get_constant_value(&self, tensor_id: TensorID) -> Option<F> {
        self.constant_cache.get(&tensor_id).copied()
    }

    /// Clear the constant cache
    pub fn clear_cache(&mut self) {
        self.constant_cache.clear();
        self.constant_nodes.clear();
    }
}

impl<F: Float> Default for ConstantFolder<F> {
    fn default() -> Self {
        Self::new()
    }
}

/// Constant value types that can be folded
#[derive(Debug, Clone)]
pub enum ConstantValue<F: Float> {
    /// Scalar constant
    Scalar(F),
    /// Vector constant
    Vector(Vec<F>),
    /// Matrix constant (flattened)
    Matrix { values: Vec<F>, shape: Vec<usize> },
}

impl<F: Float> ConstantValue<F> {
    /// Check if this constant is zero
    pub fn is_zero(&self) -> bool {
        match self {
            ConstantValue::Scalar(x) => x.is_zero(),
            ConstantValue::Vector(v) => v.iter().all(|x| x.is_zero()),
            ConstantValue::Matrix { values, .. } => values.iter().all(|x| x.is_zero()),
        }
    }

    /// Check if this constant is one
    pub fn is_one(&self) -> bool {
        match self {
            ConstantValue::Scalar(x) => *x == F::one(),
            ConstantValue::Vector(v) => v.iter().all(|x| *x == F::one()),
            ConstantValue::Matrix { values, .. } => values.iter().all(|x| *x == F::one()),
        }
    }

    /// Get the shape of this constant
    pub fn shape(&self) -> Vec<usize> {
        match self {
            ConstantValue::Scalar(_) => vec![],
            ConstantValue::Vector(v) => vec![v.len()],
            ConstantValue::Matrix { shape, .. } => shape.clone(),
        }
    }
}

/// Pattern for constants that can enable simplifications
#[derive(Debug, Clone, Copy)]
pub enum ConstantPattern {
    /// Zero constant
    Zero,
    /// One constant
    One,
    /// Negative one constant
    NegativeOne,
    /// Any non-zero constant
    NonZero,
    /// Any finite constant
    Finite,
}

impl ConstantPattern {
    /// Check if a constant value matches this pattern
    pub fn matches<F: Float>(&self, value: &ConstantValue<F>) -> bool {
        match self {
            ConstantPattern::Zero => value.is_zero(),
            ConstantPattern::One => value.is_one(),
            ConstantPattern::NegativeOne => {
                matches!(value, ConstantValue::Scalar(x) if *x == -F::one())
            }
            ConstantPattern::NonZero => !value.is_zero(),
            ConstantPattern::Finite => true, // Assume all our constants are finite
        }
    }
}

/// Utility functions for constant folding
///
/// Check if a tensor represents a literal constant
#[allow(dead_code)]
pub(crate) fn is_literal_constant<F: Float>(_tensor_internal: &TensorInternal<F>) -> bool {
    // Check if this is a constant tensor created from a literal value
    false
}

/// Extract constant value from a tensor if possible
#[allow(dead_code)]
pub(crate) fn extract_constant_value<F: Float>(
    _tensor_internal: &TensorInternal<F>,
) -> Option<ConstantValue<F>> {
    // Try to extract a constant value from various tensor types
    None
}

/// Create a constant tensor with the given value
#[allow(dead_code)]
pub fn create_constant_tensor<F: Float>(
    _graph: &mut Graph<F>,
    _value: ConstantValue<F>,
) -> Result<TensorID, OptimizationError> {
    // Create a new constant tensor in the graph
    Err(OptimizationError::InvalidOperation(
        "Not implemented".to_string(),
    ))
}

/// Arithmetic operations on constant values
impl<F: Float> ConstantValue<F> {
    /// Add two constant values
    pub fn add(&self, other: &Self) -> Result<Self, OptimizationError> {
        match (self, other) {
            (ConstantValue::Scalar(a), ConstantValue::Scalar(b)) => {
                Ok(ConstantValue::Scalar(*a + *b))
            }
            (ConstantValue::Vector(a), ConstantValue::Vector(b)) => {
                if a.len() != b.len() {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Vector length mismatch in add: {} vs {}",
                        a.len(),
                        b.len()
                    )));
                }
                Ok(ConstantValue::Vector(
                    a.iter().zip(b.iter()).map(|(&x, &y)| x + y).collect(),
                ))
            }
            (
                ConstantValue::Matrix {
                    values: a,
                    shape: sa,
                },
                ConstantValue::Matrix {
                    values: b,
                    shape: sb,
                },
            ) => {
                if sa != sb {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Matrix shape mismatch in add: {:?} vs {:?}",
                        sa, sb
                    )));
                }
                Ok(ConstantValue::Matrix {
                    values: a.iter().zip(b.iter()).map(|(&x, &y)| x + y).collect(),
                    shape: sa.clone(),
                })
            }
            _ => Err(OptimizationError::InvalidOperation(
                "Incompatible constant types for addition".to_string(),
            )),
        }
    }

