//! Graph optimization and expression simplification for computation graphs
//!
//! This module provides various optimization techniques for computation graphs,
//! including expression simplification, common subexpression elimination,
//! constant folding, and graph-level transformations.

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

// pub mod constant_folding;
// pub mod expression_simplification;
// pub mod graph_rewriting;
pub mod loop_fusion;
pub mod memory_optimization;

/// Graph optimization configuration
#[derive(Debug, Clone)]
pub struct OptimizationConfig {
    /// Enable constant folding
    pub constant_folding: bool,
    /// Enable common subexpression elimination
    pub cse: bool,
    /// Enable expression simplification
    pub expression_simplification: bool,
    /// Enable dead code elimination
    pub dead_code_elimination: bool,
    /// Enable operation fusion
    pub operation_fusion: bool,
    /// Enable memory layout optimization
    pub memory_optimization: bool,
    /// Maximum optimization passes
    pub max_passes: usize,
    /// Optimization level (0-3)
    pub level: OptimizationLevel,
}

impl Default for OptimizationConfig {
    fn default() -> Self {
        Self {
            constant_folding: true,
            cse: true,
            expression_simplification: true,
            dead_code_elimination: true,
            operation_fusion: false, // More aggressive optimization
            memory_optimization: true,
            max_passes: 5,
            level: OptimizationLevel::Standard,
        }
    }
}

/// Optimization levels
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum OptimizationLevel {
    /// No optimizations
    None,
    /// Basic optimizations (constant folding, DCE)
    Basic,
    /// Standard optimizations (basic + CSE, expression simplification)
    Standard,
    /// Aggressive optimizations (standard + operation fusion, advanced transformations)
    Aggressive,
}

impl OptimizationLevel {
    /// Get the default configuration for this optimization level
    pub fn config(self) -> OptimizationConfig {
        match self {
            OptimizationLevel::None => OptimizationConfig {
                constant_folding: false,
                cse: false,
                expression_simplification: false,
                dead_code_elimination: false,
                operation_fusion: false,
                memory_optimization: false,
                max_passes: 0,
                level: self,
            },
            OptimizationLevel::Basic => OptimizationConfig {
                constant_folding: true,
                cse: false,
                expression_simplification: false,
                dead_code_elimination: true,
                operation_fusion: false,
                memory_optimization: false,
                max_passes: 2,
                level: self,
            },
            OptimizationLevel::Standard => OptimizationConfig::default(),
            OptimizationLevel::Aggressive => OptimizationConfig {
                constant_folding: true,
                cse: true,
                expression_simplification: true,
                dead_code_elimination: true,
                operation_fusion: true,
                memory_optimization: true,
                max_passes: 10,
                level: self,
            },
        }
    }
}

/// Main graph optimizer
pub struct GraphOptimizer<F: Float> {
    config: OptimizationConfig,
    _phantom: std::marker::PhantomData<F>,
}

impl<F: Float> GraphOptimizer<F> {
    /// Create a new graph optimizer with default configuration
    pub fn new() -> Self {
        Self {
            config: OptimizationConfig::default(),
            _phantom: std::marker::PhantomData,
        }
    }

    /// Create a new graph optimizer with custom configuration
    pub fn with_config(config: OptimizationConfig) -> Self {
        Self {
            config,
            _phantom: std::marker::PhantomData,
        }
    }

    /// Create a new graph optimizer with specified optimization level
    pub fn with_level(level: OptimizationLevel) -> Self {
        Self {
            config: level.config(),
            _phantom: std::marker::PhantomData,
        }
    }

    /// Optimize a computation graph
    pub fn optimize(&self, graph: &mut Graph<F>) -> Result<OptimizationReport, OptimizationError> {
        let mut report = OptimizationReport::new();

        if self.config.level == OptimizationLevel::None {
            return Ok(report);
        }

        for pass in 0..self.config.max_passes {
            let mut changed = false;

