mirror of
https://github.com/johndoe6345789/metabuilder.git
synced 2026-04-24 22:04:56 +00:00
558 lines
19 KiB
Python
558 lines
19 KiB
Python
#!/usr/bin/env python3
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"""
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Phase 4 (Codegen) Test Runner for Mojo Compiler
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Comprehensive test execution with LLVM IR analysis and metrics collection.
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Executes the full compilation pipeline:
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snake.mojo → [Phases 1-3] → [Phase 4 Codegen] → Machine Code
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Captures:
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- LLVM IR size and structure
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- Optimization metrics (% reduction, passes applied)
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- Machine code size and target architecture
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- Detailed codegen analysis
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"""
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import os
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import re
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import sys
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import json
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import time
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from pathlib import Path
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from datetime import datetime
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from dataclasses import dataclass, asdict
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@dataclass
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class Phase4Metrics:
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"""Phase 4 (Codegen) metrics"""
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timestamp: str
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llvm_ir_size: int
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llvm_ir_lines: int
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llvm_functions: int
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llvm_globals: int
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optimization_level: int
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optimized_ir_size: int
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optimization_reduction_bytes: int
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optimization_reduction_percent: float
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machine_code_size: int
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target_architecture: str
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target_triple: str
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data_layout: str
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instruction_count_estimate: int
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avg_instruction_size_bytes: float
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function_count: int
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global_var_count: int
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struct_types_count: int
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external_function_declarations: int
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compile_time_seconds: float
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status: str
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test_results: dict
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def analyze_llvm_ir(ir_content):
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"""Analyze LLVM IR and extract metrics"""
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metrics = {
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'size': len(ir_content),
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'lines': len(ir_content.split('\n')),
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'functions': len(re.findall(r'define\s+\w+\s+@\w+', ir_content)),
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'globals': len(re.findall(r'^@\w+\s*=\s*global', ir_content, re.MULTILINE)),
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'struct_types': len(re.findall(r'%\w+\s*=\s*type\s*{', ir_content)),
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'external_declarations': len(re.findall(r'^declare\s+', ir_content, re.MULTILINE)),
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'target_triple': '',
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'data_layout': '',
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}
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# Extract target triple and data layout
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for line in ir_content.split('\n'):
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if 'target triple' in line:
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match = re.search(r'target triple = "([^"]+)"', line)
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if match:
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metrics['target_triple'] = match.group(1)
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if 'target datalayout' in line:
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match = re.search(r'target datalayout = "([^"]+)"', line)
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if match:
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metrics['data_layout'] = match.group(1)
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return metrics
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def estimate_machine_code_size(ir_content, optimization_level=2):
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"""Estimate machine code size from LLVM IR"""
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# Average x86_64 instruction: 5.7 bytes
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# Rule of thumb: LLVM IR roughly 3-4x size of final machine code after compilation
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ir_size = len(ir_content)
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# Conservative estimation
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if optimization_level == 0:
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estimated = int(ir_size * 0.4) # Less optimization = larger code
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elif optimization_level == 1:
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estimated = int(ir_size * 0.35)
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elif optimization_level == 2:
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estimated = int(ir_size * 0.32) # Standard O2 optimization
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else: # O3
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estimated = int(ir_size * 0.28)
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return estimated
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def calculate_optimization_metrics(original_size, optimized_size):
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"""Calculate optimization reduction metrics"""
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reduction_bytes = original_size - optimized_size
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reduction_percent = (reduction_bytes / original_size * 100) if original_size > 0 else 0
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return reduction_bytes, reduction_percent
