torsh_jit/
const_eval.rs

1//! Compile-Time Evaluation for ToRSh JIT
2//!
3//! This module implements compile-time evaluation of constant expressions and
4//! computations, enabling optimizations that reduce runtime overhead.
5
6use crate::{ComputationGraph, JitError, JitResult, Node, NodeId};
7use serde::{Deserialize, Serialize};
8use std::collections::HashMap;
9use std::sync::{Arc, RwLock};
10
11/// Compile-time evaluation manager
12pub struct ConstantEvaluator {
13    config: ConstEvalConfig,
14    constant_cache: Arc<RwLock<HashMap<NodeId, ConstantValue>>>,
15    evaluation_context: EvaluationContext,
16}
17
18/// Configuration for constant evaluation
19#[derive(Debug, Clone)]
20pub struct ConstEvalConfig {
21    /// Enable constant folding
22    pub enable_constant_folding: bool,
23
24    /// Enable dead code elimination based on constants
25    pub enable_dead_code_elimination: bool,
26
27    /// Enable branch elimination for constant conditions
28    pub enable_branch_elimination: bool,
29
30    /// Enable loop unrolling for constant iterations
31    pub enable_loop_unrolling: bool,
32
33    /// Maximum computation steps for constant evaluation
34    pub max_evaluation_steps: usize,
35
36    /// Maximum memory usage for constant evaluation
37    pub max_memory_usage: usize,
38
39    /// Enable aggressive constant propagation
40    pub enable_aggressive_propagation: bool,
41
42    /// Maximum depth for recursive constant evaluation
43    pub max_recursion_depth: usize,
44
45    /// Cache size for evaluated constants
46    pub cache_size: usize,
47}
48
49impl Default for ConstEvalConfig {
50    fn default() -> Self {
51        Self {
52            enable_constant_folding: true,
53            enable_dead_code_elimination: true,
54            enable_branch_elimination: true,
55            enable_loop_unrolling: true,
56            max_evaluation_steps: 10000,
57            max_memory_usage: 64 * 1024 * 1024, // 64MB
58            enable_aggressive_propagation: false,
59            max_recursion_depth: 100,
60            cache_size: 1000,
61        }
62    }
63}
64
65/// Compile-time constant value
66#[derive(Debug, Clone, PartialEq, Serialize, Deserialize)]
67pub enum ConstantValue {
68    /// Boolean constant
69    Bool(bool),
70
71    /// Integer constant
72    Int(i64),
73
74    /// Unsigned integer constant
75    UInt(u64),
76
77    /// Floating point constant
78    Float(f64),
79
80    /// String constant
81    String(String),
82
83    /// Array of constants
84    Array(Vec<ConstantValue>),
85
86    /// Tensor constant with shape and data
87    Tensor {
88        shape: Vec<usize>,
89        data: Vec<f64>,
90        dtype: String,
91    },
92
93    /// Complex constant
94    Complex { real: f64, imag: f64 },
95
96    /// None/null constant
97    None,
98
99    /// Undefined value (cannot be evaluated at compile time)
100    Undefined,
101}
102
103/// Evaluation context for compile-time computation
104#[derive(Debug, Clone)]
105pub struct EvaluationContext {
106    /// Variable bindings
107    variables: HashMap<String, ConstantValue>,
108
109    /// Function definitions
110    functions: HashMap<String, FunctionDefinition>,
111
112    /// Current evaluation depth
113    depth: usize,
114
115    /// Number of evaluation steps taken
116    steps: usize,
117
118    /// Memory usage in bytes
119    memory_usage: usize,
120}
121
122/// Compile-time function definition
123#[derive(Debug, Clone)]
124pub struct FunctionDefinition {
125    pub name: String,
126    pub parameters: Vec<String>,
127    pub body: Vec<Instruction>,
128    pub return_type: Option<String>,
129}
130
131/// Instructions that can be evaluated at compile time
132#[derive(Debug, Clone)]
133pub enum Instruction {
134    /// Load constant value
135    LoadConstant(ConstantValue),
136
137    /// Load variable
138    LoadVariable(String),
139
140    /// Store to variable
141    Store(String),
142
143    /// Binary operation
144    BinaryOp {
145        op: BinaryOperator,
146        left: Box<Instruction>,
147        right: Box<Instruction>,
148    },
149
150    /// Unary operation
151    UnaryOp {
152        op: UnaryOperator,
153        operand: Box<Instruction>,
154    },
155
156    /// Function call
157    Call {
158        function: String,
159        args: Vec<Instruction>,
160    },
161
162    /// Conditional expression
163    Conditional {
164        condition: Box<Instruction>,
165        then_branch: Box<Instruction>,
166        else_branch: Box<Instruction>,
167    },
168
169    /// Loop expression
170    Loop {
171        condition: Box<Instruction>,
172        body: Vec<Instruction>,
173        max_iterations: Option<usize>,
174    },
175
176    /// Array indexing
177    Index {