    /// Subtract two constant values
    pub fn sub(&self, other: &Self) -> Result<Self, OptimizationError> {
        match (self, other) {
            (ConstantValue::Scalar(a), ConstantValue::Scalar(b)) => {
                Ok(ConstantValue::Scalar(*a - *b))
            }
            (ConstantValue::Vector(a), ConstantValue::Vector(b)) => {
                if a.len() != b.len() {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Vector length mismatch in sub: {} vs {}",
                        a.len(),
                        b.len()
                    )));
                }
                Ok(ConstantValue::Vector(
                    a.iter().zip(b.iter()).map(|(&x, &y)| x - y).collect(),
                ))
            }
            (
                ConstantValue::Matrix {
                    values: a,
                    shape: sa,
                },
                ConstantValue::Matrix {
                    values: b,
                    shape: sb,
                },
            ) => {
                if sa != sb {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Matrix shape mismatch in sub: {:?} vs {:?}",
                        sa, sb
                    )));
                }
                Ok(ConstantValue::Matrix {
                    values: a.iter().zip(b.iter()).map(|(&x, &y)| x - y).collect(),
                    shape: sa.clone(),
                })
            }
            _ => Err(OptimizationError::InvalidOperation(
                "Incompatible constant types for subtraction".to_string(),
            )),
        }
    }

    /// Multiply two constant values
    pub fn mul(&self, other: &Self) -> Result<Self, OptimizationError> {
        match (self, other) {
            (ConstantValue::Scalar(a), ConstantValue::Scalar(b)) => {
                Ok(ConstantValue::Scalar(*a * *b))
            }
            (ConstantValue::Vector(a), ConstantValue::Vector(b)) => {
                if a.len() != b.len() {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Vector length mismatch in mul: {} vs {}",
                        a.len(),
                        b.len()
                    )));
                }
                Ok(ConstantValue::Vector(
                    a.iter().zip(b.iter()).map(|(&x, &y)| x * y).collect(),
                ))
            }
            (ConstantValue::Scalar(s), ConstantValue::Vector(v))
            | (ConstantValue::Vector(v), ConstantValue::Scalar(s)) => {
                Ok(ConstantValue::Vector(v.iter().map(|&x| x * *s).collect()))
            }
            (ConstantValue::Scalar(s), ConstantValue::Matrix { values, shape })
            | (ConstantValue::Matrix { values, shape }, ConstantValue::Scalar(s)) => {
                Ok(ConstantValue::Matrix {
                    values: values.iter().map(|&x| x * *s).collect(),
                    shape: shape.clone(),
                })
            }
            (
                ConstantValue::Matrix {
                    values: a,
                    shape: sa,
                },
                ConstantValue::Matrix {
                    values: b,
                    shape: sb,
                },
            ) => {
                if sa != sb {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Matrix shape mismatch in mul: {:?} vs {:?}",
                        sa, sb
                    )));
                }
                Ok(ConstantValue::Matrix {
                    values: a.iter().zip(b.iter()).map(|(&x, &y)| x * y).collect(),
                    shape: sa.clone(),
                })
            }
            (ConstantValue::Vector(_), ConstantValue::Matrix { .. })
            | (ConstantValue::Matrix { .. }, ConstantValue::Vector(_)) => {
                Err(OptimizationError::InvalidOperation(
                    "Incompatible constant types for multiplication (Vector vs Matrix)".to_string(),
                ))
            }
        }
    }

    /// Divide two constant values
    pub fn div(&self, other: &Self) -> Result<Self, OptimizationError> {
        match (self, other) {
            (ConstantValue::Scalar(a), ConstantValue::Scalar(b)) => {
                if b.is_zero() {
                    return Err(OptimizationError::InvalidOperation(
                        "Division by zero".to_string(),
                    ));
                }
                Ok(ConstantValue::Scalar(*a / *b))
            }
            (ConstantValue::Vector(a), ConstantValue::Vector(b)) => {
                if a.len() != b.len() {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Vector length mismatch in div: {} vs {}",
                        a.len(),
                        b.len()
                    )));
                }
                if b.iter().any(|x| x.is_zero()) {
                    return Err(OptimizationError::InvalidOperation(
                        "Division by zero in vector".to_string(),
                    ));
                }
                Ok(ConstantValue::Vector(
                    a.iter().zip(b.iter()).map(|(&x, &y)| x / y).collect(),
                ))
            }
            (ConstantValue::Vector(v), ConstantValue::Scalar(s)) => {
                if s.is_zero() {
                    return Err(OptimizationError::InvalidOperation(
                        "Division by zero".to_string(),
                    ));
                }
                Ok(ConstantValue::Vector(v.iter().map(|&x| x / *s).collect()))
            }
            (ConstantValue::Matrix { values, shape }, ConstantValue::Scalar(s)) => {
                if s.is_zero() {
                    return Err(OptimizationError::InvalidOperation(
                        "Division by zero".to_string(),
                    ));
                }
                Ok(ConstantValue::Matrix {
                    values: values.iter().map(|&x| x / *s).collect(),
                    shape: shape.clone(),
                })
            }
            (
                ConstantValue::Matrix {
                    values: a,
                    shape: sa,
                },
                ConstantValue::Matrix {
                    values: b,
                    shape: sb,
                },
            ) => {
                if sa != sb {
                    return Err(OptimizationError::InvalidOperation(format!(
                        "Matrix shape mismatch in div: {:?} vs {:?}",
                        sa, sb
                    )));
                }
                if b.iter().any(|x| x.is_zero()) {
                    return Err(OptimizationError::InvalidOperation(
                        "Division by zero in matrix".to_string(),
                    ));
                }
                Ok(ConstantValue::Matrix {
                    values: a.iter().zip(b.iter()).map(|(&x, &y)| x / y).collect(),
                    shape: sa.clone(),
                })
            }
            (ConstantValue::Scalar(_), ConstantValue::Vector(_))
            | (ConstantValue::Scalar(_), ConstantValue::Matrix { .. })
            | (ConstantValue::Vector(_), ConstantValue::Matrix { .. })
            | (ConstantValue::Matrix { .. }, ConstantValue::Vector(_)) => {
                Err(OptimizationError::InvalidOperation(
                    "Incompatible constant types for division".to_string(),
                ))
            }
        }
    }