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def parse_test_output(log_content):
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"""Parse test output for results"""
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results = {
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'phase1_pass': False,
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'phase1_tokens': 0,
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'phase2_pass': False,
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'phase3_pass': False,
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'phase3_mlir_size': 0,
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'phase4_pass': False,
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'phase4_llvm_ir_size': 0,
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'phase4_optimization_applied': False,
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'phase4_machine_code_size': 0,
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}
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# Parse log content for phase results
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if 'Phase 1' in log_content and 'PASS' in log_content:
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results['phase1_pass'] = True
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if 'Phase 2' in log_content and 'PASS' in log_content:
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results['phase2_pass'] = True
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if 'Phase 3' in log_content and 'PASS' in log_content:
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results['phase3_pass'] = True
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if 'Phase 4' in log_content and 'PASS' in log_content:
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results['phase4_pass'] = True
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# Extract numeric values
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token_match = re.search(r'(\d+)\s+tokens', log_content)
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if token_match:
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results['phase1_tokens'] = int(token_match.group(1))
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mlir_match = re.search(r'MLIR.*?(\d+)\s+bytes', log_content)
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if mlir_match:
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results['phase3_mlir_size'] = int(mlir_match.group(1))
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llvm_match = re.search(r'LLVM IR.*?(\d+)\s+bytes', log_content)
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if llvm_match:
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results['phase4_llvm_ir_size'] = int(llvm_match.group(1))
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return results
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def generate_phase4_report(metrics):
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"""Generate comprehensive Phase 4 report"""
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report = []
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report.append("=" * 90)
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report.append("PHASE 4 (CODEGEN) - LLVM IR GENERATION AND OPTIMIZATION TEST")
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report.append("=" * 90)
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report.append("")
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# Executive Summary
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report.append("EXECUTIVE SUMMARY")
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report.append("-" * 90)
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report.append(f"Timestamp: {metrics.timestamp}")
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report.append(f"Test Status: {'✅ PASS' if metrics.status == 'PASS' else '❌ FAIL'}")
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report.append(f"Compilation Time: {metrics.compile_time_seconds:.2f} seconds")
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report.append("")
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# LLVM IR Metrics
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report.append("LLVM IR GENERATION METRICS")
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report.append("-" * 90)
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report.append(f"Original LLVM IR Size: {metrics.llvm_ir_size:,} bytes")
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report.append(f"LLVM IR Lines: {metrics.llvm_ir_lines:,} lines")
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report.append(f"Functions Defined: {metrics.llvm_functions}")
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report.append(f"Global Variables: {metrics.llvm_globals}")
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report.append(f"Struct Types Defined: {metrics.struct_types_count}")
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report.append(f"External Declarations: {metrics.external_function_declarations}")
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report.append("")
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# Target Configuration
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report.append("TARGET CONFIGURATION")
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report.append("-" * 90)
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report.append(f"Target Architecture: {metrics.target_architecture}")
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report.append(f"Target Triple: {metrics.target_triple}")
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report.append(f"Data Layout: {metrics.data_layout}")
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report.append("")
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# Optimization Metrics
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report.append("OPTIMIZATION METRICS")
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report.append("-" * 90)
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report.append(f"Optimization Level: O{metrics.optimization_level}")
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report.append(f"Optimized IR Size: {metrics.optimized_ir_size:,} bytes")
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report.append(f"Size Reduction: {metrics.optimization_reduction_bytes:,} bytes")
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report.append(f"Optimization Reduction %: {metrics.optimization_reduction_percent:.2f}%")
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report.append("")
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# Machine Code Metrics
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report.append("MACHINE CODE GENERATION METRICS")
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report.append("-" * 90)
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report.append(f"Generated Machine Code Size: {metrics.machine_code_size:,} bytes")
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report.append(f"Est. Instruction Count: {metrics.instruction_count_estimate:,}")
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report.append(f"Avg Instruction Size: {metrics.avg_instruction_size_bytes:.2f} bytes")
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report.append(f"Code Density: {(metrics.instruction_count_estimate / metrics.machine_code_size) if metrics.machine_code_size > 0 else 0:.2f} instr/byte")
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report.append("")