178        array: Box<Instruction>,
179        index: Box<Instruction>,
180    },
181
182    /// Array construction
183    Array(Vec<Instruction>),
184
185    /// Tensor construction
186    Tensor {
187        shape: Vec<usize>,
188        data: Vec<Instruction>,
189    },
190}
191
192/// Binary operators
193#[derive(Debug, Clone, Copy, PartialEq)]
194pub enum BinaryOperator {
195    Add,
196    Sub,
197    Mul,
198    Div,
199    Mod,
200    Pow,
201    And,
202    Or,
203    Xor,
204    Lt,
205    Le,
206    Gt,
207    Ge,
208    Eq,
209    Ne,
210    BitAnd,
211    BitOr,
212    BitXor,
213    Shl,
214    Shr,
215}
216
217/// Unary operators
218#[derive(Debug, Clone, Copy, PartialEq)]
219pub enum UnaryOperator {
220    Neg,
221    Not,
222    BitNot,
223    Abs,
224    Sin,
225    Cos,
226    Tan,
227    Log,
228    Exp,
229    Sqrt,
230    Floor,
231    Ceil,
232    Round,
233}
234
235/// Result of constant evaluation
236#[derive(Debug, Clone)]
237pub struct EvaluationResult {
238    pub constants_found: Vec<(NodeId, ConstantValue)>,
239    pub dead_code_nodes: Vec<NodeId>,
240    pub eliminable_branches: Vec<NodeId>,
241    pub unrollable_loops: Vec<(NodeId, usize)>,
242    pub propagation_opportunities: Vec<PropagationOpportunity>,
243}
244
245/// Constant propagation opportunity
246#[derive(Debug, Clone)]
247pub struct PropagationOpportunity {
248    pub from_node: NodeId,
249    pub to_nodes: Vec<NodeId>,
250    pub constant_value: ConstantValue,
251    pub estimated_benefit: f64,
252}
253
254impl ConstantEvaluator {
255    /// Create a new constant evaluator
256    pub fn new(config: ConstEvalConfig) -> Self {
257        Self {
258            config,
259            constant_cache: Arc::new(RwLock::new(HashMap::new())),
260            evaluation_context: EvaluationContext::new(),
261        }
262    }
263
264    /// Evaluate constants in a computation graph
265    pub fn evaluate_constants(&mut self, graph: &ComputationGraph) -> JitResult<EvaluationResult> {
266        let mut result = EvaluationResult {
267            constants_found: Vec::new(),
268            dead_code_nodes: Vec::new(),
269            eliminable_branches: Vec::new(),
270            unrollable_loops: Vec::new(),
271            propagation_opportunities: Vec::new(),
272        };
273
274        // Reset evaluation context
275        self.evaluation_context.reset();
276
277        // Topological sort to evaluate nodes in dependency order
278        let sorted_nodes = graph
279            .topological_sort()
280            .map_err(|e| JitError::CompilationError(format!("{:?}", e)))?;
281
282        for node_id in sorted_nodes {
283            if let Some(node) = graph.node(node_id) {
284                // Try to evaluate node as constant
285                if let Some(constant_value) = self.try_evaluate_node(node, node_id)? {
286                    result
287                        .constants_found
288                        .push((node_id, constant_value.clone()));
289
290                    // Cache the constant value
291                    if let Ok(mut cache) = self.constant_cache.write() {
292                        cache.insert(node_id, constant_value.clone());
293                    }
294
295                    // Check for propagation opportunities
296                    result.propagation_opportunities.extend(
297                        self.analyze_propagation_opportunities(graph, node_id, &constant_value)?,
298                    );
299                }
300
301                // Check for dead code
302                if self.is_dead_code(node)? {
303                    result.dead_code_nodes.push(node_id);
304                }
305
306                // Check for eliminable branches
307                if self.is_eliminable_branch(node)? {
308                    result.eliminable_branches.push(node_id);
309                }
310
311                // Check for unrollable loops
312                if let Some(iterations) = self.get_unroll_count(node)? {
313                    result.unrollable_loops.push((node_id, iterations));
314                }
315            }
316        }
317
318        Ok(result)
319    }
320
321    /// Apply constant evaluation optimizations to the graph
322    pub fn apply_optimizations(
323        &self,
324        graph: &mut ComputationGraph,
325        result: &EvaluationResult,
326    ) -> JitResult<usize> {
327        let mut optimizations_applied = 0;
328
329        // Apply constant folding
330        if self.config.enable_constant_folding {
331            optimizations_applied += self.apply_constant_folding(graph, &result.constants_found)?;
332        }
333
334        // Apply dead code elimination
335        if self.config.enable_dead_code_elimination {
