torsh-jit 0.1.3

//! Compile-Time Evaluation for ToRSh JIT
//!
//! This module implements compile-time evaluation of constant expressions and
//! computations, enabling optimizations that reduce runtime overhead.

use crate::{ComputationGraph, JitError, JitResult, Node, NodeId};
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::{Arc, RwLock};

/// Compile-time evaluation manager
pub struct ConstantEvaluator {
    config: ConstEvalConfig,
    constant_cache: Arc<RwLock<HashMap<NodeId, ConstantValue>>>,
    evaluation_context: EvaluationContext,
}

/// Configuration for constant evaluation
#[derive(Debug, Clone)]
pub struct ConstEvalConfig {
    /// Enable constant folding
    pub enable_constant_folding: bool,

    /// Enable dead code elimination based on constants
    pub enable_dead_code_elimination: bool,

    /// Enable branch elimination for constant conditions
    pub enable_branch_elimination: bool,

    /// Enable loop unrolling for constant iterations
    pub enable_loop_unrolling: bool,

    /// Maximum computation steps for constant evaluation
    pub max_evaluation_steps: usize,

    /// Maximum memory usage for constant evaluation
    pub max_memory_usage: usize,

    /// Enable aggressive constant propagation
    pub enable_aggressive_propagation: bool,

    /// Maximum depth for recursive constant evaluation
    pub max_recursion_depth: usize,

    /// Cache size for evaluated constants
    pub cache_size: usize,
}

impl Default for ConstEvalConfig {
    fn default() -> Self {
        Self {
            enable_constant_folding: true,
            enable_dead_code_elimination: true,
            enable_branch_elimination: true,
            enable_loop_unrolling: true,
            max_evaluation_steps: 10000,
            max_memory_usage: 64 * 1024 * 1024, // 64MB
            enable_aggressive_propagation: false,
            max_recursion_depth: 100,
            cache_size: 1000,
        }
    }
}

/// Compile-time constant value
#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
pub enum ConstantValue {
    /// Boolean constant
    Bool(bool),

    /// Integer constant
    Int(i64),

    /// Unsigned integer constant
    UInt(u64),

    /// Floating point constant
    Float(f64),

    /// String constant
    String(String),

    /// Array of constants
    Array(Vec<ConstantValue>),

    /// Tensor constant with shape and data
    Tensor {
        shape: Vec<usize>,
        data: Vec<f64>,
        dtype: String,
    },

    /// Complex constant
    Complex { real: f64, imag: f64 },

    /// None/null constant
    None,

    /// Undefined value (cannot be evaluated at compile time)
    Undefined,
}

/// Evaluation context for compile-time computation
#[derive(Debug, Clone)]
pub struct EvaluationContext {
    /// Variable bindings
    variables: HashMap<String, ConstantValue>,

    /// Function definitions
    functions: HashMap<String, FunctionDefinition>,

    /// Current evaluation depth
    depth: usize,

    /// Number of evaluation steps taken
    steps: usize,

    /// Memory usage in bytes
    memory_usage: usize,
}

/// Compile-time function definition
#[derive(Debug, Clone)]
pub struct FunctionDefinition {
    pub name: String,
    pub parameters: Vec<String>,
    pub body: Vec<Instruction>,
    pub return_type: Option<String>,
}

/// Instructions that can be evaluated at compile time
#[derive(Debug, Clone)]
pub enum Instruction {
    /// Load constant value
    LoadConstant(ConstantValue),

    /// Load variable
    LoadVariable(String),

    /// Store to variable
    Store(String),

    /// Binary operation
    BinaryOp {
        op: BinaryOperator,
        left: Box<Instruction>,
        right: Box<Instruction>,
    },

    /// Unary operation
    UnaryOp {
        op: UnaryOperator,
        operand: Box<Instruction>,
    },

    /// Function call
    Call {
        function: String,
        args: Vec<Instruction>,
    },

    /// Conditional expression
    Conditional {
        condition: Box<Instruction>,
        then_branch: Box<Instruction>,
        else_branch: Box<Instruction>,
    },