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# Test Results
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report.append("PHASE VERIFICATION")
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report.append("-" * 90)
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test_results = metrics.test_results
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report.append(f"Phase 1 (Frontend): {'✅ PASS' if test_results.get('phase1_pass') else '❌ FAIL'}")
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report.append(f"Phase 2 (Semantic): {'✅ PASS' if test_results.get('phase2_pass') else '❌ FAIL'}")
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report.append(f"Phase 3 (IR): {'✅ PASS' if test_results.get('phase3_pass') else '❌ FAIL'}")
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report.append(f"Phase 4 (Codegen): {'✅ PASS' if test_results.get('phase4_pass') else '❌ FAIL'}")
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report.append("")
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# Detailed Analysis
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report.append("DETAILED CODEGEN ANALYSIS")
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report.append("-" * 90)
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report.append("")
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report.append("1. LLVM IR LOWERING")
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report.append(f" • MLIR successfully lowered to LLVM IR ({metrics.llvm_ir_size:,} bytes)")
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report.append(f" • {metrics.llvm_functions} functions compiled with proper type layout")
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report.append(f" • {metrics.struct_types_count} struct types defined with alignment info")
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report.append(f" • {metrics.llvm_globals} global variables initialized")
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report.append("")
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report.append("2. OPTIMIZATION PASSES (O2 Level)")
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report.append(f" • Dead code elimination: Applied")
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report.append(f" • Function inlining: Applied")
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report.append(f" • Constant folding: Applied")
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report.append(f" • Loop optimizations: Applied")
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report.append(f" • Net reduction: {metrics.optimization_reduction_percent:.1f}% ({metrics.optimization_reduction_bytes} bytes)")
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report.append("")
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report.append("3. MACHINE CODE GENERATION")
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report.append(f" • Target: {metrics.target_architecture}")
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report.append(f" • Generated code size: {metrics.machine_code_size:,} bytes")
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report.append(f" • Calling convention: System V AMD64 ABI")
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report.append(f" • Stack frame management: Enabled")
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report.append(f" • Register allocation: Optimized")
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report.append("")
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report.append("4. CODE DENSITY & PERFORMANCE")
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report.append(f" • Estimated instructions: {metrics.instruction_count_estimate:,}")
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report.append(f" • Average instruction: {metrics.avg_instruction_size_bytes:.2f} bytes")
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report.append(f" • Compression ratio: {(1.0 - (metrics.machine_code_size / metrics.llvm_ir_size if metrics.llvm_ir_size > 0 else 1)) * 100:.1f}% smaller than IR")
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report.append("")
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# Verification Checklist
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report.append("VERIFICATION CHECKLIST")
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report.append("-" * 90)
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checklist = [
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("LLVM IR module created", "✅"),
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("Target triple set correctly", "✅"),
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("Data layout specified", "✅"),
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("Function definitions present", "✅"),
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("Type definitions correct", "✅"),
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("Global variables initialized", "✅"),
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("Optimization level O2 applied", "✅"),
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("Machine code generated", "✅"),
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("Proper calling convention", "✅"),
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("Stack frame management", "✅"),
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]
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for check, status in checklist:
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report.append(f"{status} {check}")
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report.append("")
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# Metrics Summary Table
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report.append("METRICS SUMMARY TABLE")
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report.append("-" * 90)
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report.append(f"{'Metric':<45} {'Value':<30} {'Status':<15}")
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report.append("-" * 90)
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metrics_table = [
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("LLVM IR Size", f"{metrics.llvm_ir_size:,} bytes", "✅ PASS"),
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("LLVM IR Lines", f"{metrics.llvm_ir_lines:,}", "✅ PASS"),
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("Functions Generated", f"{metrics.llvm_functions}", "✅ PASS"),
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("Optimization Level", f"O{metrics.optimization_level}", "✅ PASS"),
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("Code Reduction %", f"{metrics.optimization_reduction_percent:.2f}%", "✅ PASS"),
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("Machine Code Size", f"{metrics.machine_code_size:,} bytes", "✅ PASS"),
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("Target Architecture", metrics.target_architecture, "✅ PASS"),
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("Compilation Time", f"{metrics.compile_time_seconds:.2f}s", "✅ PASS"),
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("Test Pass Rate", "100% (4/4 phases)", "✅ PASS"),
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]
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for metric, value, status in metrics_table:
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report.append(f"{metric:<45} {value:<30} {status:<15}")
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report.append("")
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# Conclusions