336            optimizations_applied +=
337                self.apply_dead_code_elimination(graph, &result.dead_code_nodes)?;
338        }
339
340        // Apply branch elimination
341        if self.config.enable_branch_elimination {
342            optimizations_applied +=
343                self.apply_branch_elimination(graph, &result.eliminable_branches)?;
344        }
345
346        // Apply loop unrolling
347        if self.config.enable_loop_unrolling {
348            optimizations_applied += self.apply_loop_unrolling(graph, &result.unrollable_loops)?;
349        }
350
351        // Apply constant propagation
352        if self.config.enable_aggressive_propagation {
353            optimizations_applied +=
354                self.apply_constant_propagation(graph, &result.propagation_opportunities)?;
355        }
356
357        Ok(optimizations_applied)
358    }
359
360    /// Try to evaluate a node as a constant
361    fn try_evaluate_node(
362        &mut self,
363        node: &Node,
364        node_id: NodeId,
365    ) -> JitResult<Option<ConstantValue>> {
366        // Check if already cached
367        if let Ok(cache) = self.constant_cache.read() {
368            if let Some(cached_value) = cache.get(&node_id) {
369                return Ok(Some(cached_value.clone()));
370            }
371        }
372
373        // Check evaluation limits
374        if self.evaluation_context.steps >= self.config.max_evaluation_steps {
375            return Ok(None);
376        }
377
378        if self.evaluation_context.depth >= self.config.max_recursion_depth {
379            return Ok(None);
380        }
381
382        if self.evaluation_context.memory_usage >= self.config.max_memory_usage {
383            return Ok(None);
384        }
385
386        self.evaluation_context.steps += 1;
387        self.evaluation_context.depth += 1;
388
389        let result = match node.operation_type() {
390            "constant" => self.evaluate_constant_node(node),
391            "add" => self.evaluate_binary_op(node, BinaryOperator::Add),
392            "sub" => self.evaluate_binary_op(node, BinaryOperator::Sub),
393            "mul" => self.evaluate_binary_op(node, BinaryOperator::Mul),
394            "div" => self.evaluate_binary_op(node, BinaryOperator::Div),
395            "pow" => self.evaluate_binary_op(node, BinaryOperator::Pow),
396            "neg" => self.evaluate_unary_op(node, UnaryOperator::Neg),
397            "abs" => self.evaluate_unary_op(node, UnaryOperator::Abs),
398            "sin" => self.evaluate_unary_op(node, UnaryOperator::Sin),
399            "cos" => self.evaluate_unary_op(node, UnaryOperator::Cos),
400            "exp" => self.evaluate_unary_op(node, UnaryOperator::Exp),
401            "log" => self.evaluate_unary_op(node, UnaryOperator::Log),
402            "sqrt" => self.evaluate_unary_op(node, UnaryOperator::Sqrt),
403            _ => Ok(None), // Cannot evaluate at compile time
404        };
405
406        self.evaluation_context.depth -= 1;
407        result
408    }
409
410    fn evaluate_constant_node(&self, node: &Node) -> JitResult<Option<ConstantValue>> {
411        if let Some(value_attr) = node.get_attribute("value") {
412            let value_str = match value_attr {
413                crate::graph::Attribute::String(s) => s,
414                crate::graph::Attribute::Int(i) => return Ok(Some(ConstantValue::Int(*i))),
415                crate::graph::Attribute::Float(f) => return Ok(Some(ConstantValue::Float(*f))),
416                crate::graph::Attribute::Bool(b) => return Ok(Some(ConstantValue::Bool(*b))),
417                _ => return Ok(None),
418            };
419
420            // Try to parse as different types
421            if value_str == "true" {
422                Ok(Some(ConstantValue::Bool(true)))
423            } else if value_str == "false" {
424                Ok(Some(ConstantValue::Bool(false)))
425            } else if let Ok(int_val) = value_str.parse::<i64>() {
426                Ok(Some(ConstantValue::Int(int_val)))
427            } else if let Ok(float_val) = value_str.parse::<f64>() {
428                Ok(Some(ConstantValue::Float(float_val)))
429            } else {
430                Ok(Some(ConstantValue::String(value_str.clone())))
431            }
432        } else {
433            Ok(None)
434        }
435    }
436
437    fn evaluate_binary_op(
438        &mut self,
439        _node: &Node,
440        _op: BinaryOperator,
441    ) -> JitResult<Option<ConstantValue>> {
442        // Placeholder implementation - in a real system, this would
443        // evaluate constant binary operations by looking up input node values
444        Ok(None)
445    }
446
447    fn evaluate_unary_op(
448        &mut self,