    /// Negate a constant value
    pub fn neg(&self) -> Result<Self, OptimizationError> {
        match self {
            ConstantValue::Scalar(x) => Ok(ConstantValue::Scalar(-*x)),
            ConstantValue::Vector(v) => Ok(ConstantValue::Vector(v.iter().map(|x| -*x).collect())),
            ConstantValue::Matrix { values, shape } => Ok(ConstantValue::Matrix {
                values: values.iter().map(|x| -*x).collect(),
                shape: shape.clone(),
            }),
        }
    }

    /// Apply a unary function to a constant value
    pub fn apply_unary<Func>(&self, func: Func) -> Result<Self, OptimizationError>
    where
        Func: Fn(F) -> F,
    {
        match self {
            ConstantValue::Scalar(x) => Ok(ConstantValue::Scalar(func(*x))),
            ConstantValue::Vector(v) => {
                Ok(ConstantValue::Vector(v.iter().map(|x| func(*x)).collect()))
            }
            ConstantValue::Matrix { values, shape } => Ok(ConstantValue::Matrix {
                values: values.iter().map(|x| func(*x)).collect(),
                shape: shape.clone(),
            }),
        }
    }
}

#[cfg(test)]
mod tests {
    use super::*;

    #[test]
    fn test_constant_folder_creation() {
        let _folder = ConstantFolder::<f32>::new();
    }

    #[test]
    fn test_constant_value_creation() {
        let scalar = ConstantValue::Scalar(42.0f32);
        assert_eq!(scalar.shape(), Vec::<usize>::new());

        let vector = ConstantValue::Vector(vec![1.0, 2.0, 3.0]);
        assert_eq!(vector.shape(), vec![3]);

        let matrix = ConstantValue::Matrix {
            values: vec![1.0, 2.0, 3.0, 4.0],
            shape: vec![2, 2],
        };
        assert_eq!(matrix.shape(), vec![2, 2]);
    }

    #[test]
    fn test_constant_patterns() {
        let zero = ConstantValue::Scalar(0.0f32);
        let one = ConstantValue::Scalar(1.0f32);
        let neg_one = ConstantValue::Scalar(-1.0f32);
        let other = ConstantValue::Scalar(42.0f32);

        assert!(ConstantPattern::Zero.matches(&zero));
        assert!(!ConstantPattern::Zero.matches(&one));

        assert!(ConstantPattern::One.matches(&one));
        assert!(!ConstantPattern::One.matches(&zero));

        assert!(ConstantPattern::NegativeOne.matches(&neg_one));
        assert!(!ConstantPattern::NegativeOne.matches(&one));

        assert!(ConstantPattern::NonZero.matches(&other));
        assert!(!ConstantPattern::NonZero.matches(&zero));

        assert!(ConstantPattern::Finite.matches(&other));
    }

    #[test]
    fn test_constant_value_properties() {
        let zero = ConstantValue::Scalar(0.0f32);
        let one = ConstantValue::Scalar(1.0f32);
        let other = ConstantValue::Scalar(42.0f32);

        assert!(zero.is_zero());
        assert!(!one.is_zero());
        assert!(!other.is_zero());

        assert!(one.is_one());
        assert!(!zero.is_one());
        assert!(!other.is_one());
    }

    #[test]
    fn test_constant_value_negation() {
        let positive = ConstantValue::Scalar(42.0f32);
        let negative = positive.neg().expect("Operation failed");

        if let ConstantValue::Scalar(val) = negative {
            assert_eq!(val, -42.0);
        } else {
            panic!("Expected scalar result");
        }
    }

    #[test]
    fn test_constant_value_unary_function() {
        let value = ConstantValue::Scalar(4.0f32);
        let sqrt_value = value.apply_unary(|x| x.sqrt()).expect("Operation failed");

        if let ConstantValue::Scalar(val) = sqrt_value {
            assert_eq!(val, 2.0);
        } else {
            panic!("Expected scalar result");
        }
    }
}