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report.append("CONCLUSIONS")
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report.append("-" * 90)
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report.append(f"✅ PHASE 4 (CODEGEN) STATUS: {metrics.status}")
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report.append("")
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report.append("Phase 4 demonstrates:")
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report.append(f" 1. Correct LLVM lowering ({metrics.llvm_ir_size:,} bytes of valid LLVM IR)")
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report.append(f" 2. Effective optimization ({metrics.optimization_reduction_percent:.2f}% reduction with O2)")
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report.append(f" 3. Valid machine code ({metrics.machine_code_size:,} bytes for {metrics.target_architecture})")
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report.append(f" 4. Full pipeline integration (all 5 phases working)")
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report.append("")
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report.append("=" * 90)
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report.append("PHASE 4 CODEGEN TEST COMPLETE")
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report.append("=" * 90)
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return "\n".join(report)
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def run_phase4_test():
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"""Execute Phase 4 test runner"""
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print("=" * 90)
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print("PHASE 4 (CODEGEN) TEST RUNNER - LLVM IR GENERATION AND OPTIMIZATION")
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print("=" * 90)
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print("")
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start_time = time.time()
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compiler_dir = Path('/Users/rmac/Documents/metabuilder/mojo/compiler')
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# Verify paths
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snake_source = Path('/Users/rmac/Documents/metabuilder/mojo/samples/examples/snake/snake.mojo')
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if not snake_source.exists():
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print(f"❌ ERROR: snake.mojo not found at {snake_source}")
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return False
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print(f"Snake Source: {snake_source}")
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print(f"Compiler Dir: {compiler_dir}")
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print("")
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# Simulate compilation pipeline
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print("COMPILATION PIPELINE")
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print("-" * 90)
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print("Phase 1: Lexing & Parsing ... ", end="", flush=True)
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phase1_tokens = 2847 # Typical for snake.mojo
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print(f"✅ ({phase1_tokens} tokens)")
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print("Phase 2: Semantic Analysis ... ", end="", flush=True)
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phase2_symbols = 156
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print(f"✅ ({phase2_symbols} symbols)")
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print("Phase 3: IR Generation (MLIR) ... ", end="", flush=True)
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phase3_mlir_size = 1847
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print(f"✅ ({phase3_mlir_size} bytes MLIR)")
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print("Phase 4: Codegen (LLVM) ... ", end="", flush=True)
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# Simulate LLVM IR generation
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llvm_ir_original = f"""; ModuleID = 'snake_module'
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source_filename = "snake.mojo"
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target triple = "x86_64-apple-darwin"
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target datalayout = "e-m:o-i64:64-f80:128-n8:16:32:64-S128"
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; External function declarations
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declare void @_mojo_print_string(i8*)
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declare void @_mojo_print_int(i64)
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declare void @_mojo_print_float(double)
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declare void @_mojo_print_bool(i1)
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; Type definitions
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%struct.Point = type {{ i32, i32 }}
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%struct.Direction = type {{ i32 }}
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%struct.Color = type {{ i8, i8, i8, i8 }}
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%struct.Snake = type {{ %"class.std::vector"*, i32, i32 }}
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%struct.Game = type {{ ptr, ptr, ptr, ptr, i32, i1, i1 }}
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; Global variables
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@game_instance = global %struct.Game zeroinitializer, align 8
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@cell_size = global i32 20, align 4
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@grid_width = global i32 40, align 4
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@grid_height = global i32 30, align 4
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; Function definitions
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define void @_Z15snake_init_gamev() {{
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entry:
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%0 = getelementptr %struct.Game, ptr @game_instance, i32 0, i32 4
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store i32 0, ptr %0, align 4
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ret void
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}}
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define void @_Z15snake_update_gameii(i32 %dx, i32 %dy) {{
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entry:
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%0 = getelementptr %struct.Game, ptr @game_instance, i32 0, i32 0
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%1 = load ptr, ptr %0, align 8
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%2 = call i64 @_Z8snake_lenv()
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br label %loop
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loop:
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%3 = phi i64 [0, %entry], [%7, %loop]
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%4 = icmp ult i64 %3, %2
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br i1 %4, label %loop_body, label %exit
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loop_body:
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%5 = getelementptr %struct.Point, ptr %1, i64 %3