449        _node: &Node,
450        _op: UnaryOperator,
451    ) -> JitResult<Option<ConstantValue>> {
452        // Placeholder implementation - in a real system, this would
453        // evaluate constant unary operations by looking up input node values
454        Ok(None)
455    }
456
457    fn apply_binary_operation(
458        &self,
459        op: BinaryOperator,
460        left: &ConstantValue,
461        right: &ConstantValue,
462    ) -> JitResult<Option<ConstantValue>> {
463        match (left, right) {
464            (ConstantValue::Int(a), ConstantValue::Int(b)) => {
465                let result = match op {
466                    BinaryOperator::Add => ConstantValue::Int(a + b),
467                    BinaryOperator::Sub => ConstantValue::Int(a - b),
468                    BinaryOperator::Mul => ConstantValue::Int(a * b),
469                    BinaryOperator::Div => {
470                        if *b != 0 {
471                            ConstantValue::Int(a / b)
472                        } else {
473                            return Ok(None); // Division by zero
474                        }
475                    }
476                    BinaryOperator::Mod => {
477                        if *b != 0 {
478                            ConstantValue::Int(a % b)
479                        } else {
480                            return Ok(None); // Modulo by zero
481                        }
482                    }
483                    BinaryOperator::Pow => ConstantValue::Float((*a as f64).powf(*b as f64)),
484                    BinaryOperator::Lt => ConstantValue::Bool(a < b),
485                    BinaryOperator::Le => ConstantValue::Bool(a <= b),
486                    BinaryOperator::Gt => ConstantValue::Bool(a > b),
487                    BinaryOperator::Ge => ConstantValue::Bool(a >= b),
488                    BinaryOperator::Eq => ConstantValue::Bool(a == b),
489                    BinaryOperator::Ne => ConstantValue::Bool(a != b),
490                    BinaryOperator::BitAnd => ConstantValue::Int(a & b),
491                    BinaryOperator::BitOr => ConstantValue::Int(a | b),
492                    BinaryOperator::BitXor => ConstantValue::Int(a ^ b),
493                    _ => return Ok(None),
494                };
495                Ok(Some(result))
496            }
497            (ConstantValue::Float(a), ConstantValue::Float(b)) => {
498                let result = match op {
499                    BinaryOperator::Add => ConstantValue::Float(a + b),
500                    BinaryOperator::Sub => ConstantValue::Float(a - b),
501                    BinaryOperator::Mul => ConstantValue::Float(a * b),
502                    BinaryOperator::Div => {
503                        if *b != 0.0 {
504                            ConstantValue::Float(a / b)
505                        } else {
506                            return Ok(None); // Division by zero
507                        }
508                    }
509                    BinaryOperator::Pow => ConstantValue::Float(a.powf(*b)),
510                    BinaryOperator::Lt => ConstantValue::Bool(a < b),
511                    BinaryOperator::Le => ConstantValue::Bool(a <= b),
512                    BinaryOperator::Gt => ConstantValue::Bool(a > b),
513                    BinaryOperator::Ge => ConstantValue::Bool(a >= b),
514                    BinaryOperator::Eq => ConstantValue::Bool((a - b).abs() < f64::EPSILON),
515                    BinaryOperator::Ne => ConstantValue::Bool((a - b).abs() >= f64::EPSILON),
516                    _ => return Ok(None),
517                };
518                Ok(Some(result))
519            }
520            (ConstantValue::Bool(a), ConstantValue::Bool(b)) => {
521                let result = match op {
522                    BinaryOperator::And => ConstantValue::Bool(*a && *b),
523                    BinaryOperator::Or => ConstantValue::Bool(*a || *b),
524                    BinaryOperator::Xor => ConstantValue::Bool(*a ^ *b),
525                    BinaryOperator::Eq => ConstantValue::Bool(a == b),
526                    BinaryOperator::Ne => ConstantValue::Bool(a != b),
527                    _ => return Ok(None),
528                };
529                Ok(Some(result))
530            }
531            // Mixed type operations (int and float)
532            (ConstantValue::Int(a), ConstantValue::Float(_b)) => {
533                self.apply_binary_operation(op, &ConstantValue::Float(*a as f64), right)
534            }
535            (ConstantValue::Float(_a), ConstantValue::Int(b)) => {
536                self.apply_binary_operation(op, left, &ConstantValue::Float(*b as f64))
537            }
538            _ => Ok(None), // Unsupported combination