            // Constant folding
            if self.config.constant_folding {
                let folded = self.apply_constant_folding(graph)?;
                if folded > 0 {
                    changed = true;
                    report.constant_folding_applied += folded;
                }
            }

            // Dead code elimination
            if self.config.dead_code_elimination {
                let eliminated = self.apply_dead_code_elimination(graph)?;
                if eliminated > 0 {
                    changed = true;
                    report.dead_nodes_eliminated += eliminated;
                }
            }

            // Common subexpression elimination
            if self.config.cse {
                let eliminated = self.apply_cse(graph)?;
                if eliminated > 0 {
                    changed = true;
                    report.cse_applied += eliminated;
                }
            }

            // Expression simplification
            if self.config.expression_simplification {
                let simplified = self.apply_expression_simplification(graph)?;
                if simplified > 0 {
                    changed = true;
                    report.expressions_simplified += simplified;
                }
            }

            // Operation fusion
            if self.config.operation_fusion {
                let fused = self.apply_operation_fusion(graph)?;
                if fused > 0 {
                    changed = true;
                    report.operations_fused += fused;
                }
            }

            // Memory optimization
            if self.config.memory_optimization {
                let optimized = self.apply_memory_optimization(graph)?;
                if optimized > 0 {
                    changed = true;
                    report.memory_optimizations += optimized;
                }
            }

            report.passes_completed = pass + 1;

            // If no changes were made, we can stop early
            if !changed {
                break;
            }
        }

        Ok(report)
    }

    /// Apply constant folding optimization
    fn apply_constant_folding(&self, graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
        // Temporarily disabled - would be implemented with constant_folding module
        Ok(0)
    }

    /// Apply dead code elimination
    fn apply_dead_code_elimination(
        &self,
        graph: &mut Graph<F>,
    ) -> Result<usize, OptimizationError> {
        // Simplified implementation - in a real optimizer, this would:
        // 1. Mark all reachable nodes from outputs
        // 2. Remove unreachable nodes
        // 3. Update the _graph structure

        let eliminated_count = 0;

        // Example algorithm:
        // 1. Start from all output nodes
        // 2. Traverse backwards to mark reachable nodes
        // 3. Remove unmarked nodes

        Ok(eliminated_count)
    }

    /// Apply common subexpression elimination
    fn apply_cse(&self, graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
        // Simplified implementation - in a real optimizer, this would:
        // 1. Build a hash table of equivalent expressions
        // 2. Replace duplicate expressions with references to the first occurrence
        // 3. Remove redundant nodes

        let cse_count = 0;

        // Example:
        // If we have: x*y + z and later x*y + w
        // We can compute x*y once and reuse it

        Ok(cse_count)
    }

    /// Apply expression simplification
    fn apply_expression_simplification(
        &self,
        graph: &mut Graph<F>,
    ) -> Result<usize, OptimizationError> {
        // Temporarily disabled - would be implemented with expression_simplification module
        Ok(0)
    }

    /// Apply operation fusion
    fn apply_operation_fusion(&self, graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
        // Simplified implementation - in a real optimizer, this would:
        // 1. Identify fusable operation patterns
        // 2. Replace patterns with fused operations
        // 3. Update the _graph structure

        let fused_count = 0;

        // Examples of fusion:
        // - Element-wise operations: Add + Mul → FusedAddMul
        // - Activation sequences: Linear + ReLU → FusedLinearReLU
        // - Reduction patterns: Sum + Div → Mean

        Ok(fused_count)
    }

    /// Apply memory optimization
    fn apply_memory_optimization(&self, graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
        // Simplified implementation - in a real optimizer, this would:
        // 1. Analyze memory usage patterns
        // 2. Insert memory reuse opportunities
        // 3. Optimize tensor layouts
        // 4. Add gradient checkpointing where beneficial

        let optimized_count = 0;

        // Examples:
        // - In-place operations where safe
        // - Memory pooling for temporary tensors
        // - Gradient checkpointing for memory-intensive paths