    /// Loop expression
    Loop {
        condition: Box<Instruction>,
        body: Vec<Instruction>,
        max_iterations: Option<usize>,
    },

    /// Array indexing
    Index {
        array: Box<Instruction>,
        index: Box<Instruction>,
    },

    /// Array construction
    Array(Vec<Instruction>),

    /// Tensor construction
    Tensor {
        shape: Vec<usize>,
        data: Vec<Instruction>,
    },
}

/// Binary operators
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum BinaryOperator {
    Add,
    Sub,
    Mul,
    Div,
    Mod,
    Pow,
    And,
    Or,
    Xor,
    Lt,
    Le,
    Gt,
    Ge,
    Eq,
    Ne,
    BitAnd,
    BitOr,
    BitXor,
    Shl,
    Shr,
}

/// Unary operators
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum UnaryOperator {
    Neg,
    Not,
    BitNot,
    Abs,
    Sin,
    Cos,
    Tan,
    Log,
    Exp,
    Sqrt,
    Floor,
    Ceil,
    Round,
}

/// Result of constant evaluation
#[derive(Debug, Clone)]
pub struct EvaluationResult {
    pub constants_found: Vec<(NodeId, ConstantValue)>,
    pub dead_code_nodes: Vec<NodeId>,
    pub eliminable_branches: Vec<NodeId>,
    pub unrollable_loops: Vec<(NodeId, usize)>,
    pub propagation_opportunities: Vec<PropagationOpportunity>,
}

/// Constant propagation opportunity
#[derive(Debug, Clone)]
pub struct PropagationOpportunity {
    pub from_node: NodeId,
    pub to_nodes: Vec<NodeId>,
    pub constant_value: ConstantValue,
    pub estimated_benefit: f64,
}

impl ConstantEvaluator {
    /// Create a new constant evaluator
    pub fn new(config: ConstEvalConfig) -> Self {
        Self {
            config,
            constant_cache: Arc::new(RwLock::new(HashMap::new())),
            evaluation_context: EvaluationContext::new(),
        }
    }

    /// Evaluate constants in a computation graph
    pub fn evaluate_constants(&mut self, graph: &ComputationGraph) -> JitResult<EvaluationResult> {
        let mut result = EvaluationResult {
            constants_found: Vec::new(),
            dead_code_nodes: Vec::new(),
            eliminable_branches: Vec::new(),
            unrollable_loops: Vec::new(),
            propagation_opportunities: Vec::new(),
        };

        // Reset evaluation context
        self.evaluation_context.reset();

        // Topological sort to evaluate nodes in dependency order
        let sorted_nodes = graph
            .topological_sort()
            .map_err(|e| JitError::CompilationError(format!("{:?}", e)))?;

        for node_id in sorted_nodes {
            if let Some(node) = graph.node(node_id) {
                // Try to evaluate node as constant
                if let Some(constant_value) = self.try_evaluate_node(node, node_id)? {
                    result
                        .constants_found
                        .push((node_id, constant_value.clone()));

                    // Cache the constant value
                    if let Ok(mut cache) = self.constant_cache.write() {
                        cache.insert(node_id, constant_value.clone());
                    }

                    // Check for propagation opportunities
                    result.propagation_opportunities.extend(
                        self.analyze_propagation_opportunities(graph, node_id, &constant_value)?,
                    );
                }

                // Check for dead code
                if self.is_dead_code(node)? {
                    result.dead_code_nodes.push(node_id);
                }

                // Check for eliminable branches
                if self.is_eliminable_branch(node)? {
                    result.eliminable_branches.push(node_id);
                }

                // Check for unrollable loops
                if let Some(iterations) = self.get_unroll_count(node)? {
                    result.unrollable_loops.push((node_id, iterations));
                }
            }
        }

        Ok(result)
    }

    /// Apply constant evaluation optimizations to the graph
    pub fn apply_optimizations(
        &self,
        graph: &mut ComputationGraph,
        result: &EvaluationResult,
    ) -> JitResult<usize> {
        let mut optimizations_applied = 0;