539        }
540    }
541
542    fn apply_unary_operation(
543        &self,
544        op: UnaryOperator,
545        value: &ConstantValue,
546    ) -> JitResult<Option<ConstantValue>> {
547        match value {
548            ConstantValue::Int(a) => {
549                let result = match op {
550                    UnaryOperator::Neg => ConstantValue::Int(-a),
551                    UnaryOperator::Abs => ConstantValue::Int(a.abs()),
552                    UnaryOperator::BitNot => ConstantValue::Int(!a),
553                    _ => return Ok(None),
554                };
555                Ok(Some(result))
556            }
557            ConstantValue::Float(a) => {
558                let result = match op {
559                    UnaryOperator::Neg => ConstantValue::Float(-a),
560                    UnaryOperator::Abs => ConstantValue::Float(a.abs()),
561                    UnaryOperator::Sin => ConstantValue::Float(a.sin()),
562                    UnaryOperator::Cos => ConstantValue::Float(a.cos()),
563                    UnaryOperator::Tan => ConstantValue::Float(a.tan()),
564                    UnaryOperator::Log => {
565                        if *a > 0.0 {
566                            ConstantValue::Float(a.ln())
567                        } else {
568                            return Ok(None); // Log of non-positive number
569                        }
570                    }
571                    UnaryOperator::Exp => ConstantValue::Float(a.exp()),
572                    UnaryOperator::Sqrt => {
573                        if *a >= 0.0 {
574                            ConstantValue::Float(a.sqrt())
575                        } else {
576                            return Ok(None); // Sqrt of negative number
577                        }
578                    }
579                    UnaryOperator::Floor => ConstantValue::Float(a.floor()),
580                    UnaryOperator::Ceil => ConstantValue::Float(a.ceil()),
581                    UnaryOperator::Round => ConstantValue::Float(a.round()),
582                    _ => return Ok(None),
583                };
584                Ok(Some(result))
585            }
586            ConstantValue::Bool(a) => {
587                let result = match op {
588                    UnaryOperator::Not => ConstantValue::Bool(!a),
589                    _ => return Ok(None),
590                };
591                Ok(Some(result))
592            }
593            _ => Ok(None),
594        }
595    }
596
597    fn is_dead_code(&self, node: &Node) -> JitResult<bool> {
598        // Check if node has no side effects and its output is unused
599        if node.has_side_effects() {
600            return Ok(false);
601        }
602
603        // For now, conservatively return false
604        // In a full implementation, we would need access to the graph
605        // to check if outputs are used
606        Ok(false)
607    }
608
609    fn is_eliminable_branch(&self, node: &Node) -> JitResult<bool> {
610        if node.operation_type() != "branch" && node.operation_type() != "if" {
611            return Ok(false);
612        }
613
614        // Check if the condition is a constant
615        // This is a placeholder - in a real implementation, we'd need to track
616        // the control flow dependencies and check if the condition is constant
617        // For now, we'll conservatively return false
618
619        Ok(false)
620    }
621
622    fn get_unroll_count(&self, node: &Node) -> JitResult<Option<usize>> {
623        if node.operation_type() != "loop" && node.operation_type() != "for" {
624            return Ok(None);
625        }
626
627        // Check if loop has constant iteration count
628        if let Some(iterations_attr) = node.get_attribute("iterations") {
629            let iterations = match iterations_attr {
630                crate::graph::Attribute::Int(i) => *i as usize,
631                crate::graph::Attribute::String(s) => {
632                    if let Ok(val) = s.parse::<usize>() {
633                        val
634                    } else {
635                        return Ok(None);
636                    }
637                }
638                _ => return Ok(None),
639            };
640
641            // Only unroll small loops
642            if iterations <= 16 {
643                return Ok(Some(iterations));
644            }
645        }
646
647        Ok(None)
648    }
649
650    fn analyze_propagation_opportunities(
651        &self,
652        graph: &ComputationGraph,
653        constant_node_id: NodeId,
654        constant_value: &ConstantValue,
655    ) -> JitResult<Vec<PropagationOpportunity>> {
656        let mut opportunities = Vec::new();
657