        Ok(optimized_count)
    }
}

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

/// Report of optimization results
#[derive(Debug, Clone, Default)]
pub struct OptimizationReport {
    /// Number of optimization passes completed
    pub passes_completed: usize,
    /// Number of constant folding optimizations applied
    pub constant_folding_applied: usize,
    /// Number of dead nodes eliminated
    pub dead_nodes_eliminated: usize,
    /// Number of common subexpressions eliminated
    pub cse_applied: usize,
    /// Number of expressions simplified
    pub expressions_simplified: usize,
    /// Number of operations fused
    pub operations_fused: usize,
    /// Number of memory optimizations applied
    pub memory_optimizations: usize,
}

impl OptimizationReport {
    /// Create a new empty optimization report
    pub fn new() -> Self {
        Self::default()
    }

    /// Get the total number of optimizations applied
    pub fn total_optimizations(&self) -> usize {
        self.constant_folding_applied
            + self.dead_nodes_eliminated
            + self.cse_applied
            + self.expressions_simplified
            + self.operations_fused
            + self.memory_optimizations
    }

    /// Check if any optimizations were applied
    pub fn has_optimizations(&self) -> bool {
        self.total_optimizations() > 0
    }

    /// Print a summary of the optimization results
    pub fn print_summary(&self) {
        println!("Optimization Report:");
        println!("==================");
        println!("Passes completed: {}", self.passes_completed);
        println!("Total optimizations: {}", self.total_optimizations());

        if self.constant_folding_applied > 0 {
            println!("  Constant folding: {}", self.constant_folding_applied);
        }
        if self.dead_nodes_eliminated > 0 {
            println!("  Dead code elimination: {}", self.dead_nodes_eliminated);
        }
        if self.cse_applied > 0 {
            println!("  Common subexpression elimination: {}", self.cse_applied);
        }
        if self.expressions_simplified > 0 {
            println!(
                "  Expression simplification: {}",
                self.expressions_simplified
            );
        }
        if self.operations_fused > 0 {
            println!("  Operation fusion: {}", self.operations_fused);
        }
        if self.memory_optimizations > 0 {
            println!("  Memory optimizations: {}", self.memory_optimizations);
        }
    }
}

/// Expression pattern matcher for optimization
pub struct PatternMatcher<F: Float> {
    _phantom: std::marker::PhantomData<F>,
}

impl<F: Float> PatternMatcher<F> {
    /// Create a new pattern matcher
    pub fn new() -> Self {
        Self {
            _phantom: std::marker::PhantomData,
        }
    }

    /// Check if a tensor matches a pattern for simplification
    #[allow(dead_code)]
    pub(crate) fn matches_simplification_pattern(
        &self,
        _tensor_internal: &TensorInternal<F>,
    ) -> Option<SimplificationPattern> {
        // Temporarily disabled - would be implemented with expression_simplification module
        None
    }

    /// Check if tensors can be fused
    #[allow(dead_code)]
    pub(crate) fn can_fuse(
        &self,
        _tensor1: &TensorInternal<F>,
        _tensor2: &TensorInternal<F>,
    ) -> bool {
        // Temporarily disabled - would be implemented with fusion analysis
        false
    }

    /// Check if a tensor represents a constant
    #[allow(dead_code)]
    pub(crate) fn is_constant(&self, _tensorinternal: &TensorInternal<F>) -> bool {
        // Temporarily disabled - would be implemented with constant analysis
        false
    }

    /// Check if a tensor is dead (unreachable from outputs)
    #[allow(dead_code)]
    pub(crate) fn is_dead(
        &self,
        _tensor_internal: &TensorInternal<F>,
        _reachable: &HashSet<TensorID>,
    ) -> bool {
        // Temporarily disabled - would be implemented with reachability analysis
        false
    }
}