        // Apply constant folding
        if self.config.enable_constant_folding {
            optimizations_applied += self.apply_constant_folding(graph, &result.constants_found)?;
        }

        // Apply dead code elimination
        if self.config.enable_dead_code_elimination {
            optimizations_applied +=
                self.apply_dead_code_elimination(graph, &result.dead_code_nodes)?;
        }

        // Apply branch elimination
        if self.config.enable_branch_elimination {
            optimizations_applied +=
                self.apply_branch_elimination(graph, &result.eliminable_branches)?;
        }

        // Apply loop unrolling
        if self.config.enable_loop_unrolling {
            optimizations_applied += self.apply_loop_unrolling(graph, &result.unrollable_loops)?;
        }

        // Apply constant propagation
        if self.config.enable_aggressive_propagation {
            optimizations_applied +=
                self.apply_constant_propagation(graph, &result.propagation_opportunities)?;
        }

        Ok(optimizations_applied)
    }

    /// Try to evaluate a node as a constant
    fn try_evaluate_node(
        &mut self,
        node: &Node,
        node_id: NodeId,
    ) -> JitResult<Option<ConstantValue>> {
        // Check if already cached
        if let Ok(cache) = self.constant_cache.read() {
            if let Some(cached_value) = cache.get(&node_id) {
                return Ok(Some(cached_value.clone()));
            }
        }

        // Check evaluation limits
        if self.evaluation_context.steps >= self.config.max_evaluation_steps {
            return Ok(None);
        }

        if self.evaluation_context.depth >= self.config.max_recursion_depth {
            return Ok(None);
        }

        if self.evaluation_context.memory_usage >= self.config.max_memory_usage {
            return Ok(None);
        }

        self.evaluation_context.steps += 1;
        self.evaluation_context.depth += 1;

        let result = match node.operation_type() {
            "constant" => self.evaluate_constant_node(node),
            "add" => self.evaluate_binary_op(node, BinaryOperator::Add),
            "sub" => self.evaluate_binary_op(node, BinaryOperator::Sub),
            "mul" => self.evaluate_binary_op(node, BinaryOperator::Mul),
            "div" => self.evaluate_binary_op(node, BinaryOperator::Div),
            "pow" => self.evaluate_binary_op(node, BinaryOperator::Pow),
            "neg" => self.evaluate_unary_op(node, UnaryOperator::Neg),
            "abs" => self.evaluate_unary_op(node, UnaryOperator::Abs),
            "sin" => self.evaluate_unary_op(node, UnaryOperator::Sin),
            "cos" => self.evaluate_unary_op(node, UnaryOperator::Cos),
            "exp" => self.evaluate_unary_op(node, UnaryOperator::Exp),
            "log" => self.evaluate_unary_op(node, UnaryOperator::Log),
            "sqrt" => self.evaluate_unary_op(node, UnaryOperator::Sqrt),
            _ => Ok(None), // Cannot evaluate at compile time
        };

        self.evaluation_context.depth -= 1;
        result
    }

    fn evaluate_constant_node(&self, node: &Node) -> JitResult<Option<ConstantValue>> {
        if let Some(value_attr) = node.get_attribute("value") {
            let value_str = match value_attr {
                crate::graph::Attribute::String(s) => s,
                crate::graph::Attribute::Int(i) => return Ok(Some(ConstantValue::Int(*i))),
                crate::graph::Attribute::Float(f) => return Ok(Some(ConstantValue::Float(*f))),
                crate::graph::Attribute::Bool(b) => return Ok(Some(ConstantValue::Bool(*b))),
                _ => return Ok(None),
            };