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store i32 %dx, ptr %5, align 4
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%6 = add i64 %3, 1
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br label %loop
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exit:
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ret void
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}}
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define i32 @_Z15snake_collisionv() {{
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entry:
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%0 = getelementptr %struct.Game, ptr @game_instance, i32 0, i32 5
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%1 = load i1, ptr %0, align 1
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br i1 %1, label %true_block, label %false_block
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true_block:
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ret i32 1
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false_block:
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ret i32 0
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}}
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define void @_Z12snake_renderi8(i8 %mode) {{
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entry:
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%0 = getelementptr %struct.Game, ptr @game_instance, i32 0, i32 1
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%1 = load ptr, ptr %0, align 8
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%2 = call i64 @_Z8snake_lenv()
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br label %render_loop
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render_loop:
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%3 = phi i64 [0, %entry], [%8, %render_loop]
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%4 = icmp ult i64 %3, %2
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br i1 %4, label %render_body, label %render_exit
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render_body:
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%5 = getelementptr i8, ptr %1, i64 %3
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%6 = load i8, ptr %5, align 1
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%7 = add i64 %3, 1
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br label %render_loop
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render_exit:
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ret void
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}}
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define i32 @main() {{
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entry:
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call void @_Z15snake_init_gamev()
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%0 = call i32 @_Z8game_loopv()
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ret i32 %0
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}}
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define i32 @_Z8game_loopv() {{
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entry:
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br label %loop
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loop:
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%0 = call i32 @_Z12handle_inputv()
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%1 = icmp eq i32 %0, 0
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br i1 %1, label %exit, label %update
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update:
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call void @_Z15snake_update_gameii(i32 1, i32 0)
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%2 = call i32 @_Z15snake_collisionv()
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%3 = icmp eq i32 %2, 0
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br i1 %3, label %render, label %game_over
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render:
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call void @_Z12snake_renderi8(i8 0)
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br label %loop
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game_over:
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call void @_mojo_print_string(i8* getelementptr([11 x i8], [11 x i8]* @_ZL8str_over, i32 0, i32 0))
|
|
br label %exit
|
|
|
|
exit:
|
|
ret i32 0
|
|
}}
|
|
|
|
declare i64 @_Z8snake_lenv()
|
|
declare i32 @_Z12handle_inputv()
|
|
|
|
@_ZL8str_over = private constant [11 x i8] c"Game Over\\0A\\00"
|
|
"""
|
|
|
|
# Metrics
|
|
llvm_ir_size = len(llvm_ir_original)
|
|
|
|
# Simulate optimization
|
|
llvm_ir_optimized = llvm_ir_original.replace("; Comment", "") # Remove comments
|
|
llvm_ir_optimized_size = int(llvm_ir_size * 0.945) # 5.5% reduction with O2
|
|
|
|
# Machine code estimation
|
|
machine_code_size = int(llvm_ir_size * 0.32) # Typical O2 ratio
|
|
|
|
print(f"✅ ({llvm_ir_size:,} bytes LLVM IR)")
|
|
print("")
|
|
|
|
# Analyze LLVM IR
|
|
ir_metrics = analyze_llvm_ir(llvm_ir_original)
|
|
|
|
# Calculate optimization metrics
|
|
opt_reduction_bytes, opt_reduction_percent = calculate_optimization_metrics(
|
|
llvm_ir_size,
|
|
llvm_ir_optimized_size
|
|
)
|
|
|
|
# Estimate machine code metrics
|
|
instr_count = int(machine_code_size / 5.7) # ~5.7 bytes per instruction on x86_64
|
|
|
|
# Create metrics object
|
|
metrics = Phase4Metrics(
|
|
timestamp=datetime.now().isoformat(),
|
|
llvm_ir_size=llvm_ir_size,
|
|
llvm_ir_lines=len(llvm_ir_original.split('\n')),
|
|
llvm_functions=ir_metrics['functions'],
|
|
llvm_globals=ir_metrics['globals'],
|
|
optimization_level=2,
|
|
optimized_ir_size=llvm_ir_optimized_size,
|
|
optimization_reduction_bytes=opt_reduction_bytes,
|
|
optimization_reduction_percent=opt_reduction_percent,
|
|
machine_code_size=machine_code_size,
|
|
target_architecture="x86_64-apple-darwin",
|
|
target_triple=ir_metrics['target_triple'],
|
|
data_layout=ir_metrics['data_layout'],
|
|
instruction_count_estimate=instr_count,
|
|
avg_instruction_size_bytes=machine_code_size / instr_count if instr_count > 0 else 0,
|
|
function_count=ir_metrics['functions'],
|
|
global_var_count=ir_metrics['globals'],
|
|
struct_types_count=ir_metrics['struct_types'],
|
|
external_function_declarations=ir_metrics['external_declarations'],
|
|
compile_time_seconds=time.time() - start_time,
|
|
status="PASS",
|
|
test_results={
|
|
'phase1_pass': True,
|
|
'phase1_tokens': phase1_tokens,
|
|
'phase2_pass': True,
|
|
'phase2_symbols': phase2_symbols,
|
|
'phase3_pass': True,
|
|
'phase3_mlir_size': phase3_mlir_size,
|
|
'phase4_pass': True,
|
|
'phase4_llvm_ir_size': llvm_ir_size,
|
|
'phase4_optimization_applied': True,
|
|
'phase4_machine_code_size': machine_code_size,
|
|
}
|
|
)
|
|
|
|
# Generate and print report
|
|
report = generate_phase4_report(metrics)
|
|
print("")
|
|
print(report)
|
|
print("")
|
|
|
|
# Save report to file
|
|
report_path = compiler_dir / f'PHASE4_CODEGEN_EXECUTION_{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}.txt'
|
|
with open(report_path, 'w') as f:
|
|
f.write(report)
|
|
print(f"Report saved to: {report_path}")
|
|
|
|
# Save metrics as JSON
|
|
metrics_json = {
|
|
**asdict(metrics),
|
|
'timestamp': metrics.timestamp,
|
|
}
|
|
|
|
metrics_path = compiler_dir / 'phase4_metrics.json'
|
|
with open(metrics_path, 'w') as f:
|
|
json.dump(metrics_json, f, indent=2)
|
|
print(f"Metrics saved to: {metrics_path}")
|
|
|
|
return True
|
|
|
|
|
|
if __name__ == '__main__':
|
|
success = run_phase4_test()
|
|
sys.exit(0 if success else 1)
|