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

/// Types of simplification patterns
#[derive(Debug, Clone, Copy, PartialEq)]
pub enum SimplificationPattern {
    /// x + 0 → x
    AddZero,
    /// x - 0 → x
    SubZero,
    /// x * 1 → x
    MulOne,
    /// x / 1 → x
    DivOne,
    /// x * 0 → 0
    MulZero,
    /// x - x → 0
    SubSelf,
    /// x / x → 1
    DivSelf,
    /// log(exp(x)) → x
    LogExp,
    /// exp(log(x)) → x
    ExpLog,
    /// sqrt(x^2) → abs(x)
    SqrtSquare,
    /// pow(x, 1) → x
    PowOne,
    /// pow(x, 0) → 1
    PowZero,
}

/// Optimization pass manager
pub struct OptimizationPass<F: Float> {
    name: String,
    _phantom: std::marker::PhantomData<F>,
}

impl<F: Float> OptimizationPass<F> {
    /// Create a new optimization pass
    pub fn new(name: &str) -> Self {
        Self {
            name: name.to_string(),
            _phantom: std::marker::PhantomData,
        }
    }

    /// Get the name of this pass
    pub fn name(&self) -> &str {
        &self.name
    }

    /// Run this optimization pass on a graph
    pub fn run(&self, graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
        // Each pass would implement its specific optimization logic
        Ok(0)
    }
}

/// Errors that can occur during optimization
#[derive(Debug, thiserror::Error)]
pub enum OptimizationError {
    #[error("Graph structure error: {0}")]
    GraphStructure(String),
    #[error("Pattern matching error: {0}")]
    PatternMatching(String),
    #[error("Optimization conflict: {0}")]
    Conflict(String),
    #[error("Invalid operation: {0}")]
    InvalidOperation(String),
}

/// Public API functions for graph optimization
/// Optimize a computation graph with default settings
#[allow(dead_code)]
pub fn optimize_graph<F: Float>(
    graph: &mut Graph<F>,
) -> Result<OptimizationReport, OptimizationError> {
    let optimizer = GraphOptimizer::new();
    optimizer.optimize(graph)
}

/// Optimize a computation graph with specified optimization level
#[allow(dead_code)]
pub fn optimize_graph_with_level<F: Float>(
    graph: &mut Graph<F>,
    level: OptimizationLevel,
) -> Result<OptimizationReport, OptimizationError> {
    let optimizer = GraphOptimizer::with_level(level);
    optimizer.optimize(graph)
}

/// Optimize a computation graph with custom configuration
#[allow(dead_code)]
pub fn optimize_graph_with_config<F: Float>(
    graph: &mut Graph<F>,
    config: OptimizationConfig,
) -> Result<OptimizationReport, OptimizationError> {
    let optimizer = GraphOptimizer::with_config(config);
    optimizer.optimize(graph)
}

/// Apply only constant folding optimization
#[allow(dead_code)]
pub fn apply_constant_folding<F: Float>(graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
    let config = OptimizationConfig {
        constant_folding: true,
        cse: false,
        expression_simplification: false,
        dead_code_elimination: false,
        operation_fusion: false,
        memory_optimization: false,
        max_passes: 1,
        level: OptimizationLevel::Basic,
    };
    let optimizer = GraphOptimizer::with_config(config);
    let report = optimizer.optimize(graph)?;
    Ok(report.constant_folding_applied)
}

/// Apply only dead code elimination
#[allow(dead_code)]
pub fn apply_dead_code_elimination<F: Float>(
    graph: &mut Graph<F>,
) -> Result<usize, OptimizationError> {
    let config = OptimizationConfig {
        constant_folding: false,
        cse: false,
        expression_simplification: false,
        dead_code_elimination: true,
        operation_fusion: false,
        memory_optimization: false,
        max_passes: 1,
        level: OptimizationLevel::Basic,
    };
    let optimizer = GraphOptimizer::with_config(config);
    let report = optimizer.optimize(graph)?;
    Ok(report.dead_nodes_eliminated)
}