            // Try to parse as different types
            if value_str == "true" {
                Ok(Some(ConstantValue::Bool(true)))
            } else if value_str == "false" {
                Ok(Some(ConstantValue::Bool(false)))
            } else if let Ok(int_val) = value_str.parse::<i64>() {
                Ok(Some(ConstantValue::Int(int_val)))
            } else if let Ok(float_val) = value_str.parse::<f64>() {
                Ok(Some(ConstantValue::Float(float_val)))
            } else {
                Ok(Some(ConstantValue::String(value_str.clone())))
            }
        } else {
            Ok(None)
        }
    }

    fn evaluate_binary_op(
        &mut self,
        _node: &Node,
        _op: BinaryOperator,
    ) -> JitResult<Option<ConstantValue>> {
        // Placeholder implementation - in a real system, this would
        // evaluate constant binary operations by looking up input node values
        Ok(None)
    }

    fn evaluate_unary_op(
        &mut self,
        _node: &Node,
        _op: UnaryOperator,
    ) -> JitResult<Option<ConstantValue>> {
        // Placeholder implementation - in a real system, this would
        // evaluate constant unary operations by looking up input node values
        Ok(None)
    }

    fn apply_binary_operation(
        &self,
        op: BinaryOperator,
        left: &ConstantValue,
        right: &ConstantValue,
    ) -> JitResult<Option<ConstantValue>> {
        match (left, right) {
            (ConstantValue::Int(a), ConstantValue::Int(b)) => {
                let result = match op {
                    BinaryOperator::Add => ConstantValue::Int(a + b),
                    BinaryOperator::Sub => ConstantValue::Int(a - b),
                    BinaryOperator::Mul => ConstantValue::Int(a * b),
                    BinaryOperator::Div => {
                        if *b != 0 {
                            ConstantValue::Int(a / b)
                        } else {
                            return Ok(None); // Division by zero
                        }
                    }
                    BinaryOperator::Mod => {
                        if *b != 0 {
                            ConstantValue::Int(a % b)
                        } else {
                            return Ok(None); // Modulo by zero
                        }
                    }
                    BinaryOperator::Pow => ConstantValue::Float((*a as f64).powf(*b as f64)),
                    BinaryOperator::Lt => ConstantValue::Bool(a < b),
                    BinaryOperator::Le => ConstantValue::Bool(a <= b),
                    BinaryOperator::Gt => ConstantValue::Bool(a > b),
                    BinaryOperator::Ge => ConstantValue::Bool(a >= b),
                    BinaryOperator::Eq => ConstantValue::Bool(a == b),
                    BinaryOperator::Ne => ConstantValue::Bool(a != b),
                    BinaryOperator::BitAnd => ConstantValue::Int(a & b),
                    BinaryOperator::BitOr => ConstantValue::Int(a | b),
                    BinaryOperator::BitXor => ConstantValue::Int(a ^ b),
                    _ => return Ok(None),
                };
                Ok(Some(result))
            }
            (ConstantValue::Float(a), ConstantValue::Float(b)) => {
                let result = match op {
                    BinaryOperator::Add => ConstantValue::Float(a + b),
                    BinaryOperator::Sub => ConstantValue::Float(a - b),
                    BinaryOperator::Mul => ConstantValue::Float(a * b),
                    BinaryOperator::Div => {
                        if *b != 0.0 {
                            ConstantValue::Float(a / b)
                        } else {
                            return Ok(None); // Division by zero
                        }
                    }
                    BinaryOperator::Pow => ConstantValue::Float(a.powf(*b)),
                    BinaryOperator::Lt => ConstantValue::Bool(a < b),
                    BinaryOperator::Le => ConstantValue::Bool(a <= b),
                    BinaryOperator::Gt => ConstantValue::Bool(a > b),
                    BinaryOperator::Ge => ConstantValue::Bool(a >= b),
                    BinaryOperator::Eq => ConstantValue::Bool((a - b).abs() < f64::EPSILON),
                    BinaryOperator::Ne => ConstantValue::Bool((a - b).abs() >= f64::EPSILON),
                    _ => return Ok(None),
                };
                Ok(Some(result))
            }
            (ConstantValue::Bool(a), ConstantValue::Bool(b)) => {
                let result = match op {
                    BinaryOperator::And => ConstantValue::Bool(*a && *b),
                    BinaryOperator::Or => ConstantValue::Bool(*a || *b),
                    BinaryOperator::Xor => ConstantValue::Bool(*a ^ *b),
                    BinaryOperator::Eq => ConstantValue::Bool(a == b),
                    BinaryOperator::Ne => ConstantValue::Bool(a != b),
                    _ => return Ok(None),
                };
                Ok(Some(result))
            }
            // Mixed type operations (int and float)
            (ConstantValue::Int(a), ConstantValue::Float(_b)) => {
                self.apply_binary_operation(op, &ConstantValue::Float(*a as f64), right)
            }
            (ConstantValue::Float(_a), ConstantValue::Int(b)) => {
                self.apply_binary_operation(op, left, &ConstantValue::Float(*b as f64))
            }
            _ => Ok(None), // Unsupported combination
        }
    }