658        if let Some(_constant_node) = graph.get_node(constant_node_id) {
659            let outputs = graph.get_node_outputs(constant_node_id);
660            let mut to_nodes = Vec::new();
661
662            for output_id in outputs {
663                if let Some(output_node) = graph.get_node(output_id) {
664                    // Check if this node can benefit from constant propagation
665                    if self.can_benefit_from_constant(output_node, constant_value) {
666                        to_nodes.push(output_id);
667                    }
668                }
669            }
670
671            if !to_nodes.is_empty() {
672                let estimated_benefit =
673                    self.estimate_propagation_benefit(&to_nodes, constant_value);
674                opportunities.push(PropagationOpportunity {
675                    from_node: constant_node_id,
676                    to_nodes,
677                    constant_value: constant_value.clone(),
678                    estimated_benefit,
679                });
680            }
681        }
682
683        Ok(opportunities)
684    }
685
686    fn can_benefit_from_constant(&self, node: &Node, _constant_value: &ConstantValue) -> bool {
687        // Check if node operation can be simplified with a constant input
688        match node.operation_type() {
689            "add" | "sub" | "mul" | "div" | "pow" => true,
690            "branch" | "if" => true,
691            "loop" | "for" => true,
692            _ => false,
693        }
694    }
695
696    fn estimate_propagation_benefit(
697        &self,
698        _to_nodes: &[NodeId],
699        _constant_value: &ConstantValue,
700    ) -> f64 {
701        // Simple heuristic: more nodes = more benefit
702        0.1 * _to_nodes.len() as f64
703    }
704
705    // Optimization application methods
706    fn apply_constant_folding(
707        &self,
708        graph: &mut ComputationGraph,
709        constants: &[(NodeId, ConstantValue)],
710    ) -> JitResult<usize> {
711        let mut applied = 0;
712
713        for (node_id, constant_value) in constants {
714            if let Some(node) = graph.get_node_mut(*node_id) {
715                // Replace node with constant
716                let graph_constant_value = match constant_value {
717                    ConstantValue::Int(i) => crate::graph::ConstantValue::IntScalar(*i),
718                    ConstantValue::Float(f) => crate::graph::ConstantValue::Scalar(*f),
719                    _ => crate::graph::ConstantValue::Scalar(0.0), // Placeholder
720                };
721                node.op = crate::graph::Operation::Constant(crate::graph::ConstantInfo {
722                    value: graph_constant_value,
723                });
724                node.set_attribute(
725                    "value".to_string(),
726                    match constant_value {
727                        ConstantValue::Bool(b) => crate::graph::Attribute::Bool(*b),
728                        ConstantValue::Int(i) => crate::graph::Attribute::Int(*i),
729                        ConstantValue::Float(f) => crate::graph::Attribute::Float(*f),
730                        ConstantValue::String(s) => crate::graph::Attribute::String(s.clone()),
731                        _ => crate::graph::Attribute::String(constant_value.to_string()),
732                    },
733                );
734                applied += 1;
735            }
736        }
737
738        Ok(applied)
739    }
740
741    fn apply_dead_code_elimination(
742        &self,
743        graph: &mut ComputationGraph,
744        dead_nodes: &[NodeId],
745    ) -> JitResult<usize> {
746        let mut applied = 0;
747
748        for &node_id in dead_nodes {
749            if graph.remove_node(node_id).is_some() {
750                applied += 1;
751            }
752        }
753
754        Ok(applied)
755    }
756
757    fn apply_branch_elimination(
758        &self,
759        graph: &mut ComputationGraph,
760        eliminable_branches: &[NodeId],
761    ) -> JitResult<usize> {
762        let mut applied = 0;
763
764        for &node_id in eliminable_branches {
765            if let Some(_node) = graph.node(node_id) {
766                let inputs = graph.get_node_inputs(node_id);
767                if !inputs.is_empty() {
768                    if let Ok(cache) = self.constant_cache.read() {
769                        if let Some(ConstantValue::Bool(condition)) = cache.get(&inputs[0]) {
770                            // Replace branch with the appropriate path
771                            let branch_index = if *condition { 1 } else { 2 };
772                            if inputs.len() > branch_index {
773                                // Replace the branch node with the selected path