/// Apply common subexpression elimination
#[allow(dead_code)]
pub fn apply_cse<F: Float>(graph: &mut Graph<F>) -> Result<usize, OptimizationError> {
    let config = OptimizationConfig {
        constant_folding: false,
        cse: true,
        expression_simplification: false,
        dead_code_elimination: false,
        operation_fusion: false,
        memory_optimization: false,
        max_passes: 1,
        level: OptimizationLevel::Standard,
    };
    let optimizer = GraphOptimizer::with_config(config);
    let report = optimizer.optimize(graph)?;
    Ok(report.cse_applied)
}

// Temporary stub implementations for types used in tests
// These will be replaced when the full optimization modules are completed

/// Stub implementation of ConstantFolder for testing
pub struct ConstantFolder<F: Float> {
    _phantom: std::marker::PhantomData<F>,
}

impl<F: Float> ConstantFolder<F> {
    /// Create a new constant folder
    pub fn new() -> Self {
        Self {
            _phantom: std::marker::PhantomData,
        }
    }

    /// Check if a tensor is constant
    pub fn is_constant(&self, _tensorid: TensorID) -> bool {
        false
    }

    /// Get the constant value of a tensor if it's constant
    pub fn get_constant_value(&self, _tensorid: TensorID) -> Option<F> {
        None
    }

    /// Clear the constant cache
    pub fn clear_cache(&mut self) {
        // No-op for stub
    }
}

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

/// Stub implementation of ExpressionSimplifier for testing
pub struct ExpressionSimplifier<F: Float> {
    _phantom: std::marker::PhantomData<F>,
}

impl<F: Float> ExpressionSimplifier<F> {
    /// Create a new expression simplifier
    pub fn new() -> Self {
        Self {
            _phantom: std::marker::PhantomData,
        }
    }

    /// Clear the simplifier cache
    pub fn clear_cache(&mut self) {
        // No-op for stub
    }
}

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

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

    #[test]
    fn test_optimization_config() {
        let config = OptimizationConfig::default();
        assert!(config.constant_folding);
        assert!(config.cse);
        assert!(config.expression_simplification);
        assert!(config.dead_code_elimination);
        assert_eq!(config.max_passes, 5);
    }

    #[test]
    fn test_optimization_levels() {
        let none_config = OptimizationLevel::None.config();
        assert!(!none_config.constant_folding);
        assert_eq!(none_config.max_passes, 0);

        let aggressive_config = OptimizationLevel::Aggressive.config();
        assert!(aggressive_config.operation_fusion);
        assert!(aggressive_config.memory_optimization);
        assert_eq!(aggressive_config.max_passes, 10);
    }

    #[test]
    fn test_graph_optimizer_creation() {
        let _optimizer = GraphOptimizer::<f32>::new();
        let _optimizer_with_config =
            GraphOptimizer::<f32>::with_config(OptimizationConfig::default());
        let _optimizer_with_level =
            GraphOptimizer::<f32>::with_level(OptimizationLevel::Aggressive);
    }

    #[test]
    fn test_optimization_report() {
        let mut report = OptimizationReport::new();
        assert_eq!(report.total_optimizations(), 0);
        assert!(!report.has_optimizations());

        report.constant_folding_applied = 5;
        report.dead_nodes_eliminated = 3;
        assert_eq!(report.total_optimizations(), 8);
        assert!(report.has_optimizations());
    }

    #[test]
    fn test_pattern_matcher() {
        let _matcher = PatternMatcher::<f32>::new();
    }

    #[test]
    fn test_simplification_patterns() {
        let pattern = SimplificationPattern::AddZero;
        assert_eq!(pattern, SimplificationPattern::AddZero);

        let patterns = [
            SimplificationPattern::AddZero,
            SimplificationPattern::MulOne,
            SimplificationPattern::LogExp,
        ];
        assert_eq!(patterns.len(), 3);
    }

    #[test]
    fn test_optimization_pass() {
        let pass = OptimizationPass::<f32>::new("test_pass");
        assert_eq!(pass.name(), "test_pass");
    }
}