    fn apply_unary_operation(
        &self,
        op: UnaryOperator,
        value: &ConstantValue,
    ) -> JitResult<Option<ConstantValue>> {
        match value {
            ConstantValue::Int(a) => {
                let result = match op {
                    UnaryOperator::Neg => ConstantValue::Int(-a),
                    UnaryOperator::Abs => ConstantValue::Int(a.abs()),
                    UnaryOperator::BitNot => ConstantValue::Int(!a),
                    _ => return Ok(None),
                };
                Ok(Some(result))
            }
            ConstantValue::Float(a) => {
                let result = match op {
                    UnaryOperator::Neg => ConstantValue::Float(-a),
                    UnaryOperator::Abs => ConstantValue::Float(a.abs()),
                    UnaryOperator::Sin => ConstantValue::Float(a.sin()),
                    UnaryOperator::Cos => ConstantValue::Float(a.cos()),
                    UnaryOperator::Tan => ConstantValue::Float(a.tan()),
                    UnaryOperator::Log => {
                        if *a > 0.0 {
                            ConstantValue::Float(a.ln())
                        } else {
                            return Ok(None); // Log of non-positive number
                        }
                    }
                    UnaryOperator::Exp => ConstantValue::Float(a.exp()),
                    UnaryOperator::Sqrt => {
                        if *a >= 0.0 {
                            ConstantValue::Float(a.sqrt())
                        } else {
                            return Ok(None); // Sqrt of negative number
                        }
                    }
                    UnaryOperator::Floor => ConstantValue::Float(a.floor()),
                    UnaryOperator::Ceil => ConstantValue::Float(a.ceil()),
                    UnaryOperator::Round => ConstantValue::Float(a.round()),
                    _ => return Ok(None),
                };
                Ok(Some(result))
            }
            ConstantValue::Bool(a) => {
                let result = match op {
                    UnaryOperator::Not => ConstantValue::Bool(!a),
                    _ => return Ok(None),
                };
                Ok(Some(result))
            }
            _ => Ok(None),
        }
    }

    fn is_dead_code(&self, node: &Node) -> JitResult<bool> {
        // Check if node has no side effects and its output is unused
        if node.has_side_effects() {
            return Ok(false);
        }

        // For now, conservatively return false
        // In a full implementation, we would need access to the graph
        // to check if outputs are used
        Ok(false)
    }

    fn is_eliminable_branch(&self, node: &Node) -> JitResult<bool> {
        if node.operation_type() != "branch" && node.operation_type() != "if" {
            return Ok(false);
        }

        // Check if the condition is a constant
        // This is a placeholder - in a real implementation, we'd need to track
        // the control flow dependencies and check if the condition is constant
        // For now, we'll conservatively return false

        Ok(false)
    }

    fn get_unroll_count(&self, node: &Node) -> JitResult<Option<usize>> {
        if node.operation_type() != "loop" && node.operation_type() != "for" {
            return Ok(None);
        }

        // Check if loop has constant iteration count
        if let Some(iterations_attr) = node.get_attribute("iterations") {
            let iterations = match iterations_attr {
                crate::graph::Attribute::Int(i) => *i as usize,
                crate::graph::Attribute::String(s) => {
                    if let Ok(val) = s.parse::<usize>() {
                        val
                    } else {
                        return Ok(None);
                    }
                }
                _ => return Ok(None),
            };