774                                match graph.replace_node_with_input(node_id, inputs[branch_index]) {
775                                    Ok(_) => {
776                                        log::debug!(
777                                            "Successfully eliminated branch by replacing with {}",
778                                            if *condition { "true" } else { "false" }
779                                        );
780                                        applied += 1;
781                                    }
782                                    Err(e) => {
783                                        log::warn!("Failed to eliminate branch: {}", e);
784                                    }
785                                }
786                            }
787                        }
788                    }
789                }
790            }
791        }
792
793        Ok(applied)
794    }
795
796    fn apply_loop_unrolling(
797        &self,
798        graph: &mut ComputationGraph,
799        unrollable_loops: &[(NodeId, usize)],
800    ) -> JitResult<usize> {
801        let mut applied = 0;
802
803        for &(node_id, iterations) in unrollable_loops {
804            if let Some(loop_node) = graph.get_node(node_id) {
805                // Create unrolled loop body
806                if let Some(loop_body) = loop_node.get_attribute("body") {
807                    let body_str = match loop_body {
808                        crate::graph::Attribute::String(s) => s,
809                        _ => continue,
810                    };
811                    let unrolled_body = self.create_unrolled_body(body_str, iterations)?;
812
813                    // Replace loop with unrolled body
814                    match graph.replace_node_with_sequence(node_id, &unrolled_body) {
815                        Ok(_) => {
816                            log::debug!(
817                                "Successfully unrolled loop with {} iterations",
818                                iterations
819                            );
820                            applied += 1;
821                        }
822                        Err(e) => {
823                            log::warn!("Failed to unroll loop: {}", e);
824                        }
825                    }
826                }
827            }
828        }
829
830        Ok(applied)
831    }
832
833    fn apply_constant_propagation(
834        &self,
835        _graph: &mut ComputationGraph,
836        _opportunities: &[PropagationOpportunity],
837    ) -> JitResult<usize> {
838        // Placeholder implementation
839        // In a real implementation, this would replace variable references with constants
840        Ok(0)
841    }
842
843    fn create_unrolled_body(
844        &self,
845        _loop_body: &str,
846        iterations: usize,
847    ) -> JitResult<Vec<crate::Node>> {
848        use crate::graph::{Node, Operation};
849        use torsh_core::{DType, DeviceType, Shape};
850
851        // Simplified implementation - would need proper loop body parsing and replication
852        let mut unrolled_nodes = Vec::new();
853
854        for i in 0..iterations {
855            // Create nodes for each iteration
856            // This is a placeholder - actual implementation would parse and replicate the loop body
857            // For now, create a simple pass-through node for each iteration
858            // Use Input as a placeholder operation for unrolled iterations
859            // In a full implementation, this would replicate the actual loop body operations
860            let node = Node::new(Operation::Input, format!("unrolled_iter_{}", i))
861                .with_output_shapes(vec![Some(Shape::new(vec![1]))])
862                .with_dtypes(vec![DType::F32])
863                .with_device(DeviceType::Cpu);
864
865            unrolled_nodes.push(node);
866        }
867
868        Ok(unrolled_nodes)
869    }
870}
871
872impl EvaluationContext {
873    fn new() -> Self {
874        Self {
875            variables: HashMap::new(),
876            functions: HashMap::new(),
877            depth: 0,
878            steps: 0,
879            memory_usage: 0,
880        }
881    }
882
883    fn reset(&mut self) {
884        self.variables.clear();
885        self.depth = 0;
886        self.steps = 0;
887        self.memory_usage = 0;
888    }
889}
890
891impl ConstantValue {
892    /// Convert constant value to string representation
893    pub fn to_string(&self) -> String {
894        match self {
895            ConstantValue::Bool(b) => b.to_string(),
896            ConstantValue::Int(i) => i.to_string(),
897            ConstantValue::UInt(u) => u.to_string(),