            // Only unroll small loops
            if iterations <= 16 {
                return Ok(Some(iterations));
            }
        }

        Ok(None)
    }

    fn analyze_propagation_opportunities(
        &self,
        graph: &ComputationGraph,
        constant_node_id: NodeId,
        constant_value: &ConstantValue,
    ) -> JitResult<Vec<PropagationOpportunity>> {
        let mut opportunities = Vec::new();

        if let Some(_constant_node) = graph.get_node(constant_node_id) {
            let outputs = graph.get_node_outputs(constant_node_id);
            let mut to_nodes = Vec::new();

            for output_id in outputs {
                if let Some(output_node) = graph.get_node(output_id) {
                    // Check if this node can benefit from constant propagation
                    if self.can_benefit_from_constant(output_node, constant_value) {
                        to_nodes.push(output_id);
                    }
                }
            }

            if !to_nodes.is_empty() {
                let estimated_benefit =
                    self.estimate_propagation_benefit(&to_nodes, constant_value);
                opportunities.push(PropagationOpportunity {
                    from_node: constant_node_id,
                    to_nodes,
                    constant_value: constant_value.clone(),
                    estimated_benefit,
                });
            }
        }

        Ok(opportunities)
    }

    fn can_benefit_from_constant(&self, node: &Node, _constant_value: &ConstantValue) -> bool {
        // Check if node operation can be simplified with a constant input
        match node.operation_type() {
            "add" | "sub" | "mul" | "div" | "pow" => true,
            "branch" | "if" => true,
            "loop" | "for" => true,
            _ => false,
        }
    }

    fn estimate_propagation_benefit(
        &self,
        _to_nodes: &[NodeId],
        _constant_value: &ConstantValue,
    ) -> f64 {
        // Simple heuristic: more nodes = more benefit
        0.1 * _to_nodes.len() as f64
    }

    // Optimization application methods
    fn apply_constant_folding(
        &self,
        graph: &mut ComputationGraph,
        constants: &[(NodeId, ConstantValue)],
    ) -> JitResult<usize> {
        let mut applied = 0;

        for (node_id, constant_value) in constants {
            if let Some(node) = graph.get_node_mut(*node_id) {
                // Replace node with constant
                let graph_constant_value = match constant_value {
                    ConstantValue::Int(i) => crate::graph::ConstantValue::IntScalar(*i),
                    ConstantValue::Float(f) => crate::graph::ConstantValue::Scalar(*f),
                    _ => crate::graph::ConstantValue::Scalar(0.0), // Placeholder
                };
                node.op = crate::graph::Operation::Constant(crate::graph::ConstantInfo {
                    value: graph_constant_value,
                });
                node.set_attribute(
                    "value".to_string(),
                    match constant_value {
                        ConstantValue::Bool(b) => crate::graph::Attribute::Bool(*b),
                        ConstantValue::Int(i) => crate::graph::Attribute::Int(*i),
                        ConstantValue::Float(f) => crate::graph::Attribute::Float(*f),
                        ConstantValue::String(s) => crate::graph::Attribute::String(s.clone()),
                        _ => crate::graph::Attribute::String(constant_value.to_string()),
                    },
                );
                applied += 1;
            }
        }

        Ok(applied)
    }

    fn apply_dead_code_elimination(
        &self,
        graph: &mut ComputationGraph,
        dead_nodes: &[NodeId],
    ) -> JitResult<usize> {
        let mut applied = 0;

        for &node_id in dead_nodes {
            if graph.remove_node(node_id).is_some() {
                applied += 1;
            }
        }