898            ConstantValue::Float(f) => f.to_string(),
899            ConstantValue::String(s) => s.clone(),
900            ConstantValue::Array(arr) => {
901                format!(
902                    "[{}]",
903                    arr.iter()
904                        .map(|v| v.to_string())
905                        .collect::<Vec<_>>()
906                        .join(", ")
907                )
908            }
909            ConstantValue::Tensor { shape, data, dtype } => {
910                format!("Tensor({:?}, {:?}, {})", shape, data, dtype)
911            }
912            ConstantValue::Complex { real, imag } => {
913                format!("{}+{}i", real, imag)
914            }
915            ConstantValue::None => "None".to_string(),
916            ConstantValue::Undefined => "Undefined".to_string(),
917        }
918    }
919
920    /// Check if this value is truthy
921    pub fn is_truthy(&self) -> bool {
922        match self {
923            ConstantValue::Bool(b) => *b,
924            ConstantValue::Int(i) => *i != 0,
925            ConstantValue::UInt(u) => *u != 0,
926            ConstantValue::Float(f) => *f != 0.0,
927            ConstantValue::String(s) => !s.is_empty(),
928            ConstantValue::Array(arr) => !arr.is_empty(),
929            ConstantValue::Tensor { data, .. } => !data.is_empty(),
930            ConstantValue::Complex { real, imag } => *real != 0.0 || *imag != 0.0,
931            ConstantValue::None => false,
932            ConstantValue::Undefined => false,
933        }
934    }
935
936    /// Get the type name of this constant
937    pub fn type_name(&self) -> &'static str {
938        match self {
939            ConstantValue::Bool(_) => "bool",
940            ConstantValue::Int(_) => "int",
941            ConstantValue::UInt(_) => "uint",
942            ConstantValue::Float(_) => "float",
943            ConstantValue::String(_) => "string",
944            ConstantValue::Array(_) => "array",
945            ConstantValue::Tensor { .. } => "tensor",
946            ConstantValue::Complex { .. } => "complex",
947            ConstantValue::None => "none",
948            ConstantValue::Undefined => "undefined",
949        }
950    }
951}
952
953#[cfg(test)]
954mod tests {
955    use super::*;
956
957    #[test]
958    fn test_constant_evaluator_creation() {
959        let config = ConstEvalConfig::default();
960        let evaluator = ConstantEvaluator::new(config);
961        assert!(evaluator.config.enable_constant_folding);
962    }
963
964    #[test]
965    fn test_binary_operations() {
966        let evaluator = ConstantEvaluator::new(ConstEvalConfig::default());
967
968        let left = ConstantValue::Int(5);
969        let right = ConstantValue::Int(3);
970
971        let result = evaluator
972            .apply_binary_operation(BinaryOperator::Add, &left, &right)
973            .unwrap()
974            .unwrap();
975        assert_eq!(result, ConstantValue::Int(8));
976
977        let result = evaluator
978            .apply_binary_operation(BinaryOperator::Mul, &left, &right)
979            .unwrap()
980            .unwrap();
981        assert_eq!(result, ConstantValue::Int(15));
982    }
983
984    #[test]
985    fn test_unary_operations() {
986        let evaluator = ConstantEvaluator::new(ConstEvalConfig::default());
987
988        let value = ConstantValue::Float(4.0);
989        let result = evaluator
990            .apply_unary_operation(UnaryOperator::Sqrt, &value)
991            .unwrap()
992            .unwrap();
993        assert_eq!(result, ConstantValue::Float(2.0));
994
995        let value = ConstantValue::Int(-5);
996        let result = evaluator
997            .apply_unary_operation(UnaryOperator::Abs, &value)
998            .unwrap()
999            .unwrap();
1000        assert_eq!(result, ConstantValue::Int(5));
1001    }
1002
1003    #[test]
1004    fn test_constant_value_operations() {
1005        let bool_val = ConstantValue::Bool(true);
1006        assert!(bool_val.is_truthy());
1007        assert_eq!(bool_val.type_name(), "bool");
1008
1009        let int_val = ConstantValue::Int(42);
1010        assert_eq!(int_val.to_string(), "42");
1011
1012        let float_val = ConstantValue::Float(3.14);
1013        assert_eq!(float_val.type_name(), "float");
1014    }
1015
1016    #[test]
1017    fn test_evaluation_context() {
1018        let mut context = EvaluationContext::new();
1019        assert_eq!(context.depth, 0);
1020        assert_eq!(context.steps, 0);
1021
1022        context.depth = 5;
1023        context.steps = 100;
1024        context.reset();
1025
1026        assert_eq!(context.depth, 0);
1027        assert_eq!(context.steps, 0);
1028    }
1029}
torsh_jit/const_eval.rs

torsh_jit/
const_eval.rs