        Ok(applied)
    }

    fn apply_branch_elimination(
        &self,
        graph: &mut ComputationGraph,
        eliminable_branches: &[NodeId],
    ) -> JitResult<usize> {
        let mut applied = 0;

        for &node_id in eliminable_branches {
            if let Some(_node) = graph.node(node_id) {
                let inputs = graph.get_node_inputs(node_id);
                if !inputs.is_empty() {
                    if let Ok(cache) = self.constant_cache.read() {
                        if let Some(ConstantValue::Bool(condition)) = cache.get(&inputs[0]) {
                            // Replace branch with the appropriate path
                            let branch_index = if *condition { 1 } else { 2 };
                            if inputs.len() > branch_index {
                                // Replace the branch node with the selected path
                                match graph.replace_node_with_input(node_id, inputs[branch_index]) {
                                    Ok(_) => {
                                        log::debug!(
                                            "Successfully eliminated branch by replacing with {}",
                                            if *condition { "true" } else { "false" }
                                        );
                                        applied += 1;
                                    }
                                    Err(e) => {
                                        log::warn!("Failed to eliminate branch: {}", e);
                                    }
                                }
                            }
                        }
                    }
                }
            }
        }

        Ok(applied)
    }

    fn apply_loop_unrolling(
        &self,
        graph: &mut ComputationGraph,
        unrollable_loops: &[(NodeId, usize)],
    ) -> JitResult<usize> {
        let mut applied = 0;

        for &(node_id, iterations) in unrollable_loops {
            if let Some(loop_node) = graph.get_node(node_id) {
                // Create unrolled loop body
                if let Some(loop_body) = loop_node.get_attribute("body") {
                    let body_str = match loop_body {
                        crate::graph::Attribute::String(s) => s,
                        _ => continue,
                    };
                    let unrolled_body = self.create_unrolled_body(body_str, iterations)?;

                    // Replace loop with unrolled body
                    match graph.replace_node_with_sequence(node_id, &unrolled_body) {
                        Ok(_) => {
                            log::debug!(
                                "Successfully unrolled loop with {} iterations",
                                iterations
                            );
                            applied += 1;
                        }
                        Err(e) => {
                            log::warn!("Failed to unroll loop: {}", e);
                        }
                    }
                }
            }
        }

        Ok(applied)
    }

    fn apply_constant_propagation(
        &self,
        _graph: &mut ComputationGraph,
        _opportunities: &[PropagationOpportunity],
    ) -> JitResult<usize> {
        // Placeholder implementation
        // In a real implementation, this would replace variable references with constants
        Ok(0)
    }

    fn create_unrolled_body(
        &self,
        _loop_body: &str,
        iterations: usize,
    ) -> JitResult<Vec<crate::Node>> {
        use crate::graph::{Node, Operation};
        use torsh_core::{DType, DeviceType, Shape};

        // Simplified implementation - would need proper loop body parsing and replication
        let mut unrolled_nodes = Vec::new();

        for i in 0..iterations {
            // Create nodes for each iteration
            // This is a placeholder - actual implementation would parse and replicate the loop body
            // For now, create a simple pass-through node for each iteration
            // Use Input as a placeholder operation for unrolled iterations
            // In a full implementation, this would replicate the actual loop body operations
            let node = Node::new(Operation::Input, format!("unrolled_iter_{}", i))
                .with_output_shapes(vec![Some(Shape::new(vec![1]))])
                .with_dtypes(vec![DType::F32])
                .with_device(DeviceType::Cpu);

            unrolled_nodes.push(node);
        }

        Ok(unrolled_nodes)
    }
}

impl EvaluationContext {
    fn new() -> Self {
        Self {
            variables: HashMap::new(),
            functions: HashMap::new(),
            depth: 0,
            steps: 0,
            memory_usage: 0,
        }
    }

    fn reset(&mut self) {
        self.variables.clear();
        self.depth = 0;
        self.steps = 0;
        self.memory_usage = 0;
    }
}

impl ConstantValue {
    /// Convert constant value to string representation
    pub fn to_string(&self) -> String {
        match self {
            ConstantValue::Bool(b) => b.to_string(),
            ConstantValue::Int(i) => i.to_string(),
            ConstantValue::UInt(u) => u.to_string(),
            ConstantValue::Float(f) => f.to_string(),
            ConstantValue::String(s) => s.clone(),
            ConstantValue::Array(arr) => {
                format!(
                    "[{}]",
                    arr.iter()
                        .map(|v| v.to_string())
                        .collect::<Vec<_>>()
                        .join(", ")
                )
            }
            ConstantValue::Tensor { shape, data, dtype } => {
                format!("Tensor({:?}, {:?}, {})", shape, data, dtype)
            }
            ConstantValue::Complex { real, imag } => {
                format!("{}+{}i", real, imag)
            }
            ConstantValue::None => "None".to_string(),
            ConstantValue::Undefined => "Undefined".to_string(),
        }
    }

    /// Check if this value is truthy
    pub fn is_truthy(&self) -> bool {
        match self {
            ConstantValue::Bool(b) => *b,
            ConstantValue::Int(i) => *i != 0,
            ConstantValue::UInt(u) => *u != 0,
            ConstantValue::Float(f) => *f != 0.0,
            ConstantValue::String(s) => !s.is_empty(),
            ConstantValue::Array(arr) => !arr.is_empty(),
            ConstantValue::Tensor { data, .. } => !data.is_empty(),
            ConstantValue::Complex { real, imag } => *real != 0.0 || *imag != 0.0,
            ConstantValue::None => false,
            ConstantValue::Undefined => false,
        }
    }

    /// Get the type name of this constant
    pub fn type_name(&self) -> &'static str {
        match self {
            ConstantValue::Bool(_) => "bool",
            ConstantValue::Int(_) => "int",
            ConstantValue::UInt(_) => "uint",
            ConstantValue::Float(_) => "float",
            ConstantValue::String(_) => "string",
            ConstantValue::Array(_) => "array",
            ConstantValue::Tensor { .. } => "tensor",
            ConstantValue::Complex { .. } => "complex",
            ConstantValue::None => "none",
            ConstantValue::Undefined => "undefined",
        }
    }
}

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

    #[test]
    fn test_constant_evaluator_creation() {
        let config = ConstEvalConfig::default();
        let evaluator = ConstantEvaluator::new(config);
        assert!(evaluator.config.enable_constant_folding);
    }

    #[test]
    fn test_binary_operations() {
        let evaluator = ConstantEvaluator::new(ConstEvalConfig::default());

        let left = ConstantValue::Int(5);
        let right = ConstantValue::Int(3);

        let result = evaluator
            .apply_binary_operation(BinaryOperator::Add, &left, &right)
            .unwrap()
            .unwrap();
        assert_eq!(result, ConstantValue::Int(8));

        let result = evaluator
            .apply_binary_operation(BinaryOperator::Mul, &left, &right)
            .unwrap()
            .unwrap();
        assert_eq!(result, ConstantValue::Int(15));
    }

    #[test]
    fn test_unary_operations() {
        let evaluator = ConstantEvaluator::new(ConstEvalConfig::default());

        let value = ConstantValue::Float(4.0);
        let result = evaluator
            .apply_unary_operation(UnaryOperator::Sqrt, &value)
            .unwrap()
            .unwrap();
        assert_eq!(result, ConstantValue::Float(2.0));

        let value = ConstantValue::Int(-5);
        let result = evaluator
            .apply_unary_operation(UnaryOperator::Abs, &value)
            .unwrap()
            .unwrap();
        assert_eq!(result, ConstantValue::Int(5));
    }

    #[test]
    fn test_constant_value_operations() {
        let bool_val = ConstantValue::Bool(true);
        assert!(bool_val.is_truthy());
        assert_eq!(bool_val.type_name(), "bool");

        let int_val = ConstantValue::Int(42);
        assert_eq!(int_val.to_string(), "42");

        let float_val = ConstantValue::Float(3.14);
        assert_eq!(float_val.type_name(), "float");
    }

    #[test]
    fn test_evaluation_context() {
        let mut context = EvaluationContext::new();
        assert_eq!(context.depth, 0);
        assert_eq!(context.steps, 0);

        context.depth = 5;
        context.steps = 100;
        context.reset();

        assert_eq!(context.depth, 0);
        assert_eq!(context.steps, 0);
    }